white paper - the business case for business intelligence

WHITE PAPER

The Business Case for Business Intelligence

DAVID M WALKER

Version: 1.0

Date: 30/01/2010

Data Management & Warehousing

138 Finchampstead Road, Wokingham, Berkshire, RG41 2NU, United Kingdom

http://www.datamgmt.com

Data Management & Warehousing

White Paper - The Business Case for Business Intelligence

© 2009 Data Management & Warehousing

Table of Contents Table of Contents ...................................................................................................................... 2 Synopsis .................................................................................................................................... 3 Intended Audience .................................................................................................................... 3 About Data Management & Warehousing................................................................................. 3 Introduction................................................................................................................................ 4 Why business process and business intelligence are interlinked.............................................. 5 The Primary Drivers .................................................................................................................. 7

Measurement and management of the business process .................................................... 7 Analysis of why things change in the business in order to react better in the future............. 7 Providing information for stakeholders.................................................................................. 8

The Secondary Drivers.............................................................................................................. 9 Improved Business Process.................................................................................................. 9 Improved Master Data Management (MDM)......................................................................... 9 Improved Data Quality .......................................................................................................... 9 Reduction In Operational Reporting Overhead ..................................................................... 9 Better Change Management ................................................................................................. 9 A Route To Systems Rationalisation................................................................................... 10

Anti-Drivers.............................................................................................................................. 10 “Our Competitor has one” ................................................................................................... 10 “Such and such technology can provide us with BI” ........................................................... 10 “There is some budget left over” ......................................................................................... 10 “We’ve failed before so we are trying again”....................................................................... 11 “We want to fix the data” ..................................................................................................... 11

Summary ................................................................................................................................. 12 Copyright ................................................................................................................................. 12



Synopsis This white paper looks at the business case that should lie behind the decision to build a data warehouse and provide a business intelligence solution. There are three primary drivers for making the investment in a business intelligence solution

1. Measurement and management of the business process

2. Analysis of why things change in the business in order to react better in the future

3. Providing information for stakeholders As a consequence of the investment there will also be a number of secondary benefits that will help to justify the investment and these are also discussed. Finally there are a number of ‘anti-drivers’ – reasons for not embarking on a business intelligence programme.

Intended Audience Reader Recommended Reading Executive Entire Document Business Users Entire Document IT Management Entire Document IT Strategy Entire Document IT Project Management Entire Document IT Developers Entire Document

About Data Management & Warehousing Data Management & Warehousing is a specialist consultancy in data warehousing, based in Wokingham, Berkshire in the United Kingdom. Founded in 1995 by David M Walker, our consultants have worked for major corporations around the world including the US, Europe, Africa and the Middle East. Our clients are invariably large organisations with a pressing need for business intelligence. We have worked in many industry sectors but have specialists in Telco’s, manufacturing, retail, financial and transport as well as technical expertise in many of the leading technologies. For further information visit our website at: http://www.datamgmt.com



Introduction

This white paper looks at the business case that should lie behind the decision to build a data warehouse1 and provide a business intelligence solution.2 Most businesses will describe information as a critical asset and therefore having the ability to exploit that information to the benefit of the organisation should be a fundamental capability. The value of the Business Intelligence solution is hard to quantify:

“Clearly valuing BI is not an exact science and often comes down to mindset. Comparing BI to a college education: It may be expensive and time-consuming, but there are many less tangible benefits, like increased earning power and overall improved quality of life, which come years later. It's not easy to persuade someone to go to college based on a purely financial or numbers game, and the same thing goes for Business Intelligence. You just have to believe that Business Intelligence is absolutely essential for you as an organization to invest, that this is a fundamental core competency that you have to have.”3

There are, however, three primary drivers for making the investment in a business intelligence solution



3. Providing information for stakeholders As a consequence of the investment there will also be a number of secondary benefits that will help to justify the investment but these should not be an end in themselves. The purpose of this white paper is to describe the primary reasons for making the investment and to look at some of the secondary benefits in order to help business users articulate why their organisation should make such an investment.

1 A Data Warehouse (DWH) is a repository of an organization's electronically stored data. Data warehouses are designed to specifically facilitate reporting and analysis 2 A Business Intelligence (BI) solution is the set of skills, processes, technologies, applications and practices used to support decision-making within an organisation. 3 Bill Hostmann, Vice President & Analyst, Gartner, March 2008, SearchDataManagement.com - Business intelligence ROI: value a matter of mind over money



Why business process and business intelligence are interlinked Business processes drive all organisations. These business processes are a collection of related, structured activities or tasks designed to deliver a specific goal or objective for the business. Depending on the organisation these business processes may be more or less formal in the way that they are documented, disseminated and executed. Larger businesses normally have a more structured approach to business processes but these can also become beset with inefficiencies. Business processes are the tool that allows the division of labour within an organisation, i.e. the distribution of tasks between a number of individuals whose work contribute to a single outcome.4 There are three types of business processes:

1. Management processes The processes that govern the operation of a system. Typical management processes include "Corporate Governance" and "Strategic Management".

2. Operational processes The processes that constitute the core business and create the primary value stream. Typical operational processes are “Purchasing”, “Manufacturing”, “Marketing” and “Sales”.

3. Supporting processes The processes that support the core processes. Typical supporting processes are “Accounting”, “Recruitment” and “Technical Support”.

Business processes can be broken down into two different elements:

Checkpoints This is a place where something can be directly measured – often called a fact. The number and value of sales, the amount of stock on the shelf, the number of staff employed, the visitors to a website, etc. are all common examples of facts. Information at a checkpoint can be examined in a number of different ways (sliced and diced) depending on the associated information. For example if we know the date when stock was measured and the product name and product group of an individual item then it is possible to analyse stock levels by date and product group. This associated information is usually called the ‘dimensions’ of the data. Without the dimensions the facts are just a meaningless set of numbers.5

4 Adam Smith, author of ‘The Wealth Of Nations’ and considered to be the father of modern economics identified the importance of business process as early as 1776 in his famous example of the pin factory. 5 Consider a website visitor counter that says a site has had a number visitors, without knowing when the counter was started it is impossible to know whether this is a good figure or a poor figure. Without knowing the count for each day it is impossible to know whether traffic to the site is growing or falling off, etc.



Flows A flow is what moves things from one checkpoint to another. For example the number of quotes that are created is one checkpoint, the number of sales is another checkpoint. A flow cannot be directly measured6 – we don’t know explicitly why any specific individual chose to buy at that precise point, instead it is subject of analysis – looking for the common characteristics of the individuals that obtained a quote and subsequently made a purchase (or the common characteristics of those that did not make a purchase). The objective of the analysis is to improve the flow in such a way as to benefit the organisation, in this example to promote more sales. Analysis tends to be particularly interested in how things change over time. Do some groups of individuals purchase sooner after obtaining a quotation that other groups and if so what are the common characteristics of those that behave in this way.

In a simple manufacturing process a number of components are combined to make a number of different widgets. The widgets are then combined to make a number of products.

Here it is possible to determine the productivity of an individual assembler (i.e. how many widgets does each assembler make each day) from the checkpoint. It is also possible to analyse wastage in the flow between the component and widget as long as we know the expected number of components used based the number of widgets created and the actual usage of components. We may further understand whether that wastage is a consequence of using a particular supplier. Having gained understanding it is then possible to take remedial actions outside the business intelligence solution to improve the process. Once these actions have been taken it is then possible to repeat the measurement and analysis to determine whether the actions taken have had a beneficial or detrimental effect and once again respond Without this virtuous circle the value of any data warehouse and business intelligence solution is greatly diminished. It is only possible to measure the things at the checkpoint, and the quality of analysis across a flow is highly susceptible to the quantity and quality of the data at the checkpoints. Therefore when defining the requirement it is very important to ensure that the business processes have all the required checkpoints and that the data required at that those checkpoints is identified. This is a business responsibility – technologists should not be left to guess what data is required to satisfy the needs of the business user, they will get it wrong. The technologists do have a role in providing a usable framework for defining data and information requirements, one that allows the business to clearly articulate their requirement It should also be noted that as a result of a successful action the process may change and this would have a knock-on effect on the information requirement. The data that satisfied the original requirement may no longer be enough or even relevant and new data may be required at the checkpoint.

6 It is often possible to break down a process even further and then additional checkpoints and smaller flows can be added to help create a better understanding.



The Primary Drivers Having described the relationship between business process and business intelligence it is now possible to describe the primary drivers for building a business intelligence solution.

Measurement and management of the business process

The first and most obvious driver is the measurement and management of the business process. This is the reporting of data at the checkpoints in the business process. These are often called ‘Performance Indicators’ or ‘Key Performance Indicators’ (KPI) and are a measure of performance of the organisation. Such measures are commonly used to help an organization define and evaluate how successful it is, typically in terms of making progress towards its long-term organizational goals. These measurements will also appear as reports and documents such as ‘Management Reporting Packs’. It should not be assumed however that such performance indicators and reporting packs are for senior management only. The success of providing information is in ensuring that individuals involved in the process know how they are doing. It is of little value to the organisation if the CEO knows the total number of calls answered in a call centre but the call centre manager does not know who his most and least effective operators are. Since most organisations have high-level business processes that get progressively broken down into sub-processes and ultimately to individual job-functions it is possible to identify key business processes and follow these down to the lowest level checkpoints. Taking the information that is available at this lowest process level and aggregating it appropriately at each process level often provides the clearest set of measurement requirements and if there is not an existing capability to deliver this information this in turn provides the justification for building the solution. Despite the ability to specify requirements for all aspects of the business relatively quickly it will probably not be possible for IT to build an all-encompassing solution in one go. Therefore it is also possible to use the business processes to identify those aspects that should be prioritised. Critical business processes without measurement data will be the priority. Senior management have to agree on priorities and where investment can be most effective in order to prioritise the requirements.

Analysis of why things change in the business in order to react better in the future

The second driver is the desire to understand why things happen in the business process and to take actions in order to improve them. By definition this requires information from checkpoints at either end of a process and preferably from intermediate checkpoints within the process. The finer the levels of detail at each checkpoint the more likely the causes and effects of the process changes are to be identified. It is also possible that a lack of fine detail will result in false positives – results that appear to indicate the incorrect cause because insufficient information is available. It is therefore important that analysis work results in three things:

1. Validation of the results – how does the analyst validate that the effect they are seeing has the determined cause and is there a way to independently verify this?



2. Taking actions – if something is not performing within a business process then something needs to change. The business users need to be empowered to make changes to processes to improve the situation.

3. Monitoring outcomes – some actions will not have the desired effect, some will have a disproportional positive/negative effect and some will have unexpected consequences. The business must be ready, in information terms, to monitor the outcome of the change and once again react to the consequences.

Effective analysis is a reflection of a mature measurement capability and the ability of the business to undertake change in the business processes. The largest part of the return on investment for developing a business intelligence solution comes from good analysis however this has to be built on solid foundations of process measurement. Data mining is the extension of this activity to look across multiple flows to better understand the underlying trends within the information.

Providing information for stakeholders

The third primary driver is in the delivery of information for stakeholders. In many ways this is the same as the first driver except that the information is being delivered to individuals and organisations outside the process itself. Stakeholders come in many guises:

• Shareholders The owners of the business, who, whilst they will have no direct involvement in the day to day processes have a financial interest in the success of the company.

• Regulators Many organisations are now subject to some form of regulatory control and have to be able to demonstrate compliance. Common examples will include financial, environmental/ethical, anti-discrimination, certification authorities, etc7

• Customers and Consumers Customers are becoming increasingly important stakeholders, especially where products include some form of behaviour modification incentive (i.e. collect points over a period of time and get bonus points if you then visit a shop on a specific date). There are also a growing number of examples for energy consumption using smart meters.8

• Suppliers Suppliers are also becoming engaged in using corporate information. For example a manufacturer may be given sales information broken down by various dimensions by a retail organisation and various companies now enter aggregator/associate deals that provide additional revenue streams and a two way data exchange between companies

These stakeholders and others like them have become important business intelligence users in the extended and virtual business models.

7 Anti-discrimination legislation: http://en.wikipedia.org/wiki/List_of_anti-discrimination_act 8 Smart Meter usage: http://en.wikipedia.org/wiki/Smart_meter



The Secondary Drivers The primary drivers above describe the reasons why the business should invest in business intelligence. However as a result of making the investment there are secondary benefits that add to the return on investment. It would be unusual for these secondary drivers to provide the main motivation for developing a system. Some examples of secondary drivers include:

Improved Business Process

The primary driver of analysis has an objective of incrementally improving business processes. However the opportunity to improve business processes starts with the development of a data warehouse. One of the first stages in the development is to analyse systems as potential sources for data. This often throws up gaps or overlaps in the information available from the source systems. The gaps highlight weaknesses in the processes whilst the overlaps highlight duplication in the business process. A good business intelligence delivery process will be able to highlight these shortcomings and work with the business to fill the gaps and remove the duplication.

Improved Master Data Management (MDM)

In order to be able to generate reports and ‘slice and dice’ information all the reference data hierarchies associated with individual transactional data points have to be determined. Master Data Management has the objective of providing processes for collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure consistency and control in the ongoing maintenance and application use of this information. Weaknesses in the management of master data will be highlighted by a data warehouse project and will need to be addressed

Improved Data Quality As a consequence of both the improved data processes and improved master data management combined with the visibility of information that reporting brings the business intelligence programme will identify data quality issues. It is not however sufficient to clean these in the data warehouse alone. Data Quality issues need to be addressed in the source system and the improvements will then be reflected in both the data warehouse and any other system that uses the information.

Reduction In Operational Reporting Overhead

Where data from an operational system has been enriched and included in a data warehouse solution it is possible to off-load reporting requirements from the operational system and onto the business intelligence solution. This allows appropriate reporting technology to be applied to the solution whilst removing the overhead and freeing resources on mission critical operational systems.

Better Change Management

In order to maintain a data warehouse solution there is a need to deliver good change management of the systems that provide the data to the data warehouse. These processes support the timely delivery of information to the business but also help to improve the business use of existing solutions.



A Route To Systems Rationalisation The analysis and use of data from source systems can be used to determine systems that can be retired or replaced. It is not uncommon for data from such systems to be retained in the data warehouse after the system has been de-commissioned.

The development and value of a data warehouse will be significantly hindered if the business is not prepared to invest in improving all of these aspects as part of a business intelligence solution. It is also questionable if the data warehouse can deliver against the primary drivers if these issues are not addressed. Many of the secondary drivers will deliver business benefit before the data warehouse project is complete as they fix underlying issues in the existing business processes.

Anti-Drivers Whilst this paper has addressed the reasons for creating a data warehouse or business intelligence solution there are also some very good reasons for not embarking on the journey. Some examples of these might include the following:

“Our Competitor has one” The “me too” approach to business intelligence is always destined to failure. Even if two organisations have exactly the same data sources and business intelligence solution the success and value of a data warehouse is in the business’ ability to exploit the information and adapt the organisation to meet the changing environment. This ultimately comes down to having good people within the company. In understanding that the competition is making good use of information and devising a strategy to exploit your own information more effectively it is your own strategy to exploit information that is important and not the fact that you have a data warehouse.

“Such and such technology can provide us with BI” There is no silver bullet9 to delivering information – it is a series of stepwise refinements of the way in which an organisation works that will ultimately enable the business to more effectively exploit the information available to it and consequently deliver better value to stakeholders.

“There is some budget left over” Whilst the business landscape is currently one of economic austerity it is surprising to still find organisations that find some way to make a half-hearted commitment to delivering information to the business.

“The winners that will emerge from this recession will race ahead as leaner, more efficient, more agile, and less burdened by legacy infrastructure. These companies will be bold enough to invest in IT to shrink long-term energy costs, get real-time information to their revenue generators and client support staff, get their own employees to collaborate more efficiently without the need to travel as often, and

9 Fred Brooks, The Mythical Man-Month (Anniversary Edition). "There is no single development, in either technology or management technique, which by itself promises even one order of magnitude [tenfold] improvement within a decade in productivity, in reliability, in simplicity."



most important, give their executives coordinated, correlated information that lets them react to the state of business in days, not months.”10

Addressing all of these issues requires that the organisation to be fully committed to delivering the changes associated with business intelligence.

“We’ve failed before so we are trying again”

If your organisation has been unfortunate enough to have a failed business intelligence project then it may decide to try again. But before a new project starts the business should look closely at itself to see if the factors that led to the failure last time have been addressed. Almost certainly the underlying cause of failure was a result of a lack of investment, an unwillingness to change the business or a project based on one of the anti-drivers. In all cases the project will fail again unless the underlying causes are addressed.

“We want to fix the data”

Some organisations believe that they have reporting issues because of data quality problems and that by gathering data in one place and cleaning it the situation will be resolved. This is a short-term fix that will not be sustainable and the underlying issues in the source systems will re-appear in the data warehouse and then the organisation will be left with operational system and an expensive reporting system with the same underlying problems.

10 Tony Bishop Business Execution and Recession



Summary This white paper has examined the business case that should lie behind the decision to build a data warehouse and provide a business intelligence solution. This has identified three primary drivers for making the investment:



3. Providing information for stakeholders It has also identified that delivering the solution will also deliver secondary benefits that will add to the return on investment. There are also a number of anti-drivers, reasons for not starting a project, which should be avoided when commissioning business intelligence solutions. Successful solutions require full commitment from the business users and a willingness to adapt to the changes that implementing the solution will bring. Ultimately a business intelligence solution is likely to be an expensive and time-consuming exercise that delivers essential business intelligence. There will also be many less tangible benefits such as increased earning power for the business and an overall improvement in both the operational systems and business processes as a result of work done for the data warehouse. These benefits may not be immediately understood or realised. Organisations and especially the senior management have to have the vision to understand that the investment in Business Intelligence is absolutely essential and that it is a fundamental core competency that the company has to have.

Copyright © 2010 Data Management & Warehousing. All rights reserved. Reproduction not permitted without written authorisation. References to other companies and their products use trademarks owned by the respective companies and are for reference purposes only. Some terms and definitions taken from Wikipedia

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