Posted by: mikeduckett | February 26, 2014

Are You Looking For Talent or Just Weeding Out The Chaff??

In a recent piece on Radio Marlow FM we discussed something I had spotted in the news about Google’s HR processes, i.e. their use of algorithms, not just for searching the web but for making decisions about pay and promotions. I was quite impressed, even though I jokiClip edit1ngly referred to Robomanager.

If you listen to this clip you’ll hear some comments about not being able to measure things other than results. As I said, I think you probably can identify valid measures of most things if you’re really specific about the behaviour you’re looking for, after all, if someone isn’t demonstrating a ‘quality’ (characteristic / value / capability etc) then how do you know they have it!?

Well it seems Google spend a great deal of time correlating outcomes / results with numerous behaviours . For example they even track people’s’ time spent queuing for coffee. They then treat this as one piece of behaviour that influences collaboration. Collaboration in turn is well-known to be linked to innovation and we all know Google are masters of innovation.

I recently came across two interesting linked blogs, a year apart, by Dr John Sullivan who seems to have followed Google’s use of maths and statistics in HR very closely. The first of these picked out what he calls his ‘Top 10 Most Powerful Illustrations of the “People Analytics” Approach’ in reinventing HR. ‘I would say this wouldn’t I’ – but for me, one of the most interesting points was the recognition through data analysis and not opinion, that a coaching style of management and giving frequent personal feedback is the No1 key to being a successful leader.

The second piece, Facebook’s Billion Dollar hiring lesson makes a terrific point about how much it costs companies when they miss a talented individual i.e. when they fail to spot some inherent potential in people. History has some famous examples that bring wry smiles, such as Decca Records turning down The Beatles but Sullivan is now able to put a direct price on Facebook’s mistake; not just as a missed opportunity cost.

Facebook just bought WhatsApp for nearly $15 billion having refused the two inventors Jan Koum and Brian Acton jobs only 5 years previously! He points out that for Koum to go from a reject to a main board member in 5 years must be very embarrassing. He then goes on once again to illustrate how Google use objective statistics to make hiring decisions and avoid missing talent like this.

So what’s my take on this? Why is it grabbing my attention?

There are two points I’d make:

1. Don’t fall into the trap of only measuring results. “We’re a results driven company” may sound objective and aggressive but from a performance coaching perspective you’d be wise to separate a result from the performance (behaviour) required to obtain that result; then focus on the performance. Google are proving the claim that you can’t measure subtle or so-called ‘soft’ success behaviours to be a myth. Don’t follow the example of football clubs (see my previous blog) and remove talent purely on a set of results simply because that’s all you can be bothered to measure. They may be putting in a great performance which hasn’t yet been rewarded through factors outside their control.

2. Think about your recruitment processes in terms of seeking out the ones you’re looking for.  There’s a useful way of examining your motivation for setting a goal in terms of whether your underlying motive is to avoid something negative or to seek out something desirable. Each has a subtly different effect on the way you think about what you’re doing and therefore on the likely outcome.

Although Sullivan’s blog is written in the language of avoidance of errors and ‘not missing’ talent, I suspect the reality of Google’s algorithm is that it seeks out talent. I just wonder how much recruitment, certainly in large orgnisations, is done to ensure they don’t make the mistake of hiring the wrong people. The difference in outcomes then could be that Google find what they are looking for – talent – and others find what they are looking for – non errors. I know which sounds more exciting!

I suspect that if many companies were to try to follow Google’s example the biggest first step would not be hiring statisticians but deciding precisely what they are looking for!

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