The first challenge of an analytics department is that they are off on their own and no one else in the company knows what they do. The second challenge is that they get discovered and everyone starts thinking of studies the analytics team could work on. This quickly leads to an infinity of requests for analytics work.
There are three tactics for handling this problem:
- Prioritize (obvious but disappointing)
- Delegate (tempting but too often not possible)
- Avoid (ahh, that’s something we’ve overlooked, how do we do that?)
That the company needs to prioritize requests for analytics is obvious to everyone involved, but it’s a frustrating option. We want people to embrace analytics and then we end up in a role where we spend half our time telling people we won’t do the analytics they want.
The problem of infinite requests will be familiar to experienced IT professionals who have long lived with the same phenomenon. They will also be familiar with the fact that if you push away or endlessly delay important requests then managers will just go around you and do their own shadow IT projects. The world of analytics is new enough that shadow analytics projects have not become a common problem. That’s yet to come — and it will come.
We could spend some time exploring the problems shadow analytics will bring; however, that’s not the focus of this article. Just be aware that it will bring problems such as departments doing analytics poorly and giving results that differ from those reported by the core analytics team.
Delegating some analytics work to other people in HR or directly to managers via interactive dashboards is appealing. The challenge is that this only deals with some of the simpler requests for data, leaving the analytics team still burdened with the more complex work. Providing do-it-yourself tools is a good idea, but the real value comes in when we link them to the tactic of avoiding analytics requests.
Understanding how to avoid doing analytics while still addressing the business problem brings to mind a story. I was meeting with an HR leader and discussing whether we could use the statistical tool of “survival analysis” to glean insights on increasing the number of women making partner in their professional services firm. We struggled a bit because neither of us had any great degree of depth in that statistical technique. Furthermore, we both had the instinct that unleashing the tool on the data probably wouldn’t reveal anything dramatically useful.
If we’d had an analytics department we would have asked them to do it; complained loudly if they said it was a low priority, and if they tried to delegate the work back to us we’d explain that we lacked the technical ability to do so.
Then I asked, “How many people are we talking about?”
He said, “Eight”
I asked, “And where are they?”
He said, “Right down that hall.”
The solution to finding ways to improve retention was to walk down the hall and talk to people. We could avoid a complex analytics project by taking a different approach to gathering insights on the business problem.
The deeper answer to infinite demand
Analytics is an exciting tool. Everyone wants to try it out. However, the mistake many organizations make is that they start with the tool rather than with the business problem. HR pros across the organizations (in fact, all professionals and managers) need to learn to be “analytics savvy,” which means knowing how to start with a business problem and tackle it with an evidence-based, grounded-in-data approach. Sometimes that will mean involving the analytics department; sometimes it will involve walking down the hall to talk to people.
Furthermore, the do-it-yourself tools given to HR become a lot more useful when an HR pro has clarity about what they are trying to solve for. These tools may provide enough of an answer on their own if the HR pro is really clear on the decision they are trying to make, or the tools may provide part of the answer the rest of which HR can get using methods other than advanced analytics.
As with any organizational resource, there will always be more demand than supply. With analytics, we can get ahead of the problem by helping professionals and managers learn to clearly define the problem so that heavy duty analytics are only asked for when it is truly justified.