Considering that analytics is meant to be about hard evidence, it’s surprising how much it’s riven with emotion. I’ve run across various points of conflict:
- People defending / denying the value of intuition.
- People defending / denying the value of experience.
- Tension between analysts who think the data suggests one answer and managers who want to do the opposite.
- Managers who seem more interested in shooting holes in an analyst’s arguments than in getting around to making a decision.
- Analysts who have an almost religious reverence for data that goes beyond what’s reasonable.
None of these emotional issues are unmanageable. In fact, anyone with management experience will be quite used to the fact that seemingly rational business decisions get mired in emotional conflict. It is perhaps only wishful thinking that made us believe analytics could escape this human reality.
However, there is more to this than a lament about human nature. Analytics projects tend to be heavy on data, technology, and technical skillsets. This investment in the “hard side” of analytics leaves little time or energy left for managing the political “soft side” of decision making. If you are building an analytics capability, you’ll be more successful if you design tactics to handle each of the five points of conflict I’ve listed above.
Analytics at its best involves big changes in how organizations make decisions. In fact, if it does not lead to big changes then there’d be no reason to invest in it. We will go astray if we just focus on analytics per se and not the organizational environment in which it has to operate.
Analytics is not just about new tools, it’s about a new way of approaching HR; make sure you prepare the business for that by changing culture, processes and attitudes.
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Special thanks to our community of practice for these insights. The community is a group of leading organizations that meets monthly to discuss analytics and evidence-based decision making in the real world. If you’re interested in moving down the path towards a more agile approach to people analytics, then email me at email@example.com or connect to me on LinkedIn.