Simplicity, not accuracy, is what is needed in the pay ratio definition

27 October 2017

By Tom Gosling

Anyone who’s followed our work at PwC will know that we are not big fans of pay ratios. See for example my evidence to the BEIS Select Committee Inquiry on Corporate Governance. This isn’t because we don’t think a discussion about fairness is important – on the contrary we think it’s vital. We just don’t think pay ratios are the way to go about it. However, we’re going to get them, so the question now is what ratios and how to calculate them? BEIS are currently considering the right methodology to bring forward in regulations in 2018.

It’s my strong hope that BEIS recommend an inaccurate definition for the pay ratios, as this will mean they have chosen simplicity over spurious accuracy.

Someone trying to come up with an “accurate” definition of a pay ratio faces a number of challenges around consistency of pay definitions between the CEO and other employees, and whether to use average or median. The SEC has worked through these challenges in the five years they took to develop pay ratio regulation in the US. They went for accuracy. The result was that the guidance and discussion that they published containing their rule ran to nearly 300 pages!

The main benefit that will come out of pay ratio disclosure will be the catalyst it creates for meaningful discussion within boards about the approach to pay and pay fairness across the company, and the associated narrative reporting. This is important, and something boards need seriously to engage with as part of efforts to rebuild trust in business, as we’ve written elsewhere. My view is that we could have triggered that conversation without mandating a misleading pay ratio disclosure. But what is certain is that adding complexity to the calculation is just going to be a distraction rather than a help to the quality of that discussion. 

The case against pay ratios has been made, but the argument has been lost. Let’s at least make it cheap and easy to calculate. Making a meaningless statistic more accurate isn’t going to help anyone.

A longer version of this blog can be found as part of my regular series on LinkedIn which you can access by clicking here



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