Data Use: Using key driver analysis to guide employee satisfaction research

Editor’s note: Dave Leonard is the founder of Focus on Service LLC, a

Multi-unit retailers and restaurants spend a lot of money and effort trying to understand and manage the thousands of employees in many different locations. Results are typically evaluated on a company level as part of an annual business review. However, this is not the whole picture. Basically, when you are looking at the company, all units are assumed to be “average.” This misses significant inter-unit variation and the opportunity to improve performance or correct problems at a specific location.

A basic problem is that we can always “know more than we can prove.” Managers of large, multi-unit companies “know” the following:

• management teams at different locations aren’t equally effective;

• unit management impacts employee performance;

• employee performance impacts sales and customer satisfaction; and

• management performance impacts employee turnover and morale.

But how do you “prove” it? More importantly, how do you identify the specific areas that each unit management needs to improve? And most important, what do they need to do differently that will improve employee performance and guest results?

The cost of turnover

Most managers know that employee turnover is expensive, but a large majority were unable to quantify the cost of turnover when asked in a recent poll. The cost of hiring and training a new employee can vary greatly - from only a few thousand dollars for hourly employees to between $75,000 and $100,000 for top executives. Costs that are more difficult to estimate include customer service disruption, emotional costs, loss of morale, burnout/absenteeism among remaining employees, loss of experience, continuity and “corporate memory.”

Another truth is that unit managers in multi-unit companies hold most of the keys to keeping the right talent.

Case study

The following case study demonstrates methodologies to measure employee attitudes and how to gauge key factors to keep employees happy and productive. We explore a framework within which employee satisfaction can be measured and then describe a concrete methodology to apply these findings to the workplace.

By using Palm Pilots to implement a unit-level employee survey, we were able to complete three surveys for the cost of one written/paper-based survey. This provided the client company with a snapshot of results more frequently and allowed the individual locations to measure their progress three or four times a year.

Identify the issues

Our client company, Company A, has more than 100 locations structured in regions and employs several thousand people. In our survey, more than 40 questions were initially asked covering training, management, personal development, the company and customers.

The test objectives were to identify the issues that were most important for employee retention and lower turnover. We sought to demonstrate that significant employee differences can be measured between individual units, and to develop action reports for region/unit managers that highlight differences between units.

Key driver analysis measures the strength of descriptive attributes or performance ratings in relation to a strategic characteristic. What is driving your brand in its market segment? What would make its market share rise? What makes your employees happy at work? Why?

In regression analysis the strategic characteristic is called the dependent variable. What we are looking for is significance. If an attribute is positively significant, this indicates that it has a positive relationship with the dependent variable. If the attribute is high, the dependent variable is high. If the attribute is low, the dependent variable is low. If an attribute is negatively significant, the opposite is true. High attribute, low dependent variable.

In researching employee satisfaction, the dependent variable should not be defined only as the goal of the employer (that is, employee retention, employee satisfaction, etc.). It should also include an evaluation of the impact on customer satisfaction. We are looking for the “why.” Why are employees going to remain with the company? Why are they satisfied with their jobs? What aspects of their employment drive their satisfaction? How does their performance impact guest visits and sales?

The survey was constructed as a series of statements within six different categories. Employees were asked to use a 1-7 scale to rate whether a particular aspect of the unit was important or whether they agreed or disagreed with statements about their place of employment or the company in general.

Results

Table 1 shows the relative area or category importance contributing to employee intent to stay. These normalized relative importances (adding to 100 percent) give an indication of the importance of the overall areas of employee concerns.

After running regressions of the individual questions on the employee survey, the results indicated that there were eight attributes that positively drive intent to stay. Five were negatively significant.

Figure 1 shows the specific eight key question drivers for employee retention. The beta scores are to be interpreted relative to each other. For example, if “It is fun to come to work” has a beta of .26, and “I receive regular feedback about my performance” has a beta of .12, we can say that fun at work is roughly twice as important as regular feedback.

There were also five questions that were negatively related to intent to stay. In order to interpret negative drivers, it is useful to insert a “not” within the attribute. In Figure 2 we have inserted this for further illumination.

Based on the findings shown in Figure 2, we were able to advise our client on immediate actions to improve employee perceptions and performance. The company needs to reinvest in management communication, employee health plans and training.

The power of regression analysis is that it can be run by filtered groups to more fully analyze intent-to-stay priorities. For example, length of employment affects intent-to-stay priorities. Employees with more than two years of experience put more emphasis on: “manager teamwork,” “receive regular feedback,” “boss treats fairly,” “products well received,” and “seek to increase sales.” Employees with less than two years of experience are more concerned with: “staff is happy,” “company pride,” “high standards at the company,” “receive enough training,” and “regional management cares.”

The various staff positions have differing priorities linked to employee retention. (It is often important to filter the regression by key groups in order to produce more precise, actionable results.) For example, point-of-sale employees (cashiers, salespeople, etc.) focused more on understanding the retail process (e.g., understand computer systems, promotion and being well trained), whereas backroom employees wanted a supervisor who cares and to be able to sell products that are well-received. Both of these were highly correlated with intent to stay.

Beyond the statistical “proof” developed in our initial testing and development of the employee survey, we also tracked unit sales, guest satisfaction and employee retention over 12 months. Management teams that were able to drive their employee ratings consistently higher:

• outperformed the company results on customer satisfaction;

• outperformed the company on sales results; and

• improved their employee retention and beat the company results.

Vital challenge

Measuring and improving employee retention is an increasingly vital challenge, essential to the smooth function of multi-location operations that involve far-flung management and staff personnel. Combining the reduced technology costs of Palm Pilots with the power of regression analyses identified what was important to improving performance and provided a measurable basis for each unit to target the specific areas that needed to improve.

Not all management teams are equally good at communication, training, etc. The employee survey system that was developed let them “know” their real effectiveness on the important issues impacting their employees’ performance - and what to do about them to help improve the customer experience.