As this is my first column, I felt that it would be best to explore (and challenge) the definition of the business intelligence (BI) area.

BI is certainly under stress, primarily caused by its success in many facets of enterprise systems. In particular, e-commerce applications in customer relationship management (CRM), sales force automation (SFA) and supply chain automation (SCA) have benefitted greatly from BI technology borrowed from the generic vendors.

Is this the future of BI? Is BI to be fragmented into little pieces and embedded in packaged applications ­ never to be seen again by IT eyes? Does this situation echo the debate between the enterprise warehouse and independent data marts?

One point is clear. BI is an essential component and even an architectural principle for any viable enterprise system today. However, it is not clear how the market dynamics for BI will unfold over the coming years. This market instability creates a huge uncertainty within IT groups for planning and implementing enterprise systems.

Most agree that the general objective of BI is to make businesses perform smarter and, therefore, better. However, there is little agreement about the details behind that objective.

Consider the following two approaches for defining BI ­ little BI and big BI:

Little BI (a.k.a. bottom-up BI) focuses on means ­ the traditional set of methods and technologies to support data warehousing and analytical processing, such as ETL, star schemas, multidimensional analysis and data mining. This set has extended into text mining, enterprise information portals and collaborative systems.

Big BI (a.k.a. top-down BI) focuses on ends ­ the objective of enabling smarter businesses. In other words, big BI focuses on adapting and creating business processes that react swiftly to changes in the business environment. This approach frees us to apply whatever methods and technologies may be appropriate to meet this objective.

Until now, little BI and big BI have been essentially the same. The methods and technologies matched the objective.

The combination has served us well but is aging poorly at its ripe age of fifteen years. Packaged analytics, real-time closed-loop, clickstream processing, knowledge management, customer intelligence and related trends have deformed little BI beyond recognition. Moreover, the e-commerce imperative has
driven the marketplace in diverging directions with:

  • Smart horizontal applications, such as customer relationship management;
  • Innovative vertical solutions, as in telecommunications and healthcare; and
  • Advanced technologies, such as knowledge management and text mining.

To return to basics, consider a familiar pyramid of data, information and knowledge (see Figure 1). Data becomes information when it changes our decision making. Information becomes knowledge when it changes our business processes. In other words, knowledge provides the basis for reprogramming or redesigning our business.

Figure 1: Data/Information/Knowledge Pyramid

The process of refining data into information is business operations ­ controlling existing business processes so that they provide the appropriate goods and services to customers, efficiently and reliably. In contrast, the processing of refining information into knowledge is business intelligence ­ modifying existing processes and creating new processes to enhance the competitiveness of the enterprise.

Many have compared BI to the instrument panel on an aircraft. It tells us where we have been and where we are going. It is very essential. To fly without an instrument panel is not wise!

The definition of big BI includes an additional aspect. It is as if our instrument panel includes a CAD- CAM function so that we can redesign the aircraft during the flight. If we hit turbulence, we redesign the wings to cope with that turbulence.

The analogy may seem silly for aircraft. However, when we apply the analogy to businesses, it becomes very appropriate. In today's economy, businesses must redesign themselves while in flight. The main objective of big BI is to enable businesses to do just that.

It is time for little BI to fade into the history books and for big BI to become center stage. BI should now be focused on the continuous transformation of business processes so that business can adapt to changes in customer demands and market opportunities. In other words, if BI is not changing the way you do business, then it is not BI.

Writing in England at the moment, it seems appropriate to assert, "BI is dead; long live BI!"

EMA's Take-Away

  • Put BI back into the enterprise architecture as an explicit component.
  • Design BI into the enterprise architecture from the beginning, instead of treating BI as an afterthought.
  • Do not bury BI in packaged applications, causing incompatibilities among data and processes.
  • Be careful of vendor lock- in with BI products and services. Insist that your BI vendor adopt an open architecture that integrates well across your enterprise system.

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