5 Reasons Why Your Business Intelligence Project Will Fail

Like any other IT project, business intelligence projects have a high risk of failure. Here are 5 reasons why your BI project will fail.

Absent or Weak Business Sponsor

A strong business sponsor is the most important ingredient for a successful business intelligence sponsor. This person needs to be well-respected within your organization and be able to make decisions for the organization. If the CIO is your business sponsor, you are in for a world of trouble. A CIO does not have influence over the business community and will not be well-respected when business decisions need to be made. Finding a strong business sponsor will significantly increase your projects probability of success.

The BI Technology to be used was purchased Prior to Gathering Requirements

DespairGathering requirements for a business intelligence project is one of the first steps that should influence all subsequent design and development decisions. If you have already decided on a technology platform, the technology that was chosen will influence the requirements, which may translate into business needs not being met. On future BI projects you will definitely leverage the existing technology but you should not skip this step to make sure that the technology chosen will meet the business goals.

The Business does not have Time to Participate

Business participation is mandatory in a business intelligence project. If the business is too busy to take part in the BI project, it is probably a good idea to postpone the project. A BI project cannot be successful without intimate participation by members of the business community in your organization. I would estimate that, at minimum, half of your project team needs to be from the business community.

Poor Data Quality

I have discussed the importance of data quality in an earlier post and some practical ideas on what can be done about poor data quality. Ultimately the success of your business intelligence project will rely on having quality data. It will be very difficult to develop a good framework for decision-making with underlying data of poor quality.

Lack of Data Definitions

Defining business terms for your organization is an important process. Without consistent and agreed upon definitions for business terms you will not be able to consistently give the same answer to the same question. This part of your BI project should be started as early as possible as there will be many meetings that need to be held to get your organization to come to consensus on data definitions. It will be very difficult to code your ETL process for consistency without first having consistent business definitions of terms.

I hope that this post has given you some ideas on ways to improve your next business intelligence project so that it is successful and delivers value to your organization. If you have other common reasons BI projects fail, please leave a comment.

A great book to help you get your business intelligence project started for maximum success is The Data Warehouse Lifecycle Toolkit.

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