Compensation data and analytics - a fresh perspective

What is competitive pay? How do we determine if someone is overpaid? Underpaid?

For over 60 years, the primary way for companies to answer these questions has been to consult a compensation survey. Yes -- the compensation survey dates back to 1951. In that year, a McKinsey & Co consultant named Arch Patton was hired by General Motors to conduct a multi-industry survey of executive salaries. The survey appeared in the Harvard Business Review for over a decade before moving to McKinsey Quarterly.

History of compensation surveys

Most companies rely on compensation surveys to assess the competitive, “market rate” of pay (typically defined as the 50th percentile or median of a comparable group of companies) and use that market rate as a major factor in determining the compensation of roles throughout the company.

Today’s compensation surveys have expanded to include additional elements of pay and extend deeper into organizations. But they are still based on a comparison of standard roles or “benchmark jobs”, such as CEO, Top Sales Executive, or Financial Analyst, even though many of these roles may differ greatly across companies and across countries. Firms that conduct surveys therefore engage in a process to control for these differences predicated on a labor intensive process of “job matching” by the companies that provide data to the surveys.

So, ultimately (and perhaps surprisingly), not much has changed about compensation surveys since 1951 despite myriad changes in the world of business, data, and analytics. I believe that is about to change...

Challenges with traditional surveys

Undoubtedly, there are some truly "benchmark" jobs across organizations. However, in today’s market, roles are much more fluid. Entry level accountants may be expected to combine technology and accounting skills at some companies, but not at others. Some sales professionals may have responsibilities for the broader customer experience while others don’t. Even historically standard executive roles, such as CFO, are changing and combining multiple competencies.

Another challenge with traditional surveys is that new roles are emerging in many industries and companies. “e-commerce” and “digital” are characteristics of marketing roles that didn’t exist even 10 years ago. Operations roles may now include “supply chain” and “sustainability” skills. It is hard for traditional compensation surveys to keep up with these new and hybrid roles.

And finally, while many companies have become truly global, with a mix of local and “mobile” employees, compensation surveys are generally limited to “home country” positions on a country-by-country basis with limited availability to assess global labor markets.

An approach to compensation data for the 21st century

Meanwhile, human capital data is (finally) becoming more robust at many companies. Cloud-based human capital management (HCM) systems, and self-service analytics tools such as Tableau and Qlik are making human capital data more accessible to human resources professionals. The associated flexibility allows companies to be more tailored in their analysis of data about their people.

These tools and techniques are making their way into the collection and analysis of compensation data as well. For example, Borderless Pay Insights is a relatively new compensation database and analytic tool that addresses many shortcomings of the old-style compensation survey by putting the data and analytics in users’ control.

Instead of relying on “benchmark” jobs (which may comprise only 50% or less of overall executive positions), the Borderless database includes data on all executive roles, across all countries. Users can analyze data across multiple countries and job families to assess new and hybrid roles in their organizations. Using online, graphical tools, human resource professionals can conduct multiple “what if” analyses to assess compensation and mobility packages instead of relying on a single “survey” number.

According to PwC’s 2017 Annual Corporate Directors Survey, 70% of corporate directors (who are responsible for approving executive pay levels) believe US executives are overpaid! This impression may be a result of the limitation of current approaches to “competitive pay analysis”. That is, a singular reliance on role-based, percentile-driven competitive pay data has contributed to concerns in data validity and “ratcheting” of pay over time.

Access to a more holistic and global data set such as that introduced by Borderless will allow compensation professionals to provide additional context around pay levels to decision makers, including elements of internal equity (across countries and roles), changes in executive demographics over time, and the impact of the global workforce. Accordingly, the outputs and insights from the data set and related tools will introduce a new level of discourse about executive compensation decisions.

I think even Arch Patton would approve!