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Business Intelligence projects can begin with a simple goal, but can easily go astray.
Reporting, dashboards, data integration, advanced visualization, and end-user self-service are the most strategic BI initiatives underway in enterprises today. Second-tier initiatives include data discovery, data warehousing, data mining/advanced algorithms, and data storytelling.
These BI initiatives involve multiple moving parts and actors. These projects can become complex, containing many dependent pieces. Critical decisions made at the wrong level can lead the plan to chaos. Additionally, timelines are sometimes aggressive and don’t fully account for delays.
Improving revenues using BI is is a common objective. But with the many ways that a BI project can fail, it often results in money wasted.
SME has identified the top six reasons why BI projects tend to fail.
We believe that knowing these failure points is a major step toward ensuring BI project success.
People underestimate the value of analytics because they don’t understand its true business value.
Business users don’t trust the data delivered by the analytics project.
Users don't know how to ask the right questions to deliver insights to the business.
Project leaders prioritize technical skills over business acumen.
There is a lack of communication between IT and the Business.
There is no support to improve data literacy or build a data culture.
To continue reading and to go in depth on each of the above reasons, download SME's eBook.