university of nigeria analysis as a tool for... · - 2.2.2 material price variance 11 11 17 ......
TRANSCRIPT
University of Nigeria Research Publications
ODO, John
Aut
hor
PG/MBA/02/32111
Title
Variance Analysis as a Tool for Cost Control (A Case Study of Selected)
Facu
lty
Business Administration
Dep
artm
ent
Accountancy
Dat
e
June, 2005
Sign
atur
e
VARIANCE ANALYSIS AS A TOOL FOR COST CONTROL
(CASE STUDY.'OF SELECTED MANUFACTURING COMPANIES)
OD0 JOHN
- DEPARTMENT OF ACCOUNTANCY
FACULTY OF BUSINESS ADMINISTRATION UNIVERSITY
OF NIGERIA, ENUGU CAMPUS
JUNE 2005
7
CERTIFICATION
The work embodied in this project report is original and has not been
submitted in part or full for any other Diploma or degree of this or any other
University.
This is to certify that OD0 JOHN a student in the department of
Accountancy with registration number PGIMBA/02/32111 has satisfactorily
completed the requirement for project research in partial fulfillment of the
requirements for the award of Master of Business Administration (MBA) in
Accountancy. ,
Supervisor .
----------------- DATE
Head of Department DATE
DEDICATION
Dedicated to All Lovers of Truth.
ACKNOWLEDGEMENT
My profound ahd immeasurable gratitude goes to God Almighty, who
protected me through the ups and downs in pursuance of this course.
Many people directly or indirectly contributed to the completion of
- this research. ~ o m ' e among them are: the past and the present Vice
chancellor of the school, University of Nigeria, the Dean of Management
Science, our former able HOD and the current dynamic HOD of
Accountancy Department, Distinguished lecturers of the Department
especially. Dr (Mrs.) .E. Ogamba who opened my eyes to what research is, .
May God be with you all.
This work is incomplete if 1 fail to recognize the effort of my project . . Supervisor, who is equally my academic Adviser Mr. V. U. Ezeugwu. In
fact, he is really a father to me. I know God will surely reward him here on
earth and crown it all .. with heaven on the last day.
1 must specifically thank my mother who really prayed for me
throughout this period.
Mention must also be made of my dear
total understanding .when I seemed to be too
course.
wife and children for their
busy in pursuance of this
Bravo to my entire course mates too numerous to mention GREAT
ACCOUNTANT! Keep the flag flying
I finally owe a debt of gratitude to Mr. Valentine, Lucy Ani & Debra of
the Executive Computer Center, 22 Obinagu Road, Abakpa Nike, Enugu
for they took the pain to type the project with professional devotion.
However, any error, omissions in this work is entirely mine but not
intentional.
To all authors whom I Used their works May God be with you all Amen.
OD0 JOHN
ABSTRACT
Variance Analysis is an essential tool for cost control in any
manufacturing company. It contributes to control of cost; reduce excess
wastage of. materials, Labour hours and overhead costs.
This technique is however not employed or adequately employed
amongst manufactuljng companies due to lack of experienced staff, high
staff turnover, and absence of measuring instruments.
It was the realization of what this technique can do to the control and
growth of the industrial sector that the topic " Variance Analysis as a tool t
for cost control" was selected for research.
The research work has been divided into two sections of five chapters. The
first section of this study, which comprises chapters one to three, attempts
to establish a theore'tical framework for the study. It includes background
information on the evolution of variance Analysis, the review of the related
literature and the formulation of hypothesis for the study. Chapter three
deals with the reseayih methodology employed in conducting the research
work.
The second section, consisting of chapter four and five deals with
empirical evidence So support or disapprove these hypothesis and to
establish if any, the' association between variance Analysis, cost control,
profit and growth of the manufacturing companies. With the findings of the
research, it is hoped that the study will help industrialists to address the T
problems of this sedor so as to make more profit and the sector itself will
be more effective and also contribute more to foreign exchange earned
and to the gross National product. -
vii
TABLE OF CONTENTS
TITLE PAGE:
DEDICATION: " II I1 I1 11 11 11 i - ACKNOWLEDGEMENT 11 11 11 11 I1 . .
I I
ABSTRACT: . I1 11 11 11 11 11 iii
LIST OF TABLE: " - I1 11 11 I1 11 I1 iv
TABLE OF CONTENTS: I t I1 11 I1 I1 v
CHAPTER ONE: INTRODUCTION
1.1 EVOLUTION'OF VARIANCE ANALYSIS " I t 1
1.2 STATEMENT OF PROBLEM " II II I1 4
1.3 OBJECTIVE OF STUDY " I1 11 I1 5 . 1.4 STATEMENT PF HYPOTHESIS " I1 I1 6
1.5 SIGNIFICANCE OF STUDY " II 11 11 7
1.6 SCOPE OF STUDY " 11 I1 I1 I1 8
1.7 LIMITATION TO THE STUDY I t 11 11 8
CHAPTER TWO: LITERATURE REVIEW . 2.1 DEFINITION 'OF SOME CONCEPTS: "
11 11
VARIANCE ANALYSIS
2.1.1 VARIANCE II 11 12 ..
2.1.2 STANDARD COSTING ' 11 I1 13
2.2 COMPUTATION OF VARIANCE 11 11 15
2.2.1 DIRECT MATERIAL VARIANCE I1 11 16
- 2.2.2 MATERIAL PRICE VARIANCE 11 11 17
2.2.3 DIRECT MATERIAL USAGE VARIANCE I1 19
viii
2.2.4 DIRECT WAGES COST VARIANCE " I1 21
2.2.5 DIRECT LABOUR (WAGES RATE VARIANCE) 21
2.2.6 LABOUR EFFICIENCY VARIANCE I1 I t 22
2.2.7 OVERHEAD VARIANCE I1 II 23
2.2.8 FIXED PRODUCTION OVERHEAD VARIANCE 24
2.3 BUDGETED FIXED OVERHEAD EXPENDITURE 25
2.3.1 POSSIBLE CAUSES OF VARIANCE " 11 25
2.4 INTERPRETATION AND INVESTIGATION OF VARIANCE ..
IL I t 27
2.4.1 COSTIBENEFIT ANALYSIS 11 II 32
2.4.2 REPORTING VARIANCE I1 I t 33
2.4.3 AUTHORIZED AND UNAUTHORIZED " Ll 34
2.5 CONTROL PROCEDURES I1 I1 34
2.5.1 CONTROLLING PRICE VARIANCE II IS 36
2.5.2 IMPORTANCE AND PROBLEM OF
IMPLEMENTATION 11 I1 40
3.1 RESEARCH METHODOLOGY I1 11 48
3.2 SAMPLING METHOD USED II I1 48
3.3 RESPONDENTS AND SAMPLE SIZE " I1 48
3.3.1 DETERMlNAf ION OF SAMPLE SIZEIPOPULATION 49
3.4 DATA COLLECTION ' 11 I1 54
3.5 DESCRIPTION OF QUESTIONNAIRE " 11 54
3.6 TECHNIQUE FOR DATA ORGANIZATION
ANALYSIS I1 I1 55
3.6.1 ACCEPTANCE~REJECT~ON OF HYPOTHESIS 56 -
3.7 STATISTICAL METHOD FOR DATA ANALYSIS 56
CHAPTER FOUR: DATA ANALYSIS AND PRESENTATION
4.1 PRESENTATION AND ANALYSIS OF DATA 57
4.2 STATISTICAL TEST OF HYPOTHESIS 60
4.2.1 TEST OF HYPOTHESIS 62
CHAPTER FIVE: SUMMARY OF FINDINGS RECOMMENDATION
AND CONCLUSION
5.1 FINDINGS - 5.2 RECOMMENDATION 11 11 72
5.3 CONCLUSION I 1 II 73
REFERENCES: ,
APPENDIX
- LIST OF TABLES
Company's population strength 1 1 1 1 1 1 51
Summary of Sample size Allocation 1 1 I 1 54
Distribution of Questionnaire 11 I 1 1 1 57
Usage of Variance Analysis 1 1 1 1 1 1 58
Objective of variance Analysis:
Usage for more profit 1 1 1 1 1 1
-P
59
"To control cost:' I1 It II 59
Usage for better cost control: I 1 I 1 1 1 60
No of compa~ies employing variance Analysis " 62
Chi-square test (Summary of table 4.6) " It 63
Contingency table (Expected and observed) " 64
Chi-square Table (Summary of table 4.6) " 65
4.10 Contingent Table
4.1 1 Chi-square Test C
4.12 Chi-square Table ii
CHAPTER ONE
INTROD-UCTION
EVOLUTION OF VARIANCE ANALYSIS
Industry as we know is an important feature of a society both in the highly
developed parts of the world and in developing countries Nigeria incl~isive. Aided
by technical advances, it aims at progressive ,improvement in living standards
through inass production. In the production processes 11~1man effort is applied to
~xoc~~remen t and c~~ltivation of natural resources, conversion ~f natwal resources
into colnmodities which directly or indirectly give greater consumer satisfaction
and cfi'ective distribution of nat~~ral resoL~rces and coinmodities. The procurement
and conversion processes involvecl cost; these costs needs attention or control.
At thc beginning of industrialization, physical observation \ws made as no
records wcrc used for control. Sole dependence was placed on direct supervision.
l'hc earliest costing systems were derived with the main objective of ascertaining
the cost ol 'prod~~cts.
In job order situation lacller (1974,P.15) put i t that mai~agers wanted
assiirance that work \vas not being undertaken unprofitably either because of faulty
estimating technique or insufficiently in carrying out work. Where standard
~voducts were made for stock the most effective way of maximizing profit was
sccn to be by keeping a close watch on the product cost and successive costing
periods, investigating the causes of significant fluctuations and taking any remedial
action called for. At the same time profit mn&-gin were kept under review and action I
was taken either to discontinue unprofitable lines or to make more profitable by
seducing costs, or if feasible increasing prices. i
It was noticed that this concept is widely applied altl~ough there is a gradual
movement towards the alternative concept. of variance analysis, particularly in the
mass production field. Most mass-production situations are con~plex, featuring
wide product ranges and numerous stages of manufacture. Where such
organizations or establishment continue to apply the actual cost ascertainment
concept thc mechanics of analyzing periodical cost f l i~c t~~a t ions can be extremely
laborious and often ~ ~ n r e w r d i n g . Ladler (1974 P . 4 ) also agrees with this vicw
when he stated that the complexity of the modern industries require manager to
have considerable a ~ n o i ~ n t of information concerning the activities for which they
arc responsible. What he means by this information is the application of
prolessional knowledge and skill in the and preserhtion of accounting
information in such a way as to assist i~~anagement in the forinulation of polices
and in planning and control of the operations of the undertaking under him.
This s t idy howevcr is concerned with the aspect of inlbnnation. "Variance
analysis" as a tool for cost control and as it relates to ~nanufacturing business. For
as noted in Glautier and Underdown (1982 P.587) that: - " The use of variance
analysis simplilies the control of perfor~nance for if standard costs are correctly set
one nceds only be concerned with the differences or variances betiveen actual costs
and standard costs".
Bhattacharya and Dearden (1977 P. 356) also stated thaivariance analysis is
dcsigned to bring to management's attention those areas requiring action. What
they mean is that variance Analysis are prepared for management use for the
control of costs in order to improve profit.
Control according to Edgerton and.bl-own (1972, P.527) is defined as the
measuring and correcting of activities of sub-ordinates to ensure that these
activities are contributing to the achievement of planned goals. In other words, i t is
thc management function of malting sure that plans succeed.
7
Sherwin (1972, P.529) also sees control as a process, which adjust
operations to predetermined standards and does so on the basis of information it
receives. I n this study, i t is then the result got from the variance analysis.
Inforination reaching a manager gives him the opportunity for corrective action
and is his basis for control. He cannot exercise control without such information.
Just as he cannot control without relevant information he cannot equally
control what he has no plan. Edgerton and brow ( 1 972 P.8 1 1) define planning as:-
"A syste~natic method for the effective And efficient blanagement of change
in thc best interest of the corporation, it also includes determining where the
company is to go as wcll ;IS how i t is to gct thcse os mow formally the setting of
oljjective and goals ant! the formulation and selection of alternative strategies and
course ol'action to reach the goals and objectives".
What then is implied is that there must be a plan before contsol can take place.
Koontz and 0, Donnell (1976.P.93) also described planning as the function
by which managers dctesmine (within the constraints of their role) \vl~at goals are
to be accomplished and how? When they a!-e to be reached.
They are of the opinion that bei'ore action is taken i t is most necessary to
know what is possible and what is wanted giving all the available resources within
their powers.
Koontz and 0, Donnell (1976,P.93) also emphasized the iinpostance of
planning when they said, "it is known thaiabsence of plan eniails hesitation, false
steps, untimely cl~angcs of' direction, which are so inany causes of weakness, if not
of disastcr in business. And that the question of necessity for a plan of action, then
does not arise and therefore plan of action is inclispensable.
This boils down to the same point that control cannot take place without
plan. One cannot control what has not been planned. Planning and control are
thereibsc closely related. Edgerton and brown (1972, P.528) also agreed with the
interdependence of planning and controlling as they stated planning and control are
thcrefoore closely interrelated. They summarized planning and controlling processes
as one of establishing standard against which performance can be measured.
Measuring perSormance and correcting deviations from the standard or plans.
The plans considered in this study are referred to as standard costs which
(florngren 1977 P. 186) described as carefidly predetermined costs, target costs,
tl~at shoi~lcl bc attained to build budgets, gauge perhrmance, and obtain prodi~ct I I
nodel or norm against which actual results can be compared and that standard I
costs.
Osisioma (1990, P.234) also described standard as an established criterion,
costs ase described as predetermined costs, target costs or carefully pre-planned I
.
costs whic11 management endeavors to achieve with a view to attain efficiency in
the production process. 'There are differelit types of variances amongst which are
material, labour, variable overhead, fixed overhead, and planning and operational I variances. The details of which are considered in the literature review.
1.2 STATEMENT OF PROBLEM:-
Every year federal and state governments of Nigesia allocate heavy sums of
money to industrial sector. The aim has always been to expand the industrial base
of the country to generate einployn~ent, increase consuinption of il~anufactured
goods, save foreign exchange, improve the living standards of its citizens etc.
Government apart fsom budget also gives special incentives or loans to the
industrial sector to encourage its expansion. What many Nigerians do not care to
know is weather the grants, loans or subsides are being properly utilized in the
best interest of the nation or even utilized for the purpose they were meant for.
Much is also given to this sector for research and development, which the
results are hardly noticeable.
What we know but do not always care about is that whatever government
incentive in form of loan, grants, subsidies must be converted into various cost
before that objective for which it was givcn will be achieved. Weather these are
properly utilized or not many Nigerians feel is not their concern. But we must
know that whatever subsidy or grant if not properly utilized -will not help in any
way to the overall objectives of expanding the industrial base of the country or
state. It is only when the users of such incentives are cost conscious that we will
bc sure to achieve these goals, increase profits of the industries in this sector and
equally cxp cnd or grow. In the course of this work I notice that many managers'
non-challant attitudes to cost control has a ff'ected greatly the profitability 's of
many companies. There is hardly any cost control or cost consciousness by those
responsible for various cost units. The end results are either low profits or losses.
'l'his will never lead to expansion or growth in this sector no matter whatever
amount is pumped into the sector.
Given this attitude towards costs and the existence of techniques available to
control costs, the problem of this study is then to determine the effects of variance
analysis as a tool for cost control and to find out the extent to which they may
influence costs in the n~anufacturing companies and its effects on profit in some
companics. I shall also try to investigate the causes of variance that affect
profitability's in manufacturing companies and weather the techniques are
adequately employed.in this area.
1.3 OBJECTIVE OF STUDY
Cost control leads to cost reduction and cost savings which in turn results in
higher profit because of lower cost price cum reduced selling price via higher
contribution ~nargin per unit of product
Variance analysis as a tool for cost control will be the main objective of this
study, There is the need for management in the manufacturing industry to re- 9
appraise its methods, techniques and procedures adopted and attitudes towards
costs in order to control costs of ~nanufaciurin~ companies and help the sector to
contsibute towards its growth. The overall objective of this study therefore is to '
finci out how variance analysis can help ,in cost reduction in order to increase
prolitability of the industrial sector of the economy.
ln the light of this, the.stucly will endeavor to: -
I. Ascertain the effect of variance analysis on the various cost incurred by the
manufacturing companies.
2. Determine the problelns militating against its wider implementation in Inany
companies.
3 . 1;stnl~lish its o\verall ct'kct OII profit : I I I ~ gro\\'tl~ of t h t sector. 1 . , >
- . \ , . . , . . \ : \ . . \ : . . i'\
. . . . . . . . . . . . ' . . . . . . . . . . . . \ . . . . ...., r . . . . . . . . . \ '
1 A. STATEMENT OF HYPOTHESES. 1
The aim is to test whether variance .analysis wlwn properly employed can
reduce costs and increase the profitability of those manufacturing colnpanies i employing it. It is therefore hypothesized that: - I I
I . 1-10: The number of ~~~anufacturing companies now using variance analysis as a / I
tool for cost control is not adequate not (many). Adequacy will be measured if I
at least SO% of the respondents are i~silig the method. i i
I-I I : The number of n~anufacturing companies now using variance analysis as a ; tool for cost control is adequate (many). .
I
2.Ho: Manufacturing con~panies that employ variance Analysis have better c o s ~ I
control than manufacturing companies that do not employ it. -
Hz: Manufacturing companies that employ variance Analysis do not have a better-
cost contsol.
(3) 1-10: Companies that employ variance analysis are more profitable than
companies that do not einploy it.
f-13: Companies that employ variance Analysis are not more profitable than
companies that do not.
In all the hypothesis a null or alternate hypothesis has to be stated in each
case, we shall use the
Chi- square at 0.01 and 0.05 level of significance to test the hypothesis.
Tcst statistics X' = (Oi - Ei)' E i
W11crc
Oi, Is the observed data
Ei the corresponding expected frequency of companies
employing variance analysis. The degree of freedom for x2 test is given by
CIS= (R - I ) (C - I )
W11ci-c R = roll; C = Column.
Critical value of X' = CX (R - 1 ) (C- I) -
2
1.5 SIGNIFICANCE OF THE STUDY:
The study is coi~siclered significant because of the contribution of the
~nanufacturing industry to the economic growth of Nigeria. This is seen by the
way government has been trying to encourage investment in this sector or
government participatio~? itself.
It is believed that findings from the study will help the expansion of the
industsy and consequently generate inore employment. Mangers of such
companies are also to benefit from the study, as they will be made more cost
conscious than ever before. Infact: the greatest problem of management in the
inanufacturing companies today has been how to contend with high overhead
costs in relation to total turnover.
Government on the other hand will be made aware that grants or aids to
manufacturing sector should be properly managed in order to achieve the targeted
objectives. This will also help the government to re - address itself to the problem
of government conlpanies that never make profit.
1.6 THE SCOPE OF THE STUDY:
The economy of any country is characterized by many industries. The growth
in this sector influence the growth or otherwise, the size of its GNP. The industrial
sector is made up of many firms, which in turn consist of many companies.
1 lowcvcr, the main scope of this study will cover effect of variance analysis as a
tool for cost control on the growth of this sector, by way of costs reduction and
incrcascd profitability. The key variables, which n~nlte up -the components of
variances wc hope to cover in the study, are Material, Labour, Variable overhead,
Fixed overhead, planning and operational variance and their various causes will
also be considered. Standard costing will also be covered as variances cannot exist , I
without first setting standard against which actual will be compared to get these 1 variance, hence the study is on variance analysis as a tool for cost control, cost
benefit analysis and other techniques will also be considered.
The research will however not cover budgeting or budgetary control
technique neither ~ v i l l - it go into the methods or process of setting or fore casting
standards.
1.7 LIMITATION TO THE STUDY:
Success in a work of this nature depends on the ava
variables. Such variables include time, money, materials etc.
ilability of some
9
Manuihct~iring firins are scattered all over the country, and to cover all these will
require a long period of time, but due to near impossibility of such time, I decided
to use the available manufacturing firms w'ithin the Enugu metropolis.
Moreso the money and inaterials required to embark on this work is always
huge hcnce it became a limitation to the wiiter's intention of going wider than as it
is here.
Finally a lot of difficulty was encountered during the oral interview and in
some ol'the answers received in the questionnaise. Some of the staff believed that .
only thc management board can supply some of the answers in the questionnaire
hence they regard such areas as 'sacred', hence such a belief really became a
constraint to my effort.
REFERENCES
1-aidler E. Theory And Practice Of Variance Analysis. In Variance
Accounting. - First Ed. London: Macmillan ICMA Publishers Itd
( 1 974 1'. I 5)
Glautier, W. W .E. And UnderDown, B. Standard Cost ~ n d Variance In
Accounting Theory And Practice. 2"" Ed. Massachusetts, Pitrnan
Publishing Inc. 1982 P. 58
13hattacharya S .K And Dearden John, Cost Accounting Standard Costs, i n
Accounting For Management Text And Cases. I " Ed; New Delhi Vi kas
Publishing House Put Ltd (1977 P. 356)
I-;g,crton, Henry C., And Brown. K. James. Perspective On Planning In
Management. A Book Ol'Readin~s -
New York. Mc Grow-Hill Inc. (1972. P 1 I 1)
Slwwin, S. Douglas. The Process Of Controlling In Management A Boolc Of
Readings. New Yolk Mcgrow - I-IiII Inc (1972, P. 529)
Koontz, I-larold And 0' Donne], Cyril, Nature And Purpose Of Planning In
Management, A Boolc for Reading. New York Mcgrow - Mil Inc.
(1 976.P.93)
I-:g,erton 11. C. And Brown, J. K Op. Cit P. 528 (Refer To Note 4)
1 lorngren C. T. Standard Costing, In Cost Accounting - A WIanaqerial
Emphasis. 4'" Ed.Prentice I-Ialt Int. London 1977. P. 193
Osisioma, D. C. Standard Costing In Studies In Accountancy Text And
Readings. 1'' Ed.Enugn. New Age ~ublishers 1990 P. 234 Glauiter And Underdown, Op. Cit 1' .587 (Refer To Note 2) I .ilcey T. Standard Costing. Planning And Operation
Variance 3rd Ed. 1,ondon. Bpp. Publications (1986. P. 167) ,
CHAPTER T W O
LITERATURE REVIEW
VARIANCE ANALYSIS:
This study is intended to find out if inanufacturing companies that employ
\~ariance analysis as a tool for cost control have a better-cost control and are more
profitable than the ~nanufacturing companies that do not.
I11 our cverydny life we l i~ ;ke plans, which inay or may not be executed.
When we execute these plans we are bound to havu somu deviations. TI ICS~
cleviations 01. divesgences which result when we compare plans with actual are
I;no\vn as variances, especially when we consider those relating to a
mnnui'acturing company. I n man~~facturing coiupanies effosts are ~ n a d e to find the
causes of thcsc variances with the aim of correcting and preventing future
occurrences especially the ilnfavorable variances. This is usually done by \\)hat is
known as 'variance analysis'.
2.1 DEFINITION O F SOME CONCEPTS - VAliIANCE ANALYSIS:
London school of accountai~cy (1976 P. 2 10) defines variance analysis as the
investigation and classification by cause and responsibility of variance (deviation)
l?om plan. The most notable aspect of this definition is responsibility in variance
analysis where causes are determined and-n~anagers are called to account for their
action.
According to Lucey ( 1 983 P. 16) in his own contribution described variance
analysis as the process by which the total difference between standard and actual
cost is subdivided or analyzed, the reason being to determine the cause of such
di l'fcrence. According to hi111 variance analysis encompass conlparison of standard
and actual costs than the determination of such causes.
Glautier and Underdown (1982 ~ 1 5 8 3 ) in contributing to what makes
variance analysis necessary states that its use in conjunction with standard costs
simplifies the control of performance, for if standard costs are correctly set one
needs only to be concerned with the differences or variance between actual costs
and standard costs. In connection with this therefore, they stated that variance
analysis is the method of management by exception and appropriate means of
controlling operations. I n a general sense, according to them the aim of variance
analysis to investigate variances to ascertain whether they are justified or not. If
they are justilied either because the estimates of quantities of input resources or
input prices are wrong, clcarly the standaki costs must be a?j~~sted. I f , how~.vc.r,
they are u~~justified, the cause of this variance must be investigated and corrective
action taken.
2.1 . I VARIANCE
A variance according to LSA (1 976 P. 2 10) is "a deviation of actual results
iiom expected or budgeted results which arises from the comparison of actual cost
of a particular category with standard cost". The central meaning being that
variances highlight these situations where actual results are not as planned whether
favorable or unfavorable
According to brown and Howard (1976 P. 145) a variance is the difference
between a budgeted or standard amount and the actual amount during a given
period. This definition takes into consideration the time -span within which
standard and xtual re'sults will be compared.
Osisioma (1990 P.237) a l w described n variance :IS sign - posts \vhich alert
management to the need for inquiring into causes of off standard results and a cost
variance as the difference between the standard or budgeted cost and the
comparable actual costs for a particular period. This description is in line with
Brown and Howard in terms of time span, which is necessary if we should avoid
comparison of outdated standard with actual costs.
According to Lucey (1 983 P. 16) asvariance is a dif't'erence between standard
cost and actual cost. From all these descriptions or definitions variances result after
comparing standard with actual. There are different variances like material, usage,
price, labour, rate, eflicieixy, variable overhead, fixed overhead varian .: etc.
2.1.2 STANDARD COSTING: 6 6 Owlcr and Brown (1982 P.521) defined standard costing as a pre -
dotcrmined cost calculatecl in relation to a prescribed set of working conditions,
correlating technical specifications and scientific measurement of materials and
labour to the price and wage rates expected to apply during the periocl to w11ic11 the
standard cost is expected to relates with an addition of an appropriate share of
buclgcted overhead. Its main purposes are to provide bases- of control through
variance.
From tlw I'oregoing clelinition it is clear that standard costing or costs are pre
- determined, or forecast estimates of cost to inanufacti~re a simple unit, or a ! number of units of a product during a specified immediate future period. I
According to Nweze (2000 P. 85) standard costing is a system of cost
occountiny, wIiic1-1 makes use of predetermined costs relating to each element of '
cost layout, material and or services applied.
Batty (1977 P.44) in his own defined a standard as a pre - determined
measure rclating to material, labour or. overhead; i t is a - reflection of what
unclcrstated conditions is expected of plant and personnel. A standard according to
him is primarily an expression: quantities inultiply by price. It shows what the cost
should be, therefore, according to batty standard cost may be regarded as the true
or real cost of the product concerned.
Osisioma (1990 P.234) also described a standard as an established criterion
iiodcl or norm against which actual results'can be compared, and standard costs as
)re-determined costs, target cost o r . carefully pre-planned costs which
management endeavor to achieve with a view to attain lnaxirnilm efficiency in the
xodwtion process.
Accosding to him they are not plans relating to single cost units because they
Ire detailed, off standard performance can be pinpointed, and also as they purport
lo bc what costs should be, any deviation represents a measure of performance.
'I'he clefinition of standard costing as per the Chartered Institute of
management accountant's oi'ticial terminology is a predetermined calculation of
how much cost should be under specified working condition. It is built up from an
asscssmcnt ol'the valw ol'cost clcn~cnts and corrciates tecllnical specification and
thc qi~\ntilication of materials, labour and'other costs to prices and for wage rates
espcclcd lo apply during the period in which the standard cost is expected to be
uscd. 11s main purpose is to provide bascs h r control through variance accounting
fos thc valuation of stock and work in progress and in some cases for tixing selling
Standard cosling according Brown and Howard (1976 P. 145) may be
delincd basically as a technique of cost accounting, which compares the standard
cost ol'each product or service with the actual costs to determine the efficiency of'
the operation, so that any remedial action may be taken immediately. According to
them, standard cost is a pre- determined cost that determines what each product os
service should cost under given circu~nstances,
Vickery (1973: P.754) stated that standard costing seeks to provide the
maximum guidance and information to management by ascertaining the actual cost
of cu~.~.cnt production whilst production is still in progress and by the comparison
~ ~ ' ~ I I O S C costs with the standard cost is a prc-determined cost estimated in advance Y
before production is commenced, detailed for each element of cost, which
represents the cost which is anticipated would be incurred if materials, labour were
utilized under norinal condition of efficiency. The standard thus represent a good,
but not an ideal performance, which can be attained by reasonably efficient
workers. I-Ie tried to make it clear that standard costs are good representative of
eupcctcd costs; however, they are not actually idcal costs that is, they are only
estimate of costs.
From thc foregoing definitions of variance and standard cost, few things are
in common and agreed by the entire author's in their different and varied
clelinitions.
According to Nweze (2000 P.85) he said that the processes involved are:
1 . I're-determination of standard costs
3. Recording of a c t ~ ~ a l and standard costs
3.('omparison of actual and standard costs
4. Reporting to management so that action can be talten.
'She types of standard costs according to Nweze include historical standard,
t l lcoi~t ical standard and currently attainable standard.
2.2 COMI'UTATION OF VARIANCES.
'I'he principle of variance analysis is that the difference between actual and
allowmces or standard should not be computed in an unorganized manners for the
dangers of differences over lapping or railing to be analysed at all. For this reason
consideration of a theoretical basis on which an analysis can be based or
constr~~cted is necessary.
To compute variance analysis therefore the following procedures are
ncccssary : - 1 . Compute the standard cost (allowal~cc) for the factor on the basis of the planning
I'xtor details given in the opcl.ating plans; 9
. . .--..--.- - - .. . .- ,.
2. Ascertain the actual figures
3. Find the difference between actual and standards.
4. Finally is to value the difference in ter~ils of the effect on profit, that is to state
the variance is favorable (1) or unfavorable / adverse (s).
Naming a variance is sin~ply a matter of identifying it to the people involved
To be thw considered in this discourse are materia!', labour, variable
overhead, fixed overhead, planning and operational variance and their sub
variances.
2.2.1 1)lRISCT IVkAr1'EHlAL VARIANCE:
The LSA (1976:P.220) define this variance as the difference between
standard cost of direct material specified for the production achieved whether
co~npleted or not and the actual cost of direct material used.
Mathematically, it is computed thus:.
Standard material I- less i. Actual material Cost ol' production cost of production I- Louderback and Hirsch (1986: p.289) defined inaterial cost variance as the
deviation of the total actual cost of material used for production fi-om the standard
or budgeted cost. Quantitatively it is computed thus:
MCV = (AQ X AP) - (SQ X SP)
Where: MCV = Material cost variance
AQ = Actual quantity of inaterial used
AP = Actual price per,unit of material
SQ = Standard quantity of material budgeted
Sp = Standard price per unit of material.
Direct material cost variances may be sub-divided into material price, usage,
m-l mixture and yield variances. All the definitions clearly testify that comparison
bctween actual and standard is necessary for computation and variance analysis.
2.2.2 MATERIAL PRICE VARIANCE: -
A material price variance arises on the purchase of material and is found by
comparing the actual purchase cost with h e purchase cost allo~vance (standard).
'I'llis allo\vance is of course what the purchase would have cost if the planned
(standard) price had been paid.'It is the actual quality at the standard price. Since
cvery Nl over or under spent affects the profit by the %I, the difference between
the actual cost and this allowance gives the material price variance. This variance
is then the responsibility of the purchasing officer.
'I'he I S A (1976: P.210) defines this variance as " that proportion of the
dircct material between the standard prices specified and the actual prices paid for
the direct material used".
They went fi~sther to argue that n~nterial price variance should be accounted
l'or at the time ~naterial is involved or supplied by the suppliers and is taken either
in stock or direct to a job. In other words that material price variance should be
isolated at the time of purchase. To them not only does this identify a variance as
soon as possible but it also begins the process of a preliminary assignment of
scsponsi bility.
Mathematically, material price variance is computed thi~s: -
MPV (VP) = AQ (AP-SP)
Where:
AQ = Actual quantity purchased
AP = Actual price per unit
SP = Standard price per unit ,
MPV = V P = material price variance. '1
It needs be pointed out that inany authors perfectly agree wit11 this approach
of' calculating price variance at the time of purchase r ~ t h e r than when material are
issued fiom store.
Wallter (1980: P.52) i n his view stated that: - "the first and more popular
mctl~od is to determine the price variance at the time of purchase, as soon as
o\vnership of the materials passes and that the price variance based on current
purd~asing activity and any deviation between actual and expected prices
negotiated is reported as it happens rather than after the delay of waiting for
production departments to requisition inaterial into work in progress.
The central point is that early detection method adheres to the principle of
reporting variances as quickly as possible to those who may be able to take
appropriate action.
Brown and Howard ( 1 976: P. 15 1 ) also stated that the two methods should be
the time whcn purchases werc mndc. That in case of ca1cul;~tion at the time \ \ l l~c ' i i
pui.chascs arc made, the variance on material purchased is ascertained
immediately and the stores are debited at standard cost. This has the advantage or
cffcct of eliminating the price variance on all the materials purchased as and when
h e y are received. On the other hand with calculation when requisition is made
from store considerable delay occur before the variance is ascertained; and stores
are debited at actual costs. However if "management by exception" is for
providing management with the information for quick decision making variance
for material price should be calculated when purchases are made. Moreover, raw
~nn~crials stock can be valued at standaid price instead oSFIFO, LIFO or weighted
average price. This simplifies costing procedures as all issues are at the same
standard price.
An apparent disadvantage of the sykem of reporting price is that all price
variances must be written off to the profit a d loss account in the period when the Y
19
purchase took place. If the materials are not used in this period, this means that
some of the costed materials held in store (i.e. part of the price variance relating to
the units bought in the period but not yet used) will be charged against profit. This
is contrasy to the acci-uals of matching principle of accounting. (That is the sales
should b matched with the associated cost of sales in order to measure profits). P . I his disadvantage is easily overcome, by nlalting an adjustment at the end of
the accounting period. The general consensus is that price variance should be
sharcd out (pi-o-rated) bctwcen stocks and the cost of sales. In this way stocks will
hc rcvalued to acti~al cost and only the (pice) vxiance on material in goods \vill
bc ch:~rgctl to thc proiit and loss acco~rnt. This however involves a lot of
calculations in trying to pro-rate variance between cost of goods sold and unsold
stock,
2.2.3. DIRECT MATERIAL USAGE VARIANCE
Material Usage variance is caused by Using more or less than the standad
cl~nount 01' material that is speci lied causes material usage variance. Material usage
variance is an efficiency variance and is the responsibility of the manger of the
plant department producing the finished product.
The L,SA (1976:P.221) defines this.vasiance as " that portion of the direct
material cost variance which is the difference between the standard quantity
specified for the production achieved, whether completed or not; and the actual
quantities used, both valued at standard price".
in general term the material usage variance is the standard cost of material
actually used less the standard cost 'of the material specilied: A clear distinction
must be drawn between excess usage and spoilage. The material usage variance is
: h o quite separate from the scrap written off, and relates to deviation from the
material input specified to achieve the total output from a process or operation.
Material usage variance is identified in different wayin different industries.
In nrechanical cnginecring for example, 'it is custoinary to issue from store the
exact quantity of material specified for a particular operation job or batch of
production. IS the amount of material is insufficient then more will be requested
on 311 "EXCESS Material Requisition form giving reasons for the request and
bearing the authorization of a planning manager independent ~ > f the shop foreman.
'This is reconmended as i t avoids guess work or employees hiding their
incl'licicncies by falsifying records or not recording the excess requisition.
Quantitatively the material usage variance is computed tlds: -
MUV = SI' (SQ - AQ)
Where:
MUV = Material usage variance
SQ = Standard q~~an t i ty
A() = Actual q~~an t i ty
According to I Iarper (1 976: P.264) usage variance is "the comparison of thc
actual usage with usage allowance and valuing any difference at the standard price
o1'~he inaterial.
That if the planned quantity of material had been used each time a unit was
produced then the total material usage would be equal to the number of unit
p~.odiiction ~nultiplied by the standard usage. This then is the usage allowarce and
any usage allowance above or below this allowance will affect the profit to the
cxtcnt of the value of the over or ~ ~ n d e r usage. The most notable aspect here is that
this variance helps to keep nlanage~nent on alert in case of excess material being
uscd. I t helps t l~en to control wastage of materials.
DIRECT WAGES VARIANCE
'I'his will consider direct wages cost variance, wage rate variance and Labour
l! Fliciency variance. Y
2.2.4 DIRECT WAGES COST VARIANCE:
The LSA (1976: P.232) defines this variance as: - "The difference between
the standard direct wage specified for the production achieved whether
completed or not, and the actual direct wages incurred."
Mathen~atically the compi~tation is
OR
SC - AC.
This variance is computed by comparing stanclard labour cost with the actual
direct labour cost of the output production. This variance is sub-divided into wage
rate variances and labour efijciency variances.
2.2.5. DIRECT LAROUR (WAGES) RATE VARIANCE: - 'I'his is the difference between the actual direct labour rate per hour and the
actual clirect labour rate hour n~ultiplied by the actual hours worked. The formula is
~ h u s stated
AH (ALR - sLrt)
Where:
AI-I = Actual hours worked
ALR = Actual rate of pay per hour
SLR = Standard rate of pay hour.
The LSA (1976: P.2 13) also defined this variance as
"That portion of the direct wages cost variance which is the difference
Between the standard rates of pay specified and the actual rates paid".
In other words it is the difference between the actual cost of labour and the
standard labour cost of the actual hours. The actual cost of labour is obtained fro111 - the payroll for the department or the grade of labour concerned.
A wage / labour rate variance is really a price variance in respect of the 1 I
purchase of labour and is found in exactly the same way as a price variance. It is 1 I
the difference between the wages that would have been paid if the standard rate
had been paid and are computed by multiplying the actual hours worked by the
standard wage rate. The personnel manager will non~~al ly be responsible for this
variance.
2.2.6. L A U O ~ J R EFFICIENCY VARIANCE: -
A IJabour erficiency variance is really a usage variance in respect of
"Usage" of labour time. I t is cailed "Efficiency" variance since the compariso~~ of
actual against planned times is a measure of labour eficiency. To compute a
labour cfliciency variance, thercli~re, onc ~ ~ ~ e r e l y finds the allowed time (i.e., how
long would havc been taken il'thc plt~nncd timc had bcen adhered to) and compares
. this with the actual time. The difference is then valued at the standard \\/age rate.
'The LSA (1976: P.233) deiines the variance as "That portion of the direct
wages cost variance which is the difference between the standard direct wages cost
for the production achieved, whether co~;~plcted or not anddthe actual hours at
standard rate".
The formula is: - 7
Standard Hourly X hour's value of outpwt - actual hours worked
OR
SR (SH -AH).
I t is then sufficient to consider efficiency measure as: -
"I-low long did the production take compared with how long it should have
taken". Labour efficiency variance is the responsibility of the production manager,
2 3
Osisio~na (1990: P.242) also agrees'with the view that in the use of labour,
l i~ne taken in carrying out operations is a measure of efficiency. He therefore states
that direct labour efficiency variance ineasures labour efficiency in terms of hours
saved between operations in co~nparison with the allowed standard time.
According to him, it is the portion of the direct wages variance, which is due to the
dilTerence between the standard I I O L I ~ S specified for the activities achieved and the
actual hours expended. This variance forms a good basis for the measurement of
employee perfonnance. In setting these standard hours therefore, human factors
shoulcl bc taken into consideration. 111 other words, this standard should bc "current
attainable stanclard".
2.2.7 OVERHEAD VARIANCES (VARIANCEIFIXED)
This measures the eff'ect on profit of overhead expenditure being otherwise
than stated in the budget statements. It is the difference between the budgeted
overhead expenditure and the actual expenditure, which is overhead expenditure
\~ariancc.
VARIANCE PRODUCTION OVERHEAD VARIANCE: - Variable production overheads are indirect production costs that are i~sually
assumed to vary with the labour hours worked. The total variable production
overhead variance is the difference between.
(a) The actual variable production overhead and the standard variable production
overhead cost of actual output. In other words, the question is whether the output
produced cost more or less than it should production
overhead costs. The forn~ula then is: - AH (SVOR - AVOR)
Where:
AM = Actual hours worked excluding the idle time.
SVOR = Standard variance overhead rate per hour. '3
AVOR = Actual variance overhead rate per hour.
VARIANCE OVERI-IEAD EFFICIENCY VARIANCE:
This is valued at the standard rate per hour lor variable production overhead.
Its Sormular is
SVOR (ALH - SLM)
Whese
SVOR = Standard variance overhead rate per hour.
ALI-I = Actual labour hours worked less idle time.
SLH = Standard no of labour hours that should have been worked to
produce the actual output.
'1'0 iind the variable overhead efficiency variance the following steps should
be taken.
(a) l:ind the allowed activity by n~ultiplying the n nits of production by the stanciercl
activity as laid down in the standard cost.
(b) Compare this allowance with the actual units of activity undertaken
(c) Value the difference at the standard cost per unit of activity. I I
The variance will be the responsibility of the manager responsible for the
efficient use of overhead facilities. I
2.2.8 FIXED PRODUCTION OVERHEAD VARIANCES 1 The total fixed production overhead cost variance is the total under or over 1
absorbed fixed production overhead in he period. Fixed overheads are fixed costs.
Total amount of i>xed overl~eild expenditure ought to be uncha~lged, regardless of / I
the volume of production. I Fixed overhead are not usually absqrbed by showing actual fixed overhead 1
expenditure between actual outputs. They are absorbed into the cost of production j
in a predetermined or standard rate, which is: -
7
2.3 BUDGETED FIXED OVERHKAI) EXPENDITURE: - The standard fixed oveshead cost pel: unit is
SH X SFOR
Where
SI-1 = Standard I-lours to inalte one unit
SFOR = Standard fixed overhead rate per hour.
2.3.1 POSSlBLE CAUSES OF VARIANCES
Over the task of ensuring the credibility of variance analysis as a tool for
cost control hang the threats of attributing wrong causes to variances and o f
succumbing to the problem of forcing manager concerned to psoduce plausible
causes of variances for the sake of appearances when these can be more than guess
work. I t is therefore important to note that wrong attribution of causes of variance
could be counter productive.
'I'hcrefore walltcr ( 1 980:P. 177) warned that guesswork should be avoided in
stating causes of a variance.
'1'11~. most widely causes of key variance accosding to him are as follo\vs: -
MATERlAL PRlCE VARIANCE: - - A general increase in lnarltet price agreed by all or most of the suppliers.
- Buying in srnall quantities causing loss o~~biscounts and I or addition freight costs
added to price.
- Inadequate information about sources of si~pply resulting in vulnerability to price
increase
- Bulk buying residting to low& unit cost.
RAW MATERIAL USAGE VARIANCE.
- Deviation from expected wastage levels caused by changes in handing or loading
arrangements or changes in level of skilled or care exercised by operators.
- Derivations in the quality of work performed by earlier departments.
- Inability to measure actual usage accurately through lack of precision, equipment
or ~I~rough now availability or by-passing of measuring equipment.
- Unusual operating conditions.
- Incompetent workmen or incompetent supesvision.
- Good quality of materials.
PRODUCTION YIELD VAIIIANCE:
- Malfiinctions in process or operation error.
- Use of main standard mix or ~naterials.
1 - Misjudgment of normal operating condition and consequently of the output which :
can reasonably bc expected within the operating period concesned.
- Actual operating conditions inay be more or less favorable than normal opesating
conditions.
- An unplanned wage incentive scheme or charge in labour grades used.
- 'T'cch11ological break-tI~~.oi~gh, so that operation ti-om the same machinery
bccomcs easier.
- Changes in quality of raw materials.
-Operative may be made responsible for handling greatcr quantities of raw matesial
to impsove productivity.
- Changes in inspection standard resulting in highel. os lo\ver failure rate of finished
goods than expected.
DIRECT LABOUR / WAGE RATE VARIANCE
- Wrong grade labour used .
-An unscheduled procluction scheme, whereby operatives receive higher \vages per
hour fos psoducing more output pel. hour.
-Good bargaining powel. by the personnel department.
DIRECT LABOUR EFFICIENCY VARIANCE
- Operations not being performed in accordance with standard procedures.
- 'I'he amount of output which can be achieved in one hour may havz been
misjudged when standard performance (Output level per hour) was assessed.
FIXED I'RODUCTION OVERHEAD VOLUME VARIANCE
- Misjudgment of total capacity available for possible use when budgeted output in
standard hours was calculated.
- A n increase in efficiency level without a deviation from plan in the number of
I~)urs directly charged.
- Miscalculation ol' the level oi' output which can be expected in one hour's
operation i.c. el'iiciency level.
- A change i n the level of customer demand.
- 'I'he emergence of a limiting factor, which restsicts production levels or
conversely an unexpected increase in supplies of what was expected to be a
limiting iactos.
FIXED PRODUCTION OVERHEAD EXPENDITURE VARIANCE
- Faulty cost estimation during budget preparation this can be aggravated by
uncertainly about impending inflation levels.
- Introduction of unexpected new fixed costs because the company has
inadvertently moved out of a relevant range of activity whereby fixed costs are no
longer completely static in total.
I t need be stated that the cause of all these variances are really
incxl~aust ible.
2.4 INTERPRETATIONS AND INVESTIGATION OF VARIANCE.
Variances analysis is a means of assessing performance: I t is only a neth hod
01' identiuying arcas of possible weaknesses where control action might be
necessary. It docs not provide management with a ready made indication of what 9
action needs to be taken. By themselves variances are labels, which mere!y raise
questions and provide clues but no solution.
They are merely attention directors, not answer givers.
1)ISCISION TO INVESTIGATE
As we have seen there are various reasons why variances occur. Managers
need to decide whether or not to spend time and resources in investigating the
causes of variances so that appropriate corrective action can be taken.
lnforlnation is costly. If every variance from standard were investigated or
wvcred the ongoing investigation costs might exceed the variances. Additionally,
nranngers would be swampcd with reports, which would soon lose any sense or
meaning. Therefore, from both cost and human information processing
pcrspectives, it is reasonable for guidelines to be set for variance investigation.
Managers will see only the exception not the normal variability.
We should also not forget to note that standard costs are only estimate of
avcrnge costs; it would be incorrect to treat them as being rigid. Tolerance limits
should be set, and only variance which exceed these limits should be reported for
investigation. See dia. below.
100% Standard
Adverse Tolerance limit
NOTE: the basic problem is that when a cost variance is reported to a manager 1 I
should he investigate the variance and find out why the actual and standard differ I l or should the variance be disregarded? Since an standard is oily an estimate or an Y
average expectation of what s h o ~ ~ l d be achieved, it is most unlikely that actual
results and standard will be exactly the same; and so to investigate every variance
- would be wasteful of time. Investigations also cost money and the benefits
obtainable from control action - on those occasions when control action turns out
to be possible might not justify these cost.
CIIOOSING CONTROL LIMITS:
Whatever statistical tecl~niques the manager uses he or she must set some
limits beyond which there will be an investigation. The limit could be the 99
~~erccn t 95 pcrcent range or any other. An observation that was outside the selected
range would br: investigated observations within thc sangc would be ignoscd.
In deciding whether to investigate a variance we are taking one or twc, risks.
11' we investigate and lind O L I ~ that the P ~ O C C S S is in control, we have accepted a
lhlsc hypothesis and have wasted time and effort in the investigation. If we do not
investigate and later lind out that the process is out of control we have rejected a
true hypothesis :md have born the extra cost of variance that we might have been
able to avoid by taking corrective action. In statistical theory these are called type I
and type 1 1 errors respectively
Louder back and Hirsch (1986: 1'. 289) in their own contribution on when to
investigate a variance said because investigation is costly, managers would like to
investigate only when the consequence of failing to investigate may be very costly
that managers would therefore set relatively narrow control limits lor relativel!
high - cost factors and wide limit for relatively low -- cost hctors. They also stated
that the proportion ol'the variance to the total budgeted cost will also influence
variance investigation. For example if direct labour is 75% of total variable costs
a n uncorrected problem can do a great deal more damage than if laboc~r were 15% I
of total variable cost. This also means that the proportion of a partic~ilar cost to
total variable cost will determine whether or not to investigate a variance. I I I I
Y
It is therefore true that relative and absolute size of a variance are other
important characteristics which are weighted before time and money are
- committed to investigation. Relative size usually involves measuring a variance as
a percentage of budgeted or actual cost, and the absolute size criterion woi~ld
recognize the importance of probing any variance over a certain monitqry size
regardless of its size relative to budgeted or actinl cost.
Degree 01 persistencc of a variance is also important. Again, whethcr
variance can acti~ally be corrected after causes are foiind is a factor, which has a
bearing, along with the possible cost saving which w o ~ ~ l d result fiom investigation
and corrective action.
In order to save cost and risk associated with investigation of variance some
companies use thc following control limits their guide. Thcy are referred to as
Cost-Variance investigation models". Three types of models can be identified
which are comn~only used. They are as follows:
1. Materiality significance model
I I . Statistical significance model
111. Decision model with cost benefit of investigation.
MATERIAL SIGN1 FICANCE MODEL
This simply means deciding a limit. If the size of a variance is within the
limit, i t will be considered immaterial. Only if i t exceeds the limit standard that it is
considered materially significant and worth of investigations. The simpkst filter
rule is to choose a fixed percentage say 10% and all variances that exceed the
standard by the fixed percentage will be investigated, The advontnge of the fixed
percentage rule is its great simplicity instinctive appeal and ease of I
implementation. 1
The snag with this model is deciding what percentage variation fsom
standard is materially significant. Shoi~ld a different percentage be applied to 1
favorable and unfavorable variance? Another drawback is suppose that the fixed
percentage is say 10% and an important category of expenditure has in the past
been very closely controlled so that adverse variance have never exceeded say 2%
of standard. Now if adverse variances suddenly shoot up to say 8% or 9% 01'
standard, there might well be serious expenditure in cured that ought to be
controlled but with the fixed percentage limit at lo%, the variance will not t=z
'Flagged' for investigation.
Another limitation I feel should be considered is that there is no attempt to
consider the costs and potential benefits of investigating variances. These I feel can
be overcome by varying the pre-set percentage fiom account to account. For
cxamplc, 5% for direct materials 2% for rent and 'atcs and probably 3% for direct
labour. 'The weight of the variance in relation to the budgeted cost for the period
shoi~ld also be considered. Simply put, there s h o ~ ~ l d be more flexibility in this
model; any cost which has been under control but has suddenly gone up although
no1 above the lixed percentage s h o ~ ~ l d be investigated.
STATISTICAL SIGNIFICANCE MODKL
This model relies on the measurement not only of a standard cost, but also of
a standard deviation for the expected dispersion of actual costs around the
standard, if standard is in average performance variance over t h e will average out
at zero and there is an equal propability of variance being adverse or unfavorable.
1-listorical data can be used to decide what size of variations around the average
could be expected without control action being required.
A variance will only be signaled for investigation if it seems to be i n excess
ol'a i~ormal amount to the estin~ated nom~al distribution suggests is likely,, if costs
arc still undcr control a 95% or 0.05 significance level rule would state that
variances should be investigated if they exceed 1.96 standard deviation from the
'lie advantages of the statistical significance model or rule over fixed
percentage rule are that:
a) important costs that norn-hy vary by only a small amount from standard
will be signaled for investigation if variance increased significantly.
b) Costs that usually fluctuate by large amount will not be signaled for
investigation unless variances are extremely large.
'l'he main disadvantage of the model is the problem of assessing standard
clcviation in expenditure this nlodel involves more computations.
2.4.1 COSTIBENEFIT ANALYSIS OF VARIANCE INVESTIGATION
Kaplan (1975:P.278) stated "since ally investigation will involve a certain
expenditure of effort and funds, manager will attempt to take action on only the
most significant and correctible variances. An investigation should only be
undertaken if the beneti ts expected from the investigation exceed the costs of
searching Tor and correcting the source of that cost variance". .
This model then recognizes that:
1 There are costs involved i n variance investigation
11 'I'here are no benefits to obtain if an investigation finds that the purpose is
not out of control
111 I t costs an extra amount to apply co~k-o l action if an investigation finds that
the process is out of control
Iv The beneiijs from control action on a process found to be out of control must
be at least sufficient to cover:,
a) The costs of investigation and controlling the process when it is found to be
out of control plus
b) The cost of investigating other variances when it is then found out that the
process is not out of control.
The disadvantage is the assumption that the costs of investigation and correction
are constant which presupposes that the cause of a vasiance is the same every time.
it does not allow for the process of learning from one's mistake.
111 co~~clusion control methods should be used with caution, if the parameters
of these models have changed, the model should be solved again for an updated
optional solution. There should also be flexibility in the models.
2.4.2 REI'OIITING VARIANCES
A variance report should be carefillly distinguished between conti-ollable
variance in order to yield a fair view of eat11 mangel; Users sho~dd have a co111111on
frame of reference when loolting at these figures, theis perception of the value,
materiality and effect of the variance .if left open will allow for possible
misinterpretation.
As part of a frame of reference variance that is material should be
highlighted and differentiated from those that are minor. Perhaps variances that
violate control limits should be limits should be listed separately from those that do
not.
OIt1)Eli AND AGGREGATION: Cursent research has shown that the order in
which variances are presented can affecr users perception of how efficient the
manager in question is in reporting variance we should consider whether listing of
all unfavorable variance first will have a different effect.
EXCli=PTION REPORT: Managers are often deluged with piles of reports and
other paper work. Certainly, to increase the usefi~lness of variance reports the idea
of exception reporting should be employed. The number and details of variance
~.cpostcd would be less for the plant manager thall for a line foreman. He is
interested in a seport that dsa\\ls his attention to key problem area that warrants
investigation.
4
Therefore, the question of materially is not just one of size of variance, but
also ol'who is going to see that variance inathe report.
2.4.3 AUTHORIZED AND UNAUTHOIUZED VARIANCES:
I n principle an executive should not be held responsible for derivations from
plan over which he cannot exercise control. Attempts are therefore made to
scgegate variance into controllable and uncontrollable categories.
In some cases those variance which are deemed uncont~.ollable are omitted
fi.om departmental operating statements.
In practice variance statements usually present a mixture of controllable and
irncontsollnble variances. Th&e are carefully scrutinized and discussed. It has also
been lcnown that controllability of variance diffess, as a variance, which may be
i~ncontrollable, by a line supervisor may be controllable by the divisional manager
or a top manager. Generally no reasonable manager criticizes a subordinate for
events beyond the manager's control.
In a11 deviations from plans must be reported to those responsible for
corrective action with the minimum delay. This might help to prevent any pending
damage which non- correction of the variance would have caused later.
2.5 CONTROL PROCEDURE:
Variance from the study identify area of possible wealcnesses, where control
action might be necessary where these areas have been identified by variance
analysis the following measure may be taken to control variance costs. I-Io\vever
hind ~narch (1977 P.224) advised that, for adherence to the principles of
mai~agement to be only interested in area whese difference occurred. According to
him if plan is being achieved, there is no need to investigate iiwther.
Whitmore (1 97 1 P.2) also warned that in controlling costs before any
~tttempt: is made at improving, changing, reosganizing or measuring any joys, it is I
essential to ensure that the staff concerned in the profit will co-operate. He feels
that the control measures should take motivational factors into consideration,
Whitmore (1971: P.2) therefore states that the first in any improvei-mnt or
cost reduction scheme is to pinpoint the area of high cost. He went further to state
that:" subsequently it nlay be necessary to use the various spectial;zations of
management services, which may be defined as those informative, advisory and
executive specializations which assist running o l ' i ~ s business.
I-Ie stated he Sollowii~g procedures for the rcduction in manpo\ver/ costs.
(a) By improving or simplifying methods and procedures so that fewer ,
1 employees are needed to produce the required o~ltput. I
(b) By causing employees to work at a faster pace, that is speeding up the tempo
of worlting by either introducing financial or other incentives based on work ,
I
Ineasurement or through the supervision. This means that the employee is required
to put more effort into the jobs over ;~nd above the normal req~~irement.
(c) By providing target times for jobs, al which the workers call aim.
Me however quickly noted that in the case of workers, who traditionally are
not used to being driven hard this c o ~ ~ l d lead to dissatisfaction with the firm, and a
consequent high labour tusnover, coupled with bad employee relationships bad
name for the firm ancl subsequent difficulty in obtaining labour.
Whitmore (1971 : 1). 12) according to him reduction of payroll to its
economic lev.el is also possible, ancl this is .done by selecting the personnel who are
to remain in the asea and then to remove the susplus manpower from the location
as soon s possible. That many applications fail because surplus worker are allowed
to remain in the area until other jobs are found for them. After a while, they
become re-established again in the department. The final job however is to re-
schedule the work load to the remaining staff so that the utilization of these
wol-lxrs may be brought up to the re uired fair day's work level. B
Another fact which may be investigated is the physical layout of equipment
and the flow of traffic around the department or section. Re-arrangement may be
necessary to reduce movement between areas and between equipinents.
The 1-inal stage may be improvement of work place layouts, individual
methods improvement and the more detailed aspect of the job. Appreciable savings
may be made by these minor itnprovements. Whitmore (1 97 1 :P 12) felt that
practitioners become so immersed in details that overtime spent does not justifl the
cost of the study.
2.5.1 Controlling price variances:
Price variances according to Mornegren (l977:Pl S6) are often regarded as
measure or forecasting ability rather than failurc to buy at specified prices. To him,
some control over the price variance is obtainable by getting many quotation,
buying in most economical lots, taking advantage of cash discounts and selecting
the most economical means of delivery. Price variance may lead to decisions to
change suppliers or freight carriers.
Me however stated that ihili~se to nieet price standard might result fieom a
sudden rush of sales orders or from unanticipated change in production schedule,
which in turn may require the purchasing officer to buy at i~neconomical prices or
to request delivery by air-freight. 111 these cases, the responsibility may rest with
the sales manager or the Meid of production sched~~ling, rather than with the
purchasing officer.
CONTROLLING UNPLANNED ACTIONS.
Walker (19S0: p.9) emphasized that variance al~alysis can monitor the
effects of' impulsive decision, by sales executive who offer unplanned discounts on
certain product lines. Deviations in product prices or bulk quantity cause variance
between actual and standard. Variance analysis can cvaluate thesc variances so that
thosc concerned, realizing that their spontaneo~~s actions ase being called to 7
account, will take care and learn to consider the results which their action may
have on the overall plans of their company's affairs. By monitoring their - movements the effects of their actions on other areas such as production, cost
recovery and stock levels can be quantified and kept under control.
I3hattacharya and deaden (1980: P.363) stated that a good variance analysis
will indicate variance from standard by &se anti will provide management with
usclirl cost control information. They are of the opinion that a good variance
analysis will separate causes of change due to price level change in efficiency and
change in volume.
CONTROL OF USAGE.
horngren (1977: P.200) is of the opinion that control over usage of material
is best exerted when the foreinan has the timely comparison ol' actual results \vith
standard. That when they are very important, these comparisons may be made
continually or at least h o ~ ~ r l y . 'l'he exact control procedure depends on:
I ) 'l'he nnt~ll-e' and value of materials: i~sage of sub-assemblies and expensive
part can be predicted easily and can be accurately accounted for. Prediction of
usage of bulk materials such as iron ore, alcohol, and c o d are based on average
consumption variance for these materials are aggregated as totals for given periods.
2) The type of accounting plan used. Where process costing is used, quantity
variances are often determhecl periodically. Where job-order costing is used,
quantity variance may be determined for each order if desirccl.
3) The methods used for detecting and lncasuring losses of material in
production. When a department is expected to turn out a given, job batch or
specified number of product units, a standard bill of material. Or stores requisition
may be si~bmitted to stores for withdrawal of the standard amount of direct
materials needed. As production t a l t e ~ place any additional material needed may
be obtained Srom stores only by s~ibinitting excess - materials requisition, which is 9
usually of a distinct colour. Thus, the foreman is immediately informed of off I standard performance because he must sign the excess- materials requisition. I
I
I-Iorngren (1977:P201) is again of.the opinion that where the computation of
variance is delayed due to the nat~lre of production process, or until when
production is completed, to better achieve control in these cases, inspktion at key
operation points while work is in process so that spoilage and other losses may be
measured before fill1 completion of the production. In order to exercise control
proper over virt~~ally nnytliing there must be a degree of feed back from the output
so that the input may be modified to maintain the desired effect of the output. I f the
feedback is removed in most cases, the control is lost. Feedback process is shown
in the illustration below.
FEE1~13ACIt
The "Feedback" is the process of indicating when plans are not being
achicvcd. I t is vital to the whole manngcment infomation system - without the
warning signals these can be no psompt action. Diagra~nmatically it is shown
Actual cost
Revision from feedback
Plans and uxecution Action on f e d b a c k 1 Variancc Analysis
1 l'ersonal contact and I
Feedback within a standard costing system may come from a numbe;. of
sources such as
Use of exception forms such as excess material requisition when additional
req~isitions have to be authorized berore being issued.
- Meeting with line managers and accountants on a formal or informal basis.
- Reports and statements produced at the most appropriate intervals; daily, weekly,
monthly or quarterly.
The guiding factor is the nature of the cost and therefore whether it can be
contl-olled at daily, weekly or other intervals.
The danger of distorted feedback is a serious problem. Information collected
in one form may be analyzed and edited, then presented in some unrecognizable
way. The result is that no action is taken because the manager, do not understand
the information and its significance. 'Care should be taken to establish
con~n~unication channels which avoid misunderstanding of this type. There is a
rcrd dangcr of this occurring when the data processing is completely centralized.
With the standard costing system, the information flow is based on the
variances. Any significant derivation from standards are highlighted as part of the
routine. It provides the necessary information for corrective action. Which at later
stage may be used for revising the standard costs.
ACTION.
If a ~nanage~nent information system is to be of value, it should stimulate
to correct adverse tendencies 'which are continuing; at other times it may be too
late to avoid the excess spending which has already taken place - although steps
should be taken to prevent a reoccurrence in the future. The relevant costs control
should be the guide to the action required. If costs are incurred on a daily basis,
daily action will be essentia .I . For others monitoring will be less frequent.
Managers should continr~ally be on the alel't to avoid excessive usage of services. A
conlrnon thing is switching off motors and lights when not in use may appear an
obvious approach, but regrettably the one which is not always followed especially
in government owned compame.5
2.5.2 IMPORTANCE AND PROBLEMS OF IMPLEMENTATION IN
MANUFACTURING INDUSTRIES IMPORTANCE:
Every manufacturing company is- concerned with -controlling its costs ,o f
j~rocl~~ction in order to increase its profitability or performance. Managerial
accounting is primarily concerned with providing infbrmation to management for
the purpose of achieving these objectives. Its purpose is for planning and control of
costs. Planning is the process by which managers first determine the objectives of
the organization and then determine the resource that will be needed to facilitate
he i r attainment. Control on the other hand is the process by \~lhich manager
assurcs tlmug11 l'ceclback that sesources .are obtainud ;~nd used effectively and
el'liciently in the accomplisl~n~ent of the organizution's objecti-ves.
One of the most basic and impostant elements in both the planning and
control process is a vasiance analysis. Adelberg (1986: P. 12) also acltnowledged
that variance analysis has a great role to help improve the profitability and
therefore growlh of the manufacturing sector.
Variance theiefore are tests of manager's forecasting abilities, as they are
also nlade responsible for the standard and variance.
Other advantageslbenefit of using variance a~lalysis also include comparison
of actual costs with standard cost in order.to measure perforin-ance. The departure
fsom the expected will indicate improved performance or decline in performance.
The application in practice should result, in the best resources and method being
used which will increase efficiency as well as highlight areas of strength and
weakness. 9
Importance of variance analysis as a,tool for cost control and an accounting
inforination system cannot be over-emphasized, and this is summed up by Duncan
(1990: P.25) when he stated that. Any ~nanagement accountant will know that the
application of variance analysis in an appropriate setting can provide management
with a very powerful managerial tool for control. From every point of view,
variance analysis is of benefit to a business: by setting and reviewing standards a
business will be learning a great detail how its processes operate and how its cost
behave by using those variances, a business will be monitored closely and often the
progress that it is malting or the proble~n it is fazing.
He is of the opinion that the use of variance analysis will help an
organization to understand its cost behavior and progress i t is making.
PROBLEMS:
Despite these benefits to be derived by the use of variance analysis by the
~nrln~~facturing firms, this study reveals that many do not employ it for one reasoll
or the other.
l. ,:~lt of its wider implementation in manut'L7cturing industry has been
attribulcd to many factors which are lack of I<nowledgeable and experienced
personnel. Duncan (1990: P.35) argued that the b i ~ g e s t problem with the
understanding of variance analysis is the way it is presented. Unless you a:-(>
prepared to spend Inany hours memorizing a whole series of complications you
will never get to grips with the benefits of variance analysis. Consequently many
never get beyond the " formulae stage" because they find tile formula hideous, this
leads to the situation where full o r any ~nenning is lost.
T11c notable aspect of this a r g ~ ~ m e n t is that the understanding of the subject
itself is difficult. Many are not prepared to learn it not to talk about imple~nenting
in p-aclicc what they are not knowledgeable in.
Closely followed by the abode factor is the cost involved. A heavy load of
input data is required which is expensive. Inevitably, the starting point of the
nxmagement accounting information system must be the effective collection of
accounting data. A system must be designed to meet some predetermined objective
or purpose; such as cost control or inventory valuation. To satisfy this demand
certain information is required based on the nature of the organization as all system
presupposes that the inforn~ation is needed by a designated person. To design a
standard costing system to cover all the 'individual needs in the manufacturing
organizations are not prepared to incur heavy cost just to set up a system which
they are not sure to operate or maintain. .
The other factor which prevents its wider application is the use of variance
to evaluate performance. An adverse variqnce is taken to m a l l poor perforn~ance
and a favorable variance to indicate improvement. Where profitability is also used
to measure performance, manager do not want to ernploy variance analysis for fear
that adverse variance charged to profit and loss account drastically reduce profit
and consequently lowers return on investment. They feel without variance analysis
in cxistencc this variance will not arise to be charged to the profit and loss account.
Inevitably whichever method is employed in the disposal of variance will affect the
profit $ loss account in one way or the other.
Apart from the factors t11a.t discourage the usc of the system in practice by
some organizations, there are others affecting its full use ever by the few compa~ks
operating it.
Some of thesc are hu~n in factor like the "operating environment",
Downsland (1978: P.500) cited the case of coke ovens in a steel watt where coal is
converted into coke and are not among the glamorous area often showing to
visitors. What he implies is that it is very.difficult to keep or operate an accurate ! rccosding systein in si1c11 environment with excessive heat, cold or dust as in a ,
43
cement factory. In other words accurate data collection is impossible without
modification. Data recording here is also a problem for example, an environment
where water, steam and either elements all play a part means that it is almost
- impossible to maintain weighing eqiiipment to fine precision in recording. Because
of this nluch of the data recorded is based on personal eitiinates rather than
~nechanical registration.
Monitoring of data on modern equipment according to Downsland (1978:
P.501) is generally not carried out for one or two reasons; first equipment may not
be available or may be too costly to measure to the required precision in the given
environmental conclitions. Second worlters tend to regard any monitoring of
activity as a means of checking on their work and so find ways round the
monitoring system. The matter of equipment cost is also clearly of concern and it is
often difficult to justify a large capital outlay in order possibly to improve only the
ilow or accuracy 01' information.
There is also the problem of internal competition (e.g. between various - clepal-tments) in which each departmental manger feels that he is competing ~ l . i r 1 1
other managers to get the best monthly iigures.
In some organization especially where the output of one department are rhe
input of another, Downsland (1978: P.502) stated that, the manager of one
department may produce its output figure based on some registration and
estimation, the other user department may produce input figure as registered on
modern weighing equipment. The discrepancy between the two may be generally
small but it is human nature that the. manger producing figures based on
registration and estimation will if analysis, exaggerate his output figures while the
user department lnanager may belittle his receipts to show improved performance.
The system is partly responsible for such attitudes in that i t reports t11t
weckly / monthly prolits (kc. ovelsll~hvorablc., hence encouraging :~djnstment o
figures. This adjustment would be difficult if the system did not rely on human
estimates for some of its input data hende the system is both the cause and its
effect .
Data precision is another factor whic]~ according to investigation is affecting
the realistic use of variance analysis in practice. The data items which one use as a
basis for the cost control system, for both physical and financial statistic, are
generally recorded at least daily. Where recording is more frequent, the figures
processed through the information system are usually average daily readings.
Interpretation and investigation of variance is another factor affecting its use
in practice. Variance analysis highlights areas of strength and weakness, but does
not indicate what action if any shoulcl be taken. A manager must be able to
interpret correctly the significance of variance before he can initiate contiul action.
This calls for precision in data collection.
The problem of choice of the investigation model also affects its full
implc~ncntation as a management information system in practice.
Morse (1981: P.178) also expressed some reservations about the use o f
statistical control charts in investigation and interpretation of variance when he
stated that: "despite the apparent precision of statistical control charts some person
or persons must select X and R control liinits on the basis of either professional
judgment or accepted practice: The establishment of these limit not usually based
on a formal analysis of such factors as the cost of investigation, the cost of
correcting a process that is out of control."
'The notable aspect of this statement is that despite the use of the most
sophisticated control technique, the selection of control limits is entirely based on
personal Itnowledge or experience. To help ameliorate the difficulties and
problems of the choice use of investigation models Wordale (1977: P. 125) stated
that: instcad of using single period models, one can use more sophisticated inulti
period models. As malting a decision 011 the basis of ilrst one observation is very
dil'l'lcult lo s~~bstantiate in practice and it'is therefore far more sensible to use a
quality control procedure that accumulates the information- the cumulative sum
procedure. However, different variance investigation models exist and choice will
depend on suck factors as the operation, which is being controlled, the number of
past observations available, the cost and benetits of investigation and the degree of
statistical sophistication with which the accountant can cope. The choice of multi
period n~odcl calls li)r more expensive matesids ;wd experienced accountants.
Thesc are either lacking in these organization or they are not prepared to spend on
maintaining just standard costing system which they feel they can do without.
i
REFERENCES
L. S. A Nat~lre Of Standard Costing In Manage~nent Accounting 2""dition
London. Lsa Publishers Ltd (1 976, P. 2 10)
I m x y T' Standard Costing. Planning And Operational Variances, 3'"dition.
Idondon. Bpp P~lblication (1 983, P. 16)
Glautier And Underdown. Standard Cost And Variance In Accounting Theory And
Practice, 2"" Edition, Pitn~an Publishers (1982, P. 583)
Osisionw, B. C. Standard Costing, 1" Eclition, Eni~gu New Age Publisher
( 1 900, P.237).
Owler And Brown J. L. Standard Costing, Plyn~outh Macdonald And Evans i
Publishers, (1982. P. 571)
Nweze A. U. Quantitative Approach To Management Accounting Enugu i Computer Age Publishers (2000, P.85).
Batty J . Analysis Of Mnnufact~~ring Variances London, Macdonald And Evans Itd
( 1977, P.44)
Vicltery G. B. Integrated Cost Financial Account London, Donnington Press. 2 1"
Edition (1 973. P. 754)
Brown And Howard L. R. Standard Costing In Principle And Practice Of
Management Accounting Plymouth. Macdonald & Evans (1976 P. 15 1).
Walker T. M. Variance Analysis in standard costing London Gee & Co. PutAisl~ers
Ltd (1 98, P. 17;)
I .onder bock and I Iirsch, Maurice L. Variance analysis. I'lanning and Operational
Variance, New York, Prentice I-Iall (1986, P.289)
Kaplan. R. S. and Johnson, H. T. The Rise and fall Management Accounting in
Boston ( 1975 P.278)
White more, Dennis A. Control in measuring & Control of Indirect work. London. 1
4 7
1 " Edition William I-Ieinman Ltci (1 97 1, P.2).
Morngem, C. T. Standard Costing London 4Ih edition, prentice Hall int,
( 1 977 P.lS6)
Lucy T. Nature of Standard Costing, Planning and Operational Variances.
~ondon3' '" edition BPP Publications (1 986 P.45)
Sherwin and Douglas S. The process of ~oll t rol l ing in Management. New York.
Mac Grow Hill Inc. (1972.p. 23)
Vicltery G.B. Integrated Cost and financial. Accounts London Donmington press.
2 1%' Edition, (1973 P. 85).
Walker T. M. Variance Analysis London. Gee S( Co publisher's Itd. (1980 P.7 1)
White more, Dennis A. Control in ineasuring and Control of indirect work.
London Witlinn Heinman ird 1'' edition (1 97 1 P. I 12).
I lorngren, C. 7'. Standard costing Accounting A m:lnagerial Emphasis 4"' I
Eclition prentice Mall Int. London (1 977 P. 193) I
Duncan Williams stai~darcl costing made simple in ACCA student Newsletter, I London the certiiieci Accountants Education trust. Jan. (1990 p.35).
I
I
CHAPTER THREE
3.1 RESEARCI-I R/IETI-1OI)OI~OGY.
This research is designed to obtain realistic information that is required by
variance analysis to control costs in manufacturing lirms and to show the extent of
its effect on profit. The study essentially examined the views of nunagers, finance
directors, accountants actually engaged in the practice of financial data of the
companies either in one way or the other. Going by the caption of the work it
should have been expected to cover the wl~ole country. However, owing to the sizc
and population of the country and the near impossibility of such an undertaking the
work was narrowed down to the potential m a n u f i ~ c t ~ i i n companies within reach.
The research technique used at any stage \vas such that was judged to yield
the most reliable result under the given circumstances. Extensive uses of both
primary and secondary data were used in tliis study.
3.2 SAMPLING METHOD USED
The sample hame for the research was the population of managers, fi~lance
directors and accountants engaged on the job in the practice. These are the active
population of the country. In this case finance personnel in manufacturing
companies. Within each of these companies questionnaires were administered to
these group of people in the companies.
3.3 RESPONDENTS AND SAMPLE SIZE
The respondent to the initial study or survey are only those that I felt will
give the needed data. his includes manngc1.r~' supervisors nnci others, Thc
managers are those heading the various divisions or departments, supervisors are
those category of senior staff engaged in monitoring of operations; accountant who
then designed the acco~mting system or the cost analysis and others which include
the laborers storekeeper, and other operative workers etc. 9
The scope or the sample sizes in use are the numbers of the respondents
choose for the study.
3.3.1 DETERMINATION OF SAMPLE SIZEIPOPULATION.
COMPANIES POPULATION
Annnmco 60
Nigerian Breweries -200
Juhel 100
Emcnite 40
I'op~~lation Size 400
DETERMINATION OF SAMPLE SfZE
Using the formula for the determination of sample size from a population
% - - N
1 +- N (e) ' Where
n = Sample size
N = Pop~ilation size
e = Level of significance
1 = One a constant
For the purpose of this s t ~ ~ d y the level of significance (e) '= 0.05 that is 95%
confidence limit.
e = 0.05
Substituting
Sample Size (n) = 200
I
ALLOCATION OF SAMPLE SIZE TO COMPANIES I
To determine the rnini~num number of respondents from each of the
Companies, Bowley's I'ropor~ional Allocdion formula was applied 'I'hus:
XI1 = Number of units allocated to each company
11 = 'Total Sample size
Nh = number of item in each company population.
N = Population Size Substituting
(A) ANAMMCO
n h == * 200 X 60 400 - -
(13) NIGERIAN I3llEW l3lllL.S
nh == , 200 X 200 400 -
(C) JUI-lEL
nh = 200 X 100 400 - -
(I)) EMENITE
The Sample size for each of the Company was d2tern1ined as Follows:
ANAMMCO 30
NIGERIAN BREWERIES . 100 1 JUliEL
EM ENITE
For proper and wide representation there is then the need for the determination or 1 i
allocation of the sample size to different division or cadres of each of the company.
The company's pop~~lation strength was Sound to be as follows:
Managers Supervisors Acco~intant Other Total
Nig. Breweries. 10 30 10 150 200
Total
Allocation Of Sample Size To Divisions Of Each Company: ( I ) Ana~ninco
Where
m h = Number of units allocatecl to each division.
11 = Total sample size for the company
Nh = Nuinber oi' items in the division
N = Population size.
Substituting:
Accountants
Others:
nh - - 3 0 x 4 0 = 20
60
Therefore: n h l + 11112 + nh3 + 11114 = 2+5+3+20 = 30.
(A) MANAGERS:
100 (B) SUPERVISORS:
100 (C) ACCOUNTANTS:
(D) OTHERS
(3) NIGERIAN BREWERIES:
(A) MANAGERS
n 11
(B) SUPERVISORS:
n 11
(C) ACCOUNTANTS:
n 11
(11) o'r1-1ms n 11
(4) EMENITE
(A) MANAGERS
nh -- -
(B) SUPERVISORS
nh - -
(C) ACCOUNTANTS
(D) OTHERS
1 oox l o - - 5 200
SUMMARY OF SAMPLE SIZE ALLOCATION
I I MANGERS
Nigerian 5
Breweries.
SUPERVISORS I ACCOUNTANTS / OTHER
3.4 DATA COLLECTION
Data for the necessary infor~nation 'for the study was collected from both 1 primary and secondary sources.
PRIMARY DATA: Consist of questionnaire used fof this s t d y . The
questionnaire was distributed to selected companies. The other primary data \\/as
pcrsollrll intervicw from ol'kers on the job anti those rctired but \\.it11 \ , i tnl
knowlccigc in thc arm. Secondary data consist of recent articles fi-om nzwspapers,
magazines, journals and textboolts.
3.5 DESCRIPTION OF THE QUESTIONNAIRE
One set of questionnaire properly designed to highlight the objective of the
study were used. Nos, 4, 5,sought to find out how inany companies employ- 1 variance analysis. Questions 6,7,8, & 9 sought to find out the number of companies
that investigate vdriances. Nos 10,ll &12 sought to find out the responsibility
accounting as regards reporting variance to people responsible and to management.
Question 13 then sought to find out the causes of variances. While 16- 18 is about
the revision of variances and question 21 sought to find out whether from
cxpcriencc comprmies that einploy variance analysis have a better-cost control tllan
those that do not. 9
3.6 TECHNIQUE FOR DATA ORGANIZATION AND ANALYSIS:
l'he techniclue adopted was a response to the nature of data generated. Here
the focus was the generation of sunmary statistics such as averages and
percentages. The percentage generated for example were used in analysis tn
ascertain the number that are in agreement or otherwise with a given variable or
point of view.
The hypothesis was tested by the use of the chi-square. The chi-square x' is
a general test that can be used whenever there is need to evaluate whether or not
freqi~encics, which have been obtained, differ significantly from those which are
expected.
Thc chi-square (x'~,) is defined as:
X' = (Oi-Ei) Ei
Whcre Oi and Ei refer respectively to observed and expected frequencies for each
cell. 'l'he tests wcre conducted at 5% and 1 % level oi'signilicance.
- 3.6.1 ACCEI'TANCE/KEJECTION OF HYPOTHESIS.
The null hypothesis is accepted if at the given level of significance the
calculated value of chi-square is less than or equal to the expected or that obtained
from the statistical table at that given level of significance and degree of freedom.
I t is rejected if the calculated chi-square is greater than the critical value fiom the
table at a given degree of freedom viz:
xo2 < ~ e ' , accept
x > x,', reject
3.7 STATISTICAL METHOD FOR DATA ANALYSIS
Many methods could have been adopted for data analysis. Such includes the
- use of average and or percentages but the writer adopted a statistical method by
using the chi-square model.
The chi-square as we know is a generated test that can be used whenever
there is need to evaluate whether or not frequencies which have been obtained
differ significantly from those which are expected.
CHAPTER FOUR
DATA ANALYSIS AND PRESENTATION
4.1 PRESENTATION AND ANALYSIS OF DATA
'This research study intended to flnd out whether in practice, the use of
variance analysis as a tool for cost control has any effect on the profit oi
manufacturing firms.
TI1 E I<ESI'ONSE
A total of Sour manufactu~-ing iirms were covered by the 170 completed
clucstionnaires which were returned. This represented about 85% of the total
qiwtionnaires distributed which was two hundred in all.
Questionnaires were administered in all the four ~ n a n ~ f a c t ~ ~ r i n g f i r~ns as
show i n the table below.
'Sablc 4.1
Administered Respondents
ig. llrcweries 1 100
To tir I 200
The total number of questionnaire distributed were 200 out of which 170
were returned, representing 85% of the total questionnaires administered in all. The
non- respondents accounted for 15% or 30 of the total number distributed.
Further analysis reveals that 30 q~~estionnaires distributed in Anambra motor
manufacturing company (Anammco) as per table 4.1. Above, 30 questionnaires
were distributed out of which 25 representing 13% were returned while 5
representing 2.5% were the non- respondents.
In Nigerian breweries a total of 100 questionnaires distributed, while 90
representing 45% and 10 representing 5% were the respondents and non-
respondents I-espectively.
Considering Juhel the questionnaires returned out of the 50 distributed was
40 sepresenting 20%, while the 11011- sespondents was 10 representing 5% of the
total questionnaires distributed.
Finally in Emenitc the qt~est io~m~ires distributed west: 20 wl~ile 15
rep-esenting 7% and 5 representing 2.5% were the respondents and non-
- respondents respectively. 1 Table 4.2 Usage of variance Analysis
From the responses collected out of the four firms a total of 147 indicated I
that they use vasiance analysis. This represents 87% of the respondents. Moreso 16 !
I 1
o f the respoedcnts representing 9% and il respondents representing 4% indicated I
-
Firms
Ananlinco
Nig.Brewcries
Juhel
Einenite
Total
%
1
2.5
5
0.5
9
Yes
20
84
30
13
147
No Ides
3
1
2
1
7
%
12
49
18
. 8
87
No
2
5
8
1
16
YO
15
j2
21 -
9
100
%
- 7
.5
1
5
4
Total
25
90
40
15
170
no knowledge of variance analysis usage in their firms. Breaking the analysis
further for the respondents that indicated yes, Anarnmco had 20; Nigeria breweries
had 85 while Juhel and Emenite had 35 and 12 respectively.
Table 4.3 usages for more profit
'I'he above table 4.3 which is an analysis of the respondents that indicated ,
that l h s use variancc malysis for more prolit, a total of 144 indicated yes
scprcscntin~ S5% \vhile 1 S and S indicated no and not sure representing 1 1% and
4% sespectively.
Table 4.4 objective of variance Analysis "To control cost"
Firms
Anammco
Nig. Breweries
Juhel
Emenite
Total
I Yes / %
%
12
47
19
7
83
Yes
20
SO
32
12
144
I Juhel I
30 IS
No - % Not YO
Sure
3 2 2 1
6 4 4 2
7 4 1 .5
18
1 Total
% 1 . Other 1 % 1 Total 1 % 1
/ Reasons
From the analysis above, the companies that employ variance analysis 147
of the respondents representing 87% revealed that it is n lek t for cost control,
while 10 of the respondents, which represent 6% of the total respondents,
disagreed, and a total of 13 respondents representing 7% indicated that the
companies employing variance analysis is meant for some other reasons outside
cost control.
Table 4.5 Usages for better-cost control.
From the above table 4.5, 90% of the respondents indicated that the
companies employ variance analysis for a better-cost control. This covers a total of
152 respondents while on the other hand 15 respondents revealed that the variance
Firms
Anammco
Nig.nreweries
analysis is not employed for better-cost control while 3 respondents representing
2% stated no ides
4.1 STATISTICAL TEST OF HYPOTHESIS
Jdwl I :3 I ; I I ; I I ;-I ;; I ; - Emenite -- -- -- - r r ~ t ; ~ ~ 152 90 15 8 3 2 170 loo
Yes
20
85
The analysis for this study will rely on the chi-square (x') distribution. The
chi-square test examines the extent to which the frequencies that are act~ially
observed in the study differ from the frequencies that are expected if the null
hypothesis is COI-sect. To do this we calc~ilate the statistics
YO
12
50
%
2.5
2.5
No
5
5
No
lclen
- -
--
YO
- -
Total
25
90
%
14.5
53.5
Ei Where
X' Is the (chi) X' - square test
Oi denotes observed value
Ei is the expected value.
'hxefore in each category I take the differknce between the observed and expected
values square i t to eliminate the sign and divide by the expected value. I sum this
for all categories. Coyee (1971 P. 155) stated; that it is important to note that X'
only worlts with actual numbers and not with proportions, probabilities or ratios. I
I In calculating X' the following stepsare taken.
(1) Arrange the observed frequencies in a table as show in table 4
(2) Calculate the expected value, the formula in E, which is:
Roll total X column totals I N
(3) Calculate the quantity (0i -~i) ' for each cell.
(4) S u n the value of x' (Oi-Ei) found in step 3.
The significance of chi-square
This can be evaluated by referring to a table of critical value of X' as
presented in appendix 1 1. The critical X' values indicate the value that the obtained
X' must equal or exceed to be signilicant at 0.10 levels, the 0.05 levels and the
0.01 level. i I
The critical value of x2 for any given study depends on the degree of 1 I
fieedom. 'These are the number of scores-that are free to vary based on the row I I
totals and the column totals.
l'his is given by clf = (r- 1 ) (c- 1)
Where
r = Number of' rows
c = Number of columns
Where we have 3 rows and 2 colu~nn the df - (3-1) (2- 1) =2.
The col-rccted degrees of freedom determine the critical value of X'
necessary to reject or accept the null l~ypothesis at the chosen significance level.
Where the calculated X' is less than the critical value from the table we accept the
111111 hypotlmis; where the X' is more than the critical value; we reject whereby the
reverse is [he case.
i.e. X' < CV accept
X' > CV rejects
4.1.1 TEST OF HYPOTHESIS
( I ) 1-10: 'The number of manufacturing companies now using variance analysis as a
tool for cost control is not adequate. (Not many) 1 1-1 1 : The number of manufacturing companies now using variance annlysis as n tool I I
for cost control is adequale. (Many) I
The analysis above indicates that 80% of the respondents accepted that the
Table 4.6: Companies Employing Variance Analysis
number of companies employing variance analysis is not adequate (many) while 15
:lnd 5% revealed or maintained that it is adequate and no idea respectively.
- Companies
Ananmco
Juhel
Nig. Breweries
h e n i t e - -
Total ----
The chi- test will then be used to testthis hypothesis for the variance zones: 7
Yes -
20
75
30
8
133
%
12
45
18
5
80
No
3
10
' 1 0
5
28
YO
2
5
. 5 -
3
15
No Idea
2
5
-
2
9
%
1
3
- _
1
5
Total
25
90
40
15
170
%
53
23
9
100
TOTAL, 4.7. Chi - square test (Summary o,f table 4.6)
Company
Emenite
Adequate
3
10
10
5
Where E = Expected value
R = Row totals
C = Column totals
N = Number of items.
Inadequate I No Idea I Total
'Table 4:8
Contingency Table (Expected and observed)
Cell Oi - Observed Ei - Expected (Oi - Ei). ' -.
d f = (R- 1) (C-1)
= (4-1) (3- 1)
=(3)(2) = 6
The calculated x2 is 9.1399, which is less than the critical value of 1 1.07 at
0.05 confidence level.
DECISION RULE:
Accept the null hypothesis if the calculated X' is less than tabulated value;
otlw-wise reject. The critical value (CV) at 0.05 and 0.01 levels of significance for - 9
6 5
the chi - square (x') based on 5 degrees of freedom is 11.07 and 15.09 I
respectively
xQ.05 95% = (CV) = 1 1 .O7 x2 = 9.1399
x2 0.01 99% = (CV) = 15.09 X' = 9.1399
DECISION:
The observed X' = 9.13399 and the critical value is 11.07, since the
observed value of chi - square (x') of 9.1399 is less than 11.07 and 15.09
respectively, accept the null hypothesis, that "the number of manufacturing
compaks now using variance analysis as a tool for cost control is not adequate'.
4.2.2. HYPOTHESIS 11
I 2) tIo: Manufacturing companies that employ variance analysis have better cost I
control than man~~fiict~iring con~panies that do not employ it. i I-I 1 : Manufacturing companies that employ variance analysis-do not have a better I
cost Control. I I
Table 4.9 (Sum~na~-y from table 4.5) ! I Colnpany / Yes
) Total I 152
Nig. Breweries
No I No Idea I Total I I
35
Expected values computation:
Table 4.10 Contingent Table
(Oi - Ei)-
20 22 O.lSl8
The calculated X' is 10.4526. This is less than the tabulated (CV) value of I I
1 1 .O7 at 0.05-confidence level,
DECISION I
The critical value at 0.05 level of significance for the chi-square (x') based
on 5 degrees of freedom is 1 1.07 while the observed is 10.4526.
Since the observed value is less than the critical value at 0.05 and 0.0 1 l e ~ z l I
of significance for chi - square (x') based qn 5 degrees of freedom, which is 1 1.07
and 15.09 respectively, accept the null hypothesis that "the manufacturing~g i
companies that employ variance analysis have better cast control than
manufacturing companies that do not employ it".
4.2.3. HY 1'01'1-1ESlS 1 1 1
Ho: manufacturing companies that employ variance analysis are more profitable
than companies that do not employ i t .
1-11: manufacturing companies that employ variance analysis are not more
profitable.
Table 4: 1 1 (Su~n~nnry lyom table 4.3)
Nig. Brewery 1 80
Co~npany Yes
Juhel
Expected Values:
No
Total
Not Sure 1 Total .
32 7
144 18
Table 4: 12 Contingent Table.
Cell
DECISION:
The critical value at 0.05 level of significance for the chi- square (x') based
on 5 degrees of freedbrn is 1 1.07 i.e. the critical region. The observed X' is 5.8026
The observed value of chi-square (x?) 5.8026 is less than the critical value at
0.05 and 0.01 levels of signitlcance for Chi- Square based on 5 clegrees of freedom
which is 11.07 and 15.09 respectively the null hypothesis is accepted that
"Companies that employ variance analysis are more profitable than companies
that do not employ it".
70
CHAPTER FIVE
SUMMARY OF FINDINGS, RECOMMENDATION AND CONCLUSION.
5.1 SUMMARY OF FINDINGS:
This study has revealed that there is a dearth of literature on this topic by
Nigerian authors in general. Most of all the related literature was i n foreign
journals and textbooks
Manpower problem was one the of the problem affecting the implementation I
ol' the technique in practice by ~nani~factiiring companies. The study revealed that
experienced accountants are lacking in this particular aspect of accounting. l'his
problem has been compounded by the fact that many qualified accountants prefer
to be on their o\vn in practice.
Another finding wl~ich is closely allied to the above is that of staff turnover.
It was discovered that these has been a high staff turnover \vl1ic11 is being
experienced by some of'the companies. With the expansion i n the number of banks
with exceptionally very 11ig11 pay, experienced staff in these co~npanies are easily
attsacted.
Lack of edi~cation and awareness by most industrialists has been cliscovesed
by this research to be one of the key factors militating against the implementation
of this teclmique w l ~ i c l ~ coi~ld have led to expansion in industries through increased
prolit over the years. As earlier mentionccl expansion can only be noticed when
profits continue to increase. Most of' the industrialists, i t has been foi~nd'became
such by chance or because they had the resources. Most still operate such
companies as sole trade business, proprietorship to limited liability companies.
They iind it dii'ficult at this time to separate ownership fiom the entity. Where thc
inanage~nent is directly involved, it therefor$ become difficult to control even with
all the soplisticatated techniques of control in existence. As regards companies
operated by the government, grants or subsidies by government to such company,
it was discovered either misused or misdirected to private use. The control problem
then is whether to control cost or management.
Closely related to the above is the ignorance on the part of management or
staff concerned. I t was also discovered that inany companies compute variance
analysis but ignored them, even by those related costs where variance costs formed
a high percentage oftheir total cost. I I
Another problem discovered was that of employing relatives, in-laws I I , . ~ 1 key nlanagement position. It was discovered that most of such employees were not 1
,
cost conscious. Even when it was discovered that they were extravagant, i t became
difficult to take punitive measure against their inlaw or brother. Many of such
companies still remain at their infant stage after many years in existence.
'I'here is also a strong Sceling that from the research study as portrayed by
the test of l~ypothesis one, two and three using chi-square test in chapter four \\.ere
that manul'acturing companies now employing variance analysis as a tool for cost
control is inadequate (not many), moreso that companies that employ variance
analysis have a better cost control and are more profitable than companies that do
not employ i t .
5.2 KECOMMENDATION:
The importkce of variance analysis as a tool for cost control and decision
malting for the manufacturing sector of the economy cannot be over-emphasized. I1
will reduce cost of materials, Labour and overhead. Yet not every manufacturing
firm is prepared to employ it.
However in order to encourage its use in the manufacturing industry certain
constraints or problems militating against its fill1 implementation must be solved. 1 7
therefore recolnmend the following measures which I feel and hope could
encourage its applications. They include: -
1 ) The issue of statement by the Nigerian accounting standard board (NASB) on
the i~nple~nentation of variance analysis by all manufacturing companies without
an exception. This could be taken as an auditing standard. Toe make it more
effective it should equally be included in the coillpany and allied matter decree
(CAMD).
2) Proper background in this area should be made possible and also be re-
emphasized by future accountants. This could be done by its inclusion in the I
syllabus of all universities offering accounting degree "variance analysis" this
should be extensively taught at two stages. First as a topic under cost accounting
with emphasis on decision making if possible student accountants should be aided
to do vocation jobs with companies that operate the system. I
3) On the job training or short courses to be permitted, workers handling this jobs 1
I could be allowed to go on short term training course with some accounting training i
houses. Such staff should also be encouraged to stay after training. ! i
4) Honesty of Nigerian employees who are charged with the responsibility of i recording data should be emphasized. This is because its use as a management I
information system for control can only be meaningful if data recording is
accurate. I 5) 'This should be one of the yardsticks for acceptance of any manufacturing , !
company for q~~otation on the stock exchange market. I 6) Standard costing system should be used as a motivating factor rather than a
factor, which may encourage unhealthy rivalry among divisional managers.
Employees too should be made not to take it as an instrument used to monitor their
activities.
A I
CONCLUSION: \ , * I e
1 - I I
5.3 Development of the manufactusing sector plays a vital role in the overall 1 i
However in spite of these benefits the sector has been constrained to develop
development process of the economy. Despite the various output provided by the
sector, it (economy) may not necessarily provide employment opportunities and
increase the G.N.P.
as a result of some problems among \vhicls are; lack of raw materials, high cost of
.
production, low and shortage of managerial manpower. These factors ha\~e I I
automatically led to f i l l i n revenue by this sector and low contribution to G.N.P as I
is supposed to be.
The sole of variance analysis has therefore become very necessary in the I sector, partic~ilarly as i t will encourage the maximum use of scarce recourse like. 1 labour and raw materials. It will also discourage misuse or misdirection of these
available scarce resources. However the examination of the relevant statistic
reveals that the use of variance analysis system has not been encouraging as to
effectively enhance its use as a device to. control cost and consequently develop
this sector
From the statistical analysis carried out, these is a relat-ionship between
variance analysis and the profit of the manufactui-iny companies. Mowe\w, in
spite of lack of its wider application it has been shown that its use can control
costs and consequently improve profit. This sector has contributed to the
development of the country, and the Lise of variance analysis as management
accounting information has to a large extent, supported this assertion.
Batty J. Analysis of ~~~anufacturing variances London. Macdonald & Evans ltd
1977
Brown and Howard L. R. Standarcl Costing in Principle and Practice of
Management Accounting Macdonald & Evans 1976.
I'gc~.ton and RI-own. Perspective on planning in blanage~ucnt. New York
Grow- Hill lnc. 1972.
Glautier and Under down Standard Costs a i~d variance in Accounting theory
And practice. 2""dition pitn~an publications, 1982.
Morngren C. T. Standard Costing, London William Heinernann publishers 1977.
Kaplan, R. S. and Johnson, N. T. The use and fall of management Accounting
Boston. 1937.
Koontz and 0' Donnel, Nature and purpose of planning in Management New York
Mc Grow Hill Inc. 197 1
Laicller E. Theory and practice of variance Analysis London, Macmillan. 1974.
Louderback and Mirsch. Variance Analysis, planning and Operational variance
New York. Prentice Hall. 1986.
L. S. A. Nature of standard Costing. London 211d edition L. S. A. publisher. 1976.
APPENDIX 1
Department of Accountancy, Faculty of Managenlent science, University of Nigeria, Enugu Campus,
a 15''' Fcb 2004. - I I
QUESTIONNAIRE ON VARIANCE ANALYSIS AS A TOOL FOR COST
CONTROL IN THE MANUFACTURING COMPANIES INTRODUCTION,
This questionnaire is designed to elicit information about variance Analysis
as a tool for cost control in inanufacturing companies. I We \vould appreciate your understanding to assist the ~.esexcher's effort by
responding ~\ccuratcly lo the following questions. The infbrmafion obtained \ \ , i l l be
lor academic purposc only and strict confidentiality is guaranteed. No individual
respondent or organization \vill be identified in analyzing and reporting the results.
Thanlts f-or your Co-operation
Yours faithf~~lly
Management.
QUESTIONNAIRE.
Y E S O NO 0 NOT SURE n o t h e r reasons
6. Do you investigate every variance?
a) Only unfavorable variance
b) Favorable and unt'avorable variance
c) Only unfavorable variance
7. Arc companies employing variance Ai~alysis in your understandarding more
profitable than those that do not employ it?
YESONO 0 Not Sure
8. How often are variances,investigated? I a) Montl~ly b) Quarterly
c) Annually d) Other
9. Do you use control models to set limit above or below which a variance could be 1 flagged for investigation ,
10. If your answer to 9 is yes, which of the'following nlodels do you use?
a) Material significance model
b) Statistical significance model D
c) Decision model with cost / benefit of investigation I , i 11. Do you report variances to the individual concerned and hold him responsible ! 12. Do you report all variances to the management?
a) Only adverse variance 71
b) All vasiances D
c) Not Sure a 13. How does management take action on reported variance?
a) Very s e r i o ~ ~ s and through EIIl
b) Does not take action 0
c) Not applicable D
14. From your knowledge of analysis and investigation of variance, what has been
the cause of variance in your company?
a) Poor standal-ds set I 1
b) Idle time E I
c) Inefficiency by workers 0
d) Infection D
e) All theabove 1-1
15. At the end of the accounting period, do you write off all the variance to the
profit and loss acco~mt?
Yes[-] No -1 otller colnlnent: ..............................................
-
16. I-Iow often are set standard revised?
(a) Annually- (b) Twice a year 1-1
(c) Quarterly 1-1 (d) at interval of more than one year. -1
17. Do you take human factor into consideration in the revision of your standard?
19. What was the time you last reviscd the present standard: .......................... I I
20. Do you set new standard based on the present actual results achieved and also 1 take inflation into consideration. Y e s l l N o -1 2 1 . Do companies employing variance analysis have better cost control than those
that do not employ it? .
Appendix 11
The X2 Distribution Table
Probability level O h
