📉 Three Reasons Data Projects Fail and the RAPPID Response

This Week's article from datapro.news analyses the pervasive and high failure rates plaguing all types of enterprise data projects, including basic analytics and advanced AI implementations. It identifies three primary systemic issues causing these failures: the Hype Trap (lack of defined business problems), the Foundation Fallacy (neglecting data quality), and the Adoption Abyss (insights not being used in decision-making). To address these problems, the article introduces the RAPPID Value Lifecycle, a methodology focused on ensuring measurable commercial value from data investments. RAPPID mandates a business-first approach requiring clear value definition before execution and incorporates frameworks to ensure Data Trust and guarantee that insights are Embedded into daily workflows.

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