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Failed Data Projects: No Different Than Anything Else. Things That Can Go Wrong Will.
Increasingly businesses are turning to data to help run their businesses. Benefits include cost reduction, faster and better decision making, and insight in building new products and services.
Richard Petley, director of PwC Risk and Assurance, said that “data is the lifeblood of the digital economy, it can give insight, inform decisions and deepen relationships. It can be bought, sold, shared and even stolen — all things that suggest that data has value. Yet… very few organizations can attribute a value and, more concerning, many do not yet have the capabilities we would expect to manage, protect and extract that value.”
Diane Hagglund, principal at Dimensional Research, said that “the importance of data analytics to organizations is universally recognized; yet, very few organizations have avoided significant issues with critical data analytics initiatives. Executives in particular are recognizing that the complexity and inflexibility of their existing solutions has become a significant barrier to analytics success.”
A recent study by Snowflake Computing identified reasons why data projects can fail. The reasons include:
- Low end user adoption
- Over budget
- The system didn’t provide the analytics that users were expecting
- “Zombie” projects that never attracted end users
Stephen Brobst, CTO at Terradata, identified another four reasons why data projects fail:
- Too much focus on technology, rather than business
- Subject matter experts not involved enough in the project
- Lack of enterprise adoption
- Forgetting that project costs include not just IT systems but also people’s time
