In the simplest terms, the new Equal Pay for Equal Work legislation requires that any variations in pay between similar roles are for the right reasons.
The right reasons could be experience, service, past performance, a talent score or scarce skills. Our challenge is that it’s not or, it’s and. All of these factors could be good reasons for pay differentiation, not only one.
Equally, we know many of the wrong reasons for variation, such a race, gender or any other arbitrary form of discrimination. And we know that it’s free for employees to refer a pay discrimination dispute now that the CCMA has jurisdiction over these cases. We also know that a referral carries significant risk for an organisation’s reputation.
So why do Big Data and analytics decrease your risk?
Big Data is all about integration. Integration not only of multiple factors, but multiple sources of information.
If you had the time you would:
- Look up every employee you have against your survey data, calculating each and every compa-ratio so you’re comparing like-on-like before you move on to other factors;
- Compare these compa-ratios to length of service, well as the time each employee has been in their role;
- Factor in your organisation’s job grades;
- Factor in talent scores, which take past performance and potential into account
- Factor in risk scores, if you have these, where you’ve rated the likelihood and impact of each employee’s loss;
- And you’d certainly add in race and gender to test for unfair discrimination.
The issue is, there’s not the time or the resource to examine so many very important variables that explain pay differentiation, or even to highlight unfair discrimination. It’s not an Excel exercise.
A Big Data approach can do exactly what is described above, taking all these factors into account, highlighting where pay differentiation is fair, but also identifying the risk areas where it is not fair. It is visual, in a way that is intuitive and compelling. And it can easily be done again next year (or anytime) with fresh data.
Big Data and HR analytics is thus the only real answer to the question of how we manage Equal Pay for Equal work risk. We may even be contributing to our risk by not doing the analysis.
This is not a theoretical solution – this has already been designed and implemented in exactly the way described above, and can be implemented in any organisation for less than the recruitment fee of one lost middle-manager.
I’m an accredited Master Reward Specialist with a passion for Business Intelligence, Analytics and the benefits that a Big Data approach brings to Human Resources. My company, REM Solutions, is an outsource solution for HR analytics.