How to up your Data Maturity Index

As Jose Fernandez (@jfernandez__) implies, innovation is everyone’s job, and as Andrew Althoff (@andrew_althoff) quoted him, “We are past the technology movement. Now we have to get better at using it!”

The Data Maturity Index of a professional or collegiate sports organization is directly correlated with how sustainable their on-field success will be. Below are 4 of the most impactful dynamics to improve your DMI:

Meet People on Their Level: Accessibility is critical, and organizations should have data processes designed for stakeholders with different skill sets and perspectives. This dynamic can make or break how data is or is not used. Some will dig into deep corners of data models, while others need very simple, probably color coded reports with terms like more/less and better/worse.

Speed: A brilliant insight which takes a month to arrive is not useful. What is the shelf life? Drink Fresh Milk! Allocate human capital to where it will derive results while still useful.

Embrace Iteration: Calculated risk-taking is an encouraged + assumed part of everyone’s job. Charlie Munger talks about holding two conflicting ideas in your head at once, and we need the ability and confidence to put ourselves on the grills. Great organizations document outcomes with knowledge graphs and ask what outcomes reveal about drivers and expectations for future instances? Giannis speaks about ego vs pride. Which are you leveraging?

Have your house in order. Data Cleaning/Preparation, sound data collection practices, and organization databasing + storage via Cloud all facilitate making good use of what you have. We like Snowflake for their low-maintenance, hyper-secure methods. Easy data-entry features facilitated by the above help to realize the primary mission of cloud technology; break down silos. With data sharing across departments easier than ever, great teams make the most of every opportunity.

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