I really have never understood the purpose of buying a garment where one size is intended to fit all people. It seems that one size does not fit all very effectively. The garment usually fits only a few people well; on the rest, it looks either too baggy or too tight.

The same holds true with business intelligence (BI) tools. We say, "All we need is this one query tool. It should do the trick for our data warehouse or data mart users." Yet, in reality, we have many sizes and shapes of data warehouse or mart users. And there is a significant disparity in the range of activities, skills and knowledge among information users. There are also different tools available to tackle different functions or activities. Most people would not use spreadsheet software to write a novel. Nor would they use a query tool to predict response rates on a marketing campaign. The trick is to realize that BI is for business people with differing activities and abilities, determine the range of business activities that people need to perform and figure out a suite of business intelligence tools that will do the jobs at hand.

Sounds easy, right? Not necessarily! We continue to frustrate casual users by making them learn complex statistical programming languages to perform basic queries, and we make statisticians try to stretch the capabilities of basic query tools to perform sophisticated functions. The people that fit somewhere in between are also frustrated, complaining about problems with data access and an inability to get the information they need. Many times we think the problem lies with the data ­ we don't have the right data available or it's too difficult to navigate. That may be true in part, but a major culprit is the lack of a framework for categorizing business people by what they do and how they do it, and for applying the right tool for the job.

A framework should start with analyzing the various business intelligence communities that exist within your company. Check out the poster at www.dmreview.com/posters/msbic/ (first published in the July/August, 1999 issue of DM Review) for an explanation of the five basic communities ­ tourists, operators, farmers, explorers and miners. Identifying the communities that apply to your organization is a good start. The next step involves understanding what a target user profile for each community might look like. What is the best way to develop these user profiles? Survey the users themselves!

Examples of what should go into the user profile for each community are as follows:

Business roles that exemplify the type of community (could be actual job titles or functions)

Business activities performed (establish baselines of expected performance, assess patterns or trends to reduce expenses, reward employee performance, etc.)

Information analysis activities performed (frequent review of lightly summarized data, limited conditioning of data, code and structure queries, predict, forecast and estimate, etc.)

Business deliverables as a result of activities performed (process correcting transactions, recommend changes in policy or procedure, provide business forecasts, etc.)

Business/information skills required for this community type (ability to analyze and interpret performance, expert knowledge of data content, etc.)

Technical skills/training required (minimal database knowledge, proficient usage of programming or query languages, etc.)

In addition to the community target user profiles, target information environment profiles can also be helpful. A target information environment profile for each community would answer the following questions:

  • Which components of the corporate information factory are accessed (operational data store, data mart, data warehouse, exploration warehouse, etc.)?
  • How do users interact with data? (How much history is required? What frequency of update? Is dimensional, aggregated data needed? What about a specialized, integrated view of data? Are query templates used?)
  • What methods of analysis are used (paper reports, graphs, online reports, OLAP, limited drill down, etc.)?
  • How do users interact with tools to access information (browser/thin client preferred, toolset that integrates with desktop tools, content and response times expected, etc.)?
  • What tools are recommended?

Once users have been grouped by their distinct characteristics and requirements, focused strategies can be developed that will identify appropriate data structures for access, determine appropriate access tools and user interfaces and provide required training.
There is a choice to be made involving business intelligence tool deployment within your organization. Users can obtain that one-size-fits-all query tool and hope that it's their size and will meet their needs for the distinct business activities they perform. Or you can build a framework for deciding which users need which tools by analyzing specific needs by the type of community to which the users belong. The former can yield results that feel too baggy or too tight. The latter has a chance at getting a right fit for more individuals. It's your choice!

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