Creating a Successful Business Intelligence Program

How to Create a SuccessfulBusiness Intelligence Programme

Peter Dillon-Parkin Able Solutions UK Ltd

1-800-843-8733www.learningtree.ca

©2009 Learning Tree International. All Rights Reserved.

CA0904 KM WP – cvr

CA0904 BIP WP – pg1

Introduction: The Business Intelligence (BI) Paradox . . . . . . . . . .1

1. The Business Intelligence Challenge . . . . . . . . 2

2. Defining Business Intelligence Needs . . . . . . 2

2.1. What Data is Needed? . . . . . . . . . . . . . . . . . . . . . . 2

2.2. What Are the Desired Outcomes for the Business?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

3. Success Factors for Business Intelligence Initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

4. The Five Levels and Six Critical Attributes of BI Maturity. . . . . . . . . . . . . . . . . . . . . . . . . . . 3

4.1. Level 1: Informal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

4.1.1. Critical Attribute 1: Strong Executive Support . . . . . . . . . . . . . . . . . . . .4

4.1.2. Critical Attribute 2: Key Stakeholder Identification . . . . . . . . . . . .4

4.2. Level 2: Defined. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

4.2.1. Critical Attribute 3: Early Creation of a Business Intelligence Competency Center (BICC). . . . . . . . . . . . . . . . .4

4.2.2. Critical Attribute 4: Clear Outcome Identification . . . . . . . . . . . . .4

4.3. Level 3: Managed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

4.3.1. Critical Attribute 5: Tying CSFs and KPIs to Business Drivers. . . . . . . . . . . . . . .6

4.4. Level 4: Controlled. . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

4.4.1. Critical Attribute 6: Analytics Awareness . . . . . . . . . . . . . . . . . . . . . . . . . . .6

4.5. Level 5: Optimised . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

5. Driving Your BI Initiative Forward . . . . . . . . . . . . 7

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

About Learning Tree International. . . . . . . . . . . . . . . . .8

About the Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

T A B L E O F C O N T E N T S

L E A R N I N G T R E E I N T E R N A T I O N A L White Paper

Introduction: The Business Intelligence (BI) Paradox

Back in the 1980s, I recall being asked by a client—a major supermarket chain in the UK—to provide them with reorder figures for every one of their stores. At that time, I was unable to accommodate their request for two very good reasons: First, there were no tools available to me at the time that would allow me to work with the databases on the mini-mainframe I was using and, second, I couldn’t build a file big enough on the mini-mainframe, since the maximum size I could achieve was 66MB! Back then, the lack of tools meant I had to invent my own, which was quite challenging. Ultimately, the only way I could meet the customer’s requirements was to offload the data onto a PC and purchase an external 100MB disk to hold the data, along with a copy of the Paradox RDMS to analyse it.

But this example is just one of many from that time. The early business intelligence (BI) initiatives—Decision Support Services (DSS), Executive Information Systems (EIS) and Management Information Systems (MIS)—had the same mission as BI initiatives of today, which was to provide accurate answers to questions about the enterprise in a timely manner, support decision-making activities with accurate intelligence and identify actionable outcomes. And yet they all failed, banished to the dustbin of history. What’s more, they foundered primarily because they lacked the appropriate software tools and tech-nical infrastructure—the facilitating technologies—that could support the needs of the business.

Fast forward to present day: Now many households possess over a terabyte of storage distributed over various devices, making the sizing issues I faced in the ‘80s seem quaint. In addition, the technical infrastructure that underpins BI—databases, storage and front-end functionality—are now largely commoditised, meaning that any technology company that wants to assemble and bring to market a BI solution can do so. There are also many robust, reliable business intelligence tools widely available, from open source software to commercial offerings like Microsoft BI Studio, Cognos, SAP and so forth.

Furthermore, technical issues that plagued early BI initiatives have virtually disappeared to the point where a reasonably intelligent database manager can design a digital dashboard or use a PivotTable to report on data in Excel. Add to this the fact that the storage required for the denormalised databases that support BI initiatives has become quite inexpensive, and the twin problems of tools and storage have been comprehensively vanquished.

So why, you may ask, in the BI Rapid Survey Report(1) carried out by the National Computing Centre, did 21% of respondents report that their BI system did not have the data they needed? And why, according to the same report, have 87% of BI projects not lived up to expectations?

This is the business intelligence paradox that I will address in this paper along with providing strategies that will ensure the imple-mentation of a successful BI programme.

1 Business Intelligence Programme1-800-843-8733 • www.learningtree.ca©2009 Learning Tree International. All Rights Reserved.


1. The Business Intelligence Challenge

Organisations often suffer because they pay too much attention to vendors who sell BI as a cure-all for unspecified ills. In fairness, the vendor’s job is, after all, to sell as much consultancy as they can (or as much as is asked for). However, a vendor can never know our organisation the way that we do, hence the need to identify the desired outcomes of a BI initiative internally before engaging with vendors. However, this requires a common vision within the organisation as to what business intelligence actually is and what it can (or won’t) be used for.

Let’s begin by understanding some terms. A “closed-ended” tool is one that performs only one function. A cookie cutter is a good example, as there’s really only one thing we can do with it. Many organisations buy BI solutions as if they were similarly closed-ended—a “fix” for a problem that is often unstated. Their opposite—“open-ended” tools—are more flexible. They are like a saw, which can cut trees but can also be used to make furniture, build a house or even be played as an instrument.

Treating BI solutions as closed-ended tools leads to impreci-sion about what we want BI for. BI is an open-ended tool that requires the definition of needs and objectives before we buy into a solution. And be aware: if the guy we’ve put in charge of doing that assessment works for the business that sells a solution, I believe you can guess with some degree of certainty which solution we’re going to get.

In short, early on in the process of selecting a BI solution, we need to analyse the usefulness of BI to our organisation and what outcomes we expect from our investment.

2. Defining Business Intelligence Needs

So what must be considered first? The perceptive manager needs to ask questions about BI:

• WhatisthedesiredoutcomefromaBIsolution?

• Havewepresentedastrongenoughbusinesscase in support of the BI solution?

• Whodoweneedtotalktowithintheorganisation?Outside the organisation?

• Shouldweattackstrategicortacticalproblemsfirst?

• Whatproblemshouldwestartwith?

• Istherea“minimumoption”whereweget80%of the benefit for 20% of the investment?

• Whatdataisneeded?

• Whatarethedesiredbusinessoutcomes?

• Afterallthis…doweneedBIatall?

As these questions are being addressed, it’s critical to start building a cross-discipline team in the areas of business analysis, project management, IT and the wider business community as their involvement will be crucial to the process.

2.1. What Data is Needed?

BI consists of both enabling and facilitating technologies. Enabling technologies are technologies that generate the data that BI “consumes”. Examples of enabling technologies are:

• EnterpriseResourcePlanning(ERP)

Applications used by large organisations to manage inventory, resources and business processes across all departments in the enterprise.

• ElectronicPoint-Of-Sale(EPOS)

Systems that streamline stock control and ordering systems through bar-code scanning and allow the automatic processing of credit card payments for goods.

• RadioFrequencyIDentification(RFID)tagging

Inventory data stored on a tag transmitted via radio. Often used to track buying habits, this technology is leading to an explosion in the sheer volume of data due to the possibility of all tags being unique rather than generic.

Businesses often focus solely on these types of enabling technology to provide data for their BI initiatives. This data is both structured and internal to our business—in short, the data we already have easy access to. Many organisations only analyse structured and internal data. But there are other types of data, too. For example, unstructured data refers to data we have access to but haven’t systematised, such as e-mails, project plans and the information stored away in filing cabinets. On the other hand, external data refers to data we don’t possess but need to know about, like competitor information, published comments and share-price graphs.

According to IDC/Teradata (2), 55% of the information that decision makers currently deal with for decision making is unstructured and external. This is why users of BI systems complain about “missing data”. Alastair Sim of SAS puts it best: “Organisations are not using BI to drive the decision making that will allow them to grow and innovate because they are not seeing structured and unstructured data as a single source”.

2©2009 Learning Tree International. All Rights Reserved.

Business Intelligence Programme

1-800-843-8733 • www.learningtree.ca L E A R N I N G T R E E I N T E R N A T I O N A L White Paper


2.2. What Are the Desired Outcomes for the Business?

Early in any BI initiative, the BI Manager needs to consider what the desired outcomes of the business are. In practice, there are two approaches to achieving desired outcomes:

• Tactical

Looks at a specific organisational business problem and uses BI to find a solution

Expects both costs and benefits to be short term

Example: A tactical goal for a bicycle manufacturer would be to reduce the amount of rework on the assembly line

• Strategic

Supports the long-term business-oriented aims and objectives of the organisation

Expects the costs of those long-term benefits to be spread out over time

Example: A strategic goal for a retail business would be to maintain and then increase the proportion of sales they get via the Internet

For new BI initiatives a tactical approach is recommended. It’s considerably easier to justify, will give a quicker payback and, best of all, does not exclude a simultaneous long-term strategic approach. Obviously, the best value for the company is in strategic BI, but it’s harder to get money for that and harder still to demonstrate that the organisation is getting its money’s worth. Fortunately, most tactical BI projects lead to the strategic ones, and the data accumulated while fulfilling several tactical outcomes is reusable for analysis in a strategic approach.

3. Success Factors for Business Intelligence Initiatives

To be successful, individuals involved in a BI initiative should ideally possess skills in several areas. Skills including, among others, project management, communication and data analysis. Even if we are pursuing tactical success, we need to think strategically about managing BI. In essence, the organisation is radically changing how data is accessed by taking its exclusivity out of the hands of experts and giving free access to it based on the needs of the business.

To some, this is sacrilege, but bear in mind, that a “data only in the hands of the few” approach, coupled with the less

potent technology of the past, are the key reasons that the previous attempts at BI mentioned in our introduction failed. Instead, the notion of BI as a tool needs to be weaved into the fabric of the organisation if it is to be successful. Man-agers should forget that they are using a “revolutionary technology”—or whatever buzzwords are currently in favour—and use BI in the same instinctive way that they now use Excel or PowerPoint.

Unless this happens, the end of the process will have each department or manager owning individual spreadsheets or databases, none of which gives a “single version of the truth”. In today’s terminology, this is often referred to as the “Balkanization” of data.

4. The Five Levels and Six Critical Attributes of BI Maturity

The first thing we should do before proposing to implement BI is to take a hard look at where we currently stand. After all, it’s hard to create a plan to move forward unless we know where we’re starting from. As a solution, we can identify what planning and skills we need to improve or implement a BI solution by modeling its levels of maturity.

The chart below shows a model of Business Intelligence Maturity Levels. Looking at each level, it becomes clear that some decisions have a greater influence on our success than others. Ideally, we want to graduate to the next level as quickly as possible, so the key attributes that must be achieved in each to move forward are identified here.

Level 1

Level 1Informal

Level 3Managed

Level 5Optimised

Level 4Controlled

Level 2Defined

BI

Mat

urit

y

Time

Business Intelligence Maturity Levels





4.1. Level 1: Informal

At this level, there is no official business intelligence policy within the organisation, and BI is implemented through spreadsheets, Access databases and similar tools. Data gathering is done independently, not shared properly, and there is no company-wide awareness of BI. The BI that exists is at departmental or even individual levels (Balkanization of data), which means it may occupy quite a lot of company time (money) without producing maximum returns, resulting in comparatively little return on investment (ROI).

4.1.1. Critical Attribute 1: Strong Executive Support

There has to be strong executive support for BI. Any lack of enthusiasm at the top will filter downwards. The problem with effecting any change in an organisation is simple: employees, given a choice between doing what they are told to do—or imitating their superiors—will always do the latter.

A key component of obtaining strong executive support is a convincing and detailed business case for BI. Letting executive management know the advantages to the organisation and themselves is crucial to getting them on board with the solution. The reason organisations find themselves at Level 1 is generally because of a lack of executive support.

4.1.2. Critical Attribute 2: Key Stakeholder Identification

Early identification and prioritisation of the key stakeholders is crucial. After all, if we don’t know who will benefit from a BI solution, it is unlikely that we can persuade anyone that it is in their best interest to support our initiative. Likewise, if we don’t know who is opposed to our initiative (and why), we will have problems developing convincing counter- arguments. Lastly, if we don’t know who will be impacted by it, we will have difficulty determining the key outcomes that our initiative needs.

4.2. Level 2: Defined

At Level 2, the organisation has usually gone ahead with an “IT-only solution”, often using internal transactional data only. There is generally an improved and focused custom reporting function, but BI functionality may not be used by many employees due to a lack of awareness or a belief that it is too technical and time consuming. Users often choose to stick with their spreadsheet- or database-driven analyses. This level is problematic: money has been spent with little

advantage gained, leading to a negative ROI. At worst, this initial lack of results may lead an organisation to become sceptical as to the ultimate benefits of the BI solution, which can easily lead to a self-fulfilling prophecy of disappointment.

4.2.1. Critical Attribute 3: Early Creation of a Business Intelligence Competency Center (BICC)

Many organisations identify a BI need, assign a project team to fill that need, and upon completion of the task, reassign the team to non-BI projects. Knowledge gained is therefore lost. By retaining a permanent, knowledgeable team, an organisation can:

• Maximisetheefficiency,deploymentandqualityof BI across all lines of business

• Delivermorevalueatlesscostandinlesstimethroughmore successful BI deployments

• Proactivelydriveend-useradoption

Business Intelligence is an accelerant for change in an organisation. If change is not managed, it becomes disruptive and negatively effects productivity. The BICC helps manage change by helping an organisation become one that learns from its mistakes and remembers what was done, why it was successful or unsuccessful, and reuses the successful strate-gies while discarding the unsuccessful ones.

BICCs help promote information democracy, making sure that all workers can access the information that will empower them to do a better job, and creating synergy among people, processes and technology. Ideally, BICCs should be permanent departments in all organisations and can even be staffed by employees as a secondary, part-time responsibility, separate from their primary jobs within the company.

4.2.2. Critical Attribute 4: Clear Outcome Identification

Outcome identification—what outcome(s) the organisation desires, and whether they are tactical or strategic—flows out of stakeholder identification and determines:

• Knowledge—whatknowledgeisneededfordesiredoutcomes and where is it?

• Information—whatinformationstructurescanbe identified from knowledge gathering and how can these same structures be beneficial?

• Data—whatsourcesofrawdataareneededto populate the information structures?





Pursuing the answers to these questions requires both logic and creativity. We also need specific information at various steps in the BI process. Looking at the generic BI road map (Figure 1), we can see that the Justify section requires some answers from our stakeholders.

One approach that can be used to extract answers from stakeholders is to use a Business Intelligence Meta Model (Figure 2) to facilitate brainstorming from Outcomes and Insights through Data.

Justify Plan Analyse Design Build Deploy

IdentifyDesired

Outcomes

EvaluateTransactional

Data

DefineDetailed

Requirements

Database Design

Write Business

Case

ProjectInitiationProposal

Applications Implement

ETL Evaluate

MetadataRepository

Analyse Dataand Metadata

MetadataRepository

Design

Data Mining

PrototypeDeliverables ETL Design

The figure above shows the Meta Model for the Justification aspect of a BI road map, showing the types of questions you would ask within each section. Using the BI Meta Model (BIMM) enables us to focus on what is needed to define our BI programme; the data, the right level of data, and so forth. It’s important to understand, however, that the BIMM is less about giving you the “right” answers straightaway, but more about helping you arrive at them sooner.

Figure 1: Generic BI Road Map

Figure 2: BI Meta Model with Brainstorming Questions Used to Justify a BI Initiative

Outcomes and Insights Knowledge Acquisition

Data Information and Structure

Where will we find informationabout the proposed outcomes?

Has anyone else done this?If so:How did they do it?Were they successful?

What data do we need to measure in order to establish:

Whether the proposed change is justified?Whether the benefits have been delivered?

Is the proposed change an:

Improvement?

Optimisation?

What are the high-levelbusiness requirements?

Is it a:Business Case?Feasibility Study?





4.3. Level 3: Managed

At Level 3, the basic project management of BI is in place within an organisation, usually in the form of a Business Intelligence Competency Centre (BICC)—a coalition of business, IT, and project personnel. Even so, poor BI leadership can be an issue at this level, mostly due to managers and users still resistant to the idea of BI, resulting in a lack of enterprise-wide acceptance. This situation can lead to isolated ROI gains within those departments where the BI in place is accepted, but not across the organisation. Furthermore, critical success factors (CSFs) are recognised and identified, but they may not match Key Performance Indicators (KPIs) which may be determined by instinct rather than derived from actual business drivers.

4.3.1. Critical Attribute 5: Tying CSFs and KPIs to Business Drivers

Many business initiatives aim to obtain benefits—greater efficiency, better morale, quicker access to information— that are hard to quantify. We can easily accept that “greater efficiency” is a good thing, but trying to quantify its precise cash value to the organisation can be a challenge. These benefits are essentially intangible but need to be measured. Understanding what drives the organisation is a key com-ponent of many methodologies (the Balanced Scorecard, to name one) because it recognises that the success of those intangible elements of the organisation—customer responsiveness, staff training, leanness—are critical to the financial success of an organisation.

Therefore, when identifying these key values, they can be classified as “driving” strategy, organisation or operations:

Strategic Drivers influence:

• Marketattractiveness

• Growth,concentration,innovation,customerpower

• Competitivestrengths

• Marketshare,quality,intellectualproperty

Organisational Drivers influence:

• Culture

• Leanness

• Traininganddevelopment

Operational Drivers influence:

• Customersatisfaction

• Productexcellence

• Productivity

When we clearly identify these drivers, critical success factors can also be established for them, and in turn, key performance indicators for each CSF. These may be qualita-tive rather than quantitative, but appropriately measuring intangible benefits is better than inventing a cash value and being surprised when it does not materialise.

4.4. Level 4: Controlled

The key difference between Level 4 and previous levels is strong business sponsorship. Usually, a BI “champion” has initiated enterprise-wide selling of BI to the organisation through the establishment of a BICC. The BICC can then take the ongoing role of proactively selling and project managing BI across the enterprise. The BICC plans and introduces change management programmes to deal with the business transformation that BI will engender.

Key business drivers are identified and documented and used to identify both CSFs and meaningful KPIs. A programme to capture external and unstructured data is started, both to provide the right information for decision makers and to integrate the organisation’s Balkanized information. At this point, the organisation will often start to use analytics/data mining on transactional internal data to look for patterns of use that can bring about efficiency improvements and enterprise-wide gains in ROI.

4.4.1. Critical Attribute 6: Analytics Awareness

As stated above, organisations have a tendency to measure what is easy to measure—internal transactional data. Extending the sensitivity of the organisation to external and non-transactional data presents a fuller picture to decision makers of both the organisation and the competitive envi-ronment. It is also the start of continuous improvement for the organisation. If measures are appropriate, the organisa-tion can start to improve the processes. More importantly, the measures can be refined by examining what else might impact them, and the organisation can refine existing KPIs and create new CSFs that would never have been spotted without the ability to analyse large volumes of data.





4.5. Level 5: Optimised

At Level 5, there is company-wide acceptance of BI, which is treated as one of a range of tools for managing information within the organisation, just like Word or Excel. The BICC-managed BI programme allows individual users and departments to participate in the continuous improvement of BI tools and solutions. The key business drivers, CSFs and KPIs, are refined using analytics data, and external and unstructured data are integrated into the BI solution. Analytics and data mining yields are fed back into a company-wide knowledge management process, and there are enterprise-wide gains in ROI and cost savings due to optimising BI processes.

5. Driving Your BI Initiative Forward

The BI Maturity Levels Model

Determine the level of your organisation. Be honest: There is no shame in being at Level 1 of the model, but be aware that it is risky to invest heavily in technology and consultancy without a clear idea of what the likely workload for your organisation will be.

Strategic or Tactical BI?

Identify your desired outcomes and categorise them. This way you can tell if tactical outcomes are on track, and there won’t be the temptation to guarantee short- term justification for a long-term strategic outcome.

The Six Critical Attributes

Which of the Six Critical Attributes of BI Solutions are in place? Determining this will do more to ensure the success of a BI solution than any other action by moving the organisation up the BI maturity levels and helping to identify whether the initial approach to BI should be strategic or tactical.

References

1 www.ncc.co.uk/aboutncc/press_rel/Business_Intelligence_ Implementations_fail_to_meet_objectives.cfm

2 “Taming Information Chaos”, IDC/Teradata White Paper: ww.teradata.com/t/page/175052/index.html





About Learning Tree International

Learning Tree International is a leading worldwide provider of vendor-independent training to managers and IT professionals in business and government organisations. Since 1974, over 1,900,000 course participants from over 65,000 organisations worldwide have enhanced their skills and extended their knowledge under the guidance of expert instructors with real- world experience. Learning Tree develops, markets and delivers a broad, proprietary library of instructor-led courses focused on the latest information technologies, management practices and key business skills.

Learning Tree International annually trains over 94,000 professionals in its Education Centres around the world. Learning Tree also provides training in a number of additional cities and on site at customer locations in 43 countries. For more information about Learning Tree products and services, please call 1-800-843-8733, or visit our Web site at www.learningtree.ca

About the Author

Peter Dillon-ParkinBusiness AnalystABLE Solutions UK [email protected]

Peter Dillon-Parkin is a Business Analyst, writer and instructor who founded ABLE Solutions UK Ltd to provide training and consultancy for public and private sector organisations.

Peter has worked in the software, banking and media industries,aswellasprovidedtrainingforNGOs and the military. He is a published author, and his forthcoming book, “Business Intelligence: Smarter Not Harder”, will be published at the end of 2009.

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Creating a Successful Business Intelligence Program