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This chapter is from the book

Visions for the Analytics Capability to Serve These Needs

So far, two things should start becoming clear. The first is that, in many ways, analysis is the easy part. Orchestrating analysis so that it isn’t just acted upon, but welcomed as fundamental to driving decisions and actions, is often harder and more time consuming than actually doing the analysis itself. The second is that, in the service of this first objective, you may need to start with analysis that is simpler and more transparent, both because it’s easier to orchestrate action around it, and because with less time and less rope (at least to start with), you can’t take it to the most sophisticated levels. This has major implications for a lot of things, including the vendor solutions you select and the people you hire. But once again, a major theme of this book, echoed throughout all of the conversations that inform it, is that analysis has no intrinsic value—it’s only useful if it’s acted on. And you don’t need to be absolutely right, you just need to be better. So one major attribute for any effective analytic capability is a practical orientation for progress and results.

As you move toward this practical orientation, a well-developed analytic capability is balanced across research, analysis, and testing. Managed in silos, practitioners of each of these techniques will stretch, at greater expense and with less certainty at potential insights. Statisticians will add variables of diminishing incremental explanatory power to models. Researchers will weight and re-weight survey responses to make up for sample shortcomings. Testing teams will stretch to multivariate scenarios that may be technically feasible but practically hard to coordinate and communicate. But managed together (or at least carefully coordinated), it’s much easier to squeeze what’s practical from each and switch to the next when the air starts getting too thin. Belinda Lang, former CMO of Aetna Insurance’s consumer group, relied on all three of these levers in launching and growing various new business options in her twenty years at American Express, and she cites the balance among them as a key driver of the success those options had.

Some discussion questions:

  • Which is your dominant analytic perspective?
  • Which analytic perspective pre-dominates for your boss(es), peers, and team members?
  • How does homogeneity or diversity help or hinder you? What have you caught or missed as a consequence?
  • What do you have planned to further leverage or overcome this diversity or homogeneity?
  • What organizational fault lines are most pronounced in your situation?
  • Is your communication of analytic findings tuned for the fault line you’re dealing with?
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