What Decision Support Tools are Used For

In the section on the "dirty little secrets of data warehousing" in her fascinating book "e-Data", Jill Dyché notes many IT departments don't really know how the business is using its data warehouse. It is not necessarily bad, though, if IT does not know all the specific uses. Sometimes the sign of a great warehouse is that the users "run with it" on their own.

Nevertheless, it is possible to get a general idea just what the decision support (a.k.a., business intelligence) tools used to access a data warehouse are being used for. In this essay, I will attempt to make a general statement about use of these tools. Perhaps data warehouse support people can do a better job if they have a better feel for what the tools are really being used for.

The main uses of decision support tools are:
To check that "everything" is okay

Surprise! Nothing will be done with many, perhaps most, of the queries and reports created with decision support tools. They are run to confirm a person's usually not crisply defined notion but intuitively felt notion of "okayness". If I were able to write the essay on "The Zen of Data Warehousing" (which I will not), I would say a primary function of decision support tools is to support non-action.
To confirm the "obvious"

Most end users the reports and queries are ultimately being produced for have a pretty good gut feel for what is going on in their area of concern. Decision support tools do not tell these people anything amazing that the people don't already suspect. But the information produced with the tools gives them confidence their gut feel is okay.
To figure out how something "works"

Most people are not looking for some grand Unified Theory of how firm XYZ works. Rather, they want to understand some small aspect of an operation like Customer A always pays on time, Customer B usually pays late and still takes the early payment discount, etc.
To convey information in a more digestible manner

These tools are often used to convey what a person or persons already know. These knowing people use the tools simply to present information to other people in a way that it is more easily read.
To compare information about customers, products, cost/profit centers, financial accounts

Sometimes this is side by side comparisons of a series of measures. Sometimes this is identification of the most, the least, the earliest, the latest, etc.
To compare the same type of information in different time periods

This is simply the usual daily, weekly, monthly, quarterly, yearly comparisons.
To check performance versus formal and informal goals or constraints

That is, measures of what actually occurred are compared with budgets, forecasts, quotas, or some other types of goals.
To identify the out of the ordinary

Usually the ultimate consumer of the tool's output has somewhat vague criteria of what is out of the ordinary. The decision support tools kind of do double duty in that they help refine the criteria of what is out of the ordinary and identify what fit the refined criteria of out of ordinariness.
To grab a little piece of information out of a large volume of information

These tools make picking that virtual needle out of that virtual haystack a lot simpler.
To get around an Information Technology department that does not have the time or the resources to write reports

Often end users use these tools out of impatience with the IT department. Or, the IT department gives the user these tools to relieve the pressure off of itself. The end users in these cases often write reports that could hardly be called analyses.
To provide a report "of record"

For all kinds of reasons it is often necessary for people to agree that "these are the numbers". Note they do not have to agree on all the data - just some data whose credibility must be accepted for actions to be taken. Decision support tools often are used to produce this "official" information.
To confirm and sometimes to discover trends and relationships

With all respect to the people working hard on data mining, I think that most good businesspeople have an intuitive feeling of the most important trends and relationships between factors that are affecting their business. The decision support tools perform the function of confirming their intuition. Yes, the tools also can help discover trends and relationships but it is difficult (though potentially profitable) to sift out the meaningless and spurious trends.
To help advocate a position

These tools are not just for "objective" presentation of the facts. Often they are cleverly used to help bolster the case for doing (or not doing) something.
To provide data for a what if analysis or a forecast

That is, the tools are used to feed data into a spreadsheet where the actual what-if analysis or forecast will be done. The tools can do some of the what-if-ing and forecasting themselves but most business users are more comfortable doing this work in spreadsheets.



To repeat points I have made in other essays, despite their name most of these tools are not used as the sole input into making a non-trivial decision. Nor do they directly supply what I would consider to be business intelligence. Decisions are made and business intelligence is garnered only with the combination of the output of the decision support tools, human judgment and intuition, and the ability to put the information spit out by tools into a context of information that is much wider than any data warehouse, transaction processing system, knowledge repository can handle.