Nudging down payroll’s error rate

What does behavioral psychology have to do with multi-country payroll? Or to put it another way, if governments can bring about subtle changes in people’s behavior by playing to their subconscious proclivity to do the right thing, can payroll use the same techniques to reduce errors and workloads?

Multi-country payroll managers are constantly bemoaning how the quality of data coming into payroll – over which they have little if any influence – has perhaps the greatest impact on the quality of their output. It’s the old “garbage in, garbage out” problem, but exacerbated by the fact that the garbage in question is actually being thrown over the wall from someone else’s back yard.

When it comes to bringing about changes in the behavior of a mass population, one of the most influential influencers on influencing is Richard Thaler and Cass Sunstein’s nudge theory.  First reaching widespread prominence in the 2008 book “Nudge: Improving Decisions About Health, Wealth and Happiness”, a nudge was defined by the pair as “any aspect of the choice architecture that alters people’s behaviour in a predictable way without forbidding any options or significantly changing their economic incentives.”

They explain that putting fruit at eye level counts as a nudge, while banning junk food does not. While you might argue that a business manager’s “choice architecture” is a little more limited than an overweight punter deciding what their next snack will be, you can see where I’m going with this. This is a classic manual for how you bring about changes in behavior when you don’t have the authority to enforce them.

Over here in the UK, the practice of nudging has been so successful that the Government’s Nudge Department – the Behavioural Insights Team - has just been part-privatized, with ownership passing to a combination of investment fund Nesta, the government, and the department’s employees. The Nudge Unit’s biggest success to date was in persuading 100,000 more people to carry organ donor cards by making small changes to the wording of messages on the drivers’ license renewal website.

The Nudge isn’t just theory – it’s very much rooted in statistics and actionable improvements and if it works well in bringing about a 5% or 10% turnaround in the behavior of a mass population of several million citizens, then the part privatization of the UK’s Nudge Department is partly driven by the belief that it can work equally well in the private sector, in influencing sales trends, or customer service behavior. And that could also be applied to a disempowered HR department trying to encourage the business to take responsibility for their teams.

If you’re still sceptical, a couple of examples show how nudge theory works in practice. First, there’s the demographic argument: “Everyone else has filled in their tax return, so you should”. This plays to our subconscious desire to follow the crowd – or put another way, our belief that if everyone else has made a particular choice then there has to be some merit in it.

A second example is the reciprocity argument. “You would want to have someone else’s organ if you needed it, so why don’t you sign up to be an organ donor?” This plays to our desire to treat others as we would have them treat us. And it works on a large scale by persuading us to put ourselves in someone else’s shoes.

The nudge theorists use random controls tests to see if their theories on changing behaviour would work in practice, testing current messaging versus the nudge on a random sample of subjects, then seeing if it produces the behavior they are looking for and tweaking the messaging as they go along.

In payroll, messages such as “if you don’t approve your report’s time sheets, they might not get paid” can produce similar results. Or - to apply the demographic argument - “only 2% of employees didn’t get their overtime approved in time last month, don’t miss the deadline or your employee might not get paid”. It’s pretty basic stuff, but when we’re spending so much time correcting errors, it can have a dramatic impact - not just in reducing workloads, but in heading off the problems that create those errors in the first place.

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