Including Rewards In People Analytics

The field of of people analytics has seen rapid growth over the last years. As someone who has explored the links between people and performance throughout my career, it’s been great to see this explosion of interest.

There are various definitions of people analytics, which is sometimes called HR analytics or workforce analytics. Janet Maher and John Boudreau call it “An evidence-based approach for making better decisions on the people side of the business; it consists of an array of tools and technologies, ranging from simple reporting of HR metrics all the way up to predictive modelling.”

Jonathan Ferrar and David Green in their book Excellence in People Analytics emphasise the importance of using people data to provide business value. They describe different ages in the evolution of the field with most companies now focusing on supporting leaders to navigate key challenges: “People analytics is an absolute must-have for any Chief Executive Officer or Chief Human Resources Officer.”

There is a potential hitch in all this progress, however. HR has long been a siloed function and it strikes me that this characteristic is being reflected in the work that is now published and shared in the people analytics community. Recent people analytics books, collections, conferences, and articles all seem to have a glaring gap; hardly any of them make any mention of rewards.

Recent people analytics books, collections, conferences, and articles all seem to have a glaring gap; hardly any of them make any mention of rewards.

There are a few notable exceptions. There has been some great work looking at gender and ethnicity pay gaps, for example. It’s also true that, because of the nature of rewards work, it can be harder to share the outputs in public. But in the main, reward analytics operates as a separate field from people analytics, just as rewards is usually a separate sub-function from talent. Even though rewards is full of data-savvy and analytically-minded people. This feels like a missed opportunity.

That’s because decisions about rewards are important business ones. Payroll is a significant percentage of revenue. Companies source and offer a complicated mix of pay, incentives and benefits. It’s an area where smart analytics can provide a lot of business value and generate a return on investment.

Reward design choices are also important human decisions. Rewards carry emotional as well as practical weight. A lot of organisational energy is spent discussing them. And incentives affect behaviour, often in oblique ways.

Getting total rewards right can mean the difference between competing effectively in the global talent marketplace and being left behind. A consumer-grade total rewards portfolio of pay, benefits, wellbeing and career programmes serves as a catalyst, driving attraction, retention and engagement of talent essential to business success. Yet, in many organisations, total rewards are not evolving quickly enough to keep pace with changes in the world of work.

All of this underlines that when it comes to employee experience (EX), rewards obviously matter. It’s why in our work we include total rewards as one of the four key dimensions of a High-Performance EX, as shown below:

Let me expand on this point about employee experience. I have written quite a bit about EX, and one of the things I believe strongly is that EX requires a shift in perspective. In essence, it means moving away from a traditional and top-down view of organisations towards a messy, conversational, and more personal view of life at work.

From an EX point of view, therefore, all the following things are super-interconnected: jobs, work, performance, skills, careers, learning, pay, benefits, inclusion, engagement, well-being, communications, culture…

It’s a blatantly obvious point, but worth stating — employees don’t experience life at work through a HR lens. Rather, HR needs to think about organisational effectiveness from an employee perspective. That’s the fundamental trick in making EX work.

The same logic applies to people analytics. Talent metrics only address part of the humans and work equation. If you exclude rewards, you’re not capturing the whole picture and you’re not thinking systemically.

Talent metrics only address part of the humans and work equation. If you exclude rewards, you’re not capturing the whole picture and you’re not thinking systemically.

So what does it look like to bring reward into people analytics? One example is the work we do around optimisation. Specifically, Total Rewards Optimisation (TRO) allows you to align reward investments with the employee experience. We talk about finding the “sweet spot” — the intersection that aligns what and how much you spend on total rewards with what your employees value most and least across what you offer — while uncovering how reward changes affect employee behaviour and performance on the job.

There are four key parts to TRO:

  • Understand which rewards employees value most and least using conjoint analysis, a survey methodology used in market research to understand customer preferences. You can also pull in selection data from your flex and benefit programmes to understand actual employee choices and trade offs. We also bring in employee engagement, retention, and performance data in order to analyse the linkages.
  • Assess the return on your total rewards investment, as well as the impact of the programme on your workforce, by combining employee preferences with financial data. We model various investment scenarios in order to help leaders decide how much to spend and where to get the best possible results for the right size of investment.
  • Use data to understand what employees see as the most and least valuable components of their reward packages. We help leaders make investment decisions and deliver a talent value proposition that is likely to foster desired attitudes and behaviours at a cost the organisation can afford.
  • Use segmentation to understand the different priorities and attitudes of a diverse and multigenerational workforce towards benefits, cash and work/life balance and build a competitive edge in attracting, retaining and engaging top talent.

To my mind, TRO is a great piece of people analytics. It’s got interesting and important data, cool maths, fun modelling, nice data visualisation. More importantly, you’re linking together employee preferences and behaviours to business and financial data in order to understand trade-offs and ROI. And those scenarios are typically explored interactively with leaders as different hypotheses are tested and analysed.

My broader argument, however, is that this is an example of how it’s possible to include rewards in people analytics and that this is an important thing to do. It’s one thing to look at engagement, retention and performance drivers for your key talent, and to make decisions based on that data. It’s another to look at those things alongside what you spend on total rewards and how you shape, customise and communicate your value proposition. The latter is taking a step towards thinking holistically about employee experience.

This is especially important right now as leaders are acutely aware of the importance of retaining and attracting key talent in the midst of a period of high turnover. Rather than throwing money at a problem, finding the sweet spot matters more than ever.

There’s also a point here about the state of people analytics at the current time. It’s possible to see the recent rapid growth in people analytics as a transitory moment. A point when data became more available and HR began to explore how it can be used for improving decision making. At first, growth in analytics has mostly occurred with a traditional HR mindset, within HR silos, reflecting long-held budgets and distinct backgrounds and skillsets. But in the near future, the picture might look quite different. As datafication continues apace, the current people analytics community may merge with others to become the analytics engine of an EX function or even an EX analytics team within a business intelligence function. In some of my clients, this shift is already happening.

As datafication continues apace, the current people analytics community may merge with others to become the analytics engine of an EX function.

Jonathan Ferrar and David Green also refer to this kind of transition in their recent book, as they herald a new Age of Excellence in people analytics where “the human resources function itself becomes even more data literate.”

A key question for me is whether that means “business as usual” (such as continuing to think in HR terms) or taking a leap and embedding analytics and design thinking within a truly EX mindset.

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