Why is measuring success so hard?

“How do you measure success as a data team?”

So many different answers surface when I ask this question of data leaders. “Stakeholder satisfaction”, “Employee retention/morale”, “Data Quality”, “Completing our new data warehouse”, “Decreasing cloud costs”, “No one on the team working overtime”, “Data turnaround time” etc.

These answers range from operational efficiency and effectiveness to internal team culture, to technical goals, to stakeholder perception of the data team.

Why is this such a hard question for us to answer?

Here are the first few reasons that came to mind:

  • We don’t have a clear vision for data in our org

Is the data team a group of ticket-takers that churn out reports? In what way, and by what methodology, does data support leadership decisions? Can you tie any business results to something the data team delivered?

  • Data teams align to many different functions in a company

Is your data team embedded in the business units? Is it centralized? Does it roll up to finance, marketing, IT, or software engineering? Because of the numerous places data teams sit on the org chart, data leaders have constantly shifting views of what success looks like based on who they report to.

  • We haven’t been asked to define success before

For the last decade of low interest rates and cheap cloud tools, data teams could build all sorts of fancy tools and exciting data projects. The actual ROI was never demanded because R&D budgets were flush. That’s changed and the cheap money is gone. Now the budget and staffing cuts are here, we are scrambling to define success.

  • We love data too much.

It’s hard to find clarity about success when we have (or know how to find) any data point we want. Our dashboards are clouded with KPIs that make any sort of uniform message unclear. When “these six success markers are up, but these 5 are down” good luck sharing your progress clearly with leadership.

  • Ambiguous definitions of measurements

Leaders will tell me they measure success by “customer satisfaction”, ‘Data quality”, or “by contributing to business goals”. But they never clearly define what those terms mean or how they quantitatively measure them to track success.

For as much as you love data, you are relying a lot on your gut feeling about success.

There’s a better way to do this. This summer, I’m piloting a program called the Measuring Success Launchpad.

Hit reply if you want a short video explaining how the program works.

I’m here,

Sawyer

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Just yeet the code change into prod and hope for the best