Friday, February 27

Translating data science capabilities into business ROI


I’ve focused on creating measurement frameworks that speak executive language. When I present analytics impact, I don’t talk about model performance metrics. I talk about the sales opportunities generated, the 66% improvement in engaged clients, the 40% conversion rate that made dormant contacts profitable again, the crisis dashboard that kept a trillion-dollar business operating through unprecedented disruption.

I’ve also worked to shift organizational expectations about what analytics should deliver. Early in my tenure, stakeholders wanted analytics to confirm decisions they’d already made. Now they expect analytics to reveal opportunities they hadn’t considered and to challenge assumptions that might be wrong. That shift in expectations: from analytics as scorekeeper to analytics as strategic driver creates more lasting value than any individual model.

The key to this cultural transformation was demonstrating wins consistently enough that people began to expect them. When advanced segmentation dramatically improved engagement, teams across the organization asked, “What else could we segment better?” When partnership prediction worked, other business lines asked, “Could you build something similar for us?” Success became self-reinforcing.



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