Talent Measurement Schools of Thought

Here is a puzzle: In our day-to-day life we do not treat people as inanimate objects—but we try to measure them as if they are! We treat the people in front of us as living, breathing, reacting entities, but few consider the complexity and reactivity of human nature when developing or managing with measures. Why the inconsistency?

Two Schools of Thought: The Taylor and Mayo Dichotomy

To solve this puzzle, you have to go back to school—graduate school. As a graduate student, you’ll probably learn one of two different approaches to talent measurement. One school of thought is focused on the technical aspect of measurement, and the other on the human aspect. The challenge for measurement professionals is to master both schools of thought. The two are rarely reconciled, however. Professionals generally have expertise primarily in one approach.

The technical or engineering school will teach you how to calculate reliability and validity, and introduce you to different measurement methods. This school of thought dates back to Frederick Taylor, one of the first manufacturing engineers. Frederick Taylor is considered the father of scientific management, which emphasizes task analysis, efficiency studies, time-and-motion studies, and using compensation schemes for motivation. 

The human relations school has a different point of view: Employees are complicated, and don’t work mechanistically. If your graduate program emphasizes human relations, you’re likely learn more about personality types or team functioning measures that will facilitate interactions between people at work. You’ll be introduced to validity and reliability, but you’ll be taught very little about the technology and theory of measures. The human relations school of thought dates back to Elton Mayo, a psychologist. 

The ghosts of Taylor and Mayo haunt today’s organizations. To this day, consultants, managers, and leaders adhere to one school or the other. Taylor adherents tend to advocate for measurement as a formal and rigid process. Mayo adherents focus more on group processes, interpersonal communication, and intrinsic motivation. 

Both Taylor and Mayo made essential contributions to the art of management and leadership. But it’s not an either/or choice. It often takes decades of experience to merge the two schools of thought into a practical working knowledge of measurement. Some never see the dichotomy and its implications.

I’m writing this blog post in the hope that we can accelerate the process of combining and ultimately uniting these two schools of measurement.

The Engineer: Frederick Winslow Taylor (1856 – 1915) “In the past the man has been first; in the future the system must be first.”

Taylor grew up affluent and gifted in the second half of the 19^th century, in an era of huge industrial change. He chose not to follow his father into the legal profession, although he was accepted into Harvard. Instead, he worked in industry, starting as a machinist and becoming a foreman, and went on to study engineering. 

As an engineer, he first improved manufacturing technology such as lathes and forging equipment. Early on, he noticed that these technical improvements demanded similar organizational innovations to be effective. As his ideas developed, he saw manufacturing as a larger system that could be improved by optimizing the various pieces to contribute to the larger system. Over the course of his career, he contributed his ideas to equipment (he had several important patents), business processes (such as accounting methods), and methods of managing employees.  

Taylor and Time-and-Motion Studies

As he looked at the larger manufacturing picture, Taylor was concerned that laborers were not working at full capacity. To fix this problem, he identified the optimum work-output level, and provided incentive pay for this level of output.  

Determining workers’ optimum output involved time-and-motion studies. Taylor divided the work into steps, each of which he timed separately. He then combined the time for each step into a total time for the job. By dividing the work day by the total job time, he arrived at an optimum production rate.

Workers were paid on a graduated scale. Low levels of output were paid very little, but as productivity approached the maximum, unit pay increased. Workers attaining the optimum production rate would be paid 60% more using Taylor’s methods. 

While he became infamous for his time-and-motion studies, it’s important to recognize that, for Taylor, these studies were part of a larger system of managing employees. Taylor used worker productivity as a talent measure. He studied measures of productivity to make decisions, organize work, set production expectations, motivate employees, and identify employees to retain. In the best cases, Taylor’s scientific management methods could reduce costs and increase productivity by 50% to 100%.

Human reaction to measures and management methods didn’t factor into Taylor’s thinking. He was convinced that employees only work for money. Labor problems were simply an engineering challenge to be managed. Taylor paid lip service to selecting and developing talent—he mostly set output targets. Workers who were able to keep up the pace self-selected and developed their capability.

Taylor’s blind spot—the human factor—can be seen in many contemporary organizational improvement interventions, such as re-engineering, which has a success rate as low as 30%. Human readiness and acceptance of change is often a barrier to re-engineering success.   

Taylor’s approach also was inconsistent. Sometimes it worked, sometimes it led to significant problems.

Employee reactions to Taylor’s intervention often led to work actions and strikes.  Ultimately there was an congressional investigation. By the time of Taylor’s death at age 59, Congress had outlawed use of stopwatches and bonus payments in the federal government. Scientific management was increasingly discredited.

The Humanist: George Elton Mayo (1880 – 1949) “So long as … business methods take no account of human nature … expect strikes and sabotage to be the ordinary.”

Mayo grew up in a distinguished Australian family. He began his studies in medicine and ended up studying psychology, focusing on social interactions at work. His most famous research work can be found in the Hawthorne studies, which demonstrated that employees are largely influenced by social factors, and that they react to being observed.

Mayo’s most important work coincided with the Great Depression. He believed that the industrial revolution had shattered strong social relationships in the workplace, and he found that workers acted according to sentiments and emotion. He felt that if managers treated workers with respect and tried to meet their needs, then both workers and management would benefit.  

Mayo’s research indicated that belonging to a group is a more powerful motivator than money. In his management philosophy, he saw attitudes, proper supervision, and informal social relationships as the key to productivity.

Some consider Mayo’s work to be a reaction to Taylorism. But Mayo was also concerned with output and productivity. Unlike Taylor, however, he was interested in the social and psychological interventions that increased productivity. These interventions are indeed helpful, and understanding the human factor is critical.  

Thanks to Mayo’s work, we recognize that, in organizations, informal social structures matter as much as formal structures, such as the chain of command. For example, a likeable senior engineer who dislikes a new manager could undermine the manager’s authority by making jokes at his expense during every meeting. In effect, the engineer becomes more influential than the manager—outside the hierarchy of the organizational chart.

Today, many organizational interventions emphasize team-building, and are based on the recognition that organizational culture is important, and managers have ongoing relationships with employees. By acknowledging the importance of the informal structure of an organization, factors such as relationships, informal leadership, and influence can be aligned with organizational needs and direction.

Mayo’s insights were synthesized into a school of thought referred to as human relations. The human relations school continues strong to this day, often in the form of leadership development, team building, or change initiatives. 

The insight missed by Mayo is that measurement—even Taylor’s productivity measurements—are essentially a social process. Measurement is simply a method of communication—a way to make meaning between groups.

Since Mayo, many people have failed to make this essential connection: We can extend Mayo’s insight into the importance of informal (social) structures into an understanding of the importance of the informal (connotative or personal) meanings of measures. As I have discussed before, the informal meanings of measures matter as much as, if not more than, their formal meanings. Like social structures, these connotative meanings can be managed—but only when their existence and importance are acknowledged.

If you’re creating an organizational, and you follow Taylor, you may believe that compensation is the sole motivation for performance and advancement. If you follow Mayo, you may believe that love, fear, and other ineffable human factors are the primary motivators. 

In the same way, the designers of a formal measurement system may believe that their measures will motivate by providing people with a positive opportunity to make more money (the denotative meaning). Instead, the designers may find that the connotative meanings provoke reactions that ultimately trump their intentions—reactions from outright rejection to gaming the system.

It’s odd that many of our measurement systems haven’t progressed beyond Taylor’s way of thinking. We have many tools to address the informal meanings of measures—tools we can draw on from interpersonal communications theory, management practices, and organizational learning.

Another danger of following Mayo’s approach is that it often pays too much attention to the informal and emergent social structures of an organization. While these informal structures are powerful influences on individual performance, it is possible to merge formal and informal organizational structures into a shared structure. This is where measurement can be incredibly effective, if it is used as a means of communication: It can create shared meaning that bridges the organizational and personal definitions of performance, motivation, and reward.

Finding a Middle Ground

What’s most unfortunate about the Mayo vs. Taylor bifurcation is that they were both right: The difference between the two schools of thought is ideological, not practical. In practice, we use both approaches. We need both engineers and social scientists (psychologist and sociologists) to run organizations efficiently.

If we attend one graduate school, we may learn to develop measures that are technically good, but we’ll have trouble assessing the human reaction to measurement. If we attend another school, we may learn to facilitate social interaction and meaning, but we won’t be trained to motivate, direct, or improve performance through measurement and feedback. Personally, I attended a more technical school, but my life and work experiences have led me to appreciate a balanced approach.

What Taylor missed was the importance of social structures in motivation, and the human factor in reaction to measurement. What Mayo missed was that measurement in itself is a social process, and measures have informal (social) meanings that can be managed.

Today, 80 years after Mayo’s Hawthorne studies, we should be able to merge the two schools. There is a wealth of possibilities for applying Taylor’s ideas in measuring individual productivity. At the same time, we’ve vastly increased our understanding of human relations—there’s a huge industry that’s evolved out of Mayo’s original insights.

Finally, in resolving the polarity of these two approaches, we need to acknowledge that measurement is communication, and that communication is shared meaning. By starting with a simple point—that people always react to measurement, and that the reaction is unpredictable—we can take the denotative and connotative meanings of measures, the formal and informal structures in organizations, and the two schools of thought, and synthesize them into an elegant, effective approach to talent measurement.  

Employee Performance Measurement is Increasing But Will Not Increase Efficiency

Employee performance has been measured since the start of the industrial revolution in the late 18^th century. By 1910, scientific management—the attempt to improve efficiency by applying engineering principles and measurement, in manufacturing —was reaching its peak. 

Although scientific management as a school of thought had faded by the 1930s, it continues to influence the way we measure and manage, and it provides fascinating historical insights into industry. Scientific management was largely focused on per-worker output, how to increase output by finding the right employees, incentive schemes and best practices to ensure that systems function optimally. 

Does this sound familiar? It should. Management, and our society in general, continually focus on these topics. Our use of measurement has only expanded. Today, 97% of organizations have an employee appraisal process, and many organizations are working to increase the number of appraisals to several times each year.  

With current social and technological trends, I expect human performance measurement will continue to increase. I also expect that people will continue to be surprised at the real outcomes and consequences of measurement. I’ll make another prediction: We’ll see little value from all this measurement, unless we start cultivating wisdom in our use of measures.

Frederick Taylor’s Underestimated Influence

The influence of Frederick Taylor, generally considered the founder of scientific management, has been compared to Darwin and Freud.  As Taylor wrote in his 1911 best seller Scientific Management:

… the end of our coal and iron is in sight. But our larger wastes of human effort, which go on every day through such of our acts as are blundering, ill-directed, or inefficient … are less visible, less tangible, and are but vaguely appreciated. … And for this reason, even though our daily loss from this source is greater than from our waste of material things, the one has stirred us deeply, while the other has moved us but little.

Taylor is the father of modern management.  At the turn of the century, management primarily were concerned with budgeting and hiring. Teams of workers defined the tasks. Workers in a sense were still in somewhat of a guild system and had some level of autonomy. Ideas presented by Taylor, and then Henry Ford’s production line, changed things considerably.

   Frederick W. Taylor

While famous for time and motion studies, Taylor had two bigger ideas associated with measuring employee performance:

• System improvement (also known as organizational learning)
• Employee accountability (to achieve targeted levels of performance).

These ideas continue to drive improvement efforts to this day. Taylor believed that per-individual output should be measured, and that the measure should be studied to understand both the system of work and how it can be improved. He also advocated for developing challenging targets for employee output.  

Taylor’s most famous example was of moving pig-iron, which was made completely by men’s labor.  To illustrate scientific management, he described an intervention at Bethlehem steel. He found that the average man moved about 12 ½ tons of pig iron each day, but the best handlers loaded 47 ½ tons. (I find both values astounding.)  By selecting the right men for the job, specifying how the loading task should be completed, and setting appropriate goals, he was able to improve per-employee pig-iron loading output. The loading tasks were streamlined and proper rests were enforced to ensure that a high level of output could be maintained for the entire day. Pig-iron handlers were accountable to achieve the goal of 47 ½ tons per day. Failure to consistently achieve the goal would result in reassignment.

Similarly, through careful study Taylor found the optimal shovel load was 21 pounds. This finding suggested many system-wide changes—in tools, team organization, and supervision. The organization provided different shovel sizes and shapes for different material density and characteristics. Workers that had been managed as teams were now managed as individuals, each accountable for performance targets.  Management structures changed to oversee these major changes.  

While Taylor’s time-and-motion studies are no longer relevant, given robotics and increasing service work, the measurement themes continue, and the themes of system improvement (organizational learning) and employee accountability continue to this day. In fact, these are two ideas with growing currency.

Organizational learning, which goes by many names, is simply the idea that organizations are entities that can learn and adapt. By looking deeply at the organization’s environment, processes, structures, routines, and culture, we can understand and improve them. There are many methods for encouraging organizational learning.  Whole conferences and societies have been developed around organizational learning, feedback, and measurement. In many situations, measurement of employee performance is the basis of organizational learning. 

Given the increased need to adapt organizations in our changing political, economic, social, and technical environment, I expect that measurement will increase. I worry, however, that organizations do not think clearly about the performance measures they track.

As organizations grow more complicated and employees more specialized, accountability for results has replaced the idea of managing tasks. Taylor was concerned with a moving pig-iron and micro-tasks such as lifting and carrying between stations. Now an employee is likely to have more complicated assignments comprised of dozens of tasks (for example, creating a new software feature or maintaining a database). Now we measure value-added and organizational results.  

Today, the essence of progressive management thinking could be stated as, “I do not want to micro-manage, so I am going to assign accountability for results and let my employees use their creativity and capability to get the job done.  In order to hold them accountable, I am going to measure their performance or productivity.” Many management theorists, such as Daniel Pink, argue for a result-oriented/only work environment (ROWE).  (Note that Taylor was indeed a micro-manager, so the parallel ends quickly.)  

I am a fan of managing results, not tasks. If you have ever been micro-managed, you’re probably a fan of managing results as well. I’m not completely sure, however, that we have the expertise to make it work. I see many organizations struggle with measures of performance—with pushback from employees and a blind push from management. ROWE works best when there are clear measures of performance that are linked to valued organizational outcomes.  These measures do not exist in many situations-- for example in support functions.

The final driver of increased measurement of employee performance is the computer-based work environment. Due to increasingly inexpensive databases, this environment allows more measurement and data-tracking. As computers facilitate more work, keystrokes, conversations, tasks, and transactions can be—and often are—automatically recorded. These digital trails can be compiled very cheaply. Footsteps, driving routes, and bathroom breaks can all be easily recorded with easily available technologies. It is inevitable that new measures of performance will be dreamed up, developed, and implemented. 

What Have We Learned About Managing and Leading With Measures?

My concern is our ability to manage, learn from, and improve from all this measurement. If we’re not careful, the additional performance measurement will only lead to additional misunderstanding and organizational chaos, misalignment, gaming of the system, and, in general, dysfunctional behavior. I’m not sure that our wisdom has kept pace with the amount of data and performance measures.  

In fact, problems associated with employee performance measurement appeared soon after the advent of scientific management.  Measuring employee performance often leads to strange outcomes. 

This is demonstrated by what’s known as the Hawthorn Effect, which showed, as far back as the mid-1920s, that when you measure employees’ performance, they react. Sometimes they react positively, sometimes negatively. Not surprisingly, it can be difficult to predict which outcome you will find.

The Hawthorn plant manufactured telephone equipment, and was attempting to identify the best practices to increase employee output. In one study, they focused on lighting. They increased the brightness of the lights in the plant, and employee output increased. They dimmed the lights, and, surprise—the same thing happened. Employee output increased whether the lights were brightened or dimmed. It wasn’t the quality of the lighting, but the change that employees were reacting to.

Additional studies from the Hawthorne plant, referred to as the "bank wiring room studies," revealed that social forces were affecting the output. Employees were aware of the measure and how they were studied by management. As a result the employees used the measure to communicate to management that they were, in fact, doing a reasonable job. Concerns, such as layoffs based on the measures, affected employee output. In these studies, employees attempted to communicate to management that they were working in a steady and reasonable manner.  

These studies have made it clear that measurement does not cause efficiency —there is always an underlying and very human mechanism that is a reaction to measurement. The reaction may or may not be improvement. These very human processes hinge on reactions to the measures that include communication and messaging, image management, and social interaction.

In day-to-day work environments, we continue to ignore what studies published 90 years ago clearly demonstrated. Many attempt to improve performance with measures, without giving adequate thought to managing the underlying human processes that will lead to improvement. 

Consider the testing mania present in American public schools.  These schools are expected to improve, largely because they are being measured and expected to improve. There is a blind belief in accountability. 

Similarly, consider the 97% of organizations that have performance appraisal systems that attempt to provide feedback to individuals in the hope that it will automatically improve performance, learning, and motivation.

Unknown to most, the ghost of Fredrick Taylor is alive in many of our modern organizations. Blind beliefs in simplistic ideas about measurement continue. We need to use measurement to increase efficiency, but a naive belief that productivity will increase without addressing the very human element of work is defeating the purpose, and the effectiveness, of the measures.

If you have examples of simplistic thinking behind employee performance measurement, I’d love to hear your story.

Charley Morrow