Sometimes it pays to look at the obvious.
I have been listening to all kinds of heroic HR and Talent efforts around big data over the past couple of years, and the effort involved is impressive, not to say awesome. People have analysed everything from working hours patterns (do top performers come early, stay late or both or neither?) to volume and timing of email activity and even the number and timing of snacks consumed from the free snack cupboard (I’m probably making that last one up, but who knows, with the IoT?)
But are these efforts well-advised?
The thing that puzzles me, is that we have a fabulous amount of research in place on the significance of intrinsic motivation in producing engagement, discretionary effort, peak performance and … well, talent. (A big thank-you to Harry Harlow, Douglas MacGregor, Ed Deci and Mihaly Czikszentmihalyi). There is also a more specialised, less widely known, body of research on the effect of perception on behaviour, but it exists none the less (thank you Drs Birkman, Mefferd et al). Even if you are unaware of the latter, surely factors involved in intrinsic motivation would be one of the first places you would check in your search for predictive power in the development and application of talent (i.e. before downloading sensor data from the free snack cupboard…)
We have been tackling this challenge, via a ‘benchmarking’ approach, for well over a decade. The process requires that we have (from the client) an objective assessment of individual performance for everyone in the benchmarking sample (“Star, Averagely Good, Underperform” or similar is fine; but it must be objective: “Manager X dislikes employees Y and Z but loves A” doesn’t work). We then assess each employee across a range of motivational and perceptual scales, look for correlations, evaluate face validity and so on to ensure that we are getting at potentially causal relationships, and then test for predictive power. Standard stuff - but we have a head start, because we know that motivational and perceptual factors do impact performance and engagement, massively. (As compared to snack consumption, sick days and clocking-in time.)
Let me share three big wins we have seen, only the first of which we were looking for. (Yes: the other two caught us by surprise.)
1. You end up with a selection profile that delivers success
This was why we started down this path. A client asked us to solve their recruitment problem. They had a very specific success factor when they set up the business, but then used up all the (obvious) available candidates. Their attempts to hire others who had already demonstrated great success in their industry failed miserably - because how the rest of the industry achieved success was a million miles from how they did. We benchmarked their team, identified 2-3 core factors (plus a larger number of ‘getting to the ballpark’ ones), i.e. which seemed most clearly to distinguish their stars from the rest - and the CEO was delighted. Using the benchmark in conjunction with tailored interview questions (and of course all the other components of a robust hiring process, which they had always employed), suddenly they were hiring people who matched the original core team, and their clients loved it. When we re-ran the benchmark with a much larger sample 18 months later, some of the ‘ballpark’ scores proved unstable, but the core scores were validated. And we have repeated the process for many clients since. So far so good.
2. You gain a deeper understanding of your success factors
Obvious with hindsight, but the flavour of your secret sauce (as seen in the profile of your star performers for a specific role) tells us something about what is special about your business, or at least that particular part of it. If (for example) you are running a sales team, and your star performers don’t look like typical sales people, but have some other, strongly marked, characteristics, that may well be telling us something important about your business. That may not seem a big deal, until you realise how many businesses are not able to really explain what is unique about their business (and are therefore poorly prepared to leverage and preserve that advantage in the long-term). Yes, maybe you do make really good widgets, but until we know what makes for star performance in various parts of your business, we may not know what is special about your business model. “Great widgets” is probably only part of the equation; benchmarking helps makes the people (and therefore cultural) side of the equation explicit.
3. You can be more intentional in supporting your star performers
A friend of mine undertook research in call centres, which suggested that the top 10% of operatives were likely to be an order of magnitude more productive than the next 80% (and don’t even ask about the bottom 10%). But here’s the question: who are you supporting most effectively through your systems and the way you manage your culture?
It is an important question, because by default we often try to make things work for the majority, which is fine; as long as we are not, at the same time, disadvantaging our star performers. (Pause: do you have problems retaining some of your high-value employees? Hmmmm). So having a profile of star performance - especially one which includes behavioural / perceptual data as well as the motivational - means you have a cutting edge when it comes to keeping those stars engaged and on board.
Anyway, got to go - it’s after five and I need to turn on my email-robot and raid the snack cupboard on the way out…
Originally posted on LinkedIn - Published June 15, 2016