Sometimes data scientists are more concerned with pursuing their crafts than they are at solving business problems.
Recently, Ron Kenett, the distinguished Israel-based data scientist, and I compared notes on our own successes and failures — and those of our colleagues — in helping companies with data science.
While data science does require initial investment, you should expect real results — in terms of cost savings, new revenue, improved customer satisfaction, or risk reduction — within a couple of years. Obvious as this sounds, the implications are profound.
Post-analysis work is similarly critical, as insights and algorithms must stand up to the rigors of the real world. Of greatest concern are seemingly minor political issues, again testing the patience of inexperienced junior data scientists. More senior data scientists know politics can also work in their favor, and they make time to engage all impacted by their work.
Trust is a common thread throughout these recommendations, and managers must insist that data scientists work to earn that trust. And they must give them a fair chance to do so.
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