“I’ve got plenty of data, just tell me what you want to see”
I think this must have been the 14th time I’ve heard the same comment from data guys at various companies. It was, as it always was, a frustrating comment for the CEO to hear. And you could tell.
“I expect YOU to tell me, what we should be looking at”
It was a classic mismatch in the way the two people, in their own roles were unable to align. The Data guys were silo’d and unable to connect their research with the wider objectives of the business, this meant the were simply service providers to people they assumed were in a better position to connect the dots, when in actual fact, that was the role the CEO was expecting them to fill.
In my opinion, this is where OKRs and metrics overlap, and why OKRs can be a real help in ensuring that there’s alignment, understanding and ownership. So here’s how we can use OKRs and key metrics to ensure that the data side of the business starts to actually give insight that’s topical, relevant and aligned with the wider business questions.
You want to start by having clear company level objectives and KRs, then work with the data guys to agree on what metrics each objective and KR can be measured with, you want to spend time agreeing what data is needed, how it can be collected, and consider how this information needs to be segmented and filtered.
Once you have alignment on the OKRs and the critical metrics for those OKRs, you can then move to looking at the dependant data, the data that affects these critical metrics, again, this should be a discussion between the business-side and the data-side about what is important and how it should be segmented and filtered.
Now that the critical metrics and secondary metrics have been identified, the discussion can move to how this information should be reported, with regular reporting now in place on a basic level, and the data team having clearer context on why they are monitoring this data, the more specific questions and areas of research can be directed to the data team to research.
In practice, these three steps – identifying the critical metrics, identifying the secondary metrics, defining the reporting and questions happen concurrently during the conversation, so you want to be moving forwards then looping back and adding more details as the conversation progresses. Regardless, the overall objective is the ensure the data guys have more context as to how the data they are looking at relates to larger commercial goals and OKRs.