“Actionable data” is a term that has been tossed around for years, right? How many times have you heard this: “The key to analytics success is providing actionable data.”
Okay, but what does that mean, really? Here I am, a data warehouse and analytics design guy… how can I measure whether the systems I design are producing actionable data?
I was talking with Dr. John Kenagy, owner and director of Kenagy & Associates, in preparation for an upcoming webinar and he mentioned actionable data a few times in the discussion, so we paused to ask ourselves, what does that really mean?
Here’s our algorithm for Actionable Data:
Actionable Data = Pr x Tf x Et
Here is the key:
- Pr: Personal. The data must be personal, by name; and role and workflow specific.
- Tf: Timely and fresh. The data must be timely, fresh, and high quality… no stale or bruised data fruit.
- Et: The person to whom the data is presented for action must be educated and trained about how to act in response to that data.
One of the key moments of awareness for me in this discussion was the Et variable. If I’m a data warehouse and analytics design expert, it’s not enough for me to provide personalized and timely data. I can do that easily enough, technically. I have to ensure that the organization that I’m supporting with the data warehouse and analytics solution is taking it upon themselves to educate and train their employees — the consumers of the data — on how to interpret the data and what action to take in response to the data.
If I don’t ensure that the organization is taking this holistic approach to Actionable Data, it’s in the interests of my livelihood and success to push that agenda; otherwise, the technology that I leave behind will not realize the value that it should.
Analytics and Data Warehouse Engineers: Take action to ensure you provide actionable data.