Making HR Measurement Strategic
Making HR Measurement Strategic*
Decisions about talent, human capital, and organizational effectiveness are increasingly central to the strategic success of virtually all organizations, so it is surprising how often vital decisions about talent and how it is organized are addressed with only very limited measures or with faulty logic. Consider how well your organization could address the following questions or requests if your CEO were to pose them:
- "I know that on any given day about 5 percent of our employees are absent. Yet, everyone seems to be able to cover for the absent employees, and the work seems to get done. Should we try to reduce this absence rate, and if we did, what would be the benefit to our organization?"
- "Our total employment costs are higher than those of our competitors, so I need you to lay off 10 percent of our employees. To be fair, let's reduce headcount by 10 percent in every unit to meet that goal."
- "Our turnover rate among engineers is 10 percent higher than those of our competitors. Please institute programs to get it down to the industry levels."
- "In a globally competitive environment, we can't afford to provide high levels of health care and health coverage for our employees. Every company is cutting health coverage, and so must we. Please find a cheaper health-care provision and insurance program, to cut our costs by 15 percent."
- "I read that companies with high employee satisfaction have high financial returns, so I want you to develop an employee engagement measure, and hold our unit managers accountable for raising employee engagement averages in each of their units."
- "I hear a lot about the increasing demand for work and life balance, but my generation found a way to work the long hours and have a family. Is this generation really that different? Are there really tangible relationships between work-life conflict and organizational productivity? If there are, how would we measure them and track the benefits of work-life programs?"
- "We expect to grow our sales 15 percent per year for the next 5 years. I need you to hire enough sales candidates to increase the size of our sales force by 15 percent a year, and do that without exceeding benchmark costs per hire in our industry."
- "I know that we can deliver training much more cheaply if we just outsource our internal training group and rely on off-the-shelf training products to build the skills that we need. We could shut down our corporate university and save millions."
In every case, the question or the request reflects assumptions about the relationship between decisions about human resource (HR) programs and the ultimate costs or benefits of those decisions. Too often, such decisions are made based on very naïve logical frameworks, such as the idea that a proportional increase in sales requires the same proportional increase in the number of employees, or that across-the-board layoffs are logical because they spread the pain equally. In this book, we help you understand that these assumptions are often well meaning but wrong, and how better HR measurement can correct them.
There are two issues here. First, business leaders inside and outside of the HR profession need more rigorous, logical, and principles-based frameworks for understanding the connections between human capital and organization success. Those frameworks comprise a "decision science" for talent and organization, just as finance and marketing comprise decision sciences for money and customer resources. The second issue is that leaders inside and outside the HR profession are often unaware of scientifically rigorous ways to measure and evaluate the implications of decisions about human resources. An essential pillar of any decision science is a measurement system that improves decisions, through sound scientific principles and logical relationships.
This book is based on a fundamental principle: HR measurement is valuable to the extent that it improves vital decisions about talent and how it is organized.
This perspective on HR measurement is consistent with the broader evolution of a new decision science for talent and organization, articulated by John Boudreau and Peter Ramstad in Beyond HR. This decision-science approach requires that HR measurements do more than evaluate the performance of HR programs and practices. It extends the value of measurements by providing logical frameworks that drive sound strategic decisions about talent. We provide both logical frameworks and measurement techniques to enhance decisions in several vital talent domains where decisions often lag behind scientific knowledge, and where mistakes frequently reduce strategic success.
Those domains are reflected in the questions posed at the beginning of this chapter, and include the following:
- Absenteeism (Chapter 3)
- Employee turnover (Chapter 4)
- Employee health and welfare (Chapter 5)
- Employee attitudes and engagement (Chapter 6)
- Work-life issues (Chapter 7)
- External employee sourcing (recruitment and selection) (Chapter 8)
- The economic value of employee performance (Chapter 9)
Subsequent chapters focus on payoffs from enhanced selection (Chapter 10), estimating the costs and benefits of HR development programs (Chapter 11), and talent-investment analysis as a catalyst for change (Chapter 12). Each chapter provides a logical framework that describes the vital key variables that affect cost and value. Then, each chapter provides specific measurement techniques and examples, often noting elements that frequently go unexamined or are overlooked in most HR and talent-measurement systems.
The topics we chose meet two conditions: First, they are areas where very important decisions are constantly made about talent, and that ultimately drive significant shifts in strategic value. Second, they are areas where fundamental measurement principles have been developed, often through decades of scientific study, but where such principles are rarely used by decision makers. This is not meant to imply that HR and business leaders are not smart and effective executives. However, there are always areas where the practice of decisions lags behind state-of-the-art knowledge.
The measurement and decision frameworks in these chapters are also grounded in a set of general principles that support measurement systems in all areas of organizational decision making, such as data analysis and research design, the distinction between correlations and causes, the power of break-even analysis, and accounting for economic effects that occur over time. Those principles are described in Chapter 2, "Analytical Foundations of HR Measurement," and then used throughout this book.
To begin, in this chapter we show how a decision-science approach to HR measurement leads to very different approaches from the traditional one, and we introduce the frameworks from this decision-based approach that will become the foundation of the rest of this book.