Time Matters

Time is a key element in uncovering the root causes of many human capital problems, including turnover. Traditional assessment tools such as employee surveys provide a snapshot of what is going on at a particular moment, but it’s more important to see things from a time perspective.

Many of the most important drivers of employee behavior don’t even have meaning if they are not measured over time. Consider rewards as an example. Current compensation is of course an important component of rewards. It can be measured at a single point in time, as can its relationship to current market rates for comparable jobs. However, there are other important components of rewards that cannot be measured at a single point in time. The way an individual’s pay grows from year to year is an important example. Indeed, in some organizations and for some employees, the trajectory of pay may eclipse pay levels as a motivator of employee performance and turnover behaviors. Similarly, the rate of promotion and other forms of advancement may be critically important. These are inherently dynamic constructs. They have no meaning and certainly cannot be measured unless they are examined over time.

Unless one takes a dynamic view of workforce events, one is likely to miss some of the most important aspects of the employment relationship and of human capital generally. One would be working without one of the most critical pieces in the human capital puzzle.

Time is another dimension in which surveys can be deficient. Too often organizations use surveys to present a static picture at a particular point in time. By doing so, they fail to capture the dynamic aspects that really tell the story of what is happening to their human capital. Although a survey will indicate where people stand in terms of pay, job level, and other static descriptors, a time-based (longitudinal) study will show how fast or how slowly they are moving upward through the system or broadening their experience. It will reveal the kind of human capital that is being developed and how quickly it is taking shape. In the modern economy this is indispensable information for managing human capital. It certainly proved vital to FleetBoston Financial, as the story on the following pages show.

Applying Time-Based Analysis at Fleet Financial

FleetBoston Financial, a large regional bank with more than 40,000 employees, has grown substantially in recent years, mostly through an aggressive merger and acquisition strategy. In 1998 Fleet, which was then called Fleet Financial, was experiencing a surge in voluntary turnover. Indeed, by some measures its turnover rate was almost twice the industry average, exceeding 40 percent in some occupational groups. Those defections were costly and disruptive to the organization.

The company’s HR department had been tracking turnover for some time to determine the scope of the problem. It had relied on exit interviews and employee surveys to determine what kept people with the company and what encouraged them to leave. Those traditional methods pointed to two prime causes of employee turnover: excessive workload and inadequate pay. Fleet responded with policies aimed at relieving stress and adjusting pay where possible. Nevertheless, turnover continued to rise. The company was ready to try something different.

An alternative approach was to examine the actual pattern of turnover over time to see whether objective antecedents of turnover could be identified. That approach involved rigorous statistical modeling of turnover behavior among the employees. Every day the employees of that vast organization were making decisions to stay or leave in different but easily observed circumstances. Some were in locations characterized by very tight labor markets; some were in softer markets. Some were in large units; some were in smaller ones. Some occupied jobs in which pay was comparable to market rates; others were receiving pay significantly higher than that in the market, and so on.

Simply stated, the workplace reality on the ground contained distinct variability even though Fleet espoused uniform, standardized HR policies. Those variations in effect created a natural experiment, allowing the company to evaluate how particular factors influenced behavior and measure the relative magnitude of the effects. That revealed a story about the drivers of turnover, which were at odds with what departing employees were telling exit interviewers.

The facts gleaned from Fleet’s HR database helped identify and quantify the impact of various workforce characteristics and management practices on employee turnover. To the surprise of many managers, the findings revealed that pay levels had the weakest impact on actual turnover; this was in striking contrast to what exit interviews suggested. As an illustration, the modeling determined that a 10 percent across-the-board increase in pay levels would reduce turnover by less than 1 percentage point. Thus, relying primarily on pay adjustments to stem turnover would have required a major commitment of resources with little payoff for the company. The real drivers of retention, according to the analysis, had little to do with pay and much to do with factors related to careers, such as promotions, pay growth, number of jobs, and breadth of experience at Fleet. See Figure 2-4.

Figure 2-4: Fleet’s Turnover Drivers

Clearly, the most powerful deterrent to defection was a recent promotion. Individuals promoted in the prior year were about half as likely to leave, all else being equal. Those who made the specific career transition from hourly to salaried status (i.e., from nonexempt to exempt) were also more likely to stay. Interestingly, they performed better compared with those who came into the exempt ranks from the outside. The analysis also indicated that the highest probability of defection was among employees who had been in the same positions for more than two years. In fact, the likelihood of defection shot up dramatically in that group. Simply changing jobs, even without a promotion or a significant pay increase, tended to diminish an employee’s propensity to leave.

Stability within the ranks of supervisory personnel also had a substantial effect. Specifically, the likelihood of turnover almost doubled when an employee’s supervisor left the organization, but only if that supervisor was a high performer. If the supervisor simply moved to another department, there was hardly any effect, suggesting that this had less to do with the relationship between the supervisor and the employee than with the adverse message that is sent when good people leave an organization.

The facts revealed through this analysis helped Fleet avoid costly and ineffective solutions. They encouraged management to focus on the real drivers of employee retention as the basis of a new retention strategy. Specifically, management made the following choices:

• Focus on high-performing supervisors and managers, emphasizing the elements of the employment package with the largest demonstrated impact on managerial retention, such as advancement and career development. Keeping good supervisors with the bank would have a positive effect throughout the organization; that is, keeping down the defection rate of good supervisors would reduce the overall turnover rate.

• Focus on careers and the programs and practices that help employees develop their skills and experience. Make sure high-performing employees, regardless of rank, have a clear idea of the career opportunities available to them and the financial significance of being successful in the organization.

• Concentrate on career tracks for nonexempts that involve transitions to exempt status. Those tracks were shown to be especially fruitful in enhancing retention and ultimately producing both loyal and productive employees in the exempt ranks.

• Do not allow good people to linger too long in their current positions. Move good people periodically into new and better jobs. Ironically, building an employee’s r sum by enhancing his or her experience made people stay, not leave.

• Pay special attention to new hires, ensuring that those coming into the organization are well matched to their jobs, have a realistic understanding of job requirements and the work environment, and can ramp up more deliberately into their full workload. The data analysis showed that the problem of “quick quits” would abate with such actions.

It Worked

Some of those interventions were not easy to execute. Imagine asking supervisors to facilitate job moves by their top performers when their own rewards reflect the performance of the units they manage. Imagine selling the idea that investing in employees and building their r sum s will help Fleet as much as if not more than it will help their employees. It took guts to take this on.

Fortunately, courage was not in short supply at Fleet. Under the leadership of Anne Szostak, executive vice president and corporate director of human resources and diversity and chairman and CEO of Fleet Rhode Island, the company launched its retention initiatives. Within eight months Fleet experienced a 25 percent reduction in the turnover of the nonexempt population and a 40 percent reduction among the exempts even in the face of severely tightening labor markets. The company’s own estimates of annualized savings exceeded $50 million per year. More than three years later, the results of statistical modeling show that the retention strategy continues to work in spite of all the bank’s acquisition activity. (Acquisition tends to spur increases in voluntary turnover.) Retention of top managerial talent has been remarkably successful.

None of the important facts uncovered in the Fleet case could have been gleaned from a snapshot of the company’s current employment practices. A snapshot reveals nothing about career progressions, the rate at which promotions occur, the trajectory of total pay, or the development of new skills and the acquisition of new and broader experience. It reveals little about intertemporal linkages between the turnover of supervisors and that of employees. No organization can determine root causes of workplace phenomena without taking into account the element of time. To determine cause and effect, it is necessary to know what went before. The past does matter.

Relevant facts such as these depend on the ability to analyze payroll and HR records going back several years. That is why an employee survey should be just one of many tools for learning about human capital.