One problem that seems to plague organizations these days is a lack of understanding of how Business Intelligence techniques apply to more than just the typical “what’s our sales performance” question. (See my previous post for more on applying BI techniques to IT data).
I think the root of this problem is much deeper than simply trying to understand BI technologies. I believe the problem stems from a fundamental lack of understanding how to apply a technology solution to a business problem. This may sound a bit like Dilbert-esque crazy talk, but I think I can make a pretty good case for this argument.
There’s a lot of talk and “noise” in the industry right now about “Cross Domain BI” (some call this pervasive BI, but I don’t agree with applying that term to this problem) where BI techniques are being used to tie together data from multiple dissimilar sources within an organization. This provides a unified view of just how well each aspect of the organization is performing. I think that this movement is destined for a very bumpy road unless organizations fundamentally change how they approach problem solving in general, and “BI” in particular.
Distilling the Problem
Anyone who’s been in an engineering role (not necessarily limited to software engineering by the way) for awhile has been faced with the problem of imprecise requirements or specifications. As engineers, we tend to understand how to deal with that problem (it depends a lot on the engineer, sometimes the lack of a good spec makes for a great excuse not to get the job done, or worse, leads to a product simply “built to spec” and sometimes it forces the engineer to become more involved in understanding the problem they are trying to solve) and move on. Unfortunately the trait doesn’t always hold true with those outside of engineering who typically drive Business Intelligence projects.
Agile Business Intelligence
I’ve made the base before that BI projects *must* be driven by Agile methodologies if they are going to succeed. The main point of my argument there is that a successful BI project must be able to adapt to changing requirements along the way, and must be extremely flexible in terms of the data provided to the end-user. I believe it’s also true that for “Cross-Domain” BI to succeed, there must be an Agile component to the business as a whole. If an organization is rigidly structured, with well-defined “silos” of information, any attempt to develop cross-domain BI will likely end up in several BI silos that ultimately become useless when combined. For a cross-domain BI project to succeed, each of the silos of information must understand how data from other silos can be used to improve their own performance. In order to accomplish this, there needs to be an over-arching description of the business goals for the BI project, as well as a description of the goals for each silo. Generally speaking, this is done by following the “Business Scenario”-focused process such as the Microsoft Solutions Framework (MSF).
This brings me back to my original point. In order to properly apply BI techniques to the “Cross Domain” problem, organizations must first understand the problem that they are trying to solve. If they do this by creating an over-arching “cross domain” Business Scenario that contains the following steps:
- What questions are you trying to answer?
- What data do you need to answer the questions?
- Where does the data exist?
They are more likely to succeed at delivering a useful solution. If they don’t follow this simple approach, they are likely to be left wondering what happened.