BI OIC for CIO

Business Intelligence has been on the CIO radar for over 3 years now as per research reports from the major and respected IT research companies. Billions have been spent by companies and as a category, BI projects have seen the least success across almost all IT enabled initiatives. BI consultants will go about advising you that they "know" how to make it work for your enterprise and if and when things start faltering, it's always you and your users who are responsible. I happened to ask a VP turned consultant from a large bank, "How is it that consultants have all the answers, but employees do not ?" and got no answer.

Every organization aspires to create intelligent insights from transactional data and act upon them to increase revenue, optimize profits, retain customers or create efficiencies. In most cases, users are unable to think or visualize what they want to achieve any of the above objectives and thus end up defining extremely complex scenarios and reports with a hope that they will provide some kind of "Eureka" brainwave and they will be heroes. IT organizations takes limited steps to dispell such myths and takes on the task of creating models that enable the complex reports. Maybe because they are not in the bath tub !

Typically such operational data based reports provide limited insight since the insight is driven by humans and not systems. A report viewed by different people creates different inferences and that a technology cannot provide. Technology works on models created by us and is thus limited by the information gathered and understood by the developer. This indeed is the key to actionable insight and the experience and frame of reference of the person which makes the difference.

This is not a great insight, but it is based on the experience of seeing many business leaders responding with differing insights to the same analytical report presented. It comes out of a deep domain expertise and lateral thinking. Such individuals if enrolled into the program can make the difference between a successful and not so successful BI project.

Left to IT organizations, which is the typical case with BI projects, the end result is multi-dimensional reporting which is finally used to review business but with limited insights. It is evident and obvious that right people make the difference, but the right people are normally too busy to spend long periods of time to understand the possibilities and list them down. If by chance that were to happen, the adoption by the rest of the organization suffers and gets blamed on bad "change management".

So what is the conclusion ? A few "actionable insights" based on 3 BI projects.

1. Find the "right" person within the company who can help create insights. It may be your CEO ! If you cannot find such a person, don't start the project

2. Start small and scale up as you taste success; before you attempt to build the Taj Mahal, practice some smaller buildings

3. Tools and technology matter, but in the end, the data quality makes the difference

4. Do not be averse to restarting from scratch in case the first model or the second model does not deliver. It's quicker to recreate than attempting to patch a bad one

5. Keep on asking questions at every stage, "Why do you want this ?", "How will it help you or the company ?", "Who else can benefit from this ?", you get the picture .....

6. Whatever you do in stage 1 may need to be discarded by the time you are in stage 3 and that's okay.