Conventional views of the relationships among employee attitudes, customer requirements, and financial performance have emphasized their sequential nature. You can think of these variables as successive links in a chain, in which each variable affects the next to drive some ultimate outcome. This perspective suggests that engaged employees create engaged customers who foster organizational success by delivering positive financial outcomes. Though this perspective has some validity, we believe that it fails to convey the true multidimensional nature of the interdependencies among employee and customer engagement and overall organizational financial performance.
Employee engagement does have a direct and measurable relationship to and impact on customer engagement. But, like the ways in which heart rate and respiration interact to speed life-giving oxygen to all parts of the human body, the ways in which these organizational functions interact to enhance a company's financial vigor are more complex than a simple linear chain of factors. Integrating the vital signs of employee and customer engagement into a single performance construct supported by a single performance measure -- the HumanSigma metric -- provides a comprehensive means to capture and understand this dynamic system. This is because the combined impact of a company's human systems taken together is substantially greater than the effects of the individual systems separately.
Our first experience with the power of this dynamic interaction of employee and customer engagement arose quite by accident. Several years ago, we were working with a large retailer to measure and improve its customer and employee relationships. As part of this process, we collected metrics on employee and customer engagement for each store in the chain. Not surprisingly, our analysis found strong linkages to financial performance for each separate measure.
Within the stores, these two performance indicators were reported and acted on independently of one another because, as with most such measurement programs, different functional groups within the company owned the individual parts. The corporate human resources department owned the employee engagement initiative, while store operations owned the customer measurement initiative. As you might expect, there was no formalized interaction between or integration of the two teams responsible for these programs. They rarely, if ever, communicated with one another.
One day, however, the corporate owner of the employee engagement program ran into his counterpart on the customer side at lunch in the company cafeteria. A lively discussion about the two programs ensued. It became clear that the top-performing stores were using some best practices that could be transferred to stores where employee and customer engagement were gaining considerably less traction.
With the best principles of the service-profit chain in mind, the two program owners decided that it might be interesting to compare notes on which stores were the best on each performance indicator. After all, if the sequential service-profit chain model was correct, we would expect there to be considerable overlap between the two groups of best-performing stores.
To perform the analysis, we first identified the 10 highest and 10 lowest performing stores based on their success in engaging employees. We then identified the 10 highest and 10 lowest performing stores based on their success in creating customer engagement. Our working assumption, given the demonstrated statistical linkages between employee and customer engagement, was that some of the top performers in creating employee engagement would also be among the group of top performers in developing engaged customers. Unfortunately, we were wrong: Just one store appeared on both lists. Somewhat nonplussed, we went back to the data in search of an explanation.
As we began to work through the implications of these findings, we made an intriguing discovery. Stores that performed well (those that scored in the top 50% of all stores on the measure) in employee and customer engagement -- even though they may not have had the highest scores on either metric -- tended to deliver considerably better financial results than those that scored poorly on the two measures. Furthermore, stores that performed well on both measures also outperformed those that scored high on one but not the other of these metrics.
Just as respiration and heart rate combine to efficiently and effectively deliver life-giving oxygen and nutrients to the entire human body, customer and employee engagement interact to promote an enhanced level of financial vigor throughout the organization. This relationship is depicted graphically by plotting individual stores' scores on these metrics along two axes representing local employee and customer engagement scores, with each dot representing an individual store in the chain. (See the graphic "Optimized.") By looking at the "scatter" of the points, it's easy to see the considerable variation in performance on employee and customer engagement at the local level.
Our subsequent research has confirmed that this pattern holds true not just for the large, multi-store retailer in this example, but also for companies of different sizes and in various industries. When viewed from the perspective of local business unit performance, customer and employee engagement . . . potentiate one another, creating the opportunity for accelerated improvement and growth of overall financial performance.