Fairly obvious, seen many of these situations occur over the years in analytics and data interactions. And how they are linked to business results. Good checklist. Non technical.
Getting Serious About Data and Data Science To implement successful data programs, companies need to shift goals, muster resources, and align people.
By Thomas C. Redman and Thomas H. Davenport
Data science, including analytics, big data, and artificial intelligence, is no longer a novel concept. Nor is the important foundation of high-quality data. Both have contributed to impressive business successes — particularly among digital natives — yet overall progress among established companies has been painfully slow. Not only is the failure rate high, but companies have also proved unable to leverage successes in one part of the business to reap benefits in other areas. Too often, progress depends on a single leader, and it slows dramatically or reverses when that individual departs the company. In addition, companies are not seizing the strategic potential in their data. We’d estimate that less than 5% of companies use their data and data science to gain an effective competitive edge. ... "
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