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Bachelor Thesis May 2009

Valuation of FLSmidth Estimating fair value through fundamental analysis

By Martin Bo Hansen (MH74735)

Academic Advisor: Jan Bartholdy

Department of Economics

Table of Contents 1. Preface ............................................................................................................................................................................ 3

2. Executive summary ......................................................................................................................................................... 4

3. Introduction .................................................................................................................................................................... 6

3.1 Brief introduction of FLSmidth ................................................................................................................................. 6

3.2 Problem statement ................................................................................................................................................... 6

3.3 Structure ................................................................................................................................................................... 7

3.4 Delimitations and assumptions ................................................................................................................................ 9

3.5 Method ................................................................................................................................................................... 11

3.6 Quality of the analysis ............................................................................................................................................ 11

4. Historical financial analysis ........................................................................................................................................... 14

4.2 Reorganizing accounting statements ..................................................................................................................... 14

4.2.1 Reorganizing the balance sheet – analysis of invested capital ....................................................................... 14

4.2.2 Reorganizing the income statement – analysis of NOPLAT ............................................................................ 14

4.3 Free cash‐flow analysis ........................................................................................................................................... 15

4.4 Return on invested capital analysis ........................................................................................................................ 15

4.5 Revenue growth analysis ........................................................................................................................................ 17

4.6 Weighted average cost of capital (WACC) .............................................................................................................. 18

4.6.1 Cost of equity .................................................................................................................................................. 18

4.6.2 Cost of debt ..................................................................................................................................................... 22

4.6.3 Target capital structure ................................................................................................................................... 23

4.6.4 Calculating WACC ............................................................................................................................................ 23

4.7 Preliminary conclusion ........................................................................................................................................... 24

5. Business‐as‐usual scenario valuation ........................................................................................................................... 25

6. Strategic analysis .......................................................................................................................................................... 26

6.1 Dynamics of the industry ........................................................................................................................................ 26

6.2 External analysis ..................................................................................................................................................... 27

6.2.1 PEST ................................................................................................................................................................. 27

6.2.2 Porter’s Five Forces model .............................................................................................................................. 31

6.3 Internal analysis ...................................................................................................................................................... 37

6.3.1 Resources and capabilities .............................................................................................................................. 37

6.3.2 Structure, systems and processes ................................................................................................................... 39

6.3.3 Owners and managers preferences ................................................................................................................ 41

6.3.4 Core competencies ......................................................................................................................................... 43

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6.4 Key factors for success ........................................................................................................................................... 44

6.5 Critical SWOT .......................................................................................................................................................... 45

6.5.1 Analysis of FLS’ need to change........................................................................................................................... 46

6.5.2 Evaluating opportunities and threats ............................................................................................................. 48


7. Valuation ....................................................................................................................................................................... 50

7.1 Forecast drivers ...................................................................................................................................................... 50

7.2 Scenarios ................................................................................................................................................................ 51

7.2.1 Base scenario .................................................................................................................................................. 51

7.2.1.2 Other forecast drivers .................................................................................................................................. 57

7.1.4 Base scenario valuation summary .................................................................................................................. 60

7.2.3 Bull scenario .................................................................................................................................................... 61

7.2.2 Bear scenario .................................................................................................................................................. 62

7.2.3 Scenario summary ........................................................................................................................................... 62

7.3 Value of flexibility ................................................................................................................................................... 63

7.4 Sensitivity analysis .................................................................................................................................................. 64

7.5 Simulation on forecast drivers ............................................................................................................................... 65

7.6 Peer‐group comparison .......................................................................................................................................... 67


8. Conclusion .................................................................................................................................................................... 70

9. Reflection ...................................................................................................................................................................... 73

10. Figure and table list .................................................................................................................................................... 74

11. List of sources ............................................................................................................................................................. 75

12. Appendices ................................................................................................................................................................. 77

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1. Preface A CD with all relevant files has been enclosed. That is – one Excel file for each scenario, a copy of the report

and a Power Point file with a copy of all appendices, which are also included in the back of the report.

The Excel files have been built up in a similar way. First, a set of light blue worksheets illustrate information

used in connection with the historical financial analysis. Secondly, a set of green worksheets illustrate

information used for estimating the cost of capital. Finally, red worksheets illustrate information used in

connection with the actual valuation.

The Power Point has been included in order to make the reading of the report as convenient for the reader

as possible. Through this, the reader can choose whether to have a look through the appendices on the

computer while reading, or simply to look back and forth in the actual report.

On the CD two identical sets of files have been copied – one with files in Office 2007 format and one in

Office 97 format. As the files have originally been made in 2007 format these should be used provided it is

possible, as some data might be lost when using Office 97.

Last but not least, the size of the report has been documented in appendix 29 in order to make sure that

the limits of the report have been respected.

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2. Executive summary With a starting point in the financial crisis and hence changing market situation, the present report sets out

to evaluate the outlook of FLSmidth1 and through this, to estimate the fair value of the FLS share using

fundamental analysis.

In order to evaluate FLS’ past performance, a historical financial analysis is carried out. Through analysis of

the development in invested capital, NOPLAT, Free Cash‐Flow, ROIC and revenue growth, it is clear that

during the recent five years FLS has experiences a healthy development, which among other things has

made acquisitions possible. All in all, FLS has reached a more balanced and less risky business profile, which

together with a good financial situation means that the company is generally in excellent shape to handle a

period of lower activity.

On the basis of the historical financial analysis, a business‐as‐usual valuation is carried out in order to

estimate the fair value of FLS, provided that the development during the recent five years continues into

the future. This is done despite the knowledge that this is clearly rather optimistic, but done nevertheless

as it is evaluated to be of useful comparison when estimating the actual fair value later on. This leads to a

fair value of DKK 1.110 per share, which is far above the actual share price of DKK 139. However, as the

marked is evaluated to be fully aware that past performance will be curved due to the financial crisis, this is

as expected.

In order to evaluate the future market situation together with other strategic changes, a strategic analysis

is carried out. This is done in three overall steps – an analysis of the general environment using the PESTEL

model, an analysis of the industry using Porter’s Five Forces model and finally an internal analysis of FLS.

Throughout the strategic analysis the situation during the recent five years is evaluated and compared with

the estimated future development, in the short as well as long run, seen from the perspective of FLS. This is

done in order to clarify actual future changes instead of simply analyzing the present situation, as this is

assumed to be of little value when estimating the future outlook. Through this it is concluded that the

general environment is expected to remain close to stable in the short run, while changing marginally to

the better in the long run. Having said that, as the economic factors are evaluated have the largest impact

on FLS, it seems relevant to mention that the outlook in this area is quite different. Concretely, the

economic factors are evaluated to worsen considerably in the short run, and that even in the long run they

will not reach the recent years’ levels. Contrary to the general environment, the threats within the industry

are evaluated remain close to stable in both the short and long run.

1 For the remaining part of the report simply denoted FLS

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With regards to the internal strategic analysis a wide range of aspects from resources and capabilities,

structures, systems and processes, as well as owners’ and managers’ preferences and core competencies

are analyzed. Through this a picture of a well functioning company with focus on the long term

performance is painted. On the basis of the analysis of the industry and the internal analysis, key factors for

success are defined as being low total‐costs‐of‐ownership as well as a good brand defined by quality,

reliability and good reputation.

Finally, the strategic analysis is summarized and evaluated through a critical SWOT in which relevant

connections between strengths/weaknesses and opportunities/threats are made in order to evaluate FLS’

need to change. As the last step, opportunities and threats are rated in order to identify their relative

importance.

On the basis of the historical financial analysis and strategic analysis, the actual estimation of fair value is

carried out and evaluated in a base, bear and bull scenario. This leads to a fair value of DKK 328, DKK 284

and DKK 398 respectively. With an evaluated 15% probability of either the bear or bull scenario taking

place, a weighted fair value is calculated at DKK 332.

To acknowledge that the estimated fair value does not include the value of flexibility, real options are

briefly discussed. However, due to the evaluated relatively small value of flexibility in connection with FLS

as well as insufficient information, the actual value of the portfolio of real options is not calculated.

Furthermore, to evaluate the uncertainty related to the estimated fair value, a sensitivity analysis and a

simulation based on a range of different variables are carried out. On the basis of this, the fair value is

evaluated to be connected with considerable uncertainty.

Last but not least, a peer‐group analysis is made to get a more market oriented picture of what investors

are currently willing to pay for similar companies. Through this, FLS is evaluated to be trading at a

considerable discount of 41%. Applying peer‐group multiples on FLS lead to a share price of DKK 269‐379

with an average of DKK 316.

All in all, the fair value of FLS is estimated to equal the weighted average fair value of DKK 332 per share.

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3. Introduction The current report will start out with a brief introduction of FLS. Furthermore, a problem statement will be

formulated and methods used will be discussed together with the structure of the report and the

delimitations. Finally, a section will be devoted to ensuring the quality of the report.

3.1 Brief introduction of FLSmidth With a history which goes all the way back to 1882, one of both greatness and times of trouble, FLS recently

celebrated its 125th anniversary (FLSmidth 2009b). Through the years the main focus has always been on

cement, but a vast range of other business segments have been in and out of the portfolio. After World

War 2 the line of businesses had expanded to such diverse business lines as machinery manufacture,

packaging & production, insurance and aircraft maintenance. In 1989 non‐core business lines were

responsible for 2/3 of the conglomerate’s revenue, due to which a group restructuring was carried out in

order to arrange the 125 companies within 7 divisions (FLSmidth 2009c). However, during the 90ies it

became increasingly difficult to operate all divisions in a strategic an economic feasible way, and around

the millennium FLS was in deep financial trouble. Due to global competition and a lack of focus, it became

clear that a conglomerate like structure was no longer optimal, and in the following years non‐core

business lines were sold off (FLSmidth 2009d). Today focus is once again targeted at equipment used in

connection with the production of cement and to an increasing extent also the extraction of minerals.

3.2 Problem statement During the recent years FLS has truly returned to the heyday of the past. But with a financial crisis roaring

at full strength and commodity prices plummeting, a new situation seems to be emerging. This picture is

backed up by recent years and especially recent months share price development as depicted in fig. 3.1.

Figure 3.1: Share price development of FLS vs. OMX20

Source: Own representation on the basis of Bloomberg data

0

100

200

300

400

500

600

FLS OMXC20

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In the light of this, a closer analysis of FLS is sought, through which the changing market situation and

finally the fair value will be estimated. On the basis of the above, the following research question and sub

questions are formulated:

o Research question: What is the fair value of the FLS’ share?

o Sub questions in connection with the historical financial analysis:

What has FLS’ financial situation looked like during the recent five years?

What is the weighted average cost of capital?

o Sub questions in connection with the strategic analysis:

How are the environmental factors expected to develop in the future?

What does the competitive situation within the industry look like and how is it

expected to develop in the future?

Which internal factors are most important in connection with valuing FLS?

What is FLS’ need to change and what are the most important opportunities and

threats?

o Sub questions in connection with the valuation:

What is the fair value of FLS in a business‐as‐usual scenario?

Which forecast drivers are affected by conclusions from the historical financial

analysis and/or strategic analysis?

What is the fair value of FLS in a base, bear and bull scenario respectively?

How sensitive is the estimated fair value to changes in variables?

How is FLS valued relative to its peer group?

3.3 Structure The report is split into 4 main parts as illustrated in appendix 1. The structure of the report will be discussed

in order to prepare the reader for the different sections, as well as to explain why the given structure has

been chosen.

The report has started out by an introductory chapter, in which the practical and theoretical cornerstones

will be covered. The report has already gone through brief introduction of FLS as this lays the foundation

for the larger picture in which the following parts of the introductory chapter should be seen. The company

introduction has been followed by a problem statement, which consists of an explanation of the problem as

well as the object of investigation. The problem statement furthermore defines an overall research

question together with several sub questions, which are to be answered during the report and summarised

in the final conclusion. The discussion of structure will be followed by a range of delimitations and

assumption which have been put on the report, including the reasoning for doing so. Finally, the

introductory chapter will finish off with a method section, in which the evaluation and choice of method

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will be described, as well as a section devoted to ensuring that a certain level of analytical quality is

maintained.

The analysis section consists of two chapters – a historical financial analysis and a strategic analysis.

Through a historical financial analysis, accounting statements will be rearranged in order for them to reflect

economic performance rather than accounting performance, in order to enable the writer to analyze

invested capital, NOPLAT, Free Cash‐flow, ROIC and revenue growth. The historical financial analysis will

finish off by estimating the cost of capital to be used in connection with the valuation.

On the basis of this, the recent years’ development will be extrapolated into the detailed forecast period to

derive at a very basic “business‐as‐usual” valuation. This is done in order to get an idea of what the fair

value would be provided that the recent development would continue into the future. By doing so, it will be

easier and more comprehensible to evaluate which effect strategic changes are expected to have on

different variables and through this the fair price.

After this a strategic analysis will be carried out, which will be split into yet again two main parts in order to

cover an analysis of the general environment and industry (external factors) and an analysis of different

internal factors. Throughout the strategic analysis, comparison between the situation during the recent five

years and the expected future situation will be made. The future will be split into two further categories –

the short run corresponding to the detailed forecast period (2009‐2013) and the long run corresponding to

the situation during the key forecast period (2014‐2023). First and foremost, this is done in order to bring

about an understanding of which factors were present during recent years’ financial performance, and

hence to get an idea of which changes are expected for the future. The idea is, that a more precise fair

value will be estimated by looking at strategic changes isolated seen and adding them to a historical level ‐

rather than simply trying directly to estimate the actual situation as a whole. Hence, with the recent five

years as a basis for forecasting, variables will only be taken specifically account of in the case where they

are expected to differ from the historical picture.

The analysis section will be summarized in a critical SWOT through which FLS’ need to change is evaluated.

This is done by matching internal factors with external factors and dividing them into three groups – one

group contains connections which can be exploited right away, one contains connections which are

evaluated to be latent needs to change and another group contains connection which represent acute

needs to change in order to enable the company to meet a threat in time (Lægaard, Jørgen & Vest, Mikael

2002, pp.131‐135). On the basis of this, opportunities and threats are evaluated and graded according to

their importance to the company (Lægaard, Jørgen & Vest, Mikael 2002, pp.121‐130). By doing so each

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item is evaluated relative to the others and hence enables the writer to identify the best opportunities and

the most serious threats.

Last but not least, the actual valuation using the DCF and EVA‐models will be carried out. This is done in

both a bear, base and bill scenario in order to illustrate the effect such situations would have on the fair

value. The value of flexibility will briefly be discussed in order to acknowledge that the estimated fair value

is the value of FLS without taking flexibility into account. Finally, a sensitivity analysis as well as a simulation

using VBA will be carried out to investigate the fair value’s sensitivity after which a peer‐group comparison

is made.

3.4 Delimitations and assumptions The following are delimitations and assumptions which have been put on the report, in order to make sure

that the scope is held within its limits of the report.

The used theory and models are assumed to be known to the reader, and hence will not be explained in

detail but rather briefly discussed.

As the Chinese market for cement equipment has been more or less inaccessible for western suppliers

(FLSmidth 2009a, p.16), most data available excludes China. As a natural consequence, calculations done in

this report will rely on data excluding China even though FLS in fact does in fact generate some revenue

from here.

The valuation will be carried out using McKinsey’s Excel valuation model as a starting point, as building

similar model from scratch is evaluated to take a considerable amount of time, which could be used better

elsewhere in the report. The goal of the report is to estimate the fair value of FLS and not to develop an

Excel valuation model. However, as the model only consists of the four worksheets “Historical Data”,

“Forecast Drivers”, “Results” and “Valuation Summary” a considerable amount of additions and changes

have been made. A critical perspective has furthermore been taken to the model, through which the so

called Mid‐Year‐Adjustment‐Factor2 has been changed, as the writer does not agree with McKinsey’s way

of using it. In its basic form McKinsey does not take account of the fact that cash‐flows are create

continuously during the year and not as a lump sum in the end of the year.

2 As the valuation is carried out on the 27th of February and hence two months into the new accounting year, this leads to a higher value that if the valuation was don on 1st of January. The mid‐year‐adjustment‐factor takes of this

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The cut‐off date for gathering information will be set to the 27th of February. This seems as an appropriate

date as this is the date when FLS’ 2008 annual report is published. However, the peer‐group analysis will

deviate slightly from this assumption as consensus estimates were not gathered before the middle of April.

The historical financial analysis will cover the recent five years. Going back longer than five years would

have been preferable but would at the same time lead to several problems. First and foremost, the new

IFRS were implemented from the 2005 annual accounts and applied backwards to the 2004 annual

accounts. An estimation of the 2003 annual accounts would preferably have been carried out if FLS had not

undergone major organizational changes during 2004. Among others they sold several companies which in

2004 contributed to 26% of revenue. Hence, information required to reformulate the 2003 annual accounts

to incorporate both the new accounting standards but also the divesture of companies, was insufficient.

However, it is evaluated that five years historical accounts are adequate, however a minimum, to base the

analysis upon.

Throughout the report focus will be put on analysis of the cement and the mineral divisions. First and

foremost, these two divisions are responsible for 95% of the groups’ revenue and 99% of EBIT in 2008

(FLSmidth 2009a, p.8). Furthermore, due to their size and importance there is relatively good information

available which makes a meaningful analysis possible. For the same reason, a detailed analysis on Cembrit3

isolated seen will not be carried out.

Financial markets are assumed to be efficient, which is a prerequisite for a fair value to make sense. This

assumption is rather important as a financial crises as the one we are experiencing at the moment, might

have had an effect on this. The idea with a fair value is, that the market is generally aware of an

approximate fair value of a given company and hence will act by either buying or selling the stock if it

deviates from this. For this reason share prices are assumed to move around a fair value in the long run

(Koller et al. 2005, pp. 5‐6). However, in the current market and due to constrain access to liquidity and

heavily losses on declining shares, it is plausible to imagine a case in which investors are forced to sell their

shares in a given company, even though they are well aware that it is trading far below the fair value.

Problems with inefficient stock markets during a financial crisis have been established by among others Lim

(Lim, Brooks & Kim 2008, p.571).

The valuation is based on the going concern principle, which means that FLS is assumed to continue their

operations indefinitely.

3 Formerly known under the name Dansk Eternit‐Fabrik

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Last but not least, steady state is assumed to have been reached by the end of the key forecast period in

2023/24.

3.5 Method This report sets out to estimate the objective fair value of FLS using fundamental analysis. This is done on

the basis of the viewpoint that stock markets move around a fair value in the long run, even though they

might not be a reliable indicator of value in the short run (Koller et al. 2005, p. 5‐6). Furthermore, the

perspective is taken that only one fair value exists for any given company. However, this fair value can

never be calculated to the exact value, but only be estimated trough subjective construction. Through this

subjective construction there is an inherent risk that the subjective monetary value will be biased by the

writer’s personal value system. To minimize the risk of this, the report will be carried out through a

methodological paradigm which fits critical theory. Critical theory suggests that only one objective reality

exists, but that it can never be fully apprehended, as the writer will always be inextricably linked to the

reality under investigation (Heldbjerg 2003, p.36). Hence, in order to get as close to the true fair value as

possible, the writer will continuously test personal values and through this, results and findings against

those of others. This is not done with a superior goal at hand to reach the same conclusion as others, but

rather to investigate if differences in conclusions are due to bias rooted in the writer’s value system which

are sought to be minimized.

The report will mainly be written on the basis of secondary data, but will also consist of some primary data.

Secondary data will consists of among other things books, newspaper articles, annual reports and scientific

research, while primary data will consist mainly of interviews with FLS’ IR Manager, Pernille Friis Andersen

and Equity Analyst, Lars Terp Paulsen covering FLS at Jyske Bank.

3.6 Quality of the analysis The quality of the report depends on the writer’s ability to include relevant information, but just as

importantly to exclude any irrelevant information, as well as including relevant information properly. The

chances are good that the writer’s solitary estimation of fair value is less precise than the one a wide

portfolio of Equity Analysts’ or the market in general estimates. Generally speaking, own estimations and

calculations are only relied on provided that they are evaluated to be as good as or better than those of

others. In order to make sure the quality of the analysis remain at a certain level, several factors are

continuously kept in mind throughout the report.

The qualitative research design will mainly be used for the strategic analysis, during which attention should

be given to credibility, transferability, dependability and confirmability. Credibility relates to the degree to

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which the investigation and findings are reliable. That is ‐ if the sources used have been interpreted

properly, why only the sources themselves will be able to evaluate this (Heldbjerg 2003, pp.21‐22). As far as

possible, a certain level of credibility is attempted reached by letting sources read specific parts of the

report in which they have contributed with information, through which they will be able to evaluate if they

have been properly interpreted. However, as most sources used will not be able to read the actual report,

the credibility will mostly depend on the writer’s ability to interpret sources correctly. The process of

ensuring credibility can be read from appendix 2.

Transferability relates to the degree to which results from one context can be transferred to another

(Heldbjerg 2003, p.22). This means that attention should be paid to the question if e.g. the writer’s findings

from the historical analysis can be transferred directly to the future cash‐flow. This will mainly be discussed

in connection with forecasting drivers on the basis of the strategic analysis. As with credibility, the process

of ensuring transferability can briefly be read from appendix 2.

Dependability relates to the degree to which different researchers reach the same conclusion provided

that they possess the same values and use the same method. By comparing different researchers

interpretations it is possible to identify consistent elements, which all other things being equal, should be

the most reliable (Heldbjerg 2003, p.22‐23). As far as possible the writer will endeavour to investigate to

which extent others reach the same conclusion. This will be done in among other ways by looking into

available research within the area in question. However, even though some qualitative issues are briefly

discussed in published equity research, the writer will be the only one carrying out a public in‐depth

strategic analysis of FLS in connection with this specific report. Therefore it might be difficult to ensure that

dependability is reached, for which reason the quality of the report according to this factor could be

questioned.

Last but not least, confirmability relates to the degree to which bias based on behalf of the writer’s value

system can be shunned. In other words, the goal is not to shun out value systems, but to shun out bias by

expounding the writer’s values and hence explaining how interpretation and conclusions have been

reached. Through this the reader will be able to evaluate if the interpretation and conclusions are assumed

to be reasonable (Heldbjerg 2003, p.23). As an introductory comment it seems relevant briefly to evaluate

which values might bias the writer’s conclusions if not paid attention to. First and foremost, the writer does

not own any shares in FLS which could otherwise unconsciously make him overly optimistic on their

outlook. However, as the writer does own shares in other companies and as he will be looking for a full

time job in only two years, he might be biased towards an anticipation that the general economy and hence

13

the stock markets will turn soon. Confirmability will furthermore be attempted reached by letting others

using the same methodological approach and with knowledge within strategic analysis read the report4.

As mentioned earlier, the report will also be based on a quantitative research design – especially in

connection with calculating the cost of capital and doing the valuation. For this reason the quality of the

report also depends on internal validity, external validity, reliability and objectivity. Internal validity is a

question of the extent to which the writer measures what he actually set out to measure, hence connected

to the sample size and if this leads to a valid result. External validity on the other hand, is a question of the

extent to which the results can be generalized across the remaining part of the population in question.

Reliability is a question if the exact same result would be reached if the same analysis was to be carried out

in exactly the same way all over again. Last but not least, objectivity relates to the researchers ability to

put aside subjective values in order to reach an objective conclusion (Heldbjerg 2003, pp. 20‐21). In order

to make sure that the above mentioned quality factors in connection with the quantitative analysis are kept

at a certain level, the researcher will continuously attempt to evaluate the level of validity, reliability and

objectivity.

4 Among others, fellow student Jakob Warnecke. This did not lead to any changes.

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4. Historical financial analysis In the following, the historical accounts will be analyzed in order lay the foundation for estimating the

future development and hence value of FLS.

4.2 Reorganizing accounting statements As the annual accounts as delivered in the actual annual report are not formulated for use in analyzing the

historical performance of FLS, some reorganization has to be made before a meaningful historical analysis is

possible. This is done, for among other reasons, to reflect economic profit rather than accounting profit.

Before doing this it is important to make sure that historical numbers are comparable by making

corrections for any changes in accounting policies which might have been. The process of this can be read

from appendix 3.

4.2.1 Reorganizing the balance sheet – analysis of invested capital In order to calculate the invested capital, the balance sheet must be reorganized as illustrated in appendix

4. This is done due to among other things, the fact that operating and nonoperating performance are not

distinguished among in the actual annual report, hence increasing the risk for considerable bias. This can be

done in two ways – the operating method (operating assets – operating liabilities) and the financing

method (debt + equity) (Koller et al. 2005, pp.165‐166). Both methods are used in order to reach total

funds invested which are compared in order to assure consistency.

Table 4.1: Invested capital summary

Source: Own representation

According to table 4.1 invested capital excl. goodwill has generally been rather low and even turned

negative in 2005 and 2006. This is among other things due to large prepayments from customers which

typically pay 10‐15% of the contract sum up front (FLSmidth 2009a, p.6). Turning to total funds invested

they have increased dramatically during the recent five years, which is mainly due to a large acquisition in

2007 (FLSmidth 2008b). However, as the acquisition to a large extent was financed by excess cash, total

funds invested did not increase as dramatically as could otherwise have been the case.

4.2.2 Reorganizing the income statement – analysis of NOPLAT Similar to invested capital, which does not distinguish between debt and equity as investor funds, the

income statement must be reformulated to end up with NOPLAT, which unlike the net income does not

distinguish between profits available to equity and debt holders. Hence, through this it is possible to

analyze the operating income generated by the invested capital (Koller et al. 2005, pp.162‐163).

2004 2005 2006 2007 2008

Invested capital (excl. goodwill) 1350 ‐271 ‐396 706 649

Invested capital (incl. goodwill) 1638 81 76 6446 6626Total funds invested 2928 2858 3027 7324 7110

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Table 4.2: NOPLAT summary

Source: Own calculation

From the reorganization of the income statement included in appendix 5 and according the summary in

table 4.2, it is clear that even though the revenue, as well as net income, has been increasing throughout

the recent four years, NOPLAT peaked in 2007. However, this was simply due to a historically large increase

in deferred taxes in 2007.

4.3 Free cashflow analysis In connection with valuation, the free cash flow5 is interesting, as this shows the cash flow available not

only to equity holders but also debt holders, and hence is not affected by either financing or nonoperating

items. To calculate FCF, NOPLAT and noncash operating expenses are added after which investments in

invested capital are subtracted. In other words – FCF is equal to the difference between gross cash flow and

gross investments (Koller et al. 2005, pp.164, 178‐182).

Table 4.3: Free cash‐flow summary

Source: Own calculations

From appendix 6 and as summarized in table 4.3, it is seen that FLS has had a fluctuating FCF during the

recent four years. In 2007 the company realized a considerable negative FCF mainly due to investments in

operating working capital together with the previously mentioned acquisition and through this investment

in goodwill and other intangibles. Similarly, 2005 is not evaluated to give a fair view as operating working

capital decreased abnormally much, hence affecting FCF positively. In other words, 2006 and 2008 are

evaluated to give a more fair view of the long term situation with an average reinvestment ratio between

15‐21%.

4.4 Return on invested capital analysis After having reorganized the accounting statements it is now possible to analyze ROIC, which is the ratio of

NOPLAT relative to invested capital. Other measures which could have been analyzed are ROE and ROA, but

opposite to ROIC which is only affected by the operations, they are also affected by capital structure (Koller

et al. 2005, p.183).

5 For the remaining part of the report simply denoted FCF

2005 2006 2007 2008

NOPLAT 285 707 2073 1797

2005 2006 2007 2008

Gross cash flow 421 837 2203 2052

Gross investment 1421 ‐125 ‐6500 ‐434

Free cash flow 1842 712 ‐4297 1617

Reinvestment ratio ‐337% 15% 295% 21%

16

As invested capital is calculated at a certain point of time (here ultimo 2008) an average of invested capital

ultimo 2007 and 2008 is calculated in order to reach a figure which relates to the average invested capital

during 2008 (Koller et al. 2005pp.183‐184).

Furthermore, ROIC is calculated without goodwill as this best measures internal performance and hence is

not distorted by large fluctuations in goodwill as is the case in 2007. For the same reason, ROIC excl.

goodwill is a better measure when analyzing a trend or comparing it to a peer group as is the case in this

report. Contrary, ROIC incl. goodwill6 would be a better measure when analyzing the performance for

shareholders (Koller et al. 2005, pp.183‐184).

During the recent four years ROIC has fluctuated greatly. Decomposing ROIC as done in appendix 7 shows

that the operating margin has been increasing steadily from 4% in 2005 to 11% in 2008. First and foremost,

this is due to lower COGS as well as SG&A relative to revenue, which is mainly attributable to a high

revenue growth during the period. Hence, due to a certain amount of fixed costs, COGS and SG&A now

make up a smaller amount relative to revenue.

While the operating margin has increased steadily, average capital turnover has fluctuated considerably. As

mentioned earlier, FLS generally has a low level of invested capital, which is mainly due to large

prepayments and hence low or even negative working capital. For the same reason, ROIC fluctuated

considerable during 2006 and 2007, which was mainly due to changes in average operating working capital

which turned negative in 2006. At the same time, both fixed assets as well as other assets relative to

revenue have had a decisive effect on ROIC.

Calculated directly as NOPLAT relative to average invested capital (table 4.4) furthermore illustrates how

the mix of rapidly increasing NOPLAT together with a generally low (or even negative) average invested

capital has had affect on ROIC.

Table 4.4: ROIC calculated

Source: Own calculation

According to Elling, evidence show that companies operating in a market defined by an oligopoly or

monopolistic competition, tend to direct their focus on either operating margin, capital turnover or both

(Elling, Sørensen 2004, pp.111‐114). As will be explained later, FLS is evaluated to operate under exactly

that – monopolistic competition – for which reason the above picture fits well with FLS.

6 Calculated for the reason of comparison in the worksheet called “ROIC” in the base scenario Excel file.

2005 2006 2007 2008

NOPLAT 285 707 2073 1797

Avrg. Invested Capital (excl. Goodwill) 539 ‐333 155 678

ROIC (excl. Goodwill) 53% ‐212% 1335% 265%

17

4.5 Revenue growth analysis Assuming that both profit margins and reinvestment ratios stabilize in the long run, the long‐term cash flow

growth will stem from the long term growth in revenue. Hence, analyzing the components behind historical

growth might help set the scene for future growth potential. As the basis for the revenue growth analysis

data has been gathered in a table and included in appendix 8.

During the recent five years the revenue in the cement division has increased 68% – from DKK 8,1 billion in

2004 to DKK 13,6 billion in 2008. The strongest development has found place in South America and Europe

(excluding Scandinavia) in which sales have increased 349% and 122% respectively. It is also clear that

today Asia is clearly the most important market for the cement division, with more than double the size of

the second largest market.

During the same period, sales in the mineral division increased an impressive 550% from DKK 1,6 billion in

2004 to DKK 10,3 billion in 2008. Opposite to the cement division, the mineral division has realized growth

within all markets – most in North America and Europe (excluding Scandinavia) which increased 1327% and

764% respectively.

Customer Services are slowly making up a larger part of (Rasmussen, FLSmidth 2008) the order intake

(Rasmussen, FLSmidth 2008) and through this, sales – from 11% ultimo 2005 to 22% ultimo 2008. This is in

line with management’s strategic focus on the area, as after‐market sales7 have higher margins and is less

cyclical than the initial orders (Rasmussen, FLSmidth 2008, slide 3, Paulsen 2009).

An analysis of organic growth versus growth obtained through acquisitions would furthermore have been

preferable. However, FLS has not disclosed sufficiently enough information to make this possible (Paulsen

2009, 4. March). Furthermore, the company has continuously made smaller acquisitions for which reason

(if this was possible) the work connected with decompose revenue growth is evaluated to outweigh the

analytical benefit of doing so. This is especially the case as revenue will not simply be estimated on the

basis of recent years’ development.

All in all, due to the extreme development within minerals, there is now a more balanced weight between

the two large divisions in FLS, which means that the company is no longer as dependent on the market for

cement. On a group level sales grew 140% during the last five years.

7 Customer service contracted after the delivery of the initial order

18

4.6 Weighted average cost of capital (WACC) In order to value FLS the cash‐flow must be discounted by the weighted average cost of capital8, which is

the opportunity cost that investors face when investing in FLS as opposed to other companies with similar

risk. Hence, the following formula can be denoted:

1 (, p.292Koller et al. 2005)

Where, and = Target level of debt and equity respectively against the market enterprise value

1 = Cost of debt after the marginal income tax rate

= Cost of equity Before calculating the WACC, it is important first to decide if a static or dynamic WACC is to be used. There

is no doubt that a dynamic WACC would theoretically be the most correct solution, as this would take

account of changes in e.g. interest rates and capital structure. As changes in these factors are not assumed

to be reliably estimated from year to year, problems with dependability would occur. Furthermore, using a

dynamic WACC would also mean that the DCF and EVA models would lead to two different solutions.

Hence, in order to ensure the quality of the analysis and consistency between DCF and EVA is wished, a

static WACC is evaluated to be usable. This must be kept in mind when calculating the WACC, as all

components must be estimated to fit the long term picture and hence not be biased by short term

deviations due to e.g. the financial crisis. This is done in order to limit problems connected to

transferability.

As there are many different ways of calculating each variable of the WACC, they will be estimated one by

one and at the same time reasoning for the choice of method will be given.

4.6.1 Cost of equity One method for calculating the WACC is the capital asset pricing model9. CAPM has been criticized as some

empirical evidence has shown that the basic assumption that there is a positive linear relationship between

beta and expected return does not hold (Eugene, Kenneth 1992, p.428). Furthermore, very few guidelines

are connected to the model, as it does not provide any rules for estimation of any of the variables (Koller et

al. 2005, pp.295‐296).

Another method for estimating cost of equity is the Fama‐French three‐factor model which estimates risk

as the stock’s sensitivity to three portfolios – the stock market, a portfolio based on firm size and finally a

portfolio based on book‐to‐market ratios. The Fama‐French three‐factor model was only first put forward

8 For the remaining part of the report denoted WACC

9 For the remaining part of the report denoted CAPM

19

in 1992, for which reason it is seen as rather new in a theoretical perspective (Koller et al. 2005, pp.315‐

317). Even though the model is based on strong empirical results, it still leaves many important questions

and criticism unanswered. Some furthermore argue that the evidence supporting the model was incorrectly

measured (Koller et al. 2005, p.318).

A third alternative is the arbitrage pricing theory (APT) which is more or less a generalized version of the

Fama‐French three‐factor model. It has never won strong foothold and as with the other alternatives is still

the reason for a great deal of discussion with regards to the theoretical background (Koller et al. 2005,

p.317).

As CAPM, both the Fama‐French three‐factor model and the APT are unsuccessful in providing rules for

estimation of the variables used. On the basis of the above, the writer accepts that no method is perfect,

and choose to use the CAPM, as it is based on solid theory and is the most widely used and best developed

method.

CAPM is defined as,

(Koller et al. 2005, pp. 294‐295)

Where the expected return ‐ ‐ is a function of: The risk‐free rate

The stock’s sensitivity relative to the market

The risk premium which is equal to the expected market return minus .

4.6.1.1 Estimating the riskfree rate To estimate the risk‐free rate, a long‐term government bond will be used. Even though no government

bond is completely risk‐free it will be used as a proxy for the risk‐free rate. Ideally, each cash‐flow should be

discounted by bonds with similar maturity as that specific cash‐flow. However, as this is rather impractical

and as it is assumed to have little effect on the fair value, a single yield to maturity of 10 years is used

(Koller et al. 2005, p.296). As FLS is a Danish (European) company and most of the debt is placed within

Europe (FLSmidth 2008a, p.85), the German government bond will be used as it is more liquid and has

lower credit risk than most other European bonds including the Danish (Koller et al. 2005, p.296). According

to appendix 9 the 10‐year German government bond rate is currently at historically low levels for which

reason it is evaluated to underestimate the long run risk free rate. In order to reach a risk‐free rate which is

estimated to better fit the long term picture, an average of the last 5 year‐end risk free rates will be used.

This leads to a risk‐free rate of 3,6%.

4.6.1.2 Estimating the market risk premium For several reasons the risk premium (RP) is difficult to estimate, which is also why it has been one of the

most debated aspects of finance, and why no one single method has yet gained universal acceptance. One

20

way would be to regress the market return against market variables such as the overall dividend‐to‐price

ratio, and through this derive at a RP according to the current levels. However, according to Koller et. al. no

long run trend is observable (Koller et al. 2005, p.299). The most widely used method among financial

advisors is to estimate RP on the basis of historical data (F.Brune et al. 1998, p.18). However, it assumes

that risk aversion has not changed over the years, and that previous years’ development, and hence

economic progress and inventions, are a reliable picture for the future. As already mentioned, the first

assumption is assumed to hold according to Koller et. al. Secondly, the writer assumes that historical data

and events are in fact good indicators of the future, that among other things new ground‐breaking

inventions will find place, and hence that there is no problem with transferability. For good reasons we are

not able to see into the future, and hence have no reason to believe that ground‐breaking inventions will

not find place in the future. The writer takes the point of view that we as humans do not have the

imagination to comprehend future possibilities before they are there. As an example, in 1899 the U.S.

Patent Office Director stated that “Everything that can be invented has been invented”, and in 1956 IBM’s

President at the time, Thomas J. Watson, stated that “I think there is a world market for about five

computers” (Pressman 2008, p.39). These examples demonstrate that even people close to the matter in

question are often not capable of understanding the possibilities of the future.

For the reasons above the writer chose to rely on a historical risk premium. Hence, when in the middle of a

financial crisis which we have not seen as bad since the deep depression in the 1930ies, it seems relevant

to make sure a long term risk premium includes such rare events. If not, problems with both internal and

external validity would occur. Problems with respect to internal validity is evaluated to be, that using

relatively short datasets would not enable the estimation of a long term RP but rather the RP during the

recent 40 years10. Even this would probably not even be the actual RP this given period, as it according to

some would also have problems with survivorship bias. All this is naturally interconnected with external

validity, as a RP calculated on a short dataset is not evaluated to be generalized on the future. As long

enough datasets were not available, estimates of others will be relied on. This due to the reasoning given in

section 3.6 “Quality of the analysis” – “own estimations and calculations are only relied on provided that

they are evaluated to be as good as or better than those of others”. During the years an uncountable

number of academics have attempted to estimate the actual RP and reach consensus about what it is and

how it is to be calculated. As even the vaguest agreement has still now been reached, it would not be likely

for the writer to come up with an estimate better than theirs. To sum up, for the sake of ensuring the

10 Using Datastram usable data only goes back to 1969 which is not assumed to be long enough

21

quality of the analysis a risk premium calculated by an external source on the basis of long data sets is

preferred, opposed to the writer calculating it just for the simple reason of doing it.

Koller et. al. estimate the RP calculated on data from 1926‐1996 and corrected for survivorship bias to be

between 3,5‐4,5% (Koller et al. 2005, p.303). A recent study among Danish banks and other financial

institutions showed that a RP of 4,5% was most widely used (PricewaterhouseCoopers 2008, p.2‐5). For

these reasons the RP is set at 4,5%.

4.6.1.3 Estimating FLS’ sensitivity to the market (β) According to CAPM the expected return of the stock is driven by beta, which in contrast to both the risk‐

free rate and the RP differs among firms. Beta will be estimated by regressing the return of FLS’ against the

markets return with the following model,

(Koller et al. 2005, p.306)

As the overall market return is not directly observable, a value‐weighted and well diversified index will be

used as a proxy for the market return. Evidence of empirical test argue that monthly data and at least 60

data points lead to the best results, for which reason this guideline will be followed (Koller et al. 2005,

p.307).

However, as raw regression only gives an estimate of beta, it will improved. One way to do so is to derive

an unlevered industry beta and then relevering it according to FLS’ target capital structure. However, as FLS

to a certain extent still has features of the “old” conglomerate like business structure, it has a very unique

composition that is partly related to the cement industry, partly related to the mining industry, and to a

smaller extent also related to the building material sector. As no direct comparable competitors exist, an

adjusted beta will be derived using another rather simple smoothening technique used by Bloomberg:

0,33 0,67 (Koller et al. 2005, p.314)

This smoothening technique relies of the empirical evidence first put forward by Blume, which show that

betas tend to revert to the mean of 1 (E. Blume 1975, p. 785).

To choose which index to use, betas for a range of value weighted indexes are calculated and compared as

illustrated in table 4.5.

Table 4.5: Beta alternatives

Source: Own representation and calculations on the basis of data from Bloomberg, 28.02.09

Corr. Std. dev. Beta raw Adj. Beta R2

MCSI World 0,7063 0,0473 1,7460 1,4998 0,4989

OMXC20 0,6950 0,0570 1,4247 1,2845 0,4831

DJ Ind. avrg. 0,5819 0,0399 1,7056 1,4728 0,3387

S&P 500 0,6489 0,0427 1,7776 1,5210 0,4211

Index measures again FLS

22

As FLS is a Danish company intuitively it might seem appealing to regress it against OMXC20. However, this

will lead to several problems. OMXC20 is biased towards e.g. shipping which will contribute with a much

larger effect on the index than the industry does on the overall market. Also FLS itself is part of the

OMXC20 which might also distort the picture a bit. For these reasons OMXC20 will not be used. Regressing

FLS against MSCI World results in the highest (0,4989) with a raw β of 1,746. According to the statistical

regression analysis which is included as appendix 10, the regression against MSCI World is evaluated to be

usable.

A beta of 1,746 is in the higher end of the four alternatives and intuitively seems a bit high as this according

to calculations as of 2003 leaves FLS’ beta on par with semiconductors and telecom equipment

manufacturers (Koller et al. 2005, p.311), which all other things being equal are evaluated to be more risky

than FLS. Applying Blume’s smoothening technique leads to an adjusted beta of 1,4989 which seems more

fair for which reason this will be used to calculate the WACC.

4.6.2 Cost of debt As FLS does not directly disclose its cost of debt and as the information regarding debt and interest

disclosed in the annual reports is insufficient to estimate their cost of debt directly, the writer will estimate

it through an indirect method. One way of doing so is to take the company’s credit rating and use the

average yield to maturity on a wide range of long term bonds with a similar rating. However, as seen in

appendix 11 corporate bond spreads have skyrocketed during the financial crisis and are currently at

abnormally high levels. As this is not assumed to fit the long run picture, hence potentially leading to

problems with transferability, yield spreads calculated by Koller et. al in December 2003 are used (Koller et

al. 2005, p.320).

As FLS is not credit rated, the writer will estimate it from a comparison

with their peer‐group11. Even though this leads to some problems with

transferability, the procedure is used in the lack of better alternatives.

From table 4.6 it is made clear that competitors are relatively

consistently rated A. For this reason, and due FLS’ sound financial health

as concluded in the historical financial analysis, it is assumed it to be

plausible that FLS would have a similar rating and hence spread.

The average marginal tax rate during the recent 5 years is estimated at 30,2% (3 percentage points above

the average Danish company tax level during the period) which will be used onward. As information

11 The composition of the peer‐group will be discussed in detail in section 7.6 “Peer‐group analysis”

Table 4.6: Peer‐group credit ratings

Source: Own representation on the basis of data from {{72 Strandard & Poor's 2009}}

Peer‐group S&P Spread

Metso BBB 1,02%

Sandvik A 0,48%

SKF A 0,48%

Atlas Copco A 0,48%Assa Abloy A 0,48%

Average premium 0,49%

Chosen premium for FLS A 0,48%

23

regarding marginal tax is not made readily available in the annual report, this is based on information from

Equity Analyst, Lars Terp Paulsen who has discussed the matter with FLS’ IR Manager, Pernille Friis

Andersen. The reason why FLS marginal tax rate is higher than the current Danish tax rate of 25% is due to

the fact that FLS pays tax in other countries besides Denmark.

Adding the 0,48% spread to the risk free rate of 3,6% and subtracting tax, leaves leads to an after tax cost

of debt of 2,85%.

4.6.3 Target capital structure From 2004‐2008 the debt to market value ratio has fluctuated between 1,5‐16%. During the recent couple

of years FLS has increased its debt due to acquisitions. The net debt peeked in 2007 but due to a declining

market value in 2008 the debt ratio continued to increase. FLS has proposed not to pay out dividends in

2008 as they would rather use the money for strategically clever acquisitions (FLSmidth 2009a, p.11). FLS

has a goal to operate with an equity ratio of 30% (equity ratio in 2008 was 24%) but as this is measured at

book value it is of little information to us other than they expect to increase debt from current levels

(FLSmidth 2009a, p.11). On the basis of an assumption that FLS will engage in further acquisitions in the

long run, the debt ratio is set at 15%, which is considerably above the five year average of 7,18%.

4.6.4 Calculating WACC Using the results above leads to a WACC of 9,22%. In order to investigate if this might be affected by the

writer’s potential value bias, and hence to ensure confirmability, the estimated WACC is compared with a

wide range of estimates used by analysis as well as other financial sources as illustrated in table 4.7.

Compared to the average analyst’s WACC of 10,2% the estimated WACC is slightly lower.

Table 4.7: Estimated WACC compared with analysts’ approximate average

(Paulsen 2009, interview 14. Jan., Own representation on the basis of data from Euroinvestor , 16. Jan., Bloomberg , 17. Jan.)

Historical Forward Analysts'

average choice average

Debt‐ratio 7% 15% 13,50%

Equity‐ratio 93% 85% 86,50%

Beta 1,04 1,50 1,16

Risk‐free rate 3,60% 3,60% 4,21%

Risk premium 4,50% 4,50% 5,48%

Cost of equity 8,28% 10,35% 10,62%

Cost of debt (pre‐tax) 4,08% 4,08% 4,31%

Marginal tax rate 30,20% 30,20% 29,20%

WACC 7,82% 9,22% 10,2%

24

However, as several of the analysts estimates were gathered in the beginning of January, there is a good

chance that some of them have changed. Furthermore, as they use different methods for estimating each

variable they are not directly transferable. As an example Jyske Bank uses a qualitative beta rather than a

quantitative beta (Paulsen 2009, 4. March 2008). Furthermore, some use a illiquidity premium which the

writer has not chosen to do, as FLS is a OMXC20 company and hence among the 20 most traded stocks in

Denmark, for which reason the illiquidity premium is evaluated to be close to nonexistent. Last but not

least, some are assumed to make use of a dynamic WACC which would presumably lead to a higher WACC

in the current market situation. Due to the factors just mentioned, there are no reasons to believe that

their estimations of WACC are necessarily better than the writer’s or that the estimated WACC is biased by

values, for which reason the static WACC of 9,22% as calculated is used.

4.7 Preliminary conclusion On the basis of the historical financial analysis, FLS is identified as having realized an impressive

development during the recent five years – a development which among other things has made even large

acquisitions possible. Through this FLS has reached a more balances and hence less risky business profile

compared to a few years ago. All in all, FLS is evaluated to be in a good shape to handle a period with low

activity.

25

5. Businessasusual scenario valuation On the basis of the historical financial analysis, a rather simplistic valuation will be carried out in order to

identify the value of FLS in a business‐as‐usual scenario – that is, if things continue to develop as they have

during the recent five years. Even though this seems rather optimistic, this fair value will be a valuable

comparison when making the final valuation at a later point, in which strategic considerations and other

changes will be taken account of. Hence, the difference between the “simplistic” and “proper” valuation

will demonstrate the fair values effect of going from a business‐as‐usual to a base scenario.

The development in all items but few is simply extrapolated into the detailed forecast period on the basis

of the average historical development. Items deviating from this procedure are discussed in appendix 12.

On the basis of the above and according to the valuation summary in appendix 13, the fair value in the

business‐as‐usual scenario is estimated to be DKK 1110, which is far above the share price of DKK 139 on

the cut‐off day. The large difference is a natural consequence of the recent months’ development in among

other things the general economy and commodity prices, as well as a change in FLS’ outlook, which means

that investors are fully aware that the impressive performance during the recent five years is coming to an

end.

In the following a strategic analysis will be carried out in order to paint the picture of the changing market

situation, in order to make a credible valuation which incorporates strategic changes possible.

26

6. Strategic analysis The strategic analysis will be based on a top‐down approach in which a broad analysis is made to start with

after which specific factors are analyzed in connection with FLS’ industry and afterwards factors inside the

company are looked at.

6.1 Dynamics of the industry Before starting the strategic analysis, it is crucial first to have an idea of the dynamics of the environment –

that is the level of turbulence – as this defines if an emergent12 or prescriptive13 approach to strategy can

be applied, and hence which models are usable. To do so, the Degree of Turbulence model, rates the

environmental turbulence on a scale from 1‐5 (1 being the least turbulent) on two overall factors –

changeability and predictability (Lynch 2006, p.82). A graphical understanding of the model can be obtained

from appendix 14.

The first overall factor changeability, relates to the degree to which the environment is likely to change. It

is rated according to complexity (the degree to which the company is affected by external factors) and

“familiarity of events” (the degree to which the environment present the company with completely new

situations) (Lynch 2006, p.82). With regards to the complexity, FLS is evaluated to be affected on a global

level, as the turnover is highly dependent on among other things the world GDP growth as well as

commodity prices. However, the familiarity of events are evaluated to be familiar to FLS, as the cement and

mining industries are relatively low‐tech, and has not changed that much over the recent decades.

Turning to the predictability which relates to the degree to which changes discussed above are predictable,

the rapidity of change is evaluated to be somewhere in‐between slower than response and comparable to

response. When the market changes it happens relatively fast. E.g. declining metal prices will immediately

have a readable affect on investments in new equipment by mining companies and hence FLS’ order intake.

However, as most manufacturing has been outsourced, FLS has a flexible cost structures and is able to

easily scale back their activities (FLSmidth 2008a, p.38). Finally, with respect to the visibility of the future it

is evaluated to be forecastable. Changes in the overall factors affecting FLS are somewhat forecastable, and

hence make it possible for FLS to act accordingly. Furthermore, the lead times from customers’ placement

12 In an emergent approach to strategy the objective is unclear and elements are developed continuously as the strategy develops

(Lynch 2006, p.43). This is approach is normally used by companies in turbulent environments as long term planning on the basis of past/present information is meaningless. 13 In a prescriptive approach to strategy the objective has been identified in advance and the main elements have been developed

before the actual strategy is developed (Lynch 2006, p.38). Contrary to the emergent approach, this approach is used by companies in dynamic environments.

27

of orders to fulfillment is 2‐3 years and with a record order backlog at hand14, FLS can relatively accurately

predict their level of activities in the short run.

According to appendix 14 this leads to a level of turbulence rated at 2,5, which relates to an environment

which is neither completely stable nor turbulent. For this reason the following strategic analysis will be

based on the prescriptive approach and the models accordingly, but with a few alterations on other to

make room for changes.

6.2 External analysis In the following the external aspects of the strategic analysis will be covered. That is, an analysis of the

general environment using the PEST model and an analysis of the industry using Porter’s Five Forces model.

6.2.1 PEST In order to analyse the general environment a PEST analysis will be carried out. As the PEST analysis in its

basic form describes the past/present situation and events, the user must agree that this situation is

transferable to the future (Lynch 2006, p.84‐85). The more turbulent the environment in question is, the

more difficult it is to forecast the future from past events. Hence, as the degree of turbulence was

evaluated to be medium, simply using past events to forecast the future is evaluated to lead to problems

with transferability.

For this reason the PEST analysis will be altered and carried out in three steps, instead of just one step

which would give a static picture of what the situation looks like here and now. Each macroeconomic factor

will be graded on a scale from 1‐5 ranging from a positive to negative situation for FLS. In connection with

this it is important to underline that grading should only be evaluated relative (not absolute) to historical

and future levels and in order to assess if the situation changes to the better or the worse. Furthermore,

this is done both in a historical perspective covering the recent five years and hence equal to the years

covered by the historical financial analysis, as well as in an expected future perspective. The future

perspective will furthermore be divided into the short run (SR) equal to the detailed forecast period (2009‐

2013) and the long run (LR) equal to the key forecast period (2014‐2023). In this way the distinction is

intended to contribute with valuable information in connection with the actual forecasting. By quantifying

each factor it is assumed to be easier to understand which factors have affected FLS positively/negatively in

the past and how they are expected to change in the future.

14 Appendix 15

28

In the following only the most important factors will be discussed in detail. An overview of a wider set of

macroeconomic factors evaluated to affect FLS, together with the grading of all factors, are included in

appendix 16.

6.2.1.1 Political factors Among the political factors is political stability (or more seriously – the lack of) in developing countries.

This is of utmost importance for FLS, as 67% of the revenue generated in 2008 stem from developing

countries (FLSmidth 2009a, p.8). However, FLS is well aware of the risks associated with this and through

many decades of doing business in these countries, has built up valuable knowledge. Among other things,

FLS has established well defined crisis plans to protect employees in the event of emergency in one of the

countries in question. Last but not least, in some cases the company has taken insurance to cover political

risk (FLSmidth 2008a, p. 38). As research show that the political stability on an overall world level has been

rather stable since 1996 (Kaufmann, Daniel Kraay, Aart Mastruzzi, Massimo 2008, p.24), there are no

reasons to believe that the overall situation is expected to improve in the future. In the lack of better

alternatives the writer assumes this also to hold for developing countries isolated seen as well, even though

the transferability of such statements can clearly be questioned.

Another factor that affects FLS is enforcement of new laws. These years it is mostly environmental laws

which draw the company’s attention. For one thing, cement factories are heavily polluting. According to a

WWF report, cement factories were estimated to be responsible for not less than 8% of the global CO2

emission in 2006, and that it will rise from 2 gigatons today to 5 gigatons by 2050 (Dyrskjøt 2008, p.22).

WWF is evaluated to be somewhat biased towards painting an overly negative picture, for which reason the

level of credibility could be questioned. However, the conclusion of the report is still evaluated to give a

basic idea about the scope of the problem. As more and more countries and politicians begin to pay

attention to environmental problems, this will clearly be a subject of improvement in the future. Even

though this might seem as a threat to customers, for FLS as a supplier this is an opportunity, as it opens

new possibilities for doing business. However, until now heavily‐polluting industries such as the cement,

steel and chemical industries have been protected against otherwise strong requirement to lower CO2

emission in the coming years. This is the result of a fear that these industries under strong regulation would

be forced to move out of regulated areas and into less regulated countries (Børsen 2008, p.2). As this would

clearly not help lower the CO2 emission but simply move the problem, special protracted adjustments are

worked on. However, as the cement industry is well aware of the environmental problems they take part in

causing, they themselves are taking initiatives to change things to the better in order to prevent politicians

29

from introducing even stronger regulation (Dyrskjøt 2008, p.22). Even though politicians have been slow to

introduce regulation on the cement industry in the past, this is expected to change in the long run.

6.2.1.2 Economic factors During the recent five years the average world real GDP growth rate has been 2,5% ‐ somewhat below the

long term average of 3,35% when using data for the recent 50 years15 (Bureau of Economic Analysis (BEA),

U.S. Department of Commerce 2009). However, due to the financial crisis and according to estimates from

Morgan Stanley, world GDP growth is expected to contract 1,9% in 2009 in a base scenario which would be

the first contraction in 60 years. Hereafter it is expected to return to 2,6% in 2010 (Fels, Pradhan &

Andreopoulos 2009, p.5).

Due to the financial crisis many governments are putting forward plans to increase public spending. Even

though this would be positive for FLS’ customers, such initiatives are evaluated to have close to no

observable effects on FLS. First and foremost, customers now have free capacity which would have to be

activated before investing in additional capacity. Furthermore, FLS is only indirectly affected by such

initiatives as an eventual effect would it would appear as small waves be pooled together with orders which

would have been no matter what (Paulsen 2009, 9. Feb.).

Commodity prices have been roaring for several years, with the oil price increasing to a peak of index 400

compared to 2003 levels and metal prices peaking at index 350 (International Monetary Fund October

2008, fig. 3,1, p.85). Since then prices have come down considerably. Lower oil prices makes it cheaper (but

still rather expensive and impractical) to transport cement instead of producing it locally, hence removing

pressure from new investments in equipment. With regards to declining metal prices, it decreases the

feasibility of exploration in certain mines, leading to a drastic decline in new mines and direct closing of

some already operating mines. All in all, this naturally puts pressure on the demand for FLS’ equipment.

Even though IMF estimate that both the price of oil and metals will go up from the current levels in the

short run, it is still evaluated to be below recent years record levels (International Monetary Fund 2009,

p.3). However, due to constrain access to a wide range of commodities together with a continued high

demand especially from developing countries, commodity prices are expected to increase to high levels

again in the long run.

Last but not least, it seems relevant to briefly mention inflation which has been between 4‐6% on a world

level during recent years (International Monetary Fund 2009, p.4). According to Morgan Stanley inflation is

expected to decrease considerably in 2009 to 1,5% in a base scenario after which they expected it to

15 Data analyzed in the Excel spreadsheet called “GDP” in the base scenario file

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increase once again to a moderate level of 2,9% in 2010 (Fels, Pradhan & Andreopoulos 2009, p.6). With

increased public spending and an expansionary monetary policy, there is a risk that inflation will increase

considerably during the years following 2010 as the general economy starts to recover. However, as it is

still not clear if this will actually happen and as commodity prices are only expected to increase moderately

in the short run, inflation is assumed to remain in the medium range in both the short and long run.

6.2.1.3 Social factors Major demographic changes are taking place in the developing countries these years. As an example these

countries are experiencing a rapidly growing middle class – a trend which is expected to continue in the

future. According to IMF the middle class in developing countries is expected to increase from

approximately 400 million in 2008 to 1,2 billion by 2030 (FLSmidth 2008a, p.28). As this trend is an

important driver for economic growth, the outlook for consumption of both cement and minerals is still

very positive in the long run (FLSmidth 2008a, pp.8, 24, 26).

6.2.1.4 Technological factors The increasing focus on environmental issues is opening new possibilities for product development –

especially within cement. FLS has had focus on this area for several years and through partnerships with

DTU and Højteknologifonden is currently working on a project concerning alternative energy usage in the

production of cement. A solution has already been found, but still needs to be tested in practice. Another

solution that is already on the market is the so‐called hotdisc‐technology which reduces oil consumption

and CO2 emission with as much as 30%. According to Jørgen H. Rasmussen, CEO of FLS, energy consumption

is always the first subject when discussing new systems with customers – the second is emission (Hansen

2008b, pp.4‐5). FLS is far in front of their competitors on this aspect, which might give them a first mover

advantage.

These years many companies are outsourcing production and off‐shoring work to low‐cost countries which

is made possible due to the technological development and globalization in general. FLS is part of that

trend. As 80‐90% of manufacturing is out‐sourced, in‐house manufacturing is kept at a very minimum

(FLSmidth, Tofte 2008). This is seen as both a strength and a weakness for FLS. During periods of high

growth like the industry has experienced during the recent years, the high level of outsourcing has lead to

longer lead‐times as the delivery of some critical parts have been constraint (FLSmidth, Tofte 2008). As the

delivery time is crucial when customers search the market for suppliers, this might have led to the loss of

potential orders. However, when the market suddenly turns and presents the industry with more difficult

times, FLS can relatively easily scale back activities and costs, as the high level of outsourcing leaves FLS

with a very flexible cost structure. FLS has furthermore made use of off‐shoring of work to India in order to

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get access to qualified employees as well as lower costs. In January FLS announced that they would lay‐off

600 employees equal to 6% of the workforce by the end of 2009. Lay‐offs were placed mainly in Denmark

and the US (Risom 2009). In connection with this FLS is expected to use the opportunity to off‐shore even

more work to India when the need for employees starts to build once again, which seems in line with FLS

own indications (FLSmidth , 15. min. in).

6.2.1.5 Conclusion on the PEST analysis From the PEST analysis it is clear that general environment is presenting FLS with changing situations.

According to the grading in appendix 16, and as summarized in table 6.1, the situation is expected to

remain close to stable only in the short run, while in the long run factors from the general environment are

evaluated to develop to the advantage of FLS. Having said that, economic factors are evaluated to be of the

largest significance for the performance of FLS, for which reason the development in these factors are

evaluated to better explain FLS’ outlook. Looking at the economic factors seen isolated, they are evaluated

to worsen considerably in the short run, while returning to a medium situation in the long run – still far

from being as positive as during recent years.

Table 6.1: PEST summary

PEST summary Past SR LR

Political factors average 3,2 3,2 2,8

Economic factors average 2,5 3,8 3,0

Social factors average 3,3 3,0 1,7

Technological factors average 3,0 2,3 2,0

Total average 3,0 3,1 2,4 Source: Own representation based on own qualitative evaluation

There are naturally many factors not discussed which still affect FLS. However, as the factors discussed are

evaluated to be the most important, the grading should be seen as a guideline for the overall development.

6.2.2 Porter’s Five Forces model In order to analyze the industry in which FLS operates, Porter’s Five Forces model will be relied on.

As the cement and mineral divisions are both important for FLS, two more or less separate Five Forces

models will be carried out. Furthermore, the Five Forces analyses will be carried out on the basis of a

framework suggested by Jørgen Lægaard & Mikael Vest (Lægaard, Jørgen & Vest, Mikael 2002, pp.53‐64).

According to the model which is included in appendix 17, each “force” is evaluated along a set of questions.

Each question is rated on a scale from 1 to 5 ranging from a favorable situation which means that the

specific factor contributes to making the threat low, to an unfavorable situation meaning that the factor

contributes to making the threat high. As with the grading of factors under the PEST model, grading should

once again only be seen in relative terms. As a further development of the model, and due to the same

reason as put forward under the PEST analysis, the writer includes a third dimension by rating both

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industries with an X showing what the situation has looked like during the recent five years, and if any

changes are expected for the future with SR for changes expected in the short run and LR for changes

expected in the long run.

6.2.2.1 Competition among existing players in the industry Generally there are many suppliers of the same type of equipment as FLS produces. However, with regards

to the cement industry, the two largest suppliers (FLS and Sinoma) cover as much as 66% of the market –

split more or less equally between the two. After experiencing declining market shares during recent years

FLS expects it to stabilise around current levels (FLSmidth 2008a, pp. 13, 24). Apart from the two large

players there are a couple of market followers (Polytius and KHD) and a bunch of market nichers16. With

respect to minerals the market is more fragmented and the three largest players, of which FLS is one of

them, is assumed to hold market shares of only approximately 5% each (Paulsen 2009, conducted 9. Feb.).

The market for cement equipment is therefore somewhere in‐between a differentiated oligopoly17 and

monopolistic competition18, while the market for mineral equipment is closer to direct monopolistic

competition. Due to the financial crisis and low commodity prices, the number of competitors within both

industries is assumed to be slightly lower in the short run, but that it will increase to recent years levels

again in the long run due to attractive margins.

The markets for cement and minerals as end products, and through this the demand for equipment, are

assumed to continue to grow in the future, but with large fluctuations from year to year. With respect to

the market for cement the historical average cement consumption has grown with 120% of the global GDP

growth (excl. China) (FLSmidth 2007b, slide 19), while the world mining capex has been on a more or less

continuous upward trend since at least 1978 (FLSmidth 2007b, slide 30). All in all, growth rates within

minerals are assumed to be slightly higher than that of cement (Paulsen 2009, conducted 9. Feb.).

However, due to the financial crisis and lower commodity prices, growth rates are expected to be less

favourable in the short run while increasing to an above medium situation in the long run.

As mentioned earlier, FLS has outsourced 80‐90% of their manufacturing. This is a strategy which most

competitors seem to follow – especially within minerals (Paulsen 2009, conducted 9. Feb.). With regards to

cement as end product it is ultimately one product requiring one type of equipment. However, with regards

to equipment supplied to the mineral industry it is targeted at a wide range of different commodities and

hence has different requirements. As it is difficult to reach economies of scale, most players within the

16 Appendix 18 17 By Kotler & Keller defined as relatively few competitors and differentiateable product (Kotler, Keller 2006, p.344) 18 By Kotler & Keller defined as many competitors, differentiateable product and high level of segmentation (Kotler, Keller 2006, p.344)

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industry make use of outsourcing. Players within the industry a evaluated to make even more use of

outsourcing in the long run ‐ both due to the simple fact of ongoing globalization but also because many

suppliers have yet not made use of outsourcing to quite the same extent as FLS (Paulsen 2009, 9. Feb.).

Furthermore, storehouse costs are generally evaluated to be low as equipment is built‐to‐order.

With regards to capacity expansions they can be realized relatively smoothly due to the fact that the largest

part of the manufacturing is outsourced. In line with the expected increase in the use of outsourcing the

capacity costs are expected to be even more smoothly realizable in the long term.

Due to constraint access and long lead times for new equipment in recent years, there has been an actual

market for used equipment with increasing salvage value as a consequence. However, exit barriers are

assumed to be higher both in the short to long run.

The equipment used in both the cement and mining industries is somewhat differentiateable ‐ both with

respect to price, quality and technological features. In general FLS focuses on top quality equipment and

state of the art technology in opposition to many Asian competitors who focus less on quality and more on

price. With increased focus on environmental issues and total‐cost‐of‐ownership rather than the initial

investment (FLSmidth 2008a, p.15), the possibilities for differentiation, mostly within cement, are expected

to increase it the long run.

Also, even though a production system lasts for an average of 30 years, and 50 years with upgrades and

modernization, when entire systems are replaced shifting costs are evaluated to be low (FLSmidth 2007b,

slide 19). However, in some cases (e.g. replacement of spare parts) customers will be faced with high

shifting costs when shifting to new suppliers, as a system might not function properly without all parts

being from the same supplier. Furthermore, service might have to be carried out by the supplier who

delivered the system in the first place. All in all, shifting costs are estimated to remain stable at medium

levels.

With regard to the competitors’ strategic motives for being in this industry, they are all in the industry with

their main product, which means that they all have strict focus on the industry and their competitors in

general. Had they been in the market with a bi‐product, focus would have been split and this industry

would be of less importance for that specific company. As a consequence this is evaluated to have a

negative effect on the competition.

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6.2.2.2 Competition from new entrants As great economies of scale exist within the industry and as it is expensive to start a new company, this will

have a deterrent effect on possible new entrants. Also, due to the previously discussed differentiation

within the industries and in order to give customers an incentive to switch from a well known supplier, new

entrants would have to come up with a solution which is better and/or cheaper than that of existing players

on the market. If new entrants cannot offer superior equipment customers would rather continue to do

business with suppliers they rely on.

With regards to the relationships with governments, there are no clear signals that governments should

prefer exiting players over new entrants. However, with the increased focus on environmental issues, some

governments might in the long run start favoring companies who are able to provide environmentally

friendly systems. As new entrants will probably not be able to start out by offering systems which are more

environmentally friendly and complex than existing players on the market, this is evaluated to help keep

the threat from new entrants down.

The profitability in the industry is not extraordinarily high, for which reason this is not evaluated to have a

decisive effect on the competition from new entrants. Generally speaking the mineral division has

historically had an EBIT margin 1‐3 percentage points higher than that of the cement division (FLSmidth

2008a, p.5, FLSmidth 2006, p.4, FLSmidth 2007a, p.4). This is a general picture for the industry as a whole

(Paulsen 2009, conducted 9. Feb.), which is probably due to the fact that among other things there are no

low cost competitors worth mentioning within minerals. However, they are expected to emerge in the long

run (FLSmidth, Tofte 2008, slide 28), for which reason the margin is assumed to move closer to that within

the cement industry in the long run.

A couple of things which do make it somewhat easy for a new entrant is that the industries are not defined

by complex distribution channels – equipment is sold directly to the end‐customer. Other than the actual

costs regarding the establishment of a new company, new entrants are not assumed to have extra costs

compared to established competitors. Furthermore there have been no signs of retaliation against new

entrants in the past.

6.2.2.3 Threats from substituting products With regards to the threat from substituting products, no industries are identified as having products which

in the long run will be able to substitute the equipment presently used within the cement and mineral

industries, as they are relatively specialized. However, it might be possible for companies servicing and

repairing machines and production system in other industries, to expand into the cement and mineral

industry. Also, especially within cement it might be possible for companies which are further in the process

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of developing environmentally friendly equipment in other industries, to be able to expand into the cement

industry and take market shares. This has yet not happened, but is seen as a future threat.

Furthermore, products offered by existing players in the industries can relatively easily be altered in some

areas to become substitutes of competitors’ products. However, as reputation, reliability and quality are

crucial parameters when customers decide with whom to place an order, it is still quite difficult for

competitors to simply alter their products to become perfect substitutes.

6.2.2.4 Customers bargaining power There are generally many customers19 within the two industries. However, during the recent years there

has been an ongoing consolidation (FLSmidth 2008a, p.24) (FLSmidth, Rasmussen 2007, slide 18). This trend

together with the fact that some customers will surely not survive the financial crisis, make FLS and their

competitors slightly more dependent on the surviving customers in the short run. However, in the long run

high margins within customers’ industries and a continuing increasing demand for cement and minerals are

expected to attract new customers to the market.

The products which customers produce are commodities or at least very standardized products, which can

be said to be non‐differentiable, for which reason they are sold at market price. Hence, the only way for

FLS’ customers to increase margins is by lowering costs, which will naturally put pressure on their suppliers.

During the recent years customers within both industries have been experiencing high margins, and hence

have not been directly forced to pressure prices with their suppliers. Commodity prices have come down

drastically during the recent months, for which reason margins are expected to be smaller in the future

than they have been during recent years. The equipment and production systems which customers buy

make up most of their purchases, which is assumed to help increase their bargaining power.

Until know there has not been any examples of customers within either industry making use of backwards

vertical integration. As the production of equipment is quite, it would not be feasible for customers to

simply produce equipment in order to become self‐sufficient. Instead they would have to build factories

and start actively competing for customers. This would clearly be outside their area of expertise, and hence

sounds very unlikely both historically and in the future.

As already mentioned, cement and minerals are sold at market prices, for which reason customers have a

strict focus on costs and total‐cost‐of‐ownership (FLSmidth 2008a, p.15). As there are many ways of

lowering the total‐cost‐of‐ownership, this is evaluated to be a factor of differentiation within the supply of

19 Customers are mainly cement plants and mining companies

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equipment. As environmental issues are also becoming of greater importance within the cement industry,

the possibilities of differentiation are expected to increase in the long run, while within the mineral

industry they are expected to remain stable.

Finally, customers have relatively good information with regards to price structure and margins among FLS

and their competitors, as well as their suppliers, as most of them are listed on stock exchanges and hence

make large parts of that information available through presentations and annual reports.

6.2.2.5 Suppliers bargaining power The suppliers to the industries in which FLS operates, consist of both welding companies to whom

production has been outsourced, as well as human capital (employees). As these two types of “suppliers”

are very different they will be rated individually on question 1‐5 under “Suppliers bargaining power” in

appendix 17.

There are generally many welding companies able of servicing FLS and its competitors, but due to recent

years upturn they were still far from enough to keep up with the demand. These suppliers sell products

which are substitutable as they are produced according to the customers’ specifications. If the customer is

not satisfied with a supplier, they will get another supplier to make the specific spare part. Having said that,

the possibilities of simply finding another supplier have been limited due to bottlenecks. Suppliers were

able to continue production at full capacity even if FLS or another customer chose to stop doing business

with them – someone else would simply be waiting to get in. However, the financial crisis and declining

commodity prices are evaluated to decrease the pressure on suppliers considerably in the short run,

making it easier to get the needed spare parts and change supplier if needed. In the long run the number of

suppliers is expected to follow the general demand. Furthermore, suppliers produce products for other

industries than the ones covered by FLS, hence generally making them less dependent on that specific area.

However, in the short run the industry for equipment to the cement and mineral industry is evaluated to be

of huge importance to the suppliers as they are presumably experiencing declining sales within other

industries as well. In the long run, the importance is evaluated to decrease slightly as especially the

business cycle within mining does not necessarily follow the overall economic situation.

With regards to human capital there are generally many “suppliers” but for many years there have only

been very few qualified ones available. Due to the financial crisis, unemployment rates are on the rise,

hence increasing the availability of human capital in the short run. In the long run shortage of qualified

employees is expected remain relatively high. However, the need for human capital might to a certain

extent be substituted with machines or be outsourced. Furthermore, due to the historically low

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unemployment rates, employees’ economic future has been more or less independent of the company

during recent years. In the short run increasing unemployment rates is evaluated to increase employees’

dependency on the employer, while in the long run be lower again, as most of them will be able to find new

jobs.

Some suppliers are differentiated to the question if they are able to do the job according to certain

requirements. Furthermore, there will always be shifting costs when changing supplier – that either being

costs connected to new agreements and tests with respect to the required specifications and standards on

the spare parts produced or training of a new employee. Last but not least, there have yet not been any

examples of suppliers making use of forward vertical integration.

6.2.2.6 Conclusion on the Five Forces analysis From table 6.2 it is seen that on the basis of the detailed grading in appendix 17, the threat from forces on

industry level are evaluated remain close to stable in both the short and long run. More interestingly, even

though the overall grades for the two industries are derived through different dynamics, they are

practically the same. This confirms the assumption that the divisions are relatively closely comparable and

the industry is neither completely stable nor turbulent.

Table 6.2: Summary of the Five Forces grading

The threat from… Average grade (1=low, 5=high) Cement Minerals Historical / SR / LR Historical / SR / LR

1. … existing players in the industry 3,0/3,4/3,0 3,1/3,6/3,1

2. … new entrants 3,1/3,1/2,9 3,2/3,2/3,1

3. … substituting products: 1,5/2,0/2,5 1,5/1,5/2,0

4. … customers bargaining power 2,8/3,0/2,8 2,8/3,0/2,9

5. … suppliers bargaining power a. Ordinary suppliers: b. Human capital:

3,2/2,2/2,5 4,0/3,2/3,8

3,2/2,2/2,5 4,0/3,2/3,8

Overall threat from forces 2,9/2,8/2,9 3,0/2,8/2,9

Source: Own representation on the basis of own qualitative evaluation

6.3 Internal analysis After having covered the external factors, an internal analysis will be carried out through four steps starting

with an analysis of resources and capabilities.

6.3.1 Resources and capabilities On an overall level resources and capabilities can be divided into four groups – material and immaterial

resources, human capital and organization capabilities. They will be analyzed individually in the following.

6.3.1.1 Material resources FLS’ headquarters as well as the cement division is placed in Valby, Denmark, while the mineral division is

placed in Bethlehem, USA (FLSmidth 2008a, back of report). However, FLS furthermore owns several office

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buildings in India to accommodate its Indian employees (FLSmidth 2008a, p.15) as well as the world’s

largest experiment and test center within cement equipment which is also placed in Valby (Hansen 2008a,

p.5). As most of FLS’ manufacturing has been outsourced, the company only owns very few actual

manufacturing facilities. Those which they do own are placed in Asia. Apart from this there are normal

everyday resources such as cars, interior, computers etc. which are of insignificant importance in

connection with the strategic analysis. Especially with regards to the facilities in Denmark the geographical

location can be seen both as an advantage and as a disadvantage. First and foremost, some years ago FLS

chose to move all R&D activities back to Denmark as they evaluated they would be able to safeguard their

products and patents better this way (Hansen 2008a). However, due to historically low unemployment the

access to qualified employees has prevented FLS from carrying out the targeted level of research and

development (Hansen 2008a).

6.3.1.2 Immaterial resources Through many years of acquisition, FLS now holds a portfolio of well known brands within its industries –

brands which are known for reliability, quality and high level of technical advancement (FLSmidth, Tofte

2008, Slide 9). These brands are important tools in building long lasting relationships with customers.

Furthermore, FLS possess valuable knowledge within product development and has increased the focus in

this area within the recent years. As a consequence the funds used within this area has doubled from 2004‐

2007 and plans for the future R&D budget are in the level of 2% of revenue. However, as already

mentioned FLS is influenced by the shortage of qualified employees to support this area of focus (Hansen

2008a, p.5).

Other immaterial resources important to FLS are different strategic partnerships. Among other, FLS,

Højteknologifonden and Danmarks Tekniske Universitet (DTU) have formed a partnership with the goal

together to establish the world’s first CO2 neutral cement plant. This is evaluated to be a strategically clever

move as this not only decreases pressure for new employees, but furthermore makes FLS able to build on

existing knowledge and expertise within the area of environmentally friendly solutions. Other strategic

partnerships include close partnerships with suppliers to try to ensure slot‐times, high quality and timely

delivery (FLSmidth, Tofte 2008, slide 11).

6.3.1.3 Human resources As FLS if evaluated to be an engineering company rather than a production company, FLS is a rather

knowledge intensive company. For the same reason the company’s HR department is an important

resource. The department also has the responsibility of career development and talent programs which

sees to it current employees’ full potential are realized (FLSmidth 2008a, p.46‐47).

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Furthermore, FLS is evaluated to have a competent set of board members as well as top managers.

Especially FLS’s CEO Jørgen Huno Rasmussen is evaluated to be an important resource. He took up the job

as CEO at FLS in the beginning of 2004 in connection with which he stated his areas of focus as risk

management. His goal was to make FLS more project‐oriented, where the risk of each project is evaluated

individually, rather than function oriented as most industrial companies are (Wichmann 2004). Also, in a

recent survey Jørgen Huno Rasmussen was rated as Denmark’s third best CEO/board member (Økonomisk

Ugebrev 2009, pp. 6‐7).

6.3.1.4 Organizational capabilities With the launch of new types of equipment each year and with focus on environmentally friendly solutions,

this shows that FLS is always on the very forefront with respect to product development. This is especially

impressive as the recent years upturn has not forced them into doing so – it is very likely that some

competitors have been reluctant to simply focus on the booming market “here and now”. This shows that

FLS is able to keep focus on the long term development of the business unaffected by good or bad trends in

the short term. This is furthermore valuable information as this is the only right way to optimize the long

term health of the company and hence shareholder value (Koller et al. 2005, p.4).

FLS survived a crisis around the break of the new millennium which was seriously threatening the future of

the company. They did this by among other things slimming down the organization and selling non‐core

business units. Even though it took some years for the back then partially family owned company to realize

the need for change, it still shows that FLS is able to turn around things and implement huge changes when

needed. After having been through this crisis, FLS is assumed to have more focus on danger signals in the

future (FLSmidth 2008a, pp.38‐39).

6.3.2 Structure, systems and processes The following will be split up in two parts – structure and systems, and processes.

6.3.2.1 Structure and systems Structure and systems will be analyzed through three categories – the technical system, the social system,

and the administrative system – in order to understand how they work and are interconnected.

The technical system composes the production facilities and the work processes enabling FLS to produce

and sell their products.

In order for the technical system to function properly it is crucial that enough qualified employees are

employed in the company. According to previous conclusions, this has been a problem during recent years.

According to CEO Jørgen Huno Rasmussen the R&D activities have been constrain – not because of a lack of

40

funds, but because of lack of employees (Hansen 2008a, p.5). However, as concluded in the PEST analysis

the unemployment is expected to increase in the short run, making required employees more easily

available for FLS. For this reason FLS is expected to be fully able to exploit their experiment and test center

and use the funds available for R&D in the short run.

Another part of the technical system which is worth mentioning is the use of outsourcing in manufacturing.

Due to the high degree of outsourcing together with the booming market the recent years, FLS has

experienced problems with longer lead times, late delivery and quality which did not live up to FLS’

standards (FLSmidth, Tofte 2008, slide 13). As suppliers were not able to keep up with demand, their need

to focus on customer service declined in favor of productivity and higher sales. However, with declining

commodity prices and hence less activity among customers, this is expected to change to the better.

Apart from the above mentioned problems and areas of improvement, the technical system is well

functioning and succeeds in making equipment available for customers worldwide.

The social system relates to the attitudes and norms established between employees – both employees vs.

management but also between different groups of employees. In order to properly analyze the social

system within FLS it would require an in‐depth interview with a wide range of employees at FLS. As this has

not been possible, this area will only briefly be mentioned.

For one thing FLS carry out employee satisfaction tests, as well as statistics on accidents and absence due to

illness. Both are below industry and national averages respectively (FLSmidth 2008a, p.46‐47, SP Service).

With regards to the employees’ satisfaction tests there is no available information about how they are

used, but as is done with both the statistics on accidents and absence due to illness, it is assumed that

action is taken if critical factors change in the negative direction. Furthermore, the company has both

career development and talent programs, which are assumed to decrease employee turnover (FLSmidth

2008a, p.47).

With regards to employees doing work in developing countries and especially countries with political risk,

emergency plans have been prepared to ensure their safety in the case of emergency. FLS has many years

of experience of doing business in areas like these, which is assumed to have a reassuring effect of

employees both now and in the future (FLSmidth 2008a, p.38). All in all, FLS is generally assumed to

continue to uphold the high level of focus on their employees.

The administrative system has the responsibility of making sure that the technical and social systems are

working optimally.

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The leadership style at FLS is assumed to be relatively democratic and participative as well as oriented

towards people and interpersonal relationships, rather than directive and autocratic with the larger focus

on tasks and structures. This conclusion is based on several things which point in the same direction, of

which things discussed under the social system are some of them. For this reason FLS is governed by theory

Y leaders which assume employees to naturally work towards a common goal, that they require little

control, that they can take initiative, possess creative skills and that they are capable of handling

responsibility (Brooks 2006, p.158). All this seems to fit a knowledge intensive company like FLS well. Such

companies only survive on their employees’ skills and creativity, and hence need to provide an

environment and leadership style which foster this. As leadership styles are closely connected to the

personality of especially the CEO and top management, and hence might change when some of them step

down, it is difficult to say much about what it will look like in the future. However, as mentioned before this

type of leadership is evaluated to be necessary to foster a creative environment, for which reason the

board of directors is assumed to continue to employ managers which fit this management style.

6.3.2.2Processes Many companies experience problems when making use of a linear organization structure. These problems

often occur on the borders between different departments and divisions due to confusion with respect to

e.g. responsibility and lack of initiative. For this reason some companies implement process oriented

systems that work horizontally throughout the organization rather than vertically as the actual organization

structure does it (Lægaard, Jørgen & Vest, Mikael 2002, p.103).

Examples of process oriented systems are LEAN and Total Quality Management (TQM). In 2006 FLS

declared that they would start implementing LEAN in the cement division, and that it is ultimately to be

implemented throughout the organization. The goal is to reduce the time of a typical cement project by as

much as one third. In the end of 2007 FLS had realized a reduction of 10‐15% which indicates that things

are going according to plans (FLSmidth 2008a, p.24).

6.3.3 Owners and managers preferences In the following a number of factors which might influence and maybe even limit strategic drive and

decisions will be analyzed. In other words this area is related to corporate governance, and will first and

foremost be treated according to the Nørby committee’s suggestions for good corporate governance20

(Johansen et al. 2001) after which a couple of areas evaluated also to be of importance, but which are not

covered by the committees suggestions, are discussed. Some parts which are fulfilled according to the

20 The Nørby committee was formed in 2001 by former Business Minister Ole Stavad to come up with suggestions for good corporate government

in Denmark.

42

Nørby committee’s suggestions will be omitted, putting emphasis on areas that are more interesting

and/or questionable.

The first area of importance is FLS’ relationship to stakeholders which is generally good. FLS has defined a

set of policies to ensure this. Among others, FLS has a goal to generate a profitable return to shareholders

through among other things alliances and acquisitions, as this is the key to long term success. The company

furthermore has a great deal of focus on the wellbeing of its employees – focus areas here are both

recruiting, development and to retain employees (FLSmidth 2008a, p.44). However, some of these

stakeholder interest will naturally clash at times. In January FLS announced that they would have to lay‐off

600 employees but gave them a long notice of approximately 9 months to help them prepare for the

situation and give them a chance to find new jobs (Risom 2009, p.8). This was naturally in the best interest

of shareholders, while it was not in the direct interest of the affected employees. However, this area is not

evaluate to have any limiting effects on strategy, as the incident simply shows that the management is both

able and willing to find solutions which best fits all stakeholders given the situation in question (FLSmidth

2008a, p.52).

FLS furthermore sees to it that the board of directors’ tasks and responsibilities are optimized according to

the individual board members competencies and ensures that there is a clear line between the board of

directors and the management. However, there has not been worked out an actual list with disposition of

responsibilities as the Nørby committee suggests (FLSmidth 2008a, p.43), for which reason there might be a

risk that some areas are slightly neglected and no single person is as to be made accountable for problems

within that specific area.

Another crucial area is the composition of the board of directors. FLS ensures that the board of directors is

always composed of experienced business men with relevant backgrounds and knowledge within the

company’s area of expertise. Among the board of directors, and according to Danish law, is an employee

representative which is elected for a period of 4 years (FLSmidth 2008a, p.43). This person is assumed to

speak the interest of all employees and make sure that the voices of the employees are heard. One

member of the board, Ander Vinther, is not independent according to the Nørby committee’s definitions,

as he has been employed by the company within the recent 5 years (FLSmidth 2008a, p.43). Furthermore,

no formalized self‐evaluation of the board of directors is used, but instead rather an ongoing evaluation.

Also, there is no information about evaluation of the management as well as the co‐operation between the

board of directors and the management. Nevertheless, evaluation which e.g. controls that strategies are

being implemented is assumed to be used. All in all the above is seen as slightly negative, as this might

prevent optimizing co‐operation and the way things are done.

43

With regards to the remuneration the board of directors and the top management a committee has been

established to negotiate this. While the board of directors is not included in any stock option program, the

top management is (FLSmidth 2008a, p.43). However, this program is worked out according to the Nørby

committee’s guidelines, and all information is available in the annual report. In 2008 the top management

received an average of DKK 4,5 million in direct salary and DKK 0,5 million through share‐based payments

(FLSmidth 2009a, p.89). This is assumed to be on the same level or even slightly below other OMXC20

companies, in which top management already in 2002 received average salaries of DKK 4 million

(Finansministeriet 2004) which is assumed to have increased considerably since then.

Apart from the areas covered by the Nørby committees guidelines, it furthermore seems highly relevant to

evaluate if historical ties and traditions are having a limiting effect on strategic drive. As mentioned earlier,

FLS went through a tough crisis in the beginning of the millennium, which was partly rooted in problems in

this area. The FLS family was still involved in managing the company and had emotional ties to the

company, which meant that decisions were not always taken according to the best interest of the general

shareholder. This was also the reason why the company was late to accept that the conglomerate like

structure was no longer feasible. However, today the original FLS family has no direct influence on the

management and only holds an insignificant number of shares. This together with the fact that FLS has

been drastically slimmed down to the core business areas and that management has chosen to move large

parts of FLS abroad shows that problems that might have been in this are some years ago do not exist

anymore.

Even though some areas discussed above are slightly questionable they are not evaluated to have any

mentionable affect on the strategic drive of management.

6.3.4 Core competencies In order to identify FLS’ core competencies and to specify the resources which are evaluated to give the

company a competitive advantage, the resources identified under chapter 6.4.1 “Resources and

capabilities” will now be evaluated using the VRIO framework which is included as appendix 19. Each

resource is placed in one of four groups from competitive disadvantages to sustainable competitive

advantages (SCA).

Two resources are identified as giving FLS a temporary competitive advantage. The strategic partnerships

with Højteknologifonden and DTU are evaluated to be very valuable and rare, but would not be either that

difficult or costly to imitate. Even though both partners have strategic partnerships with a wide range of

Danish companies, only one of them is within the cement industry. As the organizations are Danish based,

44

they only cooperate with Danish companies. However, similar partnerships are assumed to be possible in

other countries, for which reason it is evaluated as possible for competitors to imitate FLS’ strategy in this

area. Furthermore, CEO Jørgen Huno Rasmussen is evaluated to be a temporary competitive advantage.

Actually he has most of the qualities of a SCA (valuable, rare and difficult to imitate) – however, as the

advantage lies within him as a person, the competitive advantage is not fully controlled by the company. He

will surely choose to step back as CEO for FLS at some point, for which reason FLS is not capable of

exploiting him in the long run.

With regards to SCAs three advantages are identified. First and foremost, the experiment/test center is

evaluated to be very costly to imitate, as it is the world’s largest, and due to the fact that there are only 1‐3

other large competitors on the market who would have at least the size to build and use a test center.

However, as FLS is among the two largest companies within their industry and has strong focus on product

development, they are valuated to continue to develop the test center and continue to be in front of

competitors. This leads us to another SCA – strong focus and knowledge within product development,

especially within environmentally friendly solutions. As this takes many years of experience and a lot of

money to develop, it is evaluated to be difficult for competitors even to get to the same level as FLS on this

aspect. As three resources discussed until know (strategic partnerships, experiment/test center and strong

focus/knowledge) are all resources within product development, they are seen as tools in an overall SCA

called “Product development”.

Apart from this, FLS’ brands and reputation is also identified as being a SCA. For obvious reasons

competitors will never be able to obtain exactly the same brands as FLS, but might theoretically try to

imitate some of the qualities that these brands possess. However, this is still evaluated to be relatively

difficult and as there is assumed always to be some degree of difference between brands, this will be a

basis for differentiation. Hence, FLS’ portfolio of well known and reliable brands should clearly be exploited.

All in all, FLS is evaluated to possess a wide range of competitive advantages which will help defend their

market share in the future.

6.4 Key factors for success After having done both an external and internal analysis, focus will now turn to an area which make use of

information from both sections, and hence cannot be placed in either one of them. Key factors for success

are the factors within a specific industry which are essential to succeed in the marketplace. In the following,

key factors for success are identified, together with a brief comment on how well FLS performs according to

them.

45

Customers are international cement producers and mineral companies who buy equipment and entire

production systems from FLS and their competitors. Price is a key factor for winning customers orders.

However, during recent years customers have started focusing more on total‐cost‐of‐ownership rather than

just the initial investment (FLSmidth 2008a, p.15). Hence, customers are willing to pay more initially if this is

offset by e.g. lower production costs, fewer break downs and lower maintenance costs. For this reason

total‐cost‐of‐ownership is somewhat interconnected with another important factor ‐ quality. FLS has

always been among the more expensive players on the market – that is, with respect to the initial

investment. However, the higher initial cost is the price customers must pay for quality and reliability. This

is the opposite strategy of most Asian competitors who simply focus on a low initial investment. Relating

this to the generic strategies means that FLS has focuses on differentiation while Asian competitors focus

on cost leadership (Lynch 2006, p.452). As customers start to focus more on the total‐cost‐of‐ownership,

FLS is really beginning to reap the benefits of this strategy, which is evaluated to help stop declining

market.

As equipment is a long term investment, customers need to be sure that what suppliers say and promise

actually holds. Hence, a dissatisfied customer will not be able to simply change supplier right away, but

might be forced to continue doing business with that supplier until the purchased equipment is replaced.

For this reason good brands/reputation are important factors when customers decide which company to

do business with.

Consequently, the two overshadowing key factors for success are identified as being low total‐costs‐of‐

ownership, and a good brand defined by quality/reliability/reputation (good brand). In other words, these

are the areas where players in the industry should focus constraint resources such as employees, time and

money, in order to make sure that they are optimized at all times.

6.5 Critical SWOT To finish of the strategic analysis a critical SWOT will be carried out. This will be done first by gathering all

strengths, weaknesses, opportunities and threats discussed in the preceding chapters. A SWOT table is

included in appendix 20 and 21 in order to give a complete overview of factors identified during the

strategic analysis. Subsequently they will be evaluated to investigate if some of them fit – e.g. a strength

and an opportunity. Last but not least, opportunities and threats are evaluated and rated to identify the

best opportunities and the most serious threats.

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6.5.1 Analysis of FLS’ need to change In order to analyze FLS’ need to change, relevant connections are made between strengths/opportunities

(possible to exploit right away), strengths/threats & weaknesses/opportunities (latent needs to change at

some point) and finally weaknesses/threats (acute needs to change here and now!).

6.5.1.1 Directly exploitable opportunities 1. First and foremost, FLS is in a good position to exploit the increasing middle class (opportunity) in the

developing countries as this is where the larger part of the group revenue is placed (strength).

2. Due to the financial crisis, and in order to save money, more and more customers are repairing and

maintaining current production facilities instead of ordering completely new ones (opportunity). As FLS

is well positioned within customer services (strength), the company seems well positioned to reach their

goal of an increase in customer services of 10‐15% per year.

3. FLS produces equipment and production systems of top quality and reliability, optimizing their products

for e.g. low construction costs, to be quick to produce at full capacity and to be less energy consuming

than the average equipment (strength). With customers’ increasing focus on total‐cost‐of‐ownership

rather than simply the initial price (opportunity), FLS is in a good position to exploit this shift.

4. FLS has made use of horizontal integration several times. In 2007 the mineral division bought GL&V

Process, and hence expanded from mainly doing business within materials handling and crushing,

grinding and sizing into also covering concentration – areas which are all outside the actual mine.

However, the division still only has a slight coverage of refining, which is the end step in mining site

plants as well as all steps inside the mine – exploration, development and extraction. Given the current

market situation, a wide range of attractive possibilities for acquisition exist. For the cement division

there are similar opportunities for horizontal integration (opportunity). With good reputation with

financial institutions and due to the company’s financial strength (strengths) FLS is in a good position to

get access to liquidity needed to carry out such actions – even in the market we are experiencing at the

moment.

5. With continued high long run activity in developing countries there will constantly be opportunities to

exploit. A couple of these would be to increase focus in untapped former Soviet countries and in Asia in

general, due to further urbanization and industrialization (opportunities). However, doing business in

such areas can be both difficult, dangerous and often includes different kinds of business risks due to

political instability. As FLS has many years of experience in general and through this also a lot of

experience with doing business in such countries (strength), FLS is in a better position than most

competitors to exploit these opportunities.

47

6. Last but not least, increasing focus on environmental issues and the implementation for new

environmentally friendly laws, are increase possibilities for product differentiation and development

(opportunities). As FLS has always had strong focus on product development the company has built

valuable knowledge within these areas. Furthermore, they own the world’s largest experiment and test

center within cement and have formed different strategic partnerships. With an increased availability of

workers in the short run, FLS should be ready to exploit possibilities within R&D more or less right away.

6.5.1.2 Areas with a latent need to change The following are connections which are not urgent right away, but might present FLS with a need, or at

least a possibility, to change at some point in the future. First weaknesses which fit with opportunities will

be connected. These connections show opportunities which FLS might not be able to exploit due to a

weakness. Hence, in order to change this, the company should work on its weakness. Secondly, strengths

which fit with threats are connected. These connections show areas where the external environment

presents FLS with threats which however, due to an internal strength they should be able to handle if the

threat is identified and focused on.

7. With new possibilities for product development and differentiation within among other things

environmentally friendly solutions (opportunity), the need for R&D is set to increase in the future.

However, with a resumed long run constraint activity within R&D due to the lack of qualified employees

(weakness), this is an opportunity which FLS might not be able to seize on.

8. As mentioned earlier, political instability exists on many of FLS’ markets, and makes doing business in

these areas both difficult and risky (threat). However, with a long history of doing business in political

unstable countries, with well defined crisis plans and well functioning risk management (strength), FLS is

in a good position to overcome this threat. As these markets are where future growth is expected to

come from, this is a huge advantage over some competitors.

9. Due to the financial crisis, tightening money supply and low commodity prices, some customers are

expected to go bankrupt in the short run (threat). However, as FLS uses down‐payments of 10‐15%

(strength), they have somewhat insured themselves from some of this risk.

10. Even though the constraint access to workers seems to be waning in the short run, it is expected to

increase to an unfavorable situation again in the long run (threat). FLS has a well functioning HR

department which takes care of both career development programs and talent programs. The company

in general has strong focus on employees and their well being, and together with a democratic

leadership style (strengths) this is assumed to limit employee turnover. These strengths could probably

48

be used more proactively not only in connection with retaining present employees but also in attracting

new ones.

6.5.1.3 Threats to focus on here and now 11. As mentioned earlier, the threat from substituting products is expected to increase in the future

(threat). In order to help prevent this from happening, FLS needs to continue developing new products

which are better than those both direct and indirect competitors are able to offer. As mentioned

under point 6, FLS has strengths which could potentially help them in this aspect. However, the

constraint access to qualified workers is expected to continue in the long run, this might continue to

limit activities within R&D (weakness).

12. Last but not least, due to the financial crisis there is a risk that customers will once again turn away

from focusing on total‐cost‐of‐ownership (threat) and instead focus on the initial price which for FLS

equipment is rather high (weakness). For this reason FLS should probably evaluate the risk and

probability of this development.

All in all, FLS is evaluated to have more “positive” connections than “negative” ones which is a good sign. All

in all FLS’ need to change is low – there are not a lot of threats which they are completely unable to handle

at the moment. However, this is not the same as saying that there are no possibilities to change.

6.5.2 Evaluating opportunities and threats As there will always be more opportunities and threats than are actually possible to focus on at any given

time, it is important to evaluate all opportunities and threats in order to identify areas which should be

handled first. In order to do so, a table has been developed and included it in appendix 22 and 23. In this

table all opportunities and threats are evaluated and graded from 1‐5 along three factors – economic

effect, resources at disposal, and time horizon. From this an average grade is calculated and alternatives

are rearranged according to this grade, in order to illustrate their relative importance. As the writer is

evaluated to be able to estimate the economic affect as well as time horizon on the basis of the strategic

analysis, the degree to which the resources are at disposal is evaluated to be more or less explained during

the analysis of FLS’ need to change.

6.5.2.1 Evaluation of opportunities The most valuable opportunity is evaluated to be the increasing demand for customer services, as this is

expected to continue through the financial downturn during times in which the order intake for ordinary

projects might start to decline. For the same reason, increasing revenue from services would be a pleasant

development which is evaluated to have a considerable economic affect on FLS.

49

At the same time suppliers declining bargaining powers are evaluated to be an opportunity of high value, as

FLS might be able to exploit the situation and pressure prices. This could help prevent margins from

declining drastically when revenue starts to decline.

Last but not least, the opportunity to make use of horizontal integration and hence exploit the current

market situation makes good sense and would enable FLS to expand into areas where they are not active

today.

Apart from the above mentioned opportunities and according to appendix 22, at least four other

opportunities are evaluated to be valuable. Without going into further detail with them, they are an

increasing middle class in developing countries, further urbanization and industrialization in Asia, increasing

focus on total‐costs‐of‐ownership in the long run, and increased availability of workers in the short run.

6.5.2.2. Evaluation of threats Low commodity prices, low/negative global GDP growth, increasing free capacity in customers’ industries

and customers’ focus on consolidation rather than expansion are all threats which have to do with the

expected future order intake. According to appendix 23 they make up 4 of the 5 most serious threats at the

moment. As mentioned earlier, FLS has already laid‐off 600 employees, but it is important continuously to

analyze the situation and evaluate if further steps must be taken in order to bring down activity

accordingly.

Apart from the threats connected to the order intake the increasing threat from existing players in the

market is evaluated to be serious. This, together with the combination of a more difficult market situation

and increasing bargaining powers from customers, is evaluated to be a dangerous cocktail which might put

pressure on sales prices and hence compound the negative effect from lower order intake.

6.6 Preliminary conclusion Clouds are starting to form around FLS and their competitors, and several crucial changes are starting to

emerge. From the strategic analysis it has become clear that the market for FLS’ equipment has peaked for

now and will come under pressure during the years to come. It is now that the management of FLS must

show their worth and steer the company through the downturn. Even though the next years will present

FLS with a wide range of difficult changes, it also opens several opportunities which – if exploited – might

strengthen FLS’ market position and let the company grow even stronger on the way towards better

market conditions once again.

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7. Valuation In this section the actual valuation of FLS will be carried out. Through this we will be able to evaluate what

the fair value of FLS is and through this what the effect of the conclusions from the strategic analysis has on

the fair value. After having estimated the fair value it will be reflected on and compared in different ways.

To estimate the fair value both the DCF and EVA models will be used. The DCF model is used as this is the

most widely used and accepted method, as it simply relies on the cash flow and not the accounting based

earnings which might be misleading. However, as the DCF value the operating cash flow and hence only

shows if the company has a negative or positive cash flow in a given year, it is not a good estimate if value

is created (Koller et al. 2005, p.116). As an example, a company might end up with a negative cash flow in a

year in which it has made considerable investments in future growth which is clearly not negative. For the

same reason, the EVA model is used as a supplement to the DCF, as it provides us with additional valuable

information. Contrary to the DCF, the EVA shows if the company is earning its cost of capital in a given year

or not (Koller et al. 2005, p.116).

Furthermore, as a static rather than dynamic WACC was chosen, both methods will lead to the same fair

value which seems intuitively appealing.

7.1 Forecast drivers Some drivers will be estimated in detail on the background of earlier analysis and will hence differ between

the bear, base and bull scenario. Table 7.1 lists these drivers.

Table 7.1: Overview of detailed forecast drivers

Source: Own representation

These are the drivers which would lead to problems with transferability if they were simply forecasted on

the basis of historical development as done in the business‐as‐usual valuation. The forecast has been split

into 3 parts – a detailed forecast period from 2009‐2013 (equivalent to what was called the “short run”

during the strategic analysis), a key driver forecast period from 2014‐2023 (the “long‐run”) and the

continuing value period from 2024 and onwards. Generally speaking all drivers will be forecasted according

2009‐2013 2014‐2023 2024‐>

Revenue X X

Cost of goods sold X

Selling, Gen & Admin Expenses X

Accounts receivable X

Accounts payable X

Other current liabilities X

CFFI

‐ CAPEX X

‐ Investments in intangible assets X

Adj. EBITA‐margin X

Growth in NOPLAT X

51

to the assumption that they have reached a steady state by the last year in the key forecast period, as this

is a requirement for an accurately calculated continuing value (Møller 2005, p.21).

With regards to R&D which during the strategic analysis was mentioned several times, the writer is not able

to forecast it due to the lack of information from FLS. More specifically, FLS simply disclose that some R&D

costs are booked in the income statement during the year in which they are incurred, while others are

booked as immaterial assets provided that they are expected to generate future earnings, while specific

numbers are not made available. Some broad assumptions could have been made in connection with

estimating R&D costs, but as they have historically only made up an average of 1,26% of revenue (FLSmidth

, 15 min. in) they are assumed to be rather insignificant in connection with the valuation.

7.2 Scenarios In the base scenario section each forecast driver will be discussed in detail and an explanation forecast

method will be given. After this both the bear and bull cases will only briefly be discussed as the method for

forecasting drivers are the same as under the base scenario.

7.2.1 Base scenario No credible estimations of the long term development in revenue or order intake in the cement industry as

available from any external source, these have to be estimated from the bottom. As most items in

connection with the valuation are driven by revenue growth it seems important to direct extra attention

and time at estimating this area.

7.2.1.1 Forecasting revenue growth As a given year’s revenue is realized on the basis of orders received during a couple of years leading up to

that year, the revenue growth estimate is rather complex. First the order intake will be estimated after

which this will be translated into future revenue. The order intake within the cement division will be

analyzed with most detail as more information is available here.

7.2.1.1.1 Estimating order intake Cement projects: According to FLS, growth in cement consumption has historically had a 120% correlation

with the world GDP growth (FLSmidth 2007b, slide 19). As capacity is assumed to revert towards

consumption in the long run, this will be used to estimate the annual newly contracted cement capacity.

Apart from this, the price per million tons per year21 and FLS’ market share affects the order intake in a

given year.

21 How much annual cement production capacity a given system has. Henceforth abbreviated mty.

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From this the following formula is formulated to estimate the order intake from projects in the cement

division:

· 1,2 · · ·

Source: Own formulation

Where,

.

The GDP growth for the very short run will be based on estimates from Morgan Stanley, as they have

defined both bear, base and bull scenarios which will be of good use in connection with this report. In the

base case world GDP growth estimates are ‐1,9% for 2009 and +2,6% for 2010 (Fels, Pradhan &

Andreopoulos 2009, p.5). Information from Morgan Stanley is evaluated to be highly credible for which

reason the quality of the report is not compromised with. On the other hand, it is plausible that Morgan

Stanley is biased in some way which could lead to problems with confirmability. All in all, this is assumed

not to be the case.

After 2010 the GDP growth rate is estimated to gradually return to a long term average by the beginning of

the key driver forecast period. As a proxy for the long term GDP growth an average of the recent 60 years

will be used (3,34%). As seen from appendix 24, going back further than this leads to dramatically

fluctuating growth rates, which are not assumed to be a reliable picture for the future, and hence would

lead to problems with external validity.

During the recent years the realized price per newly contract mty has fluctuated between DKK 257‐362

million22. Several things point in the direction of lower prices in the short run. Customers’ bargaining

powers are expected to increase slightly in the short run which might increase their persistence to try to

pass on some of the pressure to their suppliers. Furthermore, competition from existing players in the

industry is expected to increase considerably in the short run, which means that FLS and their competitors

will be easier to “bend” than just a few years ago. All in all, the reasons given above (which according to

appendix 23 are both among the top 5 threats at the moment) are assumed lead to lower prices in the

short run. This however is based on the assumption that the geographical composition of order intake is

not changed considerably as customers in some countries tend to buy cheaper equipment that those in

other countries. Hence, if geographical changes found place, historical prices would not be transferable. In

order to estimate the price during the detailed forecast period it is assumed that price is a function of

22 Calculated under “Order intake estimation” in the base scenario Excel file

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supply and demand. As no data on the supply and demand of cement equipment is available, estimates will

be based on the supply and demand situation in their customers’ industries (that is in the market for

cement and minerals as end‐products) as this is assumed to resemble the situation in the market for

equipment. To do this, historical consumption and capacity estimates as well as future consumption

estimates for 2009‐2013 from Credit Suisse are relied on (Goad, Lehmann 2009, p.17). As was the case for

Morgan Stanley, Credit Suisse is evaluated to be widely respected, for which reason relying on information

provided by them is compromise with credibility. From these a utilization rate can be calculated. The

estimated price per newly contracted mty is then evaluated to follow the percent change in expected

utilization rate during the detailed forecast period. As the price in 2008 already seems relatively low the

decrease in prices for 2009 will be calculated on the basis of the average price during the recent five years,

which seems usable as the utilization rate during this period has been relatively stable. Hence, according to

this, prices are estimated to declining considerably in the short run and bottom in 2010 at DKK 241 per mty.

During the key driver forecast period the price is set at the average of the recent five years equaling DKK

308 per mty.

Last but not least, FLS’ market share is estimated. During the recent years FLS’ market share has been

under pressure as seen from appendix 18. However, after bottoming at 29% in 2006 and 2007 it increased

to 32% in 200823. As the number of competitors is expected to decline in the short run while the

competition among existing players in the market increases, large players are expected to win market

shares from smaller players as was the case in during 2008. FLS has strong brand names and possesses

leading technologies which should help them in difficult times. Furthermore, competition from new

entrants is expected to remain stable during the detailed forecast period. The positive trend from 2007 to

2008 is expected to continue and FLS’ markets share to increase to 34% in 2009. As we enter the key driver

forecast period, the long term attractiveness of the industry will once again attract new competitors for

which reason the market share is assumed to gradually decline to a long term level of 31%, which is

marginally higher than the recent five years average. The reason why the market share is set marginally

higher than recent years average is because FLS’ strong focus on environmentally friendly solutions is

expected to start show its affect. However, no rapidly increasing market share on the basis of this alone are

estimated, as there presumably will be considerable cannibalism between new revolutionary equipment

and some of FLS older alternatives. On the other hand, being the market leader within this area FLS might

gain some sort of first mover advantage which will benefit their market share.

23 Based on a range of annual reports from FLS during the period 2004‐2008

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Table 7.2: Base scenario revenue estimation summary

Source: Own representation on the basis of own calculations as well as (FLSmidth 2009a, 2004‐2008, Goad, Lehmann 2009)

A brief summary of revenue estimation variables can be seen from table 7.2.

In order to ensure debendability, estimates are compared to those in a report written for WWF in

collaboration with Lafarge24, production (assumed more or less equal consumption) is expected to reach

3500 mty by 2030 – up from 1443 mty in 2008 (Müller, Harnisch 2008, p.53). Using the method discussed

leads to an estimated consumption of 2900 mty in 2030, for which reason it can be concluded that revenue

estimates reached in this report might be slightly pessimistic. The difference could also be due to value

biases – not only on behalf of the writer but also the external source. As WWF is evaluated to be biased to

set the scene as negative as possible in order to be heard, the writers’ estimates are evaluated to be at

least as good as those put forward by WWF, for which reason they will be used.

Mineral projects: As the mineral division has historically been a smaller part of FLS there is not quite as

much information available. Furthermore, as the order intake within the mineral division is affected by the

demand for a wide range of different minerals, it is very complex to estimate in a similar manner as just

done for cement which is basically one product. For this reason, some assumptions are made. It is assumed

that the order intake in the mineral department will be greatly affected by the financial crisis as well as low

commodity prices. On the other hand, the demand for minerals is still assumed to be less cyclical than

cement ‐ partly because it is made up by many minerals of which some follow different cycles. For this

reason the project order intake in minerals for 2009 is expected to decline 65% compared to 2008 levels,

which is dramatic but still less than the estimated 93% decline within cement projects25. The order intake is

then estimated to gradually recover during the detailed forecast period to once again reach a 50%/50%

split between project order intake in the cement division and minerals division by the beginning of the key

driver forecast period. During the key driver forecast period the growth in order intake is set 1 percentage

point higher than that of cement, as the demand for minerals is assumed to be higher in the long run.

24 One of FLS’ competitors on the market for cement equipment 25 Estimated under “Order intake estimation” in the base scenario Excel document

In mio. mty 2013E 2014E

New contrahented cement capacity 53,0 112% 75,0 42% 140,0 87% 125,0 ‐11% 150,0 20% 10 ‐93% 41 311% 46 12% 53 14% 60 62Consumption (Excl. China) 1197 4% 1256 5% 1328 6% 1396 5% 1443 3% 1367 ‐5% 1317 ‐4% 1351 3% 1416 5% 1484 1544Installed capacity ultimo 1536 1557 1600 1667 1781 1906 2056 2066 2107 2153 2206Utilization rate 78% 81% 83% 84% 81% 72% 64% 65% 67% 69% 70%Market share 34% 33% 29% 29% 32% 34% 33% 33% 32% 32% 31%Estimated price per mty 320 362 267 344 261 275 246 251 258 264 311Projects, order intake 5763 8953 10854 12466 12521 935 3377 3809 4385 5004 6013Service, order intake n/a 1795 1795 3323 3200 3600 4050 4556 5126 5767 6013CEMENT ORDER INTAKE 5763 10748 12649 15789 15721 4535 7427 8366 9511 10770 12026

2007200620052004 2009E2008 2012E2011E2010E

55

Customer Service: The two divisions furthermore generate an increasing amount of its revenue from

Customer Services. According to section 6.6.1.1 “Directly exploitable opportunities” the service order intake

is estimated to continue to grow through the crisis. Through a strong presence within and focus on

customer service, FLS is able to directly exploit this. This is further backed up by the fact that it was

evaluated to be the most important opportunity to focus on here and now. FLS expects Customer Services

to continue to grow 10‐15% p.a. (FLSmidth , 27 min. in). For this reason the service orders are expected to

increase 12,5% p.a. during the detailed forecast period, while during the key forecast period it will stabilize

at 50% of the entire order intake (an increase from approximately 20% during recent years) and hence that

it will follow the same trend as project orders in the long run.

Quality of the order book: According to FLS 3% of the order book, equal to DKK 900 million, has been

cancelled due to the slump in demand. Furthermore, 10% (worth DKK 3 billion) is currently on hold

(FLSmidth , 4:30 min. in). Both cancelled orders and orders on hold are split half and half between cement

and minerals (FLSmidth , 1 hour in). When customers put orders on hold it is most often due to financial

constraints while the slump in commodity prices and hence profitability also plays in (FLSmidth , 41 min.

in). As access to liquidity is not expected to ease considerably in the short run – nor that the commodity

prices will increase anything worth mentioning – FLS is evaluated to see further cancellation and orders put

on hold. However, the worst turbulence is evaluated to be over, for which reason cancellations and orders

on hold are estimated to increase 50% further – leaving FLS with cancellations worth DKK 1,35 billion and

orders on hold worth DKK 4,5 billion. For the reason of simplicity cancelled orders will simply be subtracted

from orders received during 2008, as orders which are more than 1 year to be too expensive for customers

to cancel. Finally, orders on hold are in a similar manner subtracted from the order intake during the recent

year but instead added to the order intake in 2010 and 2011.

7.2.1.1.2 Estimating revenue In a presentation from Q2 2008 FLS has disclosed a graph explaining when revenue from cement orders are

booked (FLSmidth 2007b, slide 23). According to FLS, this is done continuously as delivery and passing of

risk takes place (FLSmidth 2009a, p.57). From this graph the percentage distribution of revenue has been

estimated into quarters26. Lead‐times are assumed to be slightly shorter in the future due to lower activity

among suppliers as well as the continuing implementation of LEAN, for which reason graph is shifted

forward one quarter in order to resemble the future lead times more closely – decreasing lead time from

approximately 11 quarters to 10 quarters.

26 A distribution matrix has been made in the worksheet called “Revenue estimation” in the base scenario Excel file

56

By doing this enables the writer to estimate the future annual revenue using a formula as follows:

0,02 0,02 0,04 0,07 0,12 0,30 0,31

0,07 0,025 0,025


The order intake in the mineral department is translated into revenue on the basis of a similar graph, using

the same formula as for cement, but with slightly different percentages for the booking of revenue as the

lead‐time within minerals is generally slightly shorter27:

0,03 0,06 0,08 0,14 0,26 0,31 0,070,03 0,03


As service is a more day‐to‐day business than large projects, service orders are finalized within just 2

quarters with an estimated 50% booked revenue in each quarter.

Finally, for the sake of simplicity and as this report has chosen not to analyze in‐depth on Cembrit, the

revenue from Cembrit is estimated to be hit immediately by the slowdown in the building sector and hence

that they will see revenue declining 10% in 2009 to levels which will not improve before 2011. From 2011

revenue is estimated to start increasing once again but only with 3% per annum as Cembrit is not part of

the long term strategy. As an in‐depth analysis has not been made on Cembrit, the estimated development

in revenue has been discussed with Equity Analyst, Lars Terp Paulsen in order to ensure dependability28.

For several reasons, translating orders into revenue as done above will never be completely precise.

Nevertheless, this method is evaluated to be a better alternative compared to simply guessing what the

revenue would be. In the long run it is not that important if the lead‐time is shifted one or two quarters one

way or the other, as the important thing is merely that the revenue from all orders are taken account of.

However, in the short run differences from the actual expected revenue and the estimated revenue using

the formula becomes clear. For 2009 FLS’ revenue guidance is DKK 20‐25 billion with slightly declining

revenue within all three divisions (FLSmidth , 30 min. in). Using the procedure explained above to leads to

an estimated revenue of DKK 28 billion for 2009. Hence, to end up with an estimated revenue in 2009 of

DKK 22,5 billion a downward correction is made. These will be spread out over 2010‐2013 instead.

27 As with the formula used to estimate the revenue within cement, the formula used for minerals is based on a graph provided by FLS 28 To read more about this process go to appendix 2.

57

All in all, and according to table 7.3, the revenue estimation leads to an average declining revenue of 0,7%

during the detailed forecast period while during the key forecast period the average is 4%.

Table 7.3: Revenue forecast in total

Source: Own representation on the basis of own estimates

7.2.1.2 Other forecast drivers Apart from de detailed estimation of revenue growth a few other drivers are briefly analyzed.

COGS: First a linear regression for COGS against revenue is conducted in order to estimate how GOGS

statistically should behave in relation to the fluctuating revenue during the detailed forecast period29. That

is – if the situation analyzed in the strategic analysis had been unchanged compared to the recent five

years. As the regression will only be based on five observations this is clearly not optimal. However, in the

lack of longer data sets is evaluated to be sufficient. The regression is calculated to be y = ‐0,7411x ‐ 898,26

with an R2 of 0,9967. Hence, based on 2008 numbers and according to the regression, the variable part of

COGS equals 74% of revenue. Furthermore, the regression estimate the fixed costs be slightly below DKK

900 million which equals 4,6% of GOGS calculated in 2008 numbers, which sounds plausible. Finally, as

costs for salaries connected to production can be found in the notes of the annual report, the direct

material is calculated as the residual. Even though this method is not perfect, it enables a forecast which

intuitively seems more correct than simply guessing. In other words, simply guessing that COGS will decline

e.g. 5% in 2009 might be more or less just as good, but through the method above it enables the writer to

give reason for his estimates.

The forecasted COGS on the basis of the linear regression will be adjusted for following strategic changes

for the short run. First and foremost, suppliers’ bargaining powers are expected to decline considerably in

the short run. Furthermore, declining commodity prices are assumed to make the small part of the spare

parts which FLS produces themselves cheaper. Hence, all in all FLS is assumed to pass on some of the price

pressure to their suppliers, which is forecasted to reduce prices 5% during 2010‐2011 and 2,5% during

29 The regression is simply calculated using a quick‐and‐dirty method in which no actual test is carried out. This is done as the writer already acknowledges that the regression if far from perfect and hence will surely lead to a negative outcome in such a test.

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024

‐ Cement 8098 6849 7745 12078 13588 11188 7991 10646 10599 10940 10855 11915 12660 13173 13701 14251 14823 15417 16036 16679 17349

Growth 17% ‐15% 13% 56% 13% ‐18% ‐29% 33% 0% 3% ‐1% 10% 6% 4% 4% 4% 4% 4% 4% 4% 4%

‐ Minerals 1647 2130 3214 6327 10307 10180 9351 10251 11110 11110 11380 12243 12906 13553 14232 14946 15695 16481 17307 18175 18702

Growth 32% 29% 51% 97% 63% ‐1% ‐8% 10% 8% 0% 2% 8% 5% 5% 5% 5% 5% 5% 5% 5% 3%

‐ Cembrit 976 1147 1216 1419 1390 1251 1251 1289 1327 1367 1408 1450 1494 1539 1585 1632 1681 1732 1784 1837 1892

Growth 9% 18% 6% 17% ‐2% ‐10% 0% 3% 3% 3% 3% 3% 3% 3% 3% 3% 3% 3% 3% 3% 3%

= Total revenue 10829 10250 12311 19967 25285 22619 18594 22186 23036 23417 23644 25608 27060 28265 29518 30829 32199 33631 35127 36691 37943

Growth 19% ‐6% 20% 63% 28% ‐11% ‐18% 19% 4% 2% 1% 8% 6% 4% 4% 4% 4% 4% 4% 4% 3%

Period average

Detailed forcast period Key forecast period

24,7% ‐0,7% 4%

Historically

58

2012‐2013. No corrections are made for 2009, as contracts and hence prices are evaluated already to have

been negotiated.

Last but not least, in January FLS laid‐off 600 employees (6% of the workforce) with 9 months notice. These

employees were laid‐off from Denmark and USA, while Indian employees were only marginally affected

(Risom 2009). As a “normal” amount of reduction in employee costs and hence lay‐offs are assumed

already to be taken account of in the linear regression, only the “over‐normal” reductions are incorporated

on top of those. The idea is that the 6% reduction in the workforce is a natural consequence of declining

revenue which should lead to a 6% reduction in employee costs – that is, if those 6% had been spread

across a representative portfolio of employees from Denmark, USA and India. As Indian salaries are

considerably lower than that of Danes and Americans, reduced costs for salaries in connection with recent

lay‐offs are assumed to be even higher than 6%. For the reason of simplicity the reduction in employee

costs are set at 60% more than statistically forecasted. As revenue starts improving again from 2011, hiring

is treated in a similar manner, as FLS is expected to exploit the situation and increase the use of off‐shoring

to India even more, rather than hire Danes and Americans once over again. Hence, by then employee costs

are expected to increase 60% less than statistically forecasted.

From table 7.4 a summary of the affects are illustrated. On the basis of the above, COGS relative to revenue

is expected to decline marginally in 2009 after which this will gradually decline to a low of 74,1% in 2010‐

2011, after which it is expected to increase to 78% in 2012 and 2013.

Table 7.4: COGS forecast calculations

Source: Own calculations. Included in the base scenario Excel file under the “Driver” worksheet

Selling, Gen. & Administration expenses: Due to the same reasoning as for COGS a linear regression is

calculated for SG&A. The regression is denoted y = ‐0,0914x ‐ 490,55 with an R2 of 0,9801, which tells us

several things. First and foremost the regression estimate fixed costs within SG&A to be slightly below DKK

500 million which equals 17% of costs in 2008. This relative figure is considerably higher than that of COGS,

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Period average

Estimated COGS/Rev 86,5% 81,4% 78,9% 78,6% 77,8% 77,60% 74,1% 74,1% 76,2% 76,2%

Statistical relationship ‐8924 ‐8495 ‐10022 ‐15696 ‐19637 ‐17661 ‐14678 ‐17340 ‐17971 ‐18253

Historical devisations from regression ‐440 153 313 1 ‐27

Effect of lower prices 626 747 388 394

Overnormal reduction in salaries connected to lay‐offs 109 272

Effect os smaller increases in salaries connected to hiring 145 34 15

Estimated COGS ‐9364 ‐8342 ‐9709 ‐15695 ‐19664 ‐17552 ‐13780 ‐16448 ‐17548 ‐17843

Fixed costs (y‐intercept) ‐898 ‐898 ‐898 6% 4,6% ‐898 ‐898 ‐898 ‐898 ‐898

Salaries n/a n/a n/a 7% 8,7% ‐1417 ‐983 ‐1352 ‐1520 ‐1565

Direct material n/a n/a n/a 87% 86,7% ‐15237 ‐11899 ‐14198 ‐15130 ‐15380

Detailed forcast periodHistorically

80,6% 75,6%

59

which makes sense as a large part of the work done in connection with administration is only assumed to

be marginally affected by changes in activity.

Adjustments for changes in salaries are treated in completely the same way as under COGS but with only

40% additional reduction in costs, as not all work done within e.g. administration is assumed to be as off‐

shoreable. As a result SG&A relative to revenue is estimated to remain rather stable during the period,

fluctuating only between 11‐11,4%.

Accounts payable & accounts receivable: The linear regression for accounts receivable relative to revenue

is denoted y = 0,3248x + 850,41 with an R² of 0,9327 while accounts payable is denoted y = 0,0849x +

676,28 with an R² of 0,9649. Using the linear regression is assumed to overestimate both variables, as

constraint access to liquidity will generally speaking probably make companies decrease the credits given to

customers. This assumption seems to be in line with FLS’ own expectations (FLSmidth , 50 min. in). In the

base scenario both accounts payable and receivable are assumed to decline 10% more than the linear

regression estimates.

Other current liabilities: As more or less half of other current liabilities are connected to prepayments the

variable will be forecasted as a percentage of order intake. Calculating this ratio retrospectively lead to a

ratio which has only fluctuated between 17‐21% for 2005‐2008. For this reason an average of these years

(20%) is assumed to be a usable estimate of other current liabilities relative to the order intake throughout

the detailed forecast period.

CFFI (CAPEX and investments) : FLS’ goal is to reduce the CFFI (excl. acquisitions) to a level of DKK 300‐400

million in the future (FLSmidth , 31:30 min. in). As investments (in associated undertakings and in securities)

are expected to remain stable and net other operating assets/liabilities to stabilize at the historical average,

reductions in CFFI are assumed to stem from reductions in CAPEX and investments in intangible assets. CFFI

is set to the middle of the targeted interval (DKK 350 million) by setting CAPEX to 2/3 of CFFI less net other

operating assets/liabilities and investments in intangible assets to the remaining 1/3.

EBITA‐margin: The EBITA‐margin in 2005‐2006 was 4,1% and 6,2% respectively which is assumed to be

rather low as they were negatively affected by among other things high COGS and SG&A. On the other

hand 2007‐2008 seem too high with 9,4% and 10,5% respectively. For this reason the EBITA‐margin is set at

the historical average of 7,8%.

60

Growth in NOPLAT: Growth in NOPLAT is set equal to the forecasted long term world GDP growth rate of

3,3%. Setting it higher than this would not make sense as this would mean that FLS was to outgrow the

general economy in the long run. On the other hand, setting it lower than 3,3% seems overly pessimistic.

7.1.4 Base scenario valuation summary According to the valuation summary included in appendix 25 several things seems relevant to mention.

Most importantly, the fair value per share is estimated at DKK 328. Other than that, 36,3% of the enterprise

value is generated during the continuing value period. As uncertainty increases the further into the future

we estimate, considerable uncertainty is related to this part of the fair value. However, this is a generally

accepted problem with the DCF‐model. According to Elling, as referred to by Møller, on average 60‐70% of

the fair value is estimated to be generated through the continuing value (Møller 2005, p.21).

Furthermore, FLS is estimated to reach a negative FCF in 2009. However, as the economic profit is positive

this means that the company adds value in 2009 but that the actual cash flow is negative due to

investments which in this case are mainly related to working capital.

Comparing the base scenario with the business‐as‐usual scenario valuation as done in fig. 7.1, shows that

the fair value would have been DKK 821 higher if the situation during the recent five years had continued

unchanged. The largest contributor to deviation in fair value is naturally revenue. However, changes in

GOGS and CFFI also have a lot to say.

Figure 7.1: Decomposing deviation in fair value between the business‐as‐usual and base scenarios.


0

200

400

600

800

1000

61

7.2.3 Bull scenario Revenue growth: In the bull scenario the financial packages and government initiative turn out to be as

effective – or even more affective – than expected. The world GDP growth which will be based on Morgan

Stanley’s bull case, only declines slightly below zero (‐0,2%) in 2009 and the world economy already

recovers considerably around the break of the new year 2009/10, leading to a world GDP growth of 4,2% in

2010 (Fels, Pradhan & Andreopoulos 2009, p.6). Recent decades continuous decline in world GDP growth30

comes to an end, for which reason the world GDP growth from 2011 gradually declines to a long term

average of 3,5% which is 5% higher than the long term average calculated in the base scenario. FLS is able

to exploit the financial crisis and win market shares from competitors, for which reason FLS’ share will

increase from 32% in 2008 to 34% in 2009‐2010, after which it will gradually decline to a long term level of

33% (1,5 percentage points higher than the historical average) as the recovering industries start to attract

new entrants. The price per mty turn out to be less price elastic at low levels of activity and hence ends

2,5% higher than under the base scenario. During the detailed forecast period growth in Customer Services

end at 15% p.a. ‐ in the higher end of the interval guided by FLS. Due to different cycles in minerals, the

demand for among others gold remains high, for which reason the order intake in minerals only decline

50%. In the long run demand for minerals is even higher than expected for which reason the growth in the

mineral division is 1,2 percentage points above that of cement. Last but not least, cancellations and orders

put on hold turn out to have peaked by the latest numbers and all orders on hold are made active again.

Other forecast drivers: Due to the fast recovery of the general economy suppliers’ bargaining power only

decreases slightly for which reason the reductions in price under COGS only reach 2,5% in 2010 and 2011.

On the other hand, the strategy with respect to Indian employees is still in effect, and it turns to be 80%

cheaper to make use of Indian workers. As the economy turns, the need to reduce accounts receivable is

less and in order not to lose orders on that account, FLS only reduce credits equal to 5% of the statistically

estimated accounts receivable. At the same time accounts payable simply follow the linear regression.

Other current liabilities remain at 20% of the order intake for which reason it ends at a higher level than in

the base case. The need to decrease CFFI loosens and turns out at DKK 400 million – in the higher end of

the guided interval. Finally, the EBIT‐margins in 2005‐2006 were further below the long term average than

originally expected, for which reason the EBITA‐margin during the key forecast period is set to 8,2% ‐ 5%

above the historic average.

As illustrated in the bull scenario valuation summary in appendix 26, the above leads to an estimated fair

price of DKK 398 per share.

30 As illustrated in appendix 24.

62

7.2.2 Bear scenario Revenue growth: The financial crisis turns worse, and even though the worst is over by the end of 2009 the

recovery is long and slow. On the basis of Morgan Stanley’s bear scenario, world GDP growth declines to a

record low of ‐3,6% in 2009 and only just ends in positive territory at 0,4% in 2010. Due to the slow

recovery world GDP growth only grows slowly towards the end of the detailed forecast period at which

point it settles at the long term level. Recent decades declining world GDP growth continue to a long run

average of 3,2% ‐ 5% below the one used in the base case. Competitors gradually win back some of the lost

market share from 2008 for which reason FLS’ share declines to the historical average of 31% by the end of

the detailed forecast. The struggle to win back market share takes part in increasing rivalry among existing

players in the market even further, leading to price cuts of 5% per mty more than in the base scenario. Due

to the continued worsening of the crisis the entire set of minerals end up affected, for which reason the

slump in the project order intake in minerals declines nearly as much as in the cement division. Continued

constraint access to liquidity means that customers have difficulties financing even maintenance and

upgrading of their equipment, and growth in Customer Services end at 10% p.a. ‐ in the lower end of the

range guided by FLS. Even though prospect in the mineral division continue to be better than that of

cement in the long run, the order intake only increases 0,8 percentage points p.a. more than cement.

Finally, cancelled orders and order put on hold continue to roll in and end at twice the recently announced

levels.

Other forecast drivers: Due to the continued worsening of the crisis, FLS is able to negotiate prices on

direct material as much as 5% lower in 2009, 2012 and 2013, while lower prices peak at 7,5% in 2010‐2011.

Even though focus is still to focus on off‐shoring to India, the economic incentive to do so turns out

considerably lower than expected at only 25%. The constrain access to liquidity means that companies in

general decrease credits to customers, for which reason accounts payable end 15% below the result

calculated on the basis of the linear regression. Other current liabilities continue at 20% of the order intake

this according to previous discussed arguments decline considerably. CFFI is kept at an absolute minimum

at DKK 300 million and the EBITA‐margin during the key forecast period is set at 7,4% ‐ 5% lower than the

base case.

According to the bear scenario valuation summary in appendix 27, the fair value is estimated at DKK 284.

7.2.3 Scenario summary After having carried out the valuation based on three scenarios, it seems relevant to get a brief overview of

the differences and evaluate which variables are most responsible for deviations in fair value. An overview

of driver forecast differences in most variables is included in appendix 28.

63

According to fig. 7.2, in both the bear and bull scenario, revenue is the largest contributor to deviations

from the base scenario. While COGS a, other current liabilities (pre‐payments) and EBITA‐margin also

makes a difference, all other drivers only affect the fair value marginally.

Figure 7.2: Decomposing deviation in fair value between bear, base and bull scenarios


On the basis of the three scenarios a weighted fair value is calculated as

illustrated in table 7.5. With an estimated 15% possibility and bull

scenarios respectively, the weighted fair value ends at DKK 332 per share,

which is close to the DKK 328 per share calculated under the base

scenario isolated seen.

7.3 Value of flexibility After having calculated the fair value, it seems relevant to evaluate if there are additional things to take

account of. One such thing could be real options, which on top of the fair value calculated using the DCF

and EVA‐models can value flexibility. All companies have real options – however, the variety, amount and

value of these options vary greatly from industry to industry. For instance, internet and biotech companies

might be worth a considerable amount of money even though they have very low or even no revenue as

well as negative earnings. This is due to the value of their real options. Hence, the value of a company’s

“portfolio” of real options increases with the level of uncertainty and managements possibility of acting on

new information (Koller et al. 2005, p.248). On an overall level there are four groups of real options –

options to defer investments, options to abandon projects, follow‐on options and a range of different

options to adjust production (Koller et al. 2005, p.550‐551).

280

300

320

340

360

380

400

Table 7.5: Weighted fair value


Scenario Possibility Fair value

Bull 15% 398

Base 70% 328

Bear 15% 284

Weighted fair value 332

64

The fair value calculated in the preceding chapter is the value of FLS as the company is composed today and

with the outlook this gives the company. In order to estimate the value of FLS’ flexibility the writer would

need to indentify the entire set of real options and have relatively good information about them. As an

example, if it turns out that the market for environmentally friendly solutions within the cement industry is

nonexistent in practice, it will not pay off for FLS to keep investing 1‐2% of revenues in developing solutions

in this area in the long run. An option would therefore be to abandon this area – something which the DCF

model does not directly allow the writer to take account of.

As FLS is an engineering company and operate in a relatively low‐tech industry which has not changed

considerably over the years, the value of FLS real options are assumed to be relatively small. This together

with the fact that not enough information is evaluated to be available to come up with an estimate of FLS

fair value including flexibility, no real options will be estimated. However, this section acknowledges that

the fair value could potentially be slightly higher. As will be seen in the following section, considerable

uncertainty is related to the fair value, for which reason it seems valuable to be aware, that the fair value

calculated without flexibility could be seen as a minimum fair value.

7.4 Sensitivity analysis On the basis of the base scenario a sensitivity analysis will be carried out on a set variables in order to

investigate changes in which factors are most crucial for the fair value. This will be done by changing one

variable at a time while keeping all other variables still as specified in the base scenario. The sensitivity will

be denoted as the marginal affect on the fair value from changing each variable.

As was discussed earlier, some uncertainty is connected to all items connected to calculating the WACC.

Furthermore, as a constant rather than a dynamic WACC has been used, together with the fact that the

same WACC was used between the three scenarios, it would be interesting to investigate the fair value’s

sensitivity to the each variable. Sensitivity analysis will also be carried out on some of the detailed forecast

drivers – revenue growth, EBITA‐margin, growth in NOPLAT, ROIC and COGS.

From table 7.6 it is clear that the fair value is most sensitive to changes in the risk premium, as increasing it

by 3 percentage points would lead to a 110% higher fair value. Generally, the fair value is extremely

sensitive to changes connected to the WACC – either on an overall level or in connection with the single

variables. This is a consequence of the fact that the continuing value is responsible for 36,3% of the

enterprise value for which reason the discount factor naturally has a lot to say. Having said that, according

to section 7.1.5, the continuing value in the base scenario makes up a considerably smaller amount here

65

than in the average valuation, which means that the WACC could easily have had an even larger affect of

the fair value.

Table 7.6: Sensitivity measured in percent impact of fair value


Other than that, the fair value is also relatively sensitive to changes in revenue growth and EBITA‐margin.

On the other hand, growth in NOPLAT as well as ROIC, both only have minor affects on the fair value. Even

though they are some of the most discussed subjects in financial literature, it should not come as a surprise

that their affect on FLS is minor. Due to the fact that ROIC was only set 1 percentage point higher than

WACC, even large fluctuations in growth in NOPLAT has a minor affect.

Last but not least, from table 7.7 it is clear that on average the sensitivity related to the drivers analyzed on

in this section is most likely to impact the fair value in the positive direction. That is – if the possibility of a

change in the positive or negative direction for the variables tested above was 50/50, the fair value would

be most likely to end increase.

Table 7.7: Absolute impact on the fair value by changing a group of drivers in the positive and negative direction respectively


All in all, the sensitivity analysis underlines the weakness of the DCF‐models – that the fair value is

extremely dependent on even relatively small changes in some variables and drivers.

7.5 Simulation on forecast drivers After having analyzed the fair values’ sensitivity to variables isolated seen, it would be interesting to

analyze how large an effect the variation in the forecast drivers have all together. A simulation using VBA

will be carried out 10.000 times on the same forecast drivers as defined in section 7,1. Intervals for possible

outcomes are defined so that they harmonize with the probability of the bear, base and bull scenario

respectively. In other words – the bear scenario for each driver is set so that it lies in the middle of a bear

‐3% ‐2% ‐1% 1% 2% 3%

Revenue growth ‐23% ‐16% ‐8% 10% 20% 32%

EBITA‐margin ‐30% ‐20% ‐10% 10% 20% 31%

Growth in NOPLAT ‐2% ‐1% ‐1% 1% 3% 6%

ROIC ‐8% ‐5% ‐2% 2% 3% 4%

COGS 10% 7% 4% ‐3% ‐7% ‐10%

Risk‐free rate 63% 35% 15% ‐12% ‐21% ‐28%

Risk premium 110% 53% 21% ‐15% ‐26% ‐35%

WACC 69% 37% 16% ‐12% ‐22% ‐29%

‐0,3 ‐0,2 ‐0,1 0,1 0,2 0,3

Beta 18% 12% 6% ‐5% ‐9% ‐14%

Change in percentage points

Change in absolute values

1% 2% 3%

Avrg. impact in positive direction 10% 22% 41%

Avrg. impact in negatie direction 8% 15% 21%

66

scenario with the possibility of 15%. Hence, as illustrated in fig. 7.3, the lower limit for simulated values is

set comparatively lower in order to make the possibility of a situation worse than the “average” bear

scenario 7,5%.

In order not to reach unrealistic scenarios where e.g. the revenue moves from bear to bull cases each year,

correlation is forced into the simulation. This is done by only picking one random number for each period.

Hence, if the revenue in 2009 starts slightly below the bull scenario, it will be similarly below the bull

scenario in 2010‐2013. Furthermore, only three different random numbers are picked – one relates to the

condition of the general economy which drives most variables, one relates to the realized gains from

making more use of Indian workers as this is not assumed to be affected by e.g. the general economy, and

one to the EBITA‐margin as it is evaluated as possible that the costs structure has changed considerably by

the beginning of the key forecast period.

The simulation leads to fair values as depicted in a histogram in fig. 7.4. According to this, the average fair

value is simulated to at DKK 344. In other words, this is slightly above both the base scenario fair value of

DKK 328 and the weighted fair value of DKK 332. Furthermore, the simulation shows a rather wide interval

ranging from DKK 270 to DKK 410. The conclusion on the simulation must therefore once again be that due

to considerable variation there is uncertainty with regards to the estimated fair value.

Base

7,5% 7,5% 70% 7,5% 7,5%

Bear Bull

Figure 7.3: Simulation range

Figure 7.4: Simulated fair value distribution


270 290 310 330 350 370 390 410

0

20

40

60

80

100

120

Fair value

Frequency

67

7.6 Peergroup comparison Finally, a peer group comparison will be carried out in order to get a more market oriented idea about the

value of FLS. In other words, as the fair value calculated using the DCF‐model shows what the writer

evaluate each share to be worth, multiples calculated through peer group comparison gives a picture of

what the investors are currently willing to pay for comparable companies.

The peer group could be defined in several ways. One way could be to calculate a weighted peer‐group by

splitting it into two groups: manufacturers of cement equipment and manufacturers of minerals

equipment. The reason this based on the conclusion from the strategic analysis, that sales from cement

equipment is more cyclical than that of mineral equipment, together with the estimated higher long term

growth rates for mineral equipment in general. However, several problems are connected with this

method. First and foremost, only few competitors within each industry are evaluated to be comparable to

FLS, hence making the peer‐group relatively narrow, which might lead to problems with transferability of

the results. Hence, in order to safeguard the quality of the report another method is used. As FLS has

outsourced most of their manufacturing, it seems fair to define them as an engineering company, for which

reason other engineering companies are chosen as peer‐group31.

In order to derive at a meaningful comparison, peer‐group companies should have similar prospects for

both ROIC and growth. One way to do this would be to analyze these two factors in depth for all companies

with the same GICS classification. However, as it would be rather comprehensive, information from Equity

Analyst Lars Terp Paulsen will be relied on. On the basis of this information an engineering peer‐group is

composed by a wide range of companies which are sufficiently comparable to FLS – among others Assa

Abloy, Atlas Copco and Sandvik (Paulsen 2009, interview 22. April).

Multiples used are P/E which depicts what investors are willing to pay per crown earned. In other words it

gives an idea about the market’s expectations with regards to the growth prospects of that given company.

This multiple seems intuitively appealing and is one of the most widely used multiples probably because it

is easily understandable for non‐professionals. However, as P/E is affected by capital structure as well as

nonoperating profits and losses, it is not the best multiple to compare the value of different companies.

The multiple EV/EBITA goes around this problem, for which reason it is included in the peer‐group analysis.

Furthermore, the multiples will be based on forward looking consensus estimates for 2009 and 2010, which

is evaluated to be most appropriate, as the fair value is based on future performance rather than past

performance, which a trailing multiple would have depicted (Koller et al. 2005, p.365‐366).

31 This has been discussed with Equity Analyst, Lars Terp Paulsen who agrees

68

Table 7.8: Peer‐group comparison

(Own representation on the basis of data from Datastream , 22. April 2009)

According to the peer‐group comparison in table 7.8, and with an average discount of 41% relative to the

peer‐group, FLS is considerably undervalued at current levels. Looking at the peer‐group isolated seen, FLS

should be trading between DKK 269‐379 with an average of DKK 316, which is close to the fair value of DKK

328 calculated in the base case as well as the weighted fair value of DKK 332 and the simulated fair value of

DKK 344.

There are several possible reasons why FLS is trading at a considerable discount compared to the peer‐

group. One is that peer‐groups including the one in question will never be completely comparable.

However, according to the discussion during the formulation of this peer‐group, problems due to this are

sought minimized considerably.

Another plausible reason is that FLS is still burdened by a bad image during times of trouble, as they were

close to bankruptcy last time they had problems. It is possible that the market has still not fully taken

account of FLS new business model and through this the fact that today they are far less cyclical than just a

few years ago. Furthermore, as FLS during the recent years has outsourced manufacturing and off‐shored

workers to a larger extent than ever before, the costs structure has changed considerably. In other words

FLS’ costs structure is much more flexible than that of most competitors, for which reason they will

presumably be in a better shape to handle a declining order intake.

Enginee ring companies Share price MV PE PE EV/EBITDA EV/EBITDA

(USD) (mio. USD) 2009 2010 2009 2010

ASSA ABLOY 'B' 10,8 3965,7 11,7 11,9 8,1 8,3

ATLAS COPCO 'A' 8,9 10528 ,4 14,6 15,5 9,6 10,1

METSO 13,9 1969,3 7,9 12,1 5,8 7,6

OUTOTEC 20,7 867,8 11,0 15,0 3,8 5,3

SANDVIK 7,0 8254,9 18,5 15,9 9,2 8,9

SKF 'B' 10,5 4.762,5 16,3 13,5 7,6 7,0

Simple average 13,3 14,0 7,4 7,9

Market weighted average 15,0 14,6 8,6 8,8

FLSmidth (DKK 182) 31,69 1686,2 7,2 9,5 4,6 5,9

Premium on FLS relative to peer‐group ‐52% ‐35% ‐46% ‐32%

Share price corrected relative to peer‐group 379 280 336 269

69

7.7 Preliminary conclusion From table 7.9 a comparison of the estimated fair values is made.

As the weighted fair value is close to Jyske Bank’s fair value,

dependability seems to be high. In other words the estimated fair

value seems plausible. In connection with this it seems appropriate

to mention that the small deviation between the two is based the

sheer coincidence as a comparison was purposely not made before

the writer had carried out his valuation, as this could otherwise

have lead to considerable bias.

Hence, relative to the share price of DKK 139 on the cut‐off date, FLS is evaluated to be considerably

undervalued. In other words, on that day there was an estimated potential relative to the fair value of

139%32. Acknowledging that considerable uncertainty is present, the fair value calculated in this report is

evaluated to be the writer’s best possible estimate.

32 Since then the share price has gone up considerably, closing at DKK 180 on the 24. April. Even though the general market has

been rather positive, this indicates that investors have begun to realize that FLS (as well as the general stock market) is undervalued at current levels.

Table 7.9: Calculated fair value alternatives

Source: Own calculations as well as Equity

Analyst, Lars Terp Paulsen

Method Fair value

Base scenario fair value 328kr. Bull scenario fair value 398kr. Bear scenario fair value 284kr.

Weighted average fair value 332kr. Fair value, Jyske Bank 322kr.

Simulated fair value 344kr.

Peer‐group comparison 316kr. Actual share price 139kr.

70

8. Conclusion The purpose of this report was to estimate the fair value of FLS using fundamental analysis. This was done

using both a DCF and an EVA model. Forecasts where based on an analysis of historical accounts as well as

a strategic analysis covering both external and internal factors.

First an analysis of the historical accounts was carried out, through which it was concluded on the basis of

the calculated invested capital, NOPLAT, FCF, ROIC and revenue growth, that FLS has generally had a

healthy development during the recent five years. The healthy development has furthermore made

acquisitions possible, through which FLS has reached a more balanced risk profile between cement and

minerals. All in all, FLS was evaluated to be in good shape to handle a period of lower activity. Finally, the

WACC was estimated at 9,2%.

On the basis of the historical financial analysis, a business‐as‐usual valuation was carried out in order to

estimate the fair value of FLS, provided that the development during the recent five years turned out to

continue into the future. This was done in order to reach a starting point for analyzing the effect of the

conclusions from the strategic analysis later on. Doing this led to a fair value of DKK 1.110 per share.

The strategic analysis started out by analyzing the dynamics of the industry, through which it was evaluated

to places somewhere in‐between stable and turbulent. Through the PEST model the general environment

was evaluated to change marginally to the worse in the short run, but also that in the long run it would

return to a situation even better than during the recent five years. All in all, FLS was evaluated to be most

dependent of economic factors such as world GDP growth, constraint access to liquidity and declining

commodity prices. Contrary to the overall situation, economic factors isolated seen were evaluated to

worsen considerably in the short run and that it would only return to a medium level in the long run.

Turning to the analysis of the industries in which FLS operates, two more or less separate analysis were

conducted. This was done in order to investigate if and where differences between the two divisions

existed. However, in the end they were evaluated to be closely comparable, as the threats from the five

forces were not only evaluated to be on more or less the same levels, but also that they would both remain

close to stable in the short as well as long run. Having said that, the overall threat within each industry was

defined by different dynamics and changes. Hence, the threat from existing players on the market as well

as new entrants where evaluated to be slightly higher within minerals, while the threat from substituting

products was assumed to slightly higher within cement.

After having analyzed the external factors, focus was turned to the internal factors. Here the most

important conclusions were as follows. The availability ‐ or rather the lack of ‐ qualified employees was

71

identified as a problem for FLS as this, rather than funds, put constraints on activities within R&D which

furthermore meant that FLS were evaluated not to be fully able to exploit one of the identified sustainable

competitive advantages – the world’s largest experiment and test center within production of cement.

However, returning to the external analysis this was evaluated to ease in the short run. One way FLS has

reacted on the lack of qualified workers has been to off‐shore large parts of the work to India. Furthermore,

outsourcing is used to a wide extent, which means that the costs structure is more flexible than most

competitors – something which was evaluated to be a strength during periods of low activity as the one we

seem to be entering. However, at the same time it was evaluated to be a weakness during times of high

activity, as this might lead to constraint access to spare parts, long lead times and problems with ensuring

quality. With regard to the leadership a democratic and participative style was detected. This together with

strong focus on employees’ wellbeing was evaluated to be the right fit for a knowledge intensive and rather

creative industry in which FLS operates. In connection with leadership it furthermore seems relevant to

mention that it was evaluated if there were factors which were assumed to potentially limit strategic drive

among top management. Even thought there were minor remarks, this was generally not evaluated to be a

problem. Finally, the key factors for success were identified as being total‐costs‐of‐ownership and a good

brand defined by quality, reliability and good reputation. Both are factors in connection with which FLS is in

a good position to compete.

The strategic analysis was finished off by a critical SWOT, in connection with which FLS’ need to change was

evaluated to be low. Finally, the most valuable opportunities and threats respectively were identified in

order to investigate where focus should be given that FLS is not able to take care of all factors at the same

time. Here increasing demand for customer services, suppliers’ decreasing bargaining powers as well as

possibilities for horizontal integration were evaluated as the most important opportunities at the moment.

Contrary to this, different threats which were all connected to a declining order intake were identified as

the most important threats.

After finishing the strategic analysis the actual valuation was carried out on a base, bull and bear scenario

respectively. In the base scenario the order intake, and hence with a slight lag the revenue, was estimated

to decline considerably in the short run. This was due not only to declining demand, but on the basis of the

strategic analysis, an estimated price pressure partially offset by an increasing market share in the short

run. With continued referral to the conclusions in the strategic analysis, among other things FLS was

evaluated to pass on some of the price pressure to their suppliers, that they would make use of even more

off‐shoring of work to India and that companies generally speaking will try to reduce credits given to

customers. All in all, the fair value in the bull, base and bear scenarios were estimated at DKK 398, DKK 328

72

and DKK 284 per share respectively. With an estimated possibility of 15% each the bear and the bull

scenarios, a weighted fair values was calculated at DKK 332. Acknowledgment was given to the fact that

this was the fair value of FLS excluding flexibility and that flexibility would preferably have been included by

making use of real options. However, due to the lack of information and as the value of flexibility in

connection with FLS was assumed to be small, this was not done.

In a sensitivity analysis changes in the risk premium was identified as being responsible for the single

largest impact on the fair value. However, the fair value was identified as highly sensitive to changes in the

WACC and its variables in general, as well as to changes in both revenue and EBITA‐margin. All in all,

changes in variables tested were identified as most likely having a positive rather than negative impact on

the fair value. As an extension of the sensitivity analysis in which the fair values’ reaction to changes in

variables isolated seen was analyzed, a simulation was carried out in order to analyze the effect on a rather

random set of changes occurring at the same time. Doing this lead to a simulated fair value of DKK 344.

Finally, a peer‐group comparison was carried out in order to investigate what investors were willing to pay

for similar companies and hence how FLS is currently priced relative to competitors. Through this

comparison FLS was identified as trading at a considerable discount compared to the peer‐group. Applying

peer‐group multiples on FLS lead to a share price of DKK 316.

All in all, the final estimated fair value was set equal to the weighted fair value of DKK 332 at which FLS is

considerably undervalued compared to the share price of DKK 139 on the cut‐off date.

73

9. Reflection During the making of the report the writer has become aware of areas which he would have done things

differently if it was to be written all over again.

First and foremost, the report would have been written in collaboration with someone else. Looking back

this would have been preferred in order to establish a healthy discussion about the methods of analysis as

well as conclusions. Even though the writers is confident that the preceding report ended up just as good as

it would have been if written in collaboration with someone else, it has taken much longer and been much

more demanding that it needed to be. This is especially true as the writer only had slight knowledge within

finance beforehand and as no courses in either analyzing historical accounts or valuation had been taken,

which meant that everything had to be learned from scratch. Having said that, this means that, all other

things being equal, the writer should be 100% into each and every detail of the report and hence that the

full possible learning outcome has been harvested.

Additionally, more time would have been used in connection with choice of company. This is true as it

turned out that FLS was divided into more business areas than first realized. Due to this it was not possible

to carry out as detailed an analysis and forecast as first planned. In other words, a more detailed and

narrow analysis would have been preferred over a broader and more general analysis as this is evaluated to

be a necessity for getting close to the actual fair value. Through this the difficulty would furthermore have

been sought increase by e.g. choosing a company where it seemed relevant to incorporate issues such as

real option from the start.

74

10. Figure and table list Figure 3.1: Share price development of FLS vs. OMXC20 Table 4.1: Invested capital summary Table 4.2: NOPLAT summary Table 4.3: Free‐cash flow summary Table 4.4: ROIC calculated Table 4.5: Beta alternative Table 4.6: Peer‐group credit ratings Table 4.7: Estimated WACC compared with analysts’ averages Table 6.1: PEST summary Table 6.2: Summary of Five Forces grading Table 7.1: Overview of detailed forecast drivers Table 7.2: Base scenario revenue estimation for cement Table 7.3: Revenue forecast in total Table 7.4: COGS forecast calculations Table 7.5: Weighted fair value Table 7.6: Sensitivity measured en percent impact on fair value Table 7.7: Absolute impact on fair value by changing a group of drivers in the positive/negative direction respectively Table 7.8: Peer‐group comparison Table 7.9: Calculated fair value alternatives Figure 7.1: Decomposing deviation in fair value between the business‐as‐usual and base scenario Figure 7.2: Decomposing deviation in fair value between the bear, base and bull scenario Figure 7.3: Simulated range of fair values Figure 7.4: Simulated fair value distribution

75

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serv.com/portal/play.php?k=12349486202304fc9d1efef824701940fca8003286a9651176 [2009, April 7th] .

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77

12. Appendices

Appendix 1: Illustrated structure of the report

Appendix 2: Ensuring quality of the report

Appendix 3: Accounting policies

Appendix 4: Reorganized balance sheet

Appendix 5: Reorganized income statement

Appendix 6: Free cash flow analysis

Appendix 7: Decomposition of ROIC

Appendix 8: Revenue growth analysis

Appendix 9: 10‐year German government bond rate

Appendix 10: Beta regression analysis

Appendix 11: Spreads over US treasuries

Appendix 12: Variable which are not extrapolated into the future

Appendix 13: Business‐as‐usual valuation summary

Appendix 14: Degree of turbulence

Appendix 15: Order backlog

Appendix 16: PEST analysis

Appendix 17: Porter’s Five Forces analysis

Appendix 18: Market share

Appendix 19: VRIO Framework

Appendix 20: Critical SWOT – Strengths and opportunities

Appendix 21: Critical SWOT – Weaknesses and threats

Appendix 22: Relative rating of opportunities

Appendix 23: Relative rating of threats

Appendix 24: Historical world read GDP growth rates

Appendix 25: Base scenario valuation summary

Appendix 26: Bull scenario valuation summary

Appendix 27: Bear scenario valuation summary

Appendix 28: Driver scenarios compared

Appendix 29: Word count

78

Appendix 1: Illustrated structure of the report

•Preface

•Executive summary

•Introduction

•Brief company introction

•Problem statement

•Structure

•Delimitations

•Method

•Quality of the analysis

Introductory part

Ch.1‐3

•Historical accounts analysis

•Analysis of invested capital

•Analysis of NOPLAT

•Free cash flow analysis

•ROIC analysis

•Revenue growth analysis

•Estimating WACC

• (Business‐as‐usual valuation)

•Strategic analysis

•External analysis

•Dynamics of the environment

•Environmental analysis (PESTEL)

•Industry analysis (5‐Forces)

•Internal analysis

•Key factors for success

•Critical SWOT

•Analysis of FLS' need to change

•Evaluating opportunities and threats

Analysis part

Ch. 4‐6

•Forecast drivers

•Scenario valuations

•Value of flexibility

•Sensidivity analysis

•Simulation

•Peer‐group comparison

Valuation part

Ch.7

•Conlusion

•Reflection

Concluding part

Ch.8‐9

79

Appendix 2: Ensuring quality of the analysis

The following are a couple of general comment connected to ensuring the quality of the analysis:

In order to ensure credibility cited sources have been attempted contacted in order to make sure that have

been interpreted correctly. As discussed earlier this has generally been rather difficult for which reason this

could be a slight problem. However, sources with which the writer has had personal contact (mainly Lars

Tarp Poulsen) have been contacted. This has not lead to any changes.

With respect to transferability, a discussion with Lars Terp Paulsen finally lead to slight change in my

estimates. With regards to the revenue estimation in Cembrit the writer had first simply set it do develop

as that within the cement division in the short run after which it was set to 3% in the long run. However,

according to Lars Tarp Paulsen, Cembrit is a much more day‐to‐day business for which reason they will be

hit by the general slowdown much faster. Furthermore, Cembrit generally follows another business cycle

than cement. As Cembrit has not been analysed in depth it was evaluated to be plausible that my estimates

were not as good a Lars’ in this area. Hence, in order to ensure the quality of the analysis the revenue

growth for Cembrit in the short run was finally changes according to the new information. The new revenue

estimates for Cembrit were finally evaluated by Lars Terp Paulsen to be plausible.

80

Appendix 3: Accounting policies In order to make sure that numbers are comparable it is important to investigate if there have been

changes to the accounting policies used. If so, changes should as far as possible be attempted incorporated

retrospectively.

Up to and including the annual report of 2004 the accounting policies used were in accordance with

Årsregnskabsloven (FLSmidth 2005, p.38). However, from 2005 and onwards FLS has carried out the annual

report according to IFRS (FLSmidth 2006, p.40). In order to make 2004 comparable to the remaining years

following the IFRS standards, a few corrections are taken account of.

IFRS 1: Pension obligations were previously treated according to IAS 19. However, according to IFRS 1

regarding first‐time adoption all not already included, actuarial gains and losses on 1 January 2004 have

been recognized in the equity. No adjustment, however have been made for the effect of actuarial losses

regarding FLS Aerospace, as it was sold during 2004. Furthermore, previously included actuarial gains and

losses regarding 2004 have been reversed from the profit and loss account and included in the equity

together with the non‐recognized actuarial gains and losses. Actuarial gains and losses for 2005 have been

recognized directly in the equity as a consequence of the revised IAS 19 (FLSmidth 2006, p.47).

IFRS 2: According to IFRS 2 stock options should be included as part of the staff costs according to the

accruals principle until the expected time of acquisition and offset against the equity. Stock options have

not previously been included in the profit and loss accounts or the balance. Old plans (cash settlements),

which are mainly related to employees who have left the FLS, are recognized at full fair value on the

balance sheet date, while value adjustments are recognized in the balance sheet as liabilities and in the

profit and loss account as financial items (FLSmidth 2006, p.47).

IFRS 3: According to IFRS 3 it is no longer allowed to amortizes on goodwill, which should instead undergo

an annual impairment test (FLSmidth 2006, p.47). For this reason booked impairments from 2004 are

reversed. Impairment tests for both 2004 and 2005 have not resulted in any write down on the goodwill.

Liabilities in connection with anniversary obligations must be booked in the profit and loss accounts

continuously as the obligation is built up. The provision for anniversary obligations is classified as a long‐

term liability. Previously, anniversary bonuses where simply included in the profit and loss accounts at the

time of payment. In connection with the new standards current obligations built up in previous accounting

years are credited on long term liabilities and debited in shareholders’ equity. However, as the actual

obligation primo and ultimo 2004 are the same, there are no effects on the profit and loss accounts.

The above changes affect deferred tax, for which reason this is taken account of in the opening balance on

1. January 2004. All in all the adjustments for the 2004 income statement increases EBITDA with DKK 64

million, and EBIT with DKK 87 million (FLSmidth 2006, p.48). Similarly, the 2004 balance sheet is adjusted

with regards to immaterial assets (DKK 25 million) and financial assets (DKK ‐38 million) together with

equity (DKK‐60 million) and long term liabilities (DKK 47).

81

Appendix 4: Reorganized balance sheet

Own calculations on the basis of annual reports.

Copied from the worksheet called “Reformulated” in the base scenario file.

Invested capital calculation 2004 2005 2006 2007 2008

Operating cash 217 205 246 399 506

Inventories 529 552 832 1463 1802

Accounts Receivable 3915 3878 5425 8011 8564

Other Current Assets 687 350 502 1198 1190

Operating assets 5348 4985 7005 11071 12062

Accounts Payable 2340 2571 3445 4670 6071

Other Current Liabilities 2026 2817 3638 5201 5239

Tax Payable 43 117 129 299 248

Operating liabilities 4409 5505 7212 10170 11558

Operating working capital 939 ‐520 ‐207 901 504

Net Property Plant and Equip 1007 1047 1000 1237 1405

Other assets net of other liabilities ‐610 ‐814 ‐1205 ‐1449 ‐1274

Value of operating leases 14 16 16 17 14

Invested capital (excl. goodwill) 1350 ‐271 ‐396 706 649

Acquired intangibles and goodwill 197 237 309 5425 5522

Cumulative amortization and pooled goodwill 91 115 163 315 455

Invested capital (incl. goodwill) 1638 81 76 6446 6626

Excess cash 1100 2679 2886 802 420

Long term investments 190 98 65 76 64

Total funds invested 2928 2858 3027 7324 7110

Short Term Debt 69 153 132 491 94

Long Term Debt 215 167 161 2225 1458

Operating Leases 14 16 16 17 14

Debt and debt equivelants 298 336 309 2733 1566

Deferred Income Taxes ‐188 ‐379 ‐734 ‐64 ‐146

Cumulative amortization and pooled goodwill 91 115 163 315 455

Total Common Equity 2560 2644 3188 4204 5013

Minority Interest 25 4 4 10 22

Retirement Related Liabilities 142 138 97 126 200

Equity and equity equivelants 2630 2522 2718 4591 5544

Total funds invested 2928 2858 3027 7324 7110

82

Appendix 5: Reorganized income statement



NOPLAT calculation 2005 2006 2007 2008

Revenues 10250 12311 19967 25285

Costs of Goods Sold ‐8342 ‐9709 ‐15695 ‐19664

Selling, Gen & Admin Expenses ‐1447 ‐1730 ‐2241 ‐2836

Depreciation Expense ‐136 ‐130 ‐130 ‐255

Other Operating Expense 97 94 69 126

Adj. Operating leases 1 1 1 1

Adj. EBITA 423 837 1971 2657

Reported taxes 18 183 ‐584 ‐667

Taxes on interest income 183 167 289 413

Tax shield on interest expense ‐148 ‐122 ‐274 ‐493

Taxes on non‐operating income 0 ‐3 2 ‐30Tax shield on lease interest expense 0 0 0 0

Change in deferred tax ‐191 ‐355 670 ‐82

NOPLAT 285 707 2073 1797

Net Income 478 1141 1294 1515

Increase in deferred taxes ‐191 ‐355 670 ‐82

Minority Interest ‐2 ‐9 0 0

Amortzation 24 48 152 140

Special items after tax 0 9 ‐4 77

Loss/gain from discontinuing operations 54 ‐25 ‐1 ‐59Adj. Net income 363 809 2111 1591

After tax interest expense 328 271 704 1267

After tax operating lease interest 0 0 0 0

Total income available to investors 692 1081 2815 2859

After tax interest income ‐407 ‐372 ‐742 ‐1061Non ‐operating income after tax 0 ‐2 0 0

NOPLAT 285 707 2073 1797

83

Appendix 6: Free cash flow analysis



Historical free cash flow calculation 2005 2006 2007 2008

NOPLAT 285 707 2073 1797

Depreciation Expense 136 130 130 255

Gross cash flow 421 837 2203 2052

Investment in operating working capital 1459 ‐313 ‐1108 398

Net capital expediture ‐176 ‐249 ‐386 ‐627

Investments in intangibles and goodwill ‐64 ‐120 ‐5268 ‐237

Investments in operating leases ‐2 0 ‐1 3

13 ‐85 ‐90 ‐181

Increase (decrease) in other operating liabilities 191 476 334 6

Increase (decrease) in other fixed assets 0 166 19 204

Gross investment 1421 ‐125 ‐6500 ‐434

Free cash flow 1842 712 ‐4297 1617

Reinvestment ratio ‐337% 15% 295% 21%

84

Appendix 7: Decomposition of ROIC


Copied from the worksheet called “ROIC” in the base scenario file.

2005 2006 2007 2008

2005 2006 2007 2008 81,4% 78,9% 78,6% 77,8%

2005 2006 2007 2008 4% 7% 10% 11% 14,1% 14,1% 11,2% 11,2%

2005 2006 2007 2008 78% ‐251% 1269% 392% ‐0,9% ‐0,8% ‐0,3% ‐0,5%

53% ‐212% 1335% 265% 1,3% 1,1% 0,7% 1,0%

33% 16% ‐5% 32% 2,0% ‐3,0% 1,7% 2,8%

19,0 ‐36,9 128,6 37,3 10,0% 8,3% 5,6% 5,2%

‐6,9% ‐8,2% ‐6,6% ‐5,4%

0,1% 0,1% 0,1% 0,1%

100%

minus

Gross margin

minus

SG&A/revenue

minus

Other operating exp./rev.

minus

plus

Operating leases/revenue

Cash tax rate

Pre‐tax ROIC

plus

Other assets/revenue

Avrg. cap. turns

X (1‐cash tax rate) X

Depreciation/revenue

1 divided by

Operating working capital/rev.

plus

Fixed assets/revenue

ROIC

Operating margin

2005 2006 2007 2008 Average pp. change

100,0% 100,0% 100,0% 100,0% 100,0%

Gross margin 81,4% 78,9% 78,6% 77,8% 80,6% ‐3,6%

SG&A/revenure 14,1% 14,1% 11,2% 11,2% 12,7% ‐2,9%

Other operating exp (inc.). /rev. ‐0,9% ‐0,8% ‐0,3% ‐0,5% ‐0,6% 0,4%

Depreciation/revenue 1,3% 1,1% 0,7% 1,0% 1,7% ‐0,3%

Operating margin 4,1% 6,8% 9,9% 10,5% 5,7% 6,4%

Operating working capital/rev. 2,0% ‐3,0% 1,7% 2,8% 0,9% 0,7%

Fixed assets/revenue 6,0% 8,3% 5,6% 5,2% 6,3% ‐0,8%

Other asstets/revenue ‐6,9% ‐8,2% ‐6,6% ‐5,4% ‐6,8% 1,6%

Operating leases/revenue 0,1% 0,1% 0,1% 0,1% 0,1% ‐0,1%Avg cap 80,5 ‐36,9 128,6 37,3 52,4 ‐43,2

Pre‐tax ROIC 331,5% ‐250,8% 1268,7% 392,0%Cash tax 32,6% 15,5% ‐5,2% 32,3%

ROIC excl. goodwill 223,39% ‐211,78% 1334,55% 265,23%

85

Appendix 8: Revenue growth analysis

Own calculations on the basis of annual reports. Copied from the worksheet called “Sales” in the base scenario file.

Own calculations on the basis of annual reports as well as information from Equity Analyst, Lars Terp Paulsen, Jyske Bank. Copied from the worksheet called “Orderbook hist” in the base scenario file.

Cement in DKK mio.

Denmark 68 19% 60 ‐12% 38 ‐37% 67 76% 52 ‐22% ‐16 ‐24%

Scandinavia excl. DK 62 ‐24% 31 ‐50% 23 ‐26% 56 143% 24 ‐57% ‐38 ‐61%

Rest of Europe 1139 ‐23% 967 ‐15% 915 ‐5% 1120 22% 2529 126% 1390 122%

Nort America 1178 ‐21% 1118 ‐5% 1633 46% 2803 72% 2316 ‐17% 1138 97%

South America 228 12% 150 ‐34% 196 31% 500 155% 1023 105% 795 349%

Africa 2750 59% 1138 ‐59% 1292 14% 2937 127% 2360 ‐20% ‐390 ‐14%

Australia 45 ‐24% 25 ‐44% 38 52% 29 ‐24% 51 76% 6 13%

Asia 2628 46% 3360 28% 3610 7% 4566 26% 5233 15% 2605 99%

Cement in total 8098 17% 6849 ‐15% 7745 13% 12078 56% 13588 13% 5490 68%

Minerals in DKK mio.

Denmark 1 0% 1 0% 1 0% 3 200% 1 ‐67% 0 0%

Scandinavia excl. DK 30 100% 29 ‐3% 27 ‐7% 137 407% 127 ‐7% 112 373%

Rest of Europe 103 ‐13% 77 ‐25% 164 113% 617 276% 906 47% 787 764%

Nort America 165 ‐20% 350 112% 717 105% 1446 102% 2397 66% 2190 1327%

South America 342 76% 424 24% 562 33% 1190 112% 2492 109% 2298 672%

Africa 375 15% 403 7% 655 63% 969 48% 1205 24% 880 235%

Australia 192 ‐1% 296 54% 283 ‐4% 551 95% 1158 110% 964 502%Asia 439 125% 550 25% 805 46% 1414 76% 2021 43% 1826 416%

Minerals in total 1647 32% 2130 29% 3214 51% 6327 97% 10307 63% 9057 550%

Cembrit in mio. DKK 976 9% 1147 18% 1216 6% 1419 17% 1390 ‐2% 493 51%

Total 10721 19% 10126 ‐6% 12175 20% 19824 63% 25285 28% 15040 140%

Total ?

Total ?

Sales development

2005 2006 2007 20082004

2004 2005 200820072006

0

1.000

2.000

3.000

4.000

5.000

6.000

mio. DKK

Order intake cement ‐ cement vs. services & spare parts

Cement Services & spsare parts

0%

20%

40%

60%

80%

100%

2004 2008

Divisional sales vs. group sales

Cembrit

Minerals

Cement

0500

1.0001.5002.0002.5003.0003.5004.0004.5005.000

mio. DKK

Order intake Minerals ‐minerals vs. services & spare parts

Minerals Services & spsare parts

86

Appendix 9: 10year German government bond rate

(Own production on the basis of Euroinvestor , date: 01.01.09)

012345678910

04‐01‐1989

04‐01‐1990

04‐01‐1991

04‐01‐1992

04‐01‐1993

04‐01‐1994

04‐01‐1995

04‐01‐1996

04‐01‐1997

04‐01‐1998

04‐01‐1999

04‐01‐2000

04‐01‐2001

04‐01‐2002

04‐01‐2003

04‐01‐2004

04‐01‐2005

04‐01‐2006

04‐01‐2007

04‐01‐2008

Rate

10‐year German government bond

87

Appendix 10: Beta regression analysis Model ~ , , 1,2, … , 60 where

·

Where, Y is the monthly share price development of FLS in % X1 is the monthly development in MSCI World in %

Assumptions 1. Normally distributed

is normally distributed, ~ 0,

The points are placed along a straight line, and more or less with the same number of points in each side of the line, for which reason the assumption is assumed to be fulfilled.

2. Linearity 0, . . ·

Assumes that the relationship described by the model is linear.

The assumption is assumed to be fulfilled, as the points are approximately asymmetrically arranged around 0. Also, if we disregard the 1‐3 outliers there are no tendency of any pattern.

3. Variation in error component constant constant

Assumes the variation in the error component is constant and independent of the value of X

According to the graph under assumption 2, this assumption is assumed to be fulfilled, as there are no wedge or trumpet formation.

4. Independent error components

, 0 ~ independent error components

Assumes that there is no pattern in the error components – that there is no systematic change in the sign.

‐4

‐3

‐2

‐1

0

1

2

3

4

‐4 ‐3 ‐2 ‐1 0 1 2 3 4U‐fractiles

Standard Risiduals

‐4

‐3

‐2

‐1

0

1

2

3

4

‐60% ‐40% ‐20% 0% 20% 40%

Stan

dard residualts

FLS share development

88

According to the graph there might be a slight breach in this assumption.

Output

From the graph it seems appropriate to construct a linear regression model.

According to the statistical output generated by Excel the model is defined as 0,0252 1,746

Hypothesis testing 1. Formulation of hypothesis

: 0 (The line is not usable) : 0 (The line is usable)

2. Significance level 0,05 5%

3. Choice of test statistic ^

^ ^ ~ 1

4. Test statistic From the output it is seen that t= 7,5984

5. Critical value

7,5984 , , 2,00 => : 0 rejected – hence, the line is usable 6. P‐value

From the table it can be seen that the P‐value is practically speaking 0 – hence very significant

As is rejected

7. Conclusion

Maintain ‐ MSCI World Index is in fact a usable in explaining the development in FLS’ monthly share price development.

‐5

0

5

0 10 20 30 40 50 60 70

Stan

dard residuals

Observation

y = 1,746x + 0,0252R² = 0,4989

‐60%

‐40%

‐20%

0%

20%

40%

‐30% ‐20% ‐10% 0% 10%

MSCI W

orld USD

FLSmidth

FLS vs. MSCI World

SUMMARY OUTPUT

Regression Statistics

Multip le R 0,7063

R Square 0,4989

Adjusted R Squa 0,4902

Standard Error 0,0835Observations 60

ANOVA

df SS MS F Significance F

Regression 1 0,402100944 0,402100944 57,73569912 2,89218E‐10

Residual 58 0,403941671 0,006964512

Total 59 0,806042615

Coeffic ients Standard Error t Stat P‐value Lower 95% Upper 95% Lower 95,0% Upper 95,0%

Intercept 0,0252 0,0109 2,3228 0,0237 0,0035 0,0470 0,0035 0,04700,015427428 1,7460 0,2298 7,5984 0,0000 1,2860 2,2060 1,2860 2,2060

89

Appendix 11: Spreads over US treasuries

Source: Own representation on the basis of data from Bloomberg

0

1000

2000

3000

4000

5000

6000

7000

06‐01‐2006 06‐01‐2007 06‐01‐2008 06‐01‐2009

Spread

Spreads over US treasuries

BBB‐

BBB

A

AA

AAA‐S

AAA

AAA‐J

90

Appendix 12: Variable which are not extrapolated into the future Revenue growth: The five year historical average is used for the detailed forecast period, while it is gradually reduced to 3% during the key forecast period. This is done as it would not make sense for FLS to outgrow the general economy in the long run.

Goodwill: No additions or disposals are taken account of. Even though there is a good chance that FLS through horizontal integration will make use of the current acquisition opportunities, trying to estimate the size together with the effect they would have on other drivers such as revenue seems too random. In other words, this is done in order to keep the quality of the analysis high as problems with dependency could otherwise arise.

Extraordinary items are set to 0 as a five year average would lead to an annual extraordinary income of DKK 105 million for which the writer has no direct explanation.

Interest rates: The interest rate on excess cash is set equal to the risk free rate, while all other interests are set equal to the cost of debt.

Debt: Even though FLS has a long term goal to operate with an equity ratio of 30%, this would presumable imply that they would gradually need increase debt, which among other things would be used for acquisitions. However, due to a similar rationing as with goodwill, trying to estimate changes in debt is sufficiently random to make the quality of the analysis higher by simply keeping it stable until more reliable estimates can be used. In other words, it would not make sense to increase debt just for the reason of doing it ‐ the writer would have to estimate how and where the proceeds were to be used. If this is not done, excess cash would skyrocket indefinitely which seem unrealistic.

Dividends: During the period 2004‐2007 FLS has paid out a stable DKK 372 million in dividends each year. As earnings continue to grow in the long run, it would not be realistic to carry on seeing dividends at these levels, as they would make up a continuing smaller amount of earnings. However, as the dividend relative to earnings during the latest five years has been between 29‐254% a historical average would be far too high. As the size of dividend has no effect in the calculated fair value future dividends are simply assumed to be 1/3 of earnings which seems plausible.

Other adjustments to equity are set to 0 as the writer has no real chance of estimating future levels and as historical averages are not assumed to give much sense.

Tax: Tax paid is set equal to current tax payable, hence keeping tax payable constant at current levels. The effective tax rate is simply set equal to the marginal tax rate.

ROIC: The thought is, that if FLS earns an ROIC above the WACC, this will attract new entrants until competition has increased sufficiently to lower RIOC to the level of the WACC. Similar to this thought, FLS would not be able to maintain any competitive advantage they might have in the long run, which furthermore points in the direction of a long term ROIC close or equal to the WACC. As research shows that ROIC tend to revert towards a mean in the long run (Koller et al. 2005, pp. 142‐150)(Kotler, Keller 2006), the question is how fast ROIC reverts towards this mean, as well as what this mean might be. During 1964‐2003 the average ROIC on a wide range of companies was 9% (Koller et al. 2005, p.146). ROIC could be set equal to WACC which was estimated at 9,2% and is hence practically equal to the average long term ROIC calculated above. However, according to Koller et. al. this has historically proven to be overly pessimistic for companies initially earning a high ROIC which FLS is (Koller et al. 2005, p.149). Linking this to the previous mentioned thought that a ROIC higher than the WACC would attract competition still makes sense as ROIC would presumably have to be sufficiently higher than the WACC in order for it to be feasible to even start up a company. All in all ROIC, is set to 10,2% in the long run ‐ 1 percentage point higher than WACC.

91

Appendix 13: Businessasusual valuation summary

Source: Output from the Excel file

Value of Operations: DCF approach Value of Operations: Economic Profit Value of EquityFree Cash Discount PV Economic Discount PV Operating Value 62.056

Year Flow Factor of FCF Year Profit Factor of EP Excess Mkt Securities 420

2009 (4.012) 0,916 (3.673) 2009 909 0,916 833 Financial Investments 62 2010 47 0,838 39 2010 810 0,838 679 Excess Pension Assets 0 2011 (483) 0,767 (371) 2011 1.157 0,767 888 2012 (492) 0,703 (345) 2012 1.547 0,703 1.087 Enterprise Value 62.538 2013 (490) 0,643 (315) 2013 2.049 0,643 1.318 (1.552) 2014 1.815 0,589 1.069 2014 2.503 0,589 1.474 (14) 2015 1.052 0,539 567 2015 3.273 0,539 1.765 (200) 2016 1.731 0,494 855 2016 3.980 0,494 1.965 Preferred Stock 0 2017 2.578 0,452 1.165 2017 4.725 0,452 2.136 (22) 2018 3.596 0,414 1.488 2018 5.479 0,414 2.267 0 2019 4.777 0,379 1.810 2019 6.209 0,379 2.352 0 2020 6.097 0,347 2.115 2020 6.876 0,347 2.385 Future Stock Options 0 2021 7.514 0,318 2.386 2021 7.441 0,318 2.363 (37) 2022 8.974 0,291 2.609 2022 7.863 0,291 2.286 60.713

2023 10.404 0,266 2.769 2023 8.108 0,266 2.158 Cont. Value 174.190 0,266 46.368 Cont. Value 97.505 0,266 25.955 53.200

Operating Value 16 58.536 Present Value of Economic Profit 51.911 1141,22

Invested Capital (incl. goodwill) 6.626 Continuing value % Operating value 79,2% 598,00

Operating Value 58.536 NAMid -Year Adjustment Factor 1,060 Mid -Year Adjustment Factor 1,060 90,8%Operating Value (Adjusted) 62.056 Operating Value (Adjusted) 62.056 NA

Comparison of key ratios Evaluation of entry and exit multiples

From: 2004 2009 2014 2019To: 2008 2013 2018 2023 2008 2024

Revenue growth (CAG) 23,6% 25,9% 19,6% 9,2% Operating Value 62.056 174.190Adjusted EBITA growth (CAG) 84,5% 16,1% 19,1% 9,2%NOPLAT growth (CAG) 84,8% 17,0% 19,2% 9,2% Excess Mkt Securities 420Invested capital growth (CAG) 334,1% 30,4% 14,7% 9,1% Financial Investments 62

Adj. EBIT/Revenues 6,3% 6,8% 6,8% 6,8% Enterprise Value 62.538 174.190

Revenues/Invested Capital (pre-Goodwill) (13,1) 15,4 6,4 6,0 Revenue 25.285 313.250ROIC (after tax, pre-Goodwill) -127,2% 74,3% 31,2% 29,0% Adjusted EBITA 2.657 21.454ROIC (after tax, including Goodwill) 909,4% 18,8% 21,0% 21,2% NOPLAT 1.797 15.222Average Economic Profit 465 1.294 3.992 7.299

Enterprise / Revenue 2,5 0,6Cash Tax Rate 18,8% 29,0% 29,0% 29,0% Enterprise / Adjusted EBITA 23,5 8,1WACC 8,1% 9,2% 9,2% 9,2% Enterprise / NOPLAT 34,8 11,4

Averages

Equity Value

Value Difference - Low

Long-Term Operating Provision

DebtCapitalized Operating LeasesRetirement Related Liability

Minority Interest

Restructuring Provision

Stock options

Value Difference - High

Value per ShareNo. shares (thousands)

Date: 03.06.08 -High -Low

92

Appendix 14: Degree of Turbulence

(Own production on the basis of: Lynch 2006, p.83)

Environmental Repetitive Expanding Changing Discontinuous Surprisingturbulence

Regional Regional Global

technological socio‐political economicFamiliarity Discontinuous Discontinuousof events familiar novel

Rapidity of Slower than Comparable to Faster thanchange response response response

Visibility of Recurring Forecastable Predictable Partially Unpredictable

future predictable surprising

Turbulence 1 (low) 2 3 4 5 (high)level

Predictability

Complexity National National

Familiar Extrapolable

Chan

geab

ility

93

Appendix 15: Order backlog


Copied from the worksheet called “Sales” in the base scenario file.

0

5.000

10.000

15.000

20.000

25.000

30.000

35.000

40.000

mio. D

KK

Order backlog

94

Appendix 16: PEST analysis

PEST analysis(Points 1‐5: From good to bad situation)

Political factors Past SR LR Economic factors Past SR LR

Political stability in developing countries

Enforcement of laws → E.g. environmental laws

Taxation law

Employment and safety law

Competition law and government policy

4 3 3 3 3

4 3 333

4 1 333

Real GDP growth

Inflation

Consumer expenditure and disposable income

Cost of debt33

Currency fluctuations and exchange rates

Increased public spending

Unemployment → Due to low unemployment FLS has not been able to attract enough qualified engineers for many years

Changes in oil price / energy costs / transport costs

Changing mineral prices

Constraint access to liquidity

3 3 2 2 3 3 4 1

1,5 2

5 3 4 4 4

2,5 2 4 4 5

333

33

34

2

33

Social factors Past SR LR Technological factors Past SR LR

Shifts in values and cultures → The more materialistic people get, the more minerals and cement is used

Education →The more focus put on the need for education in developing countries, the higher the need will be for cement and minerals in the long term

Demografic changes →An increasing middle class in developing countries →Increasing average age of death increases the need for e.g. new buildings

3 3 4

3 3 3

2 2 1

Identified new research initiatives (especially within environmentally friendly solutions)

Outsourcing

Off‐shoring

4

2 3

3 2 2

2

22

Own representation on the basis of qualitative evaluation

PEST summary Past SR LR Political factors average 3,2 3,2 2,8 Economic factors average 2,5 3,8 3,0 Social factors average 3,3 3,0 1,7 Technological factors average 3,0 2,3 2,0 Total average 3,0 3,1 2,4

33 Discussed in connection with calculating the costs of capital

95

Appendix 17: Porter’s Five Forces analysis RED = Minderal division , GREEN= Cement division

X = Historical (recent 5 years) situation

SR = Short run

LR = Long rung

Competition among existing players within the industry: Favourable

situation (1 point)

Slightly favourable situation (2 point)

Medium situation (3 point)

Slightly unfavourable situation (4 point)

Unfavourable situation (5 point)

1. Are there many competitors? SR, X, LR, SR X, LR

2. Are the several size wise equal competitors? X X

3. Does the entire market grow slowly? X X LR LR SR, SR

4. Are competitors burdened by high fixed costs and/or storehouse costs?

LR, LR X, X

5. Could you say that there exists non‐differentiation LR X, X

6. Are there low shifting costs for customer when changing supplier?

X, X

7. Do capacity expansions in the industry take place in large steps?

LR, LR X X

8. Are different strategic motives the reason for strong competition?

X X

9. Are there high exit barriers in the industry? X X SR,LR,SR,LR

(Reproduced and altered further on the basis of: Lægaard, Jørgen & Vest, Mikael 2002, pp.54‐55)

Competition from new entrants: Favourable

situation (1 point)





1. Do pronounced economies of scale exist within the industry?

X X

2. Is it expensive to establish as a new company? X X

3. Does a high degree of product differentiation exist within the industry?

LR X X 34

4. Are customers faced with high shifting costs when changing to a newly established competitor?

X X35

5. Do new entrants have difficult access to distribution channels?

X X

6. Do new entrants have other relative cost disadvantages? X X

7. Does the government favor existing players in the industry?

LR X X

8. Does history predict retaliatory action against new entrants?

X X

9. What is the profitability in the industry? X, LR X

(Preproduced and altered on the basis of: Lægaard, Jørgen & Vest, Mikael 2002, pp.56‐57)

34 Discussed under section 6.3.1 ” Competition among existing players in the industry” 35 Discussed under section 6.3.1 ” Competition among existing players in the industry”

96

Threats from substituting products: Favourable

situation (1 point)



Slightly unfa‐vourable situation (4 point)

Unfa‐vourable situation (5 point)

1. Are there producers in other industries, whose products in the long run can become substitutes?

X , X SR, LR LR

2. Does products exist, which through slight changes can become substitutes?

X , X

(Reproduced and altered on the basis of: Lægaard, Jørgen & Vest, Mikael 2002, pp.58‐59)

Customers bargaining power: Favourable

situation (1 point)





1. Are there few customers in the market to take the product and/or is the company dependent on few customers?

X, LR, X, LR SR, SR

2. Does the purchase in the industry make up a large part of the customer’s total purchases?

X , X

3. Are products sold in connection with which it is not possible to differentiate?

X , X

4. Provided that the customer wants a new supplier, is it connected with low shifting costs?

X , X36

5. Do customers experience low profitability in their industries, which makes them pressure prices in the supplier industry?

X X SR, LR, SR, LR

6. Do customers threaten with a backwards vertical integration?

X X

7. Will the customers pay for a differentiated product? LR X X

8. Do customers have complete information regarding price and margins in different parts of the industry?

X X


36 Discussed under section 6.3.1 ” Competition among existing players in the industry”

97

Suppliers bargaining power: Favourable

situation (1 point)





1. Are there few suppliers and are they available? a. Ordinary suppliers: b. Human capital:

SR, SR SR, SR

LR, LR

LR, LR X, X X, X

2. Do the suppliers sell a product without any real substitutes? a. Ordinary suppliers: b. Human capital:

X, X

X, X

3. Is the company without importance for the economic future of the supplier? a. Ordinary suppliers: b. Human capital:

SR, SR

LR, LR SR, SR

X, LR, X, LR

X, X

4. Are alternative suppliers differentiated? a. Ordinary suppliers: b. Human capital:

X, X X, X

5. Have suppliers created shifting costs? a. Ordinary suppliers: b. Human capital:

X, X X, X

6. Do suppliers threaten with forwards vertical integration? (only relevant with respect to ordinary supplier)

X, X


The threat from… Average grade (1=low, 5=high) Cement Minerals Historical / SR / LR Historical / SR / LR

1. … existing players in the industry 3,0/3,4/3,0 3,1/3,6/3,1

2. … new entrants 3,1/3,1/2,9 3,2/3,2/3,1

3. … substituting products: 1,5/2,0/2,5 1,5/1,5/2,0

4. … customers bargaining power 2,8/3,0/2,8 2,8/3,0/2,9

5. … suppliers bargaining power c. Ordinary suppliers: d. Human capital:

3,2/2,2/2,5 4,0/3,2/3,8

3,2/2,2/2,5 4,0/3,2/3,8

Overall threat from forces 2,9/2,8/2,9 3,0/2,8/2,9

98

Appendix 18: Market share

Own representation on the basis of FLS’ annual report 2004‐2008

5%

10%

15%

20%

25%

30%

35%

2004 2005 2006 2007 2008

FLSmidth

Sinoma

Polysius

KHD

Andre

99

Appendix 19: VRIO Framework Vroom framework

Val‐uable?

Rare? Costly/difficult to imitate?

Capable of being exploited by the firm? (Balancing factor)

Competitive implications

Expected competitive economic performance

Resource

No ‐ ‐ No Competitive disadvantage

Below normal ...

Yes No ‐ Competitive parity

Normal Headquarters, cement, Valby (Location)

Headquarters, minerals, Bethelehem (Location)

Office buildings in India (Location) Production facilities in Asia (Location) Normal everyday resources (e.g. cars, interior and computer)

Close partnerships with key suppliers HR department

Career development and talent programs

Competent board members and top management

Qualified employees

Management’s experience from tough times

Focus on long term development of the business

Yes Yes No Temporary competitive advantage

Above normal Strategic partnerships with Højteknologifonden and DT

CEO, Jørgen Huno Rasmussen

Yes Yes Yes Yes Sustainable competitive advantage

Above normal World’s largest experiment/test centre for cement

Portfolio of well known and reliable brands + strong reputation

Strong knowledge and focus on product development – especially environmentally friendly ones

(Reproduced and developed further on the basis of Lynch 2006, p,221)

100

Appendix 20: Critical SWOT – Strengths and opportunities Strengths Opportunities

5,9

1

2

3

4

10

6

5,9

11

6

6

11

• Long history

• Operating in a dynamic environment

• More than 50% of rev. generated in developing countries – strong long‐term

outlook

• Low fixed costs due to limited in‐house production (80‐90% outsourced)

(FLSmidth, Tofte 2008)

• M: Foreseeable future ‐ record order backlog ‐ long lead times (FLSmidth,

Robles 2008, slide 6)

• Strong brand names ‐ reputation for quality equipment and exceeding

promised performance (FLSmidth, Birch 2008, slide 9)

• First class customer service – well positioned – increasing focus

• Sold plants are optimized for low construction costs, are quick to produce at

full capacity and to be less energy consuming than the average plant on the

market ‐ but are more expensive initially (FLSmidth, Birch 2008, slide 10)

• Good reputation with financial institutions make financing easier (FLSmidth,

Birch 2008, slide 10)

• Use of down payments of 10‐15% => negative working capital (FLSmidth,

Robles 2008, slide 6)

• M: Equipment produced is less manpower intensive to operate than most

competitors (FLSmidth, Robles 2008, slide 10)

• C: Large market share

• Able to supply entire plants instead of just single machines (FLSmidth, Robles

2008, slide 13)

• Strategic partnerships with DTU and Højteknologifonden

• M: Not dependent on a single or few metals (FLSmidth, Tofte 2008, FLSmidth,

Robles 2008)

• Off‐shoring of some services, IT, and engineering (FLSmidth, Tofte 2008)

• Risk of volatile raw material prices are passed on to customers (FLSmidth,

Tofte 2008)

•Well defined crisis plans and strong focus on risk management, together with

experience in political unstable countries

• Leading technology – especially within environmental friendly alternatives

(FLSmidth, Tofte 2008)

• Company is less cyclical on an overall level than a few years age

• Strong focus on employees’ wellbeing, strong HR department which offers

career development programs as well as talent programs

•FLS has survived a life threatening company crisis – valuable experience

• LEAN is being implemented

• Owns the world’s largest experiment and test center

• Experienced management and staff in general

• Democratic leadership style used

•Good relationship with stakeholders

•Good relationship with shareholders

•Strong focus and knowledge within R&D

• Democratic leadership style

• Focus on shareholder value

4

8

5

1

6

5

3

2

6,7

6,7

6,7

• Horizontal & vertical integration

‐ Mining is primarily involved in processing and

only slightly in mining

• Continued increase in the need for cement and

minerals due to e.g.

‐ High global GDP (LR) ‐ Increased public spending (SR) ‐ Further urbanization and industrialization

in Asia (LR) ‐ High commodity prices (LR) – oil

important for the cement division while metals are important for the mineral division

‐ Social factors expected to increase to the better (SR/LR) ‐ E.g. increasing middle class in

developing countries (SR/LR)

• Increasing availability of workers (SR)

• Decreasing bargaining powers among suppliers

(SR)

• M: Further focus on “untapped” former Soviet

countries (SR) – old and inefficient facilities (Robles,

FLSmidth January 2007)

• Increasing customer focus on total‐cost‐of‐

ownership (SR)

• Increasing demand for customer services (SR)

• Political factors expected to increase to the better

(LR)

‐ E.g. increasing focus on CO2

emission/new laws (SR/LR)

• Technological factors expected to increase to the

better (LR)

‐ E.g. new possibilities for product

development (SR/LR)

• Decreased threat from new entrants (LR)

‐ E.g. increased product differentiation

especially within cement (LR)

‐ Decreased margins within the industry for

mineral equipment (LR)

101

Appendix 21: Critical SWOT – Weaknesses and threats Weaknesses Threats

7,12 • Constraints on R&D activities – lack of qualified workers

• Sold plants are more expensive initially (but has lower total‐cost‐of‐ownership)

(FLSmidth, Birch 2008, slide 10)

• Long lead‐times: Delivery time is important when customers decide who to do

business with (FLSmidth, Birch 2008, slide 11)

• Operating in cyclical sectors

11

9

10

12

• Increasing free capacity in customers’ industries

• Constraint access to workers (LT)

• Political instability in some developing countries (SR/LR)

• Constraint access to workers (LR)

• Customers’ focus on consolidation rather than

expansion (FLSmidth, Robles 2008, slide 5) (SR)

• Consumer price inflation – developing countries focus

on basic needs as food instead of e.g. infrastructure (SR)

• Increased competition from low‐cost competitors; many

exist within the cement industry, few within mining (LR)

• Economic factors are overall expected to change to the

worse (SR)

‐ Low commodity prices (SR)

‐ Low global GDP (SR)

• Increasing overall threat from customers bargaining

powers (SR)

‐ Fewer but larger customers due to tightening

money supply for some customers,

bankruptcies and consolidation (SR)

‐ Increased economic pressure on customers –

some of it passed on to suppliers (SR)

• Increasing overall competition from existing

competitors (SR)

‐ Slower growth (SR)

‐ Medium high exit barriers (SR)

‐ M: Increased competition from Asia (LR)

• Increasing overall threat from substituting products (LR)

‐ Partly from new/future business areas

(environmentally friendly equipment)

• Risk of supply‐chain constraints; low control over the

supply of equipment from suppliers due to limited in‐

house production.

• Constraint access to liquidity (SR)

102

Appendix 22: Relative rating of opportunities Evaluation of opportunities: Points Economic effect Resources at disposal Time horizon

5. Very large Completely at disposal now Right away

4. Large ... ...

3. Considerable Partly at disposal now Short term (within a few years)

2. Small … …

1. Nine / negative Not at disposal now Long term

(Own development with inspiration from Lægaard, Jørgen & Vest, Mikael 2002, p.125)

Evaluation of opportunitiesGreen = Opportunities to fokus on now

Orange = Opportunities to focus on at a later point Red = Opportunities which should not be focused on at all due to no/negative economic effect

Weighted points in total

Economic effect

Resources at disposal

Time horizon

Increasing demand for customer services 4,7 4 5 5

Decreasing bargaining powers among suppliers 4,3 3 5 5

Horizontal integration 4,3 4 4 5

Increasing middle class in developing countries 4,0 3 4 5

Further urbanization and industrialization in Asia 4,0 3 4 5

Increasing focus on total cost of ownership 4,0 2 5 5

Increased availabi lity of workers in the short run 4,0 2 5 5

Increasing focus on CO2 emission/new laws ‐> product development 3,7 5 2 4

High commodity prices in the long run 3,7 5 4 2

High global GDP in the long run 3,7 5 4 2

Increased public spending 3,7 1 5 5

Further focus on untapped former Sovjet countries 3,3 3 4 3

Vertical integration 3,3 1 4 5

Decreasing threat from new entrants 3,0 2 5 2

103

Appendix 23: Relative rating of threats Evaluation of threats:Points Economic effect Resistance resources at disposal Time horizon

5. Threatens future existence

Completely at disposal now Right away

4. Large ... ...

3. Considerable Partly at disposal now Short term (within a few years)

2. Small … …

1. None Not at disposal now Long term

(Developed with inspiration from Lægaard, Jørgen & Vest, Mikael 2002, p.126)

Evaluation of threatsGreen = Threats to focus on here and now Orange =

Threats to focus on at a later point

Avrg. points in

total

Economic effect

Resistance resources

Time horizon

Low commodity prices ‐> low order intake 4,7 5 4 5

Low global GDP ‐> low order intake 4,7 5 4 5

Increasing free capacity in customers' industries ‐> low order intake 4,3 4 4 5

Customers' focus on consolidation rather than expansion ‐> low order intake 4,0 3 4 5

Increasing overall threat from competition among existing players on the market 4,0 4 3 5

Continued political instability in some developing countries 3,7 2 4 5

Increasing overall threat from customers bargaining powers in the short run 3,3 4 1 5

Constraint access to workers in the long run 2,7 3 3 2

Increasing overall threat from substituting products 2,0 2 3 1

Consumer price inflation 2,0 2 1 3

104

Appendix 24: Historical world real GDP growth rates

(Own production on the basis of data from: Bureau of Economic Analysis (BEA), U.S. Department of Commerce 2009)

‐13,0

‐8,0

‐3,0

2,0

7,0

12,0

17,0

1930

1933

1936

1939

1942

1945

1948

1951

1954

1957

1960

1963

1966

1969

1972

1975

1978

1981

1984

1987

1990

1993

1996

1999

2002

2005

2008

World GDP growth

GDP Growth y‐o‐y 5 year moving avrg. Avrg. Of the century

105

Appendix 25: Base scenario valuation summary

Based on the output in the “Valuation summary” worksheet in the Base scenario Excel file



2009 (730) 0,916 (669) 2009 1.170 0,916 1.072 Financial Investments 62 2010 3.321 0,838 2.783 2010 1.000 0,838 838 Excess Pension Assets 0 2011 1.715 0,767 1.316 2011 1.550 0,767 1.190 2012 2.092 0,703 1.470 2012 1.230 0,703 864 Enterprise Value 19.280 2013 2.291 0,643 1.474 2013 1.262 0,643 812 (1.552) 2014 286 0,589 169 2014 596 0,589 351 (14) 2015 1.083 0,539 584 2015 610 0,539 329 (200) 2016 1.198 0,494 592 2016 659 0,494 325 Preferred Stock 0 2017 1.279 0,452 578 2017 698 0,452 315 (22) 2018 1.339 0,414 554 2018 740 0,414 306 0 2019 1.402 0,379 531 2019 785 0,379 298 0 2020 1.468 0,347 509 2020 833 0,347 289 Future Stock Options 0 2021 1.537 0,318 488 2021 882 0,318 280 (37) 2022 1.609 0,291 468 2022 935 0,291 272 17.455

2023 1.685 0,266 449 2023 990 0,266 264 Cont. Value 24.174 0,266 6.435 Cont. Value 12.403 0,266 3.302 53.200



Operating Value 17.732 NAMid -Year Adjustment Factor 1,060 Mid -Year Adjustment Factor 1,060 -45,1%Operating Value (Adjusted) 18.798 Operating Value (Adjusted) 18.798 NA


From: 2004 2009 2014 2019To: 2008 2013 2018 2023 2008 2024

Revenue growth (CAG) 23,6% -1,5% 4,7% 4,4% Operating Value 18.798 24.174Adjusted EBITA growth (CAG) 84,5% 1,2% -3,9% 4,4%NOPLAT growth (CAG) 84,8% 2,3% -3,9% 4,4% Excess Mkt Securities 420Invested capital growth (CAG) 334,1% 3,4% 5,3% 3,1% Financial Investments 62


Revenues/Invested Capital (pre-Goodwill) (13,1) 17,5 15,8 13,6 Revenue 25.285 37.943ROIC (after tax, pre-Goodwill) -127,2% ##### 88,1% 75,5% Adjusted EBITA 2.657 2.969ROIC (after tax, including Goodwill) 909,4% 25,1% 16,5% 17,4% NOPLAT 1.797 2.112Average Economic Profit 465 1.243 661 885


Averages

Equity Value




Minority Interest


Stock options




106

Appendix 26: Bull scenario valuation summary

Based on the output in the “Valuation summary” worksheet in the Bull scenario Excel file



2009 (186) 0,916 (170) 2009 1.369 0,916 1.253 Financial Investments 62 2010 3.334 0,838 2.795 2010 1.189 0,838 996 Excess Pension Assets 0 2011 1.864 0,767 1.431 2011 1.728 0,767 1.326 2012 2.088 0,703 1.467 2012 1.455 0,703 1.022 Enterprise Value 23.025 2013 2.358 0,643 1.517 2013 1.482 0,643 953 (1.552) 2014 789 0,589 465 2014 884 0,589 520 (14) 2015 1.405 0,539 757 2015 894 0,539 482 (200) 2016 1.485 0,494 733 2016 951 0,494 470 Preferred Stock 0 2017 1.564 0,452 707 2017 1.008 0,452 456 (22) 2018 1.642 0,414 680 2018 1.068 0,414 442 0 2019 1.724 0,379 653 2019 1.131 0,379 428 0 2020 1.810 0,347 628 2020 1.198 0,347 415 Future Stock Options 0 2021 1.900 0,318 603 2021 1.268 0,318 403 (37) 2022 1.995 0,291 580 2022 1.342 0,291 390 21.200

2023 2.094 0,266 557 2023 1.420 0,266 378 Cont. Value 29.534 0,266 7.862 Cont. Value 17.665 0,266 4.702 53.200





From: 2004 2009 2014 2019To: 2008 2013 2018 2023 2008 2024

Revenue growth (CAG) 23,6% 1,6% 4,2% 4,7% Operating Value 22.543 29.534Adjusted EBITA growth (CAG) 84,5% 3,4% -2,5% 4,7%NOPLAT growth (CAG) 84,8% 4,4% -2,5% 4,7% Excess Mkt Securities 420Invested capital growth (CAG) 334,1% 3,8% 4,7% 3,3% Financial Investments 62


Revenues/Invested Capital (pre-Goodwill) (13,1) 21,5 19,0 17,2 Revenue 25.285 44.038ROIC (after tax, pre-Goodwill) -127,2% ##### 110,7% 100,2% Adjusted EBITA 2.657 3.618ROIC (after tax, including Goodwill) 909,4% 28,0% 19,9% 21,0% NOPLAT 1.797 2.570Average Economic Profit 465 1.445 961 1.272


Averages

Equity Value




Minority Interest


Stock options




107

Appendix 27: Bear scenario valuation summary

Based on the output in the “Valuation summary” worksheet in the Bear scenario Excel file



2009 (262) 0,916 (240) 2009 1.366 0,916 1.250 Financial Investments 62 2010 2.619 0,838 2.195 2010 830 0,838 695 Excess Pension Assets 0 2011 1.701 0,767 1.306 2011 1.319 0,767 1.013 2012 2.188 0,703 1.537 2012 1.062 0,703 746 Enterprise Value 16.924 2013 2.405 0,643 1.547 2013 1.046 0,643 673 (1.552) 2014 (262) 0,589 (154) 2014 383 0,589 226 (14) 2015 794 0,539 428 2015 418 0,539 226 (200) 2016 983 0,494 485 2016 468 0,494 231 Preferred Stock 0 2017 1.085 0,452 490 2017 493 0,452 223 (22) 2018 1.134 0,414 469 2018 525 0,414 217 0 2019 1.184 0,379 449 2019 558 0,379 211 0 2020 1.236 0,347 429 2020 593 0,347 206 Future Stock Options 0 2021 1.291 0,318 410 2021 630 0,318 200 (37) 2022 1.348 0,291 392 2022 668 0,291 194 15.099

2023 1.407 0,266 375 2023 709 0,266 189 Cont. Value 20.251 0,266 5.391 Cont. Value 8.954 0,266 2.383 53.200





From: 2004 2009 2014 2019To: 2008 2013 2018 2023 2008 2024

Revenue growth (CAG) 23,6% -5,1% 6,4% 4,2% Operating Value 16.441 20.251Adjusted EBITA growth (CAG) 84,5% -1,3% -4,5% 4,2%NOPLAT growth (CAG) 84,8% -0,3% -4,5% 4,2% Excess Mkt Securities 420Invested capital growth (CAG) 334,1% 1,8% 6,3% 2,9% Financial Investments 62


Revenues/Invested Capital (pre-Goodwill) (13,1) 15,2 18,6 12,7 Revenue 25.285 33.551ROIC (after tax, pre-Goodwill) -127,2% ##### 98,6% 67,1% Adjusted EBITA 2.657 2.494ROIC (after tax, including Goodwill) 909,4% 23,8% 14,5% 15,3% NOPLAT 1.797 1.777Average Economic Profit 465 1.125 457 632


Averages

Equity Value




Minority Interest


Stock options




108

Appendix 28: Driver scenarios compared

2004‐2008 2009‐2013 2014‐2034 2024‐>

Bull 3,1% 3,5%

Base 2,0% 3,3%

Bear 0,4% 3,2%

Bull 275 318

Base 259 311

Bear 233 295

Bull 34,0% 33,0%

Base 33,0% 31,0%

Bear 32,0% 31,0%

Bull 2,0% 4,4%

Base ‐0,7% 4,5%

Bear ‐4,2% 5,1%

Bull 76,6%

Base 75,6%

Bear 74,3%

Bull 10,9%

Base 11,2%

Bear 11,6%

Bull 34,1%

Base 32,7%

Bear 31,4%

Bull 23,9%

Base 21,6%

Bear 20,5%

Bull 12,1% 8,2%

Base 12,7% 7,8%

Bear 13,6% 7,4%

Bull 3,5%

Base 3,3%

Bear 3,2%

7,8%

311

4,6%

g‐NOPLAT

EBITA‐

margin

World GDP

growth

Acc.

Pay./Rev.

Acc.

Rec./Rev.

SG&A/Rev.

COGS/Rev.

Revenue

growth

Market

share

cement

Price per

mty cement

24,4%

38,4%

12,7%

80,6%

24,7%

31,0%

109

Appendix 29: Word count

In order to ensure that the 70 page limit of the report is respected, the final word count is documented.

According to ASB’s 2.200 character (no spaces) page standard, 70 pages equal 154.000 characters. As

documented in the word count, counting from (and including) the preface all the way to the reflection,

148.488 characters have been used.

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