and career development,” or “greater job challenge,” the costs associated with turnover are somewhat controllable. That is, the firm can alter its HR manage- ment practices to reduce the voluntary turnover. However, if the turnover is due to such factors as death, poor health, or spouse transfer, the costs are
uncontrollable.
The point is that in human resource measurement, the objective is not simply to measure costs but also to reduce the costs of human resources by devoting resources to the more controllable factors. To do this, we must do two things well:
1. Identify, for each HR decision, which costs are controllable and which are not.
2. Measure these costs at Time 1 (prior to some intervention designed to re- duce controllable costs) and then again at Time 2 (after the inter vention).
Hence the real payoff from determining the cost of employee behaviors lies in being able to demonstrate a financial gain from the wise application of human resource management methods. The following sections present both hypo- thetical and actual company examples of such measurement in the areas of employee attitudes, absenteeism, turnover, work-life programs, and training.
In 1998, Sears executives recognized a fertile opportunity to improve operations through better measurement and understanding of the connection be- tween employee attitudes and behaviors in stores, and associated customer atti- tudes and behaviors that led to financial performance. At the time, Sears store managers had little idea about this connection, and so they often operated stores to minimize labor costs or with little attention to employee attitudes. Store managers often believed that the key to store success was mostly in the more tangible ele- ments of merchandise. 10 Although the top leadership at Sears believed there was a connection between retail-store employees’ attitudes and financial results, they had no hard data to demonstrate it, and in a pragmatic industry like retail, the decisions of store managers and executives often require compelling evidence.
The Sears model didn’t just examine whether employee attitudes correlated with financial outcomes. Instead, Sears created a model with a logical set of connections between employee attitudes and store financial performance, in- cluding customer behavior as a critical intervening variable. Sears created a logic based on the proposed connections between employee attitudes, behav- iors, customer responses, and financial outcomes. Sears also used analytics and measures to test and refine the logic, producing an integrated and data-based depiction of the strength of the relationships. Finally, Sears then created an effective process to embed the results in the organization’s decision systems, by carefully communicating the results to business leaders and employees, holding store managers accountable for the attitude measures that had proven to be related to store financial outcomes, and continuing to measure and refine the model so that even deeper insights emerged regarding particular merchandise categories and customer segments.
Many retailers might try to copy the Sears measures, even the modeling techniques, but they might fail to realize the benefit from the model, because the logic, analytics, and measures of the system are not in themselves enough to make it work. It is the integration of these elements, and their connection to the fundamental operating processes of the Sears organization, that creates the organizational change. The following sections describe some key elements of the Sears approach.
Measures, Data, and a Causal Model
In retailing, there is a chain of cause and effect running from employee behav- ior to customer behavior to profits. Employee behavior, in turn, depends to a large extent on attitude. Over two quarters, Sears managers collected survey data from employees and customers and financial data from 800 of its stores. A team of consulting statisticians then factor-analyzed the data into meaningful clusters and used causal pathway modeling to assess cause/effect relationships.
Based on initial results, Sears adjusted the model and continued to collect data for a new iteration at the end of the next quarter.
How did Sears benefit from the model? It could see how employee attitudes drove not just customer service, but also employee turnover and the likelihood that employees would recommend Sears and its merchandise to friends, family, and customers. It discovered that an employee’s ability to see the connection between his or her work and the company’s strategic objectives was a driver of positive behavior. It also found that asking customers whether Sears is a “fun place to shop” revealed more than a long list of more specific questions would. It began to see exactly how a change in training or business literacy affected revenues.
Although Sears used a 70-item questionnaire to assess employees’ attitudes, it found that a mere 10 of those questions captured the predictive relationship between employee attitudes, behavior toward the customer, and customer satisfaction. Items such as the following predicted an employee’s attitude about his or her job:
� I like the kind of work I do.
� I am proud to say I work at Sears.
� How does the way you are treated by those who supervise you influence your overall attitude about your job?
Items such as the following predicted an employee’s attitude about the company:
� I feel good about the future of the company.
� I understand our business strategy.
� Do you see a connection between the work you do and the company’s stra- tegic objectives?
In summary, Sears produced a model, revised it three times, and created a kind of balanced scorecard for the company—the Sears Total Performance Indicators, or TPI—that showed pathways of causation all the way from employee attitudes to profits. The company conducts interviews and collects data continually, assembles its information quarterly, and recalculates the impacts on its model annually to stay abreast of the changing economy, chang- ing demographics, and changing competitive circumstances. The revised model (see Figure 2–3 ) became a tool to help Sears managers run the company in 1998.
For example, consider the quality of management as a driver of employee attitudes. The model shows that a 5-point improvement in employee attitudes will drive a 1.3-point improvement in customer satisfaction in the next quarter, which in turn will drive a 0.5-percent improvement in revenue growth. If Sears knew nothing about a local store except that employee attitudes had improved by five points on its survey instrument, it could predict with confidence that if
Attitude about the job
Employee behavior
Service Helpfulness
Customer recommendations
Attitude about
the company Employee retention
Merchandise Value
Return on assets Operating margin Revenue growth A COMPELLING PLACE TO WORK A COMPELLING PLACE TO SHOP
A COMPELLING PLACE TO INVEST
5 UNIT INCREASE IN EMPLOYEE
ATTITUDE
1.3 UNIT INCREASE IN CUSTOMER
IMPRESSION
DRIVES
0.5% INCREASE IN REVENUE
GROWTH Customer
impression
Customer retention
DRIVES
Figure 2–3 Revised model:
the employee- customer-profit chain.
(Source: Rucci, A. J., Kirn, S. P., &
Quinn, R. T.
(1998, Jan.–Feb.).
The employee- customer profit chain at Sears, Harvard Business Review, p. 91.
Used with permission.)
revenue growth in the district as a whole was 5 percent, revenue growth at this particular store would be 5.5 percent.
Process: Impact on Managers’ Behavior and on the Firm
With the data in place, Sears leaders then began to hold store managers account- able for the elements of the model. They were rated and tracked with regard to the employee-attitude measures, and the system tracked the relationship between those attitudes, customer behaviors, and store performance. As the system evolved, Sears created web portals that allowed store managers to highlight and click on particular connections in the employee-customer-profit model for further study. Eventually, Sears invited store managers and others to post their best prac- tices to the website, and these were also integrated with the logical model.
Thus, not only could Sears store managers now track the measures, they could undertake the analysis using the proven logic of the model to evaluate and predict their own store’s performance. Moreover, if they saw an area where improvement seemed to have potential to enhance store performance significantly, they could click and see the best practices of other stores that had enhanced those attitudes or behaviors. 11
A note of caution is in order, because in other types of organizations, the direction of causality may not be as clear as it is in retailing. In fact, it may well be the case that the financial performance of a firm predicts satisfaction with security and overall satisfaction, rather than vice versa. This is precisely what one study found in an analysis of employee attitudes and financial performance for 35 companies over 8 years. 12