Proposed Development Metrics

In this section, we present our proposed metrics for development. Development metrics are among the most difficult to create. Staffing and retention metrics have a well-defined focus and a limited group of employees to examine. Therefore, it is possible to calculate fairly precise measures. Development, on the other hand, represents an enormously diverse array of activities, many of which are not accounted for or tabulated in any information system. Furthermore, they must include every employee every year, not just a subset, such as those who leave or stay.

Our review suggests that development metrics could be created at three levels:

• Organization or organization sub-unit level.

• Intervention or program level.

• Individual employee level.

We have opted to create organization or sub-unit metrics rather than intervention or individual level metrics. Our rationale is simple: After 40 years of failure to establish intervention or individual-level measures as a viable accountability system, we see little reason to recommend them now. They are not likely to succeed. Some organizations certainly may do them, and may have wonderfully valid data that we applaud. But our interest is in broadly applicable metrics, so we have chosen a different direction.

Metric One: Development Quality. One of the chief goals of development is to have people ready to fill vacancies as needed. An appropriate metric of development quality is the percentage of vacancies that the organization can fill internally. It is important to keep in mind that this metric is not intended to suggest that all vacancies should be filled internally, but rather that they could be because development is effectively preparing employees to take on new responsibilities. Also, in instances where new hires are used to replace those who leave or those positions emptied due to the internal hire’s promotion, it is necessary to subtract these vacancies since they represent an expanded job base. Finally, there will be positions that the organization decides to fill externally. Thus, the metric should be presented as a percentage of vacancies only in situations where the desire exists to fill internally. With that in mind, the ideal situation is one where organizations fill 100 percent of the positions (that management wishes to fill internally) internally.

Metric Two: Capacity to Meet Potential Needs. Capacity metrics provide an assessment of the organization’s ability to meet future needs for innovation, problem solving, and growth driven by human capital in the future. The premise of Capacity to Meet Potential Needs is that there is substantial cost to any organization that does not develop people in advance of the roles they must assume. The cost may occur because an employee leaves, with nobody qualified to fill the position, resulting in lost productivity and perhaps costs to recruit externally when it is not desirable. Another negative scenario occurs because growth opportunities requiring quick action by the organization present themselves, leading to opportunity costs if capacity is not present.

We believe these situations are best combated by two metrics. Before this can be addressed, however, an organization needs to have a reliable, flexible and mobile workforce. That is, it is possible for an organization to have only just enough competent employees to meet current demand, but not an excess that could be utilized should the need arise. Thus, we propose using the following metric:

Capacity is built by a certain degree of over-investment in development so that more than one person can fill a position. This metric requires an organization to determine which positions are essential to the organization’s business and success. These should be positions that are deemed critical to the organization’s future. Also, how many of these key positions should be filled internally? The final element that must be examined is the number of key positions that have at least one additional employee suitable to fill the position if necessary. This data plays a dual role—both in calculating the metric and by forcing the organization to examine its succession planning procedures. Capacity also depends on an employee’s motivation to use learning and development to enhance performance. Traditionally, this has been stated as motivation to learn. However, given that the primary desired outcome of organizational development programs is improvement in work outcomes, an exclusive focus on motivation to learn or train is too limiting. The process of improving work through learning also involves an employee’s willingness to transfer knowledge acquired to improve work processes. Thus, motivation to learn is a necessary but not sufficient condition for successful development.

To address this, a new metric is recommended: Employee Motivation to Improve Work Through Learning (MTIWL). This metric posits that an individual’s motivation to improve work through learning is a function of his or her motivation to train and motivation to transfer, symbolically:

MTIWL = Motivation to Train + Motivation to Transfer

Because organizations have an appropriate interest in something more than just “learning for learning’s sake,” the MTIWL construct focuses on motivational influences that will lead to improved work outcomes from training.

Metric Three: Development Customer Satisfaction. Perceptual data is inherently flawed due to its subjectivity. Nevertheless, customer satisfaction is an important aspect and should not be limited to only recruiting metrics. Unlike most development satisfaction data, this book recommends adopting the Results Assessment System’s approach for two reasons. First, there is an established need to collect perceptual data from the manager’s standpoint of development participants rather than of the participants themselves. While participants may be consumers of development, it is their managers who are the true customers. Second, the perceptual data to be collected focuses on utility of development for improving performance. Typical perceptual data asks how much participants like development activity. Research has consistently shown that this has no relationship to learning or performance outcomes. The appropriate measure is utility of development for improving performance. The recommended metric should be: Average Manager Rating of Training and Development Utility for Improving Performance.

Metric Four: Formal Development Investment per Employee. Traditionally, training investments have been measured by training expense as a percent of payroll, but this measure is flawed for a variety of reasons. The improved metric—Formal Development Investment per Employee—takes a more holistic approach and considers the following:

• Expanding beyond training cost to include other formal development.

• Including the hidden cost of the participant’s salary.

• Converting to a per person ratio so it is more usable by management. We acknowledge one key shortcoming in that it does not include the cost of informal development, which is simply too difficult to cost. The metric is calculated as follows:

  • Internal Costs (IC) = training expenses + direct costs of learning events

  • External Costs (EC) = tuition reimbursement + conference registration fees + outsourcing + other development costs

  • Hidden Cost (HC) = (participant days in training + conference days attended) × average payroll per day

  • Formal Development Cost (FDC) = IC + EC + HC

  • Formal Development Investment = FDC/FTE

Metric Five: Human Capital Development Contribution (HCDC). While some claim that the value of development cannot be precisely calculated, HCDC is the measure that comes closest to anything we have seen. As stated earlier, in the financial world economic value added, or EVA, has become a popular way to value business units. EVA is simply the profit attributable to a business unit less the cost of capital employed in that unit. Fitz-enz (2000) proposed a measure he called human capital value added (HCVA), which he defined as revenues minus expenses except for pay and benefits, divided by number of full-time employees (FTEs). Unfortunately, this value is flawed in that it attributes all profit to human capital and ignores the role of financial capital. This new metric, Human Capital Development Contribution, is calculated as follows: