White Paper - The Business Case For Business Intelligence

Data Management & Warehousing

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

White Paper - The Business Case for Business Intelligence

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

© 2009 Data Management & Warehousing Page 2


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
1 2
warehouse and provide a business intelligence solution.

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
3
invest, that this is a fundamental core competency that you have to have.”

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




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
4
outcome.

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
5
dimensions the facts are just a meaningless set of numbers.

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
6
checkpoint. A flow cannot be directly measured – 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
7
financial, environmental/ethical, anti-discrimination, certification authorities, etc

• 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
8
consumption using smart meters.

• 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”
9
There is no silver bullet 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
10
them react to the state of business in days, not months.”

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:




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


White Paper - The Business Case For Business Intelligence

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (19)

Similar to White Paper - The Business Case For Business Intelligence

Similar to White Paper - The Business Case For Business Intelligence (20)

More from David Walker

More from David Walker (20)

Recently uploaded

Recently uploaded (20)

White Paper - The Business Case For Business Intelligence