There is more data than ever available for human resource specialists, including:
- The unemployment rates in specific occupations, in specific cities.
- Employee turnover rates in particular industries, and places.
- The relationship between particular workplace styles and productivity.
- Graduation rates in certain fields (and thus the supply of new accountants, lawyers, engineers).
And, within certain large employers such as the big accounting firms, retail chains, or large information technology companies such as Google or Microsoft, further internal data can be scrutinized.
Jason Warner, the VP of HR at Google (and formerly Starbucks), recently pondered the role of enhanced information on the human resources field:
I’m not a statistician, but for large sample sizes at large companies, there is a LOT of information that is just waiting to be discovered by progressive HR organizations who can pull the data and turn it into meaningful information. We had talked about doing this at Starbucks right before I left; running multivariate regression analysis against the thousands of store level staff to better predict attrition and the demographic trends that play out when you have large sample sizes of people.
But HR is rarely predictive. It tends to be more like ‘old medicine’, identifying what is wrong and then prescribing a fix. “You see, your attrition spiked so now we need to recruit more…..” Exit interviews. Employee relations. Compensation reviews. Most all of it analyzes post data.
It is admittedly difficult to be predictive, but it is also because we don’t ask enough smart questions. We ought to be significantly better as an HR function at predicting things. Because predictive HR is a lot more helpful that diagnostic HR.
For example, we can reasonably predict what range the US unemployment level is likely to be in the next 2 years, by comparing the delta in unemployment from the top of the boom in 1999/2000 to the peak in unemployment in 2003 (50 basis points, or 2% points overall) and fudge a little for the gravity of the economic issues that we face. It’s probably going to jump to about 8% (we can now wait and see if I’m right). And from that, HR should be able to extrapolate candidate flow and inform a recruiting strategy and resourcing plan. But the vast majority of groups won’t ever do this.
I expect in the next decade (provided I make it that far), that we’ll see much more predictive HR at the best companies.
I think Warner is right. Workplaces will start to be shaped by this knowledge.
A firm that has below-average employee retention rates might change up the workplace, offering employees something different.
Maybe we’ll soon know much more about how turnover really affects productivity, for example. The conventional wisdom is the cost to recruit, hire, and train a replacement is very high in terms of dollars and lost productivity. But maybe, based on our discussion here last week, it may be that some turnover is desirable and actually raises productivity through the introduction of new ideas – even best practices – from new employees coming from competitive and complementary firms.
