People analytics: how much should you spend on technology?


Can significant investment in expensive people analytics technology ever be justified?

Compare people analytics to marketing analytics: in the case of marketing analytics, the case for expensive technology is reasonably clear because sample sizes have orders of magnitude in the hundreds of thousands. On that scale, high-tech data fishing will usually pay for itself with the discovery of a few new profitable market segmentations.

In the case of people analytics, however, few global workforces are sufficiently large to justify these expensive fishing expeditions in the hope of finding valuable workforce patterns. And even if patterns are found, the ROI would be virtually swallowed up by the cost of the technology required to generate it.

Experience suggests that when it comes to people analytics, optimal ROIs are generated not by expensive data fishing, but by focusing on specific well-defined problems identified by the business. The solutions to most of these problems do not require significant technology investments and can instead be solved with low-cost packages like SPSS and cost-effective cloud technologies. In truth, we’ve even helped companies save $10m using just Excel as part of a well-planned structured data methodology. I’ll post something on people data strategies in the next few days.

The bottom line is that ROIs on people analytics could be even higher if companies avoid unnecessary capital outlays on excessive technology.