Profits Per Partner Expected To Go Up Over The Next Year

Profits Per Partner Expected To Go Up Over The Next Year – A review of several years of financial and employee data from global retailers reveals a significant impact.

Conclusion. Leaders may be more used to looking at the business case and ROI calculations of the marketing and sales teams, but they should start reaching out to the talent department to build their case. How could that be? Since employee and customer revenue are so closely related, find the author. In their study, stores with a more employee-based customer base had more experience in previous rotations, were more skilled, and focused more on full-time employment, increasing revenue by 50%.

Profits Per Partner Expected To Go Up Over The Next Year

Most people believe, and research confirms, that a great customer experience leads to increased revenue. But who can claim this success? The marketing department demonstrated advertising campaigns and brand awareness efforts that coincided with normal sales growth. Product groups can identify the impact of specific features on customer satisfaction or revenue growth. The sales team definitely sees themselves as the main team bringing revenue to the door. But what about the human resources department?

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Employees, especially customer-facing employees, play a central role in the customer experience. As consumers in our everyday lives, this link seems intuitive: a single interaction with an employee can make or break your experience in a store, doctor’s office, phone call, or even through virtual interactions such as chat or social media. However, for the executives who run the company, the role that employees play in creating a great customer experience, or in generating revenue in general, is a little less clear because it can be very difficult to define.

Recent research has begun to explore this relationship, showing that companies that perform well on employee experience measures tend to do well on customer experience measures, suggesting that increased employee satisfaction can lead to increased customer satisfaction. However, this study has limitations in establishing causal relationships. Because the results are based on organization-wide data, we can’t say with certainty that employee performance is actually driving business results, rather than, say, weak press releases or new product launches affecting them. both employees and customers.

We wanted to go further and see if we could get closer to identifying and measuring the impact these employee causes have on customer experience and business outcomes, such as revenue and profit. Demonstrating this not only provides compelling new evidence of the importance of employee investment, but also shows leaders the power to determine that ROI in their organizations.

To do this, we need to obtain inside information from organizations whose business relies heavily on customer-facing employees. We selected major global retail brands who agreed to share their anonymous data for research purposes. To focus on the influence of employees on customer decisions, we have a dedicated in-store service department, which is made up of employees who interact directly with customers, provide customized products for them, and are generally competent and approachable. . Ultimately, we obtained three years of in-depth financial and employee data from these more than 1,000 physical locations in the United States.

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Our question is: Does customer-facing staff at these locations, all considered equal, affect revenue and profits?

The results are surprising. Not only were we able to establish a clear relationship between employees and earnings, but the impact was significant. In fact, if the average store could move from the lower quartile to the upper quartile on every employee experience measure we studied, it would increase its revenue by more than 50% and its profits by almost that much.

First, we obtain monthly revenue and profit reports from each of these stores. We standardized this financial result by dividing the total employee hours worked in each store. The outcome variables—earnings and hourly earnings—represent measures of employee or labor productivity that can be compared across stores of different sizes.

Next, to determine employee size from the equation, we selected a number of metrics available in the company’s standard internal HR information system, including employee longevity, full-time/part-time status, internal rotation, and skill level. . This is of course not meant to represent a complete record of employee experience. There are many other components of the employee experience that can affect sales and service quality, such as self-reported well-being, diversity within teams, formal training, or use of communication/productivity technology for employees. When data on these other factors are available, they can be easily incorporated into the analytical framework we describe. (In fact, doing so could reveal that employees are contributing more to customer satisfaction and financial results than we anticipated here.) However, our metrics are a key aspect of the employee experience, and as we’ve seen, they have a huge impact. strong. on sales and profitability.

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By combining financial data with people data, two sources of information that are usually stored in different departments and rarely combined, we answer our main question: whether staffing will have an impact at the start of each month. about the sales made at that store during that month.

To isolate the effect of employees on income, we use multivariate regression and control for factors such as time of year, demographics and income of the surrounding area, and demand shocks. Again, the fact that we study multiple business units of the same company and a nationally recognized brand is important. This is a strong control variable because we are able to maintain constant elements such as brand strength and reputation over time, equipment and website quality, and the nature of the business. Compared to studies using only external company data, this allows us to further isolate the causal effects of employee metrics on customer decisions and revenue.

Combined with our control variables and the nature of the data panels, we believe that our estimates of the effects of employee actions are causal: employee experience drives customer experience, which in turn drives customer experience. increased revenue.

In fact, we found that this change in employee experience measure was a strong predictor of subsequent earnings. Simply put, a store with a customer-facing employee base that has more employees, has more experience in previous rotations, is more skilled, and is more focused on the regular job generates more sales per hour. In fact, if the average store could move from the lowest job quartile to the top quartile on each of the four dimensions, it would go from $57 per person to $87 per person. This is a revenue increase of more than 50 percent. And this increase in revenue has not been accompanied by skyrocketing costs. In fact, a parallel analysis of operating profit shows that a similar change in employee experience results in a 45% increase in profit from $41 to $59 per hour.

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This difference is dramatic. Consider a simple ROI calculation for moving stores from the lower quartile to the upper quartile. The store currently costs $16 per employee per hour and makes a profit of $41. By putting in an additional $12 per hour to reach the top quartile of the employee experience, the store earns an additional $18 for each hour of profit. That’s 150% ROI!

Of course, this ROI calculation is simplistic and may be too ambitious to reflect the actual strategy. Significantly improving employee metrics may not be possible overnight, and our back-of-the-envelope accounting logic excludes other related costs (such as implementing employee technologies designed to keep employees happy and reduce turnover) or recognize their dynamics. effect over time the realization of the effect. In our research, we also consider real scenarios and model them in a more sophisticated accounting framework. The example assumes that CHRO has set goals for each store: stores at the bottom of each metric must increase their performance to the median, and stores in the third quartile must increase their performance to 75 percent, which if met with a 6 percentage increase in the company’s total annual turnover would be appropriate. With some basic assumptions about discount rates, time of impact, and additional upfront costs, we find that the 5-year ROI for this employee investment will be around 30% and the 10-year ROI will be more than 80%.

This is just an illustrative example, and we are not here to discuss specific choices about possible talent management strategies or accounting metrics. We leave this decision to field managers and financial modeling experts – our point is simple. Establishing a clear relationship between employee experience metrics and financial outcomes and measuring that relationship paves the way for data-driven talent strategies and concrete ROI calculations for people-related investments.

The figures we present here are certainly rather specific to the companies we study. But we believe that the effect we found is large enough to convince leaders that they should recognize it

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