Here's our list of the top 10 BI software mistakes you should avoid, why and how:
1) Lack of executive sponsorship and active business involvement.
Everyone knows that any major IT effort needs executive sponsorship, but in the case of a BI software implementation the big mistake by the CFO, the chief marketing officer or other sponsor is to not be actively involved. It takes frequent injections of business process and strategy savvy to guide the IT team and prevent scope or data creep.
BI projects typically go way over budget when a directionless IT staff isn't given enough parameters about how much data is enough. They get into the bragging rights trap my warehouse is bigger than yours. Costs skyrocket, response times lag, results are muddied and the entire project capsizes from its own weight.
Without continuous guidance from the business side, "IT tries to stuff everything into a warehouse to address absolutely any question a user could conceivably ask," notes Howard Dresner, a former Gartner analyst who coined the phrase business intelligence and author of a new book on performance management on performance management.
As a result, IT burns tons of cash, takes far too long and creates inordinate complexity. Warehouses neednt be big, they just need to be useful."
2) Inadequate scrutiny over the data.
Just having the right extraction-transform-load tool doesn't make the data correct and current. Poor quality data can destroy the credibility and utilization of data warehouses and business intelligence systems.
This is not an IT challenge but a business challenge. If the key business staff aren't involved in identifying the right data stores and solving the inconsistencies how many definitions of customer are in your systems? the project will fail.
3) Not easy to use.
Too many IT implementers forget that the biggest benefits of a BI software solutions come from widespread deployment. This means the user profile will range from a doctorate in mathematics to an associate degree from the local community college.
The software user interface, graphics and what-if query capabilities have to be intuitive. If the fancy chi-squared distributions are the most prominent tool, you'll freak out many users. Keep the heavy-duty tools easily available, though the power users want everything.
4) Poor performance.
User expectations about query response times will be much higher than you realize. If the data warehouse has more than one terabyte or more than 100 heavy users, consider more processor horsepower via a data warehouse appliance. Develop more cubes or other ways to optimize performance now, not afterwards.
A related mistake is not recognizing the enthusiasm factor. A successful system begets huge interest.
"Some organizations are cursed with success and can't seem to keep up with user demand," warns Wayne Eckerson, director of research at The Data Warehousing Institute (TDWI), the pre-eminent organization in the BI field for IT pros.
5) Too many or too few BI software tools.
Both Dresner and Erickson warn that IT has to be careful about how many tools are available. Too many tools lead to a lot of confusion and soaring training costs. Too few tools frustrate the users.
Just relying on the tools provided by an ERP vendor may not be the way to go, warns Dresner. Think strategically about the toolset, he recommends.