Six misconceptions of a BI implementation – part 2


Last month I raised the issue of the success of BI systems being constrained by some common misconceptions about both the design and deployment processes and listed 4 popular misconceptions. Here are a further 2:

Business users know exactly what they want before a BI project begins, and those requirements won’t change. The time-honoured tradition of gathering requirements from business users, creating specifications based on those requirements, developing applications from the specs and then giving users a look at the resulting software makes sense for a lot of applications.

But it doesn’t always work well on BI projects. Often, the traditional approach ends with users saying that the BI applications you’ve worked so hard to build don’t give them what they need. They might not have had such a solid grasp on the business needs to begin with or those needs might have evolved during the months it took to finalise the applications.

An Agile BI approach, with incremental rollouts of features and functionality, could be more fruitful. At the least, you should keep in close contact with users all along the way so you don’t get caught by changing requirements.

Spread sheets will no longer be the tool of choice for BI analysis. Organizations have a love/hate relationship with spread sheets when it comes to BI. For IT and BI managers, spread sheets should give way to business intelligence tools, which offer increased functionality for users and better management capabilities for BI teams. But users will quickly go back to their spread sheets if they think BI software is too difficult to use or if they see limitations in the analytical capabilities provided by BI implementations.

The solution to this is to adopt spread sheets as part of a BI portfolio and support their effective and judicious use. The problem now isn’t that they’re being used for BI purposes it’s that they’re being used for the wrong things and in the wrong ways. For example, users shouldn’t be copying data from various sources into Excel and integrating it in worksheets, then manipulating the data and doing analyses on their own versions of information. That’s a recipe for creating data inconsistencies — and inconsistent BI findings.

BI systems can pay big dividends if they’re built and managed properly. The goal of a BI project isn’t to deploy the tool with the most features; it’s to produce the maximum amount of business value possible. There shouldn’t be any misconception about that and avoiding the ones above will help you deliver what you’ve promised.