Ten reasons why organizations fail to achieve widespread user adoption for their BI projects.
1. The total cost of BI software is too expensive for mass deployment: The complexity, inflexibility and expensive of traditional BI tools and licensing arrangements inhibits user adoption. Under these conditions, only select power users gain access to the reporting tool because the cost and additional infrastructure required for mass rollout is unrealistic.
2. The BI tool is hard for non-technical business users to use independently: If business users view the BI tool as a burden and hindrance to productivity it will remain shelf-ware.
3. The BI tool doesn’t help the right people to do their jobs better: The BI tool must help deliver the right information to the right people.
4. The data is not updated with sufficient frequency: Without regular data updates your BI tool will produce inaccurate information, leading to inaccurate business decisions. Executive backing and usage rates will quickly decline.
5. The right data is not collected: If you fail to collect the data needed to support operational objectives your BI tool will produce irrelevant reports. The tool itself will be viewed as irrelevant.
6. Lack of BI technical expertise and training for IT department: If your IT department lacks the necessary training to properly administer and oversee your BI project, it’s game over.
7. IT personnel cannot support excessive business user demands: If the tool cannot support business user self-service, your IT department will be overrun by ongoing support requests.
8. Not knowing how or what to apply BI to (lack of best practices): If you don’t know what business functions to measure, a BI tool is useless.
9. Lack of training for end users: If users don't understand how to use the BI tool, the underlying data, or data analysis generated by the BI tool to improve their performance, they wont.
10. Lack of executive or managerial support: Poor planning and a poorly defined business case will destroy the necessary financial backing for a large-scale rollout.
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