Using Driver Analysis to Improve Employee Loyalty

Buffer

Researchers have shown a consistent relationship between employee attitudes and customer attitudes. Specifically, they have found that satisfied/loyal employees, compared to dissatisfied/disloyal employees, have more satisfied customers. Examining different bank branches, Schnieder & Bowen (1985) found that branches with satisfied employees have customers who are more satisfied with service and are less likely to churn compared to branches with dissatisfied employees. Companies must consider employees’ needs and attitudes as part of their overall Customer Experience Management (CEM) strategy. Employees, after all, impact everything the customers see, feel, experiences. From marketing and sales to service, employees impact each phase of the customer life cycle, either strengthening or weakening your company’s relationship with the customer.

Ensuring employees are satisfied and loyal is essential to building long-lasting relationships with your customers. In my prior post, I presented an employee survey that you can use to ensure you are providing your employees with the necessary tools, information, work environment and support for them to be satisfied with and successful at their job. In this week’s post, I will demonstrate how to analyze the resulting data from that employee survey. The goal of the analysis is to help you prioritize efforts to improve the quality of the employee relationship.

The Optimal Employee Survey

Your optimal employee relationship survey needs to include a set of questions that are designed to help you improve the employee experience at work and employee loyalty. I have created an employee survey, the Employee Relationship Diagnostic, that measures the four key areas regarding the employee relationship. These sections and their questions are:

1. Employee Loyalty – 3 questions (overall sat, recommend, intent to leave)
2. Employee Experience – 26 employee experience questions for work attributes across the employee life cycle
3. Relative Performance – 2 questions asking about competitive ranking and reasons behind ranking
4. Company-Specific Questions – (e.g., reasons driving ratings, demographics)

This employee survey is designed to help companies gain key employee insights in 4 areas: 1) Determining employee loyalty and satisfaction levels; 2) Identifying reasons behind dis/loyalty; 3) Prioritizing improvement efforts; 4) Gaining competitive benchmark.

Analyzing the Employee Survey Data: Two Key Pieces of Information

After the employee survey is conducted and the employees have provided their feedback, the next step is analyzing the survey data. We will focus on two of the sections of the survey: Employee Loyalty and Employee Experience. Using the Employee Relationship Diagnostic, here are the measures:

1. Employee Loyalty: Measures that assess the likelihood of engaging in positive behaviors. I use three questions to measure employee loyalty: 1) Overall satisfaction, 2) Likelihood to recommend and 3) Likelihood to leave (reverse coded). Using a 0 (Not at all likely) to 10 (Extremely likely) scale, higher ratings indicate higher levels of customer loyalty. A single employee loyalty score, the Employee Loyalty Index (ELI) is calculated by averaging the responses across the three loyalty questions.
2. Satisfaction with the Employee Experience:  Measures that assess the quality of the employee experience. The employee survey includes 26 specific employee experience questions that fall into five general work areas: 1) senior management, 2) focus on the customer, 3) training, 4) performance management and 5) Compensation. Using a 0 (Extremely Dissatisfied) to 10 (Extremely Satisfied) scale, higher ratings indicate a better employee experience (higher employee satisfaction).

Summarizing the Data

You need to understand only two things about each of the 26 employee experience questions: 1) How well you are performing and 2) The impact on employee loyalty (e.g., how important it is in predicting employee loyalty):

1. Performance:  The level of performance is summarized by a summary statistic for each employee experience question. Different approaches provide basically the same results; pick one that senior executives are familiar with and use it. Some use the mean score (sum of all responses divided by the number of respondents). Others use the “top-box” approach which is simply the percent of respondents who gave you a rating of, say, 9 or 10 (on the 0-10 scale).  So, you will calculate 26 performance scores, one for each work attribute. Low scores reflect a poor employee experience while high scores reflect good employee experience.
2. Impact:  The impact on employee loyalty can be calculated by simply correlating the ratings of the work attribute with the employee loyalty ratings. This correlation is referred to as the “derived importance” of a particular work attribute. So, if the the survey has measures of 26 work attributes, we will calculate 26 correlations. The correlation between the satisfaction scores of a work attribute and the employee loyalty index indicates the degree to which performance on the work attribute has an impact on employee loyalty behavior. Correlations can be calculated using Excel or any statistical software package. Higher correlations (max is 1.0) indicate a strong relationship between the employee experience and employee loyalty (e.g., work attribute is important to employees). Low correlations (near 0.o) indicate a weak relationship between the employee experience and employee loyalty (e.g., work attribute is not important to employees).

Figure 1. Employee Loyalty Driver Matrix helps you prioritize improvement initiatives.

Graphing the Results: The Loyalty Driver Matrix

So, we now have the two pieces of information for each work attribute: 1) Performance and 2) Impact. Using both the performance index and derived importance for a business area, we plot these two pieces of information for each business area.

The abscissa (x-axis) of the Loyalty Driver Matrix is the performance index (e.g., mean score, top box percentage) of the work attributes. The ordinate (y-axis) of the Loyalty Driver Matrix is the impact (correlation) of the work attribute on employee loyalty.

The resulting matrix is referred to as a Loyalty Driver Matrix (see Figure 1). By plotting all 26 data points, we can visually examine all work attributes at one time, relative to each other.

Understanding the Loyalty Driver Matrix: Making Your Business Decisions

The Loyalty Driver Matrix is divided into quadrants using the average score for each of the axes. Each of the work attributes will fall into one of the four quadrants. The business decisions you make about improving the employee experience will depend on the quadrant in which each work attribute falls:

1. Key Drivers: Work attributes that appear in the upper left quadrant are referred to as Key Drivers. Key drivers reflect work attributes that have both a high impact on employee loyalty and have low performance ratings relative to the other work attributes. These work attributes reflect good areas for potential employee experience improvement efforts because we have ample room for improvement and we know work attributes are linked to employee loyalty; when these work attributes are improved, you will likely see improvements in employee loyalty.
2. Hidden Drivers: Work attributes that appear in the upper right quadrant are referred to as Hidden Drivers. Hidden drivers reflect work attributes that have a high impact on employee loyalty and have high performance ratings relative to other work attributes. These work attributes reflect the company’s strengths that keep the employee base loyal. Consider using these work attributes in recruitment and training collateral.
3. Visible Drivers: Work attributes that appear in the lower right quadrant are referred to as Visible Drivers. Visible drivers reflect work attributes that have a low impact on employee loyalty and have high performance ratings relative to other work attributes. These work attributes reflect the company’s strengths. These areas may not impact employee loyalty but they are areas in which you are performing well. Consider using these work attributes in recruitment and hiring collateral.
4. Weak Drivers: Work attributes that appear in the lower left quadrant are referred to as Weak Drivers. Weak drivers reflect work attributes that have a low impact on employee loyalty and have low performance ratings relative to other work attributes. These work attributes are lowest priorities for investment. They are of low priority because, despite the fact that performance is low in these areas, these areas do not have a substantial impact on whether or not employees will be loyalty toward your company.

Figure 2. Results of employee loyalty metrics.

Example

A software company wanted to understand how their employees felt about their work environment. Using an employee survey, they solicited feedback from all employees and received completed surveys from nearly 80% of them. The results of the employee loyalty questions appear in Figure 2. While employee loyalty appears good, we see that there is room for improvement.

Applying driver analysis to this set of data resulted in the Loyalty Driver Matrix in Figure 3. The results of this driver analysis shows that Career opportunities, Training and Company communications are key drivers of customer loyalty; these work attributes are the top candidates for potential employee experience improvement efforts; they have a large impact on employee loyalty AND there is room for improvement.

Figure 3. Employee Loyalty Driver Chart

While the Loyalty Driver Matrix helps steer you in the right direction with respect to making improvements, you must consider the cost of making improvements. Senior management needs to balance the insights from the feedback results with the cost (labor hours, financial resources) of making improvements happen. Maximizing ROI occurs when you are able to minimize the costs while maximizing employee loyalty. Senior executives of this software company might find that the cost of improving communications requires less investment but would result in significant improvements in employee loyalty.

Summary

Loyalty Driver Analysis is a business intelligence solution that helps companies understand and improve the health of the employee relationship. The Loyalty Driver Matrix is based on two key pieces of information: 1) Performance of the work attributes and 2) Impact of that work attributes on employee loyalty. Using these two key pieces of information for each work attribute, senior executives are able to make better business decisions to improve employee loyalty to improve customer loyalty and accelerate business growth.