Five Reasons Why Business Intelligence Projects Fail

Reason #1: Business Intelligence solutions that are not business user requirements driven. This is often a problem when ‘generic’ BI solutions are implemented. They can be based on perceived business requirements or what has been sold to the customer.

The problem with this is that the BI solution does not address any of the businesses pain points nor solve any of their business problems. For this reason

business users do not adopt the solution and will probably not champion any further iterations or improvements on the BI solution.

It is therefore imperative that any BI solution be driven by the requirements of the business and not by technology or a technologists view or understanding of the business.

Reason #2: Project involvement by Business. Although business is the ultimate customer they need to be involved in the BI process. This means from the project conceptualisation, through business analysis and development to deployment. A BI project needs a business sponsor who will champion the project and sell it internally. This sponsor also needs the authority to make decisions when required or when there is a deadlock on a certain issue.

When the business sponsor is continually involved, this assists in expectations management. That is avoiding the situation whereby the project sponsor / business is involved in the beginning of the project (project charter and business analysis) and then the BI project team disappears for a period of time and reappears months later with a BI solution.

Reason #3: Lack of solution adoption. Users may fail to adopt BI solutions for various reasons. One of these is when a project is not user requirement driven (reason #1) and does therefore not satisfy the business user’s requirements.

Another reason is poor change management; people do not like change and do not readily accept new solutions. Users are often new to the concepts of BI and education is important here. If not properly educated in terms of specific toolsets, solutions and the benefits of the new solution, users may fail to adopt the new solution. One that is not adopted or used is doomed to failure.

 Reason #4: Thinking technology is a ‘silver bullet’. When implementing a BI solution, often too much focus is placed on the product, either database, OLAP or front end, or on BI suites such as Cognos, Hyperion, etc. Technology itself will not solve any problems. It needs to go hand-in-hand with a robust solution methodology.

Reason #5: Long project lifecycles. When tackling any BI project, especially larger ones, and iterative project approach should be taken. Projects should be broken into subject, business or other logical areas and each delivery should not take longer than three months.

Projects that take the ‘big bang’ approach often fail because business users and sponsors loose interest during long delivery times, the business changes as well as the business requirements, and the project generally loses momentum. This can then result in an outdated solution that the users will not adopt.

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