Research: How Employee Experience Impacts Your Bottom Line
Executives might be more accustomed to seeing business cases and ROI calculations from marketing and sales teams, but they should start empowering talent departments to make their own case. Why? Because customer-facing employees and revenue are strongly linked, the authors find. In their research, stores whose customer-facing employee base was more tenured, had more experience in prior rotations, was higher skilled, and was more skewed towards full time, generated a 50% increase in revenue.
Most people believe — and research backs them up — that great customer experience drives revenue growth. But who claims credit for these successes? Marketing departments will point to advertising campaigns and brand awareness efforts that coincide with above-normal sales growth. Product teams can quantify the impact of specific features on customer satisfaction or increased revenue. Sales teams of course view themselves as the go-to group for bringing revenue in the door. But what about Human Resource departments?
Employees, especially customer-facing employees, would seem to play a central role in customer experience. As consumers in our daily lives, this link seems intuitive: a single interaction with an employee can make or break your experience in a store, at the doctor’s office, on a telephone call, or even via virtual interactions such as chat or social media. Yet, for executives leading businesses, the role employees play in creating a great customer experience, or more generally in driving revenue, tends to be a lot less clear — because it can be so difficult to quantify.
Recent research has begun to explore this link, showing that companies that perform well on employee experience metrics also tend to perform well on customer experience metrics, and suggesting that improvements in employee satisfaction can drive improvements in customer satisfaction. But these studies have limits when it comes to establishing a causal link. Because the results are based on organization-level data, we can’t say for sure that employee metrics are really what’s driving business outcomes — and not for example a bad press cycle or a great new product launch that’s impacting both employees and customers.
We wanted to go a step further and see whether we could get closer to identifying — and quantifying — this causal impact of employees on customer experience and business outcomes like revenue and profits. Proving this out would not only represent compelling new evidence about how much employee investments matter, but also show executives the power of quantifying these ROIs in their own organizations.
In order to do so, we needed to get internal data from an organization whose business relied heavily on customer-facing employees. We settled on a large global retail brand that agreed to share its anonymized data for research purposes. To zero in on the impact of employees on customer decisions, we focused on a particularly service-oriented in-store department — staffed with employees who interact directly with customers, provide them with a bespoke product, and are generally expected to be knowledgeable and helpful. We ultimately obtained three years of in-depth employee and financial data from over 1,000 of these brick-and-mortar locations across the U.S.
Our question was: does the composition of customer-facing employees in these locations — all else equal — affect revenue and profits?
The results were striking. Not only were we able to establish a clear link between employees and revenue, but the impact was substantial. In fact, if an average store could move from the bottom quartile to the top quartile in each of the employee experience metrics we studied, they would increase their revenue by more than 50%, and profits by nearly as much.
Here’s how we did it.
The analysis: Breaking down the siloes between employee and financial data
First, we took monthly revenue and profit statements from each of these stores. We standardized these financial outcomes by dividing by the total employee-hours worked in each store each month. The resulting variables — hourly revenue and profit — represent a measure of employee or labor productivity that can be compared across stores of different sizes.
Next, in order to quantify the employee side of the equation, we selected a handful of metrics which were readily available in the company’s standard internal HR information system, including employee longevity, full time/part time status, internal rotations, and skill level. These were not of course meant to represent an exhaustive catalog of employee experience generally. There are plenty of other components of employee experience that are likely to affect sales and service quality, such as self-reported employee well-being, within-team diversity, formal training, or the use of employee communication/productivity technologies. When data on these other factors are available, they can easily be incorporated into the analysis framework we describe. (In fact, doing so is likely to reveal that employees have even larger effects on customer satisfaction and financial outcomes than we estimate here.) Still, our metrics constitute core aspects of employee experience, and as we shall see, strongly impact sales and profitability.
By combining financial data with people data — two sources of information that tend to be siloed in different departments and rarely integrated — we were set up to answer our central question: whether the employee composition at the start of each month would impact the sales generated in that store over the course of that month.
To isolate the effects of employees on revenue, we used multivariate regressions and controlled for factors like time of year, demographics and income of surrounding areas, and local demand shocks. Again, the fact that we studied multiple business units from a single company and one nationally recognized brand was crucial. This represented a powerful control variable, because we were able to hold constant things like brand strength and reputation over time, quality of equipment and website, and nature of business. In comparison to studies that use only external, company-level data, this enabled us to more effectively isolate the causal effects of employee metrics on customer decisions and revenue.
All together with our control variables and the panel nature of the data, we were confident that our estimates of the impact of employee metrics would represent a causal relationship: employee experience drives customer experience which in turn drives revenue growth.
The results: Employee experience drives revenue
We indeed found that changes in these measures of employee experience were a strong driver of subsequent revenue. Put simply, stores whose customer-facing employee base was more tenured, had more experience in prior rotations, was higher skilled, and was more skewed towards full time generated far more sales per hour. In fact, if an average store could move from the bottom quartile of performance to the top quartile in each of the four dimensions it would go from generating $57 per person-hour worked to $87 per person-hour. That’s more than a 50% increase in revenue. And these revenue increases were not accompanied by skyrocketing expenses. In fact, a parallel analysis of operating profits showed that a similar shift in employee experience would result in a 45% increase in profits per person-hour, from $41 to $59.
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These differences are dramatic. Consider a simple ROI calculation of moving a store from the bottom quartile to the top quartile. The store currently spends $16 per employee-hour and generates $41 in profits. By investing an additional $12 per hour to get to the top quartile of employee experience, the store will earn an extra $18 per hour of profit. That’s a 150% ROI!
To be sure, this ROI calculation is simplistic and perhaps too ambitious to reflect a realistic strategy. Improving employee metrics so dramatically might not be feasible overnight, and our back-of-the-envelope accounting logic doesn’t include other associated costs (e.g., of implementing a technology for employees designed to keep them happier and reduce turnover) nor does it acknowledge the time-dynamic effects of realizing impact. In our research, we also considered more realistic scenarios and modeled them within more sophisticated accounting frameworks. One example supposed the CHRO set targets for each store — stores in the bottom half of each metric have to raise their performance up to the median, and stores in the third quartile have to raise their performance up to the 75th percentile — which, if successfully achieved, would correspond to a 6% increase in total annual revenue across the company as a whole. With some basic assumptions about discount rates, time to impact, and additional up-front costs, we find that the 5-year ROI of this employee investment would be around 30%, and the 10-year ROI would be in excess of 80%.
This is just an illustrative example and we are not here to debate specific choices about feasible talent management strategies or accounting parameters. We leave these decisions to on-the-ground store managers and experts in financial modeling — our point is simple. Establishing a clear link between employee experience metrics and financial outcomes, and quantifying this relationship paves the way for both data-driven talent strategies and concrete ROI calculations for people-related investments.
The takeaway: Empowering HR to make their business case
The numbers we present here are of course to some extent specific to the company that we studied. But we believe the effects we’ve uncovered are large enough to convince executives that they need to recognize the impact their people have on customer experience and revenue. Any organization that has customer-facing employees should realize that they matter immensely to business success. They are not simply a cost to be minimized — as retail, call center, and service employees are far too often thought of by executives — but potentially very high impact investments. How much is it worth to your organization to reduce turnover of top talent by 20%? How about to improve employee satisfaction scores by 10%? How much is it costing your organization not to know these answers?
Executives might be more accustomed to seeing business cases and ROI calculations from marketing and sales teams, but they should start empowering talent departments to make their own case. Just imagine an HR leader presenting numbers like these the next time they are seeking budget for a training program or an employee wellness software.
By capturing and connecting the right data, executives will begin to see the link between employees, customers, and revenue. The results may inspire them to take a fresh look at the role CHROs play in corporate growth. Indeed, with business cases like this, HR should finally be able to shed its age-old “cost-center” reputation and start stepping up to its rightful place — a strategic function that drives both customer experience and revenue. The stage will then be set for what we believe will constitute the next generation of solutions: technologies that don’t just integrate across, but fundamentally break down the silos between employee, customer, and business data; that build this kind of intelligence into every business process; and that solve for the employee-customer-business synergy from the beginning.