Utilising People Analytics To Provide Deeper Insights

The biggest challenge facing organisations today is inflation and the cost-of-living crisis. What role can people analytics play in helping leaders and employees tackle these issues?

The biggest challenge facing organisations today is inflation and the cost-of-living crisis. In this presentation, I will ask a simple question: What role can people analytics play in helping leaders and employees tackle these issues?

Let’s start at the beginning:

HR has been doing analytics for a long time, but it’s fair to say that, in the main, HR analytics (or “people analytics”) has involved a lot of reporting.

That means counting things and measuring the effectiveness of programmes. A good deal of time has been spent on simply getting data about the workforce into shape (agreeing common definitions, cleaning data, and automating reporting).

So in 2016 Janet Marler and John Boudreau were correct, when they did a meta analysis of the field, in stating that people analytics was primarily focused on providing data for better decisions within HR.

The good news is that since then things have started to change. That relatively narrow description has been expanded. The variety of papers in this conference amply demonstrates that people analytics is evolving to address issues that provide far more value.

This shift is partly due to the pandemic. Covid gave organisations a fundamental employee experience “stress test”. HR has been asked to provide better analytics in order to help. Leaders want to know how employee experience is being affected and what this means for people management, performance development, teamwork, collaboration, and productivity.

Another important shift relates to how HR thinks about its own purpose and mission. The function is gradually evolving from an internally-focused and compliance-driven mindset. It’s becoming a more strategic function.

So Jonathan Ferrar and David Green are right to point out, in their recent book, that people analytics now is more focused on providing value. It’s about addressing business challenges and surfacing solutions. Those things need to help the business perform better, they need to support leaders with their priorities, and they should have value for employees too.

So what I want to do in this session is put that to the test. I want to think about how people analytics can provide value when it comes to addressing the biggest challenge facing, organisations, leaders and employees right now.

For sure, the biggest organisational and people challenge at the moment is rising inflation and the cost-of-living of crisis.

Employers are facing a very tough set of problems. You know the headlines. Inflation is the highest it’s been in 40 years. At the same time growth is low. And on top of that the labour market is tricky. There’s a lot of turnover and companies are finding it hard to attract people with the skills they need.

In our research, we see that three-quarters of companies are finding it hard to retain and recruit employees with digital skills and 63% of employers say the same about professional staff in general. In order to fill gaps, most companies have stepped up their recruitment efforts.

In addition, employers are facing pressure from unions and other stakeholders. In the UK, the number of strikes is already at a decades-long high.

For all these reasons, “inflation and financial/market instability” is the Number 1 concern for CEOs (according to the Summer 2022 Fortune/Deloitte CEO Survey.)

From an employee perspective, of course, things are also very difficult:

Employees are under pressure. As an example, again according to our research, 36% of employees say they’re living from pay cheque to pay cheque. One-on-three say financial problems are having a negative impact.

36% of employees are living pay cheque to pay cheque

There’s a cost for individuals and businesses to this. At an individual level, financial wellbeing and anxiety impacts people’s physical, social, and emotional wellbeing too. For businesses, there are operational costs, such as absence and presenteeism (and perhaps “Quiet Quitting”). Of course, people are also more likely to move jobs if they can pick up even a small pay increase.

If you look at the data that sits behind the headline of a “Great Resignation” then it appears there are a lot of people making sideways moves. Some of this may be because people are re-evaluating their job after lockdown. It’s also very likely due to this urgent need to earn more as living costs rise.

In response, employers are having to react. These are some of the changes companies are making:

They’re targeting salary increases and offering one-off payments and they’re investing in broader support and assistance for employees.

These changes are potentially expensive and in some cases they’re being made quickly as an urgent response to events. Rather than being evidence-based, they’re sometimes driven by anecdote and leaders’ instinct. What’s often missing is an understanding of motivation that’s rooted in behavioural science.

What’s often missing is an understanding of motivation that’s rooted in behavioural science

Surely there’s a role for great analytics here?

Let’s begin by trying to break things down a little and to consider the kinds of questions we might want to answer:

At the risk of sounding like Donald Rumsfeld, what are our known-knowns and known-unknowns? More specifically, when it comes to total-rewards, what are we spending money on and are these the things that employees really value?

By total rewards, I mean three things:

1. Foundational elements like pay and benefits
2. Performance-based components like merit-increases and incentives
3. Plus career and environmental dimensions, such as learning and development

Take just benefits, for a moment. In my experience, established companies often have programmes that are designed for their legacy workforce rather than the needs of their future and up-and-coming talent. As such, it’s possible that you’re spending money on things that your mission-critical talent doesn’t really value. This is obviously a waste.

Benefits needs and preferences aren’t static; they change with the times.

One example is how employees’ views about private health in the UK have changed following the pandemic. Health insurance has been seen as a benefit for senior leaders. But there’s growing interest generally in health plans as people struggle to see their GP and get appointments on the NHS. By being more innovative when it comes to health plans both employees and employers can “win”.

Another example is “green benefits”. These can include things like supporting people to buy electric cars or introducing cycling-to-work schemes or investing pensions in sustainably-focused funds. These can help with your overall Net Zero commitments and they’re a way of tapping into the energy that your employees have about climate action.

As well as understanding needs and costs we should also ask ourselves if we’re incentivising the right behaviours. Specifically, are we driving high engagement and motivation? Are we encouraging collaboration and innovation? Are we doing enough to encourage people (that we want to stay) to grow a career here?

And there are other important considerations, such as ensuring we’re building an organisation that’s inclusive and where rewards and recognition are aligned to our values.

What these questions show is that you need to think systemically about total rewards. The danger is that you might “fix” one problem over here, just to create another problem somewhere else.

That’s enough theory.

How can you operationalise this kind of thinking?

The first question we should try to answer is what it is that people really need and want when it comes to their total rewards (so that we’re not simply responding reflexively to problems as and when they occur).

It makes sense to begin with, “what do we already know?” It might be a lot. For example, you know take up rates for benefits and you have feedback on providers, and you can look at data from your Employee Assistance Programmes, and so on.

But even with all that, you may still not be able to answer the question fully.

So you can ask people — through surveys and focus groups, for example. Surveys can be of various degrees of sophistication. We sometimes use Max-Diff surveys in order to force choices.

I find focus groups valuable. We often run them virtually (using a chat-based tool). They provide rich insights and a deep understanding of preferences. However, it’s hard to connect that feedback to specific cost data.

In terms of what you may or may not know already, here’s an example: I’m currently working with a very large tech company that has vast quantities of information about and from their people. I mean “enormous”. They are super data rich. They run very frequent pulse surveys using a survey widget tool. They run lots of polls. They have masses of open feedback on internal social media. They have input from Employee Resource Groups. They get insights from team huddles and other events. But having sifted through it none of it is specific enough to help them answer the exam question for total rewards: “What do employees really need and want?” It’s all noise and no signal.

So if this is the case for you too, how do you get a clear signal — what’s another option?

The approach that we find most useful is conjoint, which you may or may not be familiar with.

In case you’re not, then adaptive conjoint was first used in the 1980s in market research. It’s a way of testing different product attributes to estimate a preference score. It yields better information than asking people about each attribute individually.

That’s because a conjoint survey asks you to make trade offs between different sets of choices. The software is adaptive in that it tries to be efficient by testing the most relevant choices based on earlier responses.

There are two elements. You have to design a Reward Matrix with different rewards and options (typically decrease, stay the same, and increase). You can, of course, also calculate the cost of these options.

And then a conjoint survey tests those in combination. It’s a very different experience from an opinion survey. You have to make some tough choices. And the communication of the survey is important since you’re talking about people’s reward and you’re presenting options where it can decrease.

After running a conjoint survey, you can then use the results to understand the perceived value of different reward elements. This is the second step in what we call Total Rewards Optimization (TRO).

You can run a simulation of the impact on the perceived value of potential reward changes and the implications for costs. Effectively, these are “What-If Analyses”.

For example, are there simple changes that don’t cost much that would be greatly valued? Are there expensive programmes you’re paying for that people don’t actually value very much?

Are there simple changes that don’t cost much that would be greatly valued? Are there expensive programmes you’re paying for that people don’t actually value very much?

The graph on the right (above) shows the change in value for different reward elements and the associated cost

You can also segment the results for different talent and demographic groups. Are you offering rewards that are valued by your long-tenured employees, but not so much by new, younger hires? Can you build a better understanding of the needs and preferences of those critical talent groups you’re struggling to retain or attract?

As a third step, you can then build a model of all the potential options. In this graph, the cost or investment is shown on the horizontal / x-axis and the perceived value on the vertical / y-axis. It also shows an efficient frontier — based on plotting the most efficient allocations at various cost levels.

This means you can find your total rewards “sweet spot”.

For example, that could be spending the same amount of money, but increasing value. Or it could be spending less, because you need to cut cost, but doing so in a way that preserves value. Or perhaps you want to increase value and don’t mind spending a bit more in order to maximise talent retention. The point is that these are options based on analytics rather than instinct.

And typically we run an online simulation that’s used to build different portfolios as an aid to decision-making in a workshop setting:

It’s worth reflecting that traditionally, decisions on rewards have been set from the top-down (think budgets cascading through a hierarchy). The approach I’m outlining here to TRO is about building-in an understanding of employee needs to make sure you’re aware of the impact of those decisions on engagement and behaviour. It’s about understanding and mitigating risks. It’s also about involving people and capturing employee voice.

TRO is about building-in an understanding of employee needs to make sure you’re aware of the impact of those decisions on engagement and behaviour

So that’s the analytics. What happens to those findings? How are they turned into actions?

Here are a couple of examples.

In this first case (below) the analysis was turned into programme changes. This is a large global organisation that was struggling with turnover. Through the analysis they realised they had been too concerned by those foundational elements of total rewards (like pay) and that they weren’t paying sufficient attention to elements like Learning & Development. The analysis was able to quantify the impact of focusing more on L&D which meant there was a business case for investing in some of the programmes shown here. And there was indeed a payoff. Turnover dropped and engagement increased and they saved some money.

This second example is a recent and topical one. It’s from another large organisation that had a focus on recruitment, especially graduates and experienced hires:

In this case, the review of total rewards highlighted a need for more than programme changes. The top priority was actually financial wellbeing — things like assistance, education and tools on topics like clearing debt, building up savings, and applying for a mortgage.

They built a microsite to deliver employees with a semi-personalised experience. Effectively, as an employee, after answering some questions, you’re given a “score” and directed to particular resources that are relevant for your situation.

Their curriculum was based around four life stages. It mainly delivers financial education (as opposed to advice — although you can imagine “robo-advice” being deployed in the future).

It’s proven to be very popular. The resources are all “bite size”, so the average user visit only lasts around 15 minutes. And the peak time of day for accessing the portal is between 5pm and 6pm, in other words as people are transitioning from core working hours. Of course, everything is mobile-first.

The tool and the curriculum has continued to evolve based on feedback.

It’s also part of a broader shift in communications that the company is building out over time, whereby employees are delivered a personalised employee experience. In other words, rather than employees hunting for information on an intranet, as is typical in most places, it’s about delivering content that’s relevant to you, on your phone, in the moments that matter for you.

It’s worth building this point out a little. If people analytics is about providing value to the business and employees, then at heart it’s about improving employee experience (EX).

That might be a bit of a controversial statement here and it certainly requires a longer discussion. But if you ask me “what is people analytics for?” then my answer is “transforming employee experience”.

If you ask me “what is people analytics for?” then my answer is “transforming employee experience”

When I talk about employee experience, I’m including total rewards as one of the core dimensions of EX alongside the work itself, the sense of purpose you get from your job, and the culture and climate of the organisation you work for.

When it comes to thinking this way, there are always three steps to take when “Utilising People Analytics To Provide Deeper Insights”:

1. The first is to begin by really understanding employee needs; this is also a great way to start involving people of course
2. The second is to use those insights to help prioritise and plan changes; your “organisational compass points” here are your people strategy, your values, and your EVP
3. The third is to spark behaviour change through people leadership capability and technology; again involvement is key through design-thinking, testing and iteration

Of course, this all needs to be aligned to some kind of ambition or “blueprint”.

When you start thinking this way, you can broaden your horizons further.

Organisations have traditionally considered people’s experience at work quite narrowly. The focus is on roles, levels, training, compensation, benefits, etc. But it’s just as important to think about what those things mean in human terms.

The goal is to translate ”employee experience” and “the deal” into how I think about “my health, my wealth, and my career”.

When providing value to employees (as well as the business) it’s really about helping me achieve success at work and in life (however I define that.)

So, I’ve covered an awful lot of ground in this talk. But this is where some of my clients that are using people analytics to transform EX are heading.

They’re using people analytics to transform EX through human-centred design that’s based on a deep understanding of needs and wants.

Using people analytics to transform EX through human-centred design that’s based on a deep understanding of needs and wants

This presentation — or at least a version of it, as I skipped around a bit — was given to the HR Analytics Summit in London on the 8th of September 2022.