5 Common Business Intelligence Project Mistakes #5
Fifth in a 5-part series
You avoid problems in favor if a “Deal with it later” approach.
This is the mistake that closes the series. It happens frequently in Bi implementations and unfortunately, at times there is always a good excuse for it, such as lack of BI strategy roadmap, budget issues, lack of buy-in, and political environment. This approach is fatal, because the team chooses to ignore certain critical project issues from the start: Here are the main issues:
- Data Quality Issues
Most of the projects can benefit from implementing some sort of ETL control which would identify and block invalid data from entering datamart or datawarehouse. Frequently, this is not a high item priority. As a result, by the time a team realizes that data quality process is manual and intensive, it might be too late to implement efficiently. Just remember that users will not utilize BI system with erroneous or incomplete data.
2. Stagnancy Issues
BI projects have to evolve and keep up with the business. As the business rules and logic changes, appropriate modifications will have to be propagated to your system. This means that you should expect change requests right away and have a plan in mind: how you will prioritize requests and how you will schedule them.
3. Ambition Issues
The truth is that your BI project will more likely do better once started on a smaller scale, then gain traction and achieve more support. Trying to solve all issues at once from the start will unfortunately hyper-extend your team and render an inability to focus on solvable issues. Take it slow and try to work in a phased iterative approach.
Each of the four items above can be overcome by deciding to tackle the challenges from the start, obtaining clarifications or permissions if necessary, and concentrating on the solution. Word of caution: one of the caveats of this approach is that it always almost requires scope extension —especially considering that items such as MDM and Data Quality are seldom related to just your project. So you are at constant risk of never actually finishing anything.
As a review, the Five Common BI Mistakes are:
- You don’t get operations / infrastructure colleagues on-board early in the process.
- You don’t create a proof-of-concept/pilot/quick win iteration before full implementation.
- You don’t establish a proper overall communication plan for the project.
- You fail to implement a proper training program.
- You avoid problems in favor if a “Deal with it later” approach.
These five common Business Intelligence mistakes and the ways to avoid them have hopefully been instructive for you, and will help you guarantee success for your next BI project.