Why Is It So Hard to Become a Data-Driven Company?


It's really hard to do data well at large, non-digital-native organizations:

(Fortune 1000) companies reported struggling to make progress — and in many cases even losing ground — on managing data as a business asset, forging a data culture, competing on data and analytics, and using data to drive innovation. Only 29.2% report achieving transformational business outcomes, and just 30% report having developed a well-articulated data strategy. Perhaps most tellingly, just 24% of respondents said that they thought their organization was data-driven this past year, a decline from 37.8% the year before(...)

Heh. This is a headspace I've been in for a little while now. The deeper we get into working with enterprises, the more obvious it becomes that doing data well is about so many things that have nothing to do with technology.

  • Does your existing employee base have raw quantitative reasoning skills? Can they form a question that could be answered with the data?
  • What are the behavioral norms around decision-making? What do people accept as "good enough" justification to do a thing?
  • How willing are people to say "I don't know"? Epistemological uncertainty is a hard thing for most humans to handle!!!
  • Are executives willing to "kill their darlings" if the data recommends doing so?

And so much more. None of this has to do with "can I stand up modern data technology"—rather, it's about the ways that data needs to weave itself into the fabric of day-to-day existence at a company in order to actually create change.

Squishy, I know, but real. I'm pretty convinced that changing existing culture is harder than creating new culture from scratch, which is why it's digital native companies that have most effectively adopted data-driven operating systems. It's not that they have all of the best data people, it's that they have broad consensus about how central data is to their very existence.


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