Inside-Outside Balance

Where do the facts that support your human capital decisions come from? If you are like most executives, you draw on facts originating inside and outside your organization. That is always a good approach, assuming that the facts you gather and use are the “right” ones, that is, facts that are appropriate to the situation and to the context of the organization. External facts can alert you to innovative practices that may benefit your organization; they provide a sense of where your industry is heading and often answer the question of how you stack up against rivals on any number of important factors, such as pay, training, and productivity, among others. However, many external facts found through benchmarking and other means are not particularly relevant. In the worst cases they are misleading. Using them to guide decisions can only lead to bad outcomes.

One reason why these external facts may be misleading is that they are inaccurate. Most HR benchmarking studies, even those involving sophisticated statistical modeling, rely on self-reporting. Usually, the senior HR executive or, perhaps more likely his representative, is asked to reply to a survey containing questions about the HR programs and practices. For instance, the respondent may be asked whether the company has a gain-sharing program. Unfortunately, the term gain sharing means different things to different people. To some it specifically signifies the original industrial engineering–type plans, such as Scanlon, Rucker, and Improshare, that focused on hard measures of operational performance and tracked performance relative to some historical or benchmark standard. To others it refers to any form of variable pay, including pay based on financial performance, such as profit sharing, revenue sharing, and even shareholder value. These are very different types of programs that have very different implications for human capital management. When they are pooled inadvertently in the summary of survey responses, the informational value is blurred or lost.

External comparisons also raise the problem of say-do. A company may say that it has a particular program even though the reality (the “do”) is quite different. Think for a moment about the high-tech firm, Digitt, which thought it was paying for performance. If we had relied on interview or survey responses from the HR department or, frankly, from any company officials, we surely would have characterized the company’s reward system as pay for performance. Virtually every generic category of variable pay was in place, and broad segments of the population were covered. However, as we’ve seen, this was not the reality. Measures of actual pay-performance sensitivity—the year-to-year variation in pay related to changes in different measures of performance—were insignificant compared with those of other workforce attributes, such as years of service and level in the hierarchy.

The most important problem with benchmarking is that it fails to account for context. It thus flies in the face of the systems character of human capital management. If performance is indeed about “fit” or alignment, applications of benchmark data can be seriously misleading for an organization. Here’s an example.

TechCo, the computer-chip maker discussed in Chapter 1, discovered the perils of creating a human capital strategy that was based on external benchmarking and so-called best practices. Historically, the company held a solid position in its industry as an efficient, reliable low-cost manufacturer of chips. Its workforce consisted primarily of experienced engineers who knew the company’s library of chips and their possible applications, forged strong relationships with customers, and understood the company’s sales, design, and manufacturing processes.

This chip maker, however, began to mimic the people practices of recognized technology leaders, firms such as Intel and Apple that made their money through innovation, not efficient process engineering. For example, it began to hire the “best and brightest” engineers at premium pay even though the work would hardly be challenging to top-flight engineers. Also, it made stock options an important part of its total compensation scheme even though the company’s stringent command and control management system, which had been designed to ensure process efficiency, precluded the kind of entrepreneurial and risk-taking behavior that such rewards encourage. Those “best practices”—external facts—simply did not fit the organization’s business strategy and organizational culture. The result? TechCo found itself plagued by inflated labor costs, declining quality, lower profits, and high turnover among its most experienced design engineers. The new recruits also left because the work was incompatible with their desire to be innovators.

TechCo experienced trouble because it relied on external facts drawn from its benchmarking of other firms in its industry. Some of those facts might have been useful in expanding the range of possible choices for executives, but they did not directly answer whether those choices were a good fit for TechCo. That question could be answered only with facts drawn from within.

The fundamental problem was that TechCo’s management failed to recognize the true source of value in its workforce: firm-specific human capital. Whereas the innovators may require the best and the brightest and the leading-edge thinkers, TechCo’s business model put primacy on solid homegrown talent, engineers who knew the company’s library of chips and could adapt existing designs to new commercial applications quickly. That institutional knowledge made it possible for the company to serve customers with high-quality, low-cost chips in a timely manner. In this competitive business, margins are low and errors in design or production are deadly to profits. Nothing could substitute for the experience of engineers who had grown with the company. The policies TechCo put in place pursuant to benchmarking were geared towards general, not firm-specific, human capital. Therefore, they were a direct assault on the core assets on which TechCo’s business model was built. It is not surprising that those assets began to erode.

Finally, it is important to note that TechCo’s command and control management system was incompatible with the more participative reward system that the company was putting in place. Benchmarking failed to capture the systemic nature of practices in other firms and led TechCo to put in place practices that were fundamentally incompatible with each other.

The TechCo story is a cautionary tale about focusing too intently on external facts while ignoring internal data. In most cases internal facts are the best guide on human capital issues. Careful examination and analysis of a company’s own data (e.g., employee and customer surveys, financial data, accounting data, operations data) will produce critical facts and insights about that company’s workforce. Those facts and insights will lead to better decision making and the development of an effective human capital strategy. What accounts for profitability and growth? Who gets hired, who stays, who advances, how are rewards distributed, and how is talent developed? How frequently should managers cycle through positions? How broadly should incentives be distributed? How much should the organization staff up for a busy season, and how does turnover affect the organization’s performance metrics?

The answers to questions like these form the backbone of fact-based decisions about human capital. When they are joined to disciplined, sophisticated analysis, they can help you identify (1) the human capital factors that drive business performance in your organization and (2) the combination of people practices most likely to optimize the productivity and value of your human capital.

Gathering internal facts about human capital used to be laborious and often unproductive. Pertinent data about pay, benefits, time in position, rapidity of promotions, and so forth, had to be pieced together from individual employee files. Thanks to advances in information technology those data are now readily available in enterprise resource planning systems, payroll databases, and human resource information systems (HRIS), all of which are becoming standardized across industries. Many companies have spent tens of millions of dollars on these information systems, yet most sit on the data they contain, maintaining and tapping into them mostly for compliance purposes. This is unfortunate because when properly used, these systems tell the human capital story of an organization. They are the ultimate source of facts that can and should inform decisions about human capital management.

Finding the Right Balance

If both external and internal facts are needed for good decisions about human capital, what is the right balance? Because business strategy generally drives human capital strategy, it is necessary to create a workforce that is capable of making the strategy work. Thus, to the extent that your business model is truly unique, internal data should dominate. You should know the most relevant facts about your internal labor market and develop metrics to track its most critical dimensions. However, don’t ignore external facts. Your internal labor market does not exist in isolation; it is in constant interaction with a larger and competitive labor market. As a result, external facts are needed to determine how successful your policies and practices are likely to be in the face of competitive market conditions. Obviously, your company must be competitive in pay and benefits if it hopes to attract and retain good people and make its strategy work, but you can be competitive in different ways. Should you focus on matching pay and benefits to market levels or emphasize advancement? Will learning and career opportunity do the job? Only the internal lens can shed light on these choices. Unfortunately, for too many companies that lens isn’t even in the tool kit.

Sources of Internal Facts

We find that the best approach to obtaining internal facts is twofold:

1. Gather qualitative facts through surveys and interviews, which will yield perceptions about how the organization functions and “expert opinion” about current realities and future needs.

2. Gather quantitative facts through measurement and statistical modeling. Our key tools for measurement are Internal Labor Market (ILM) Analysis and Business Impact Modeling. You will be introduced to them in later chapters.