The fourth theory of worker motivation
By J.J. Haefner
Motivating your work force always has been the key to keep businesses humming. The simple act of moving from an authoritarian environment, where managers act as if workers cannot be trusted, to an environment where workers can be autonomous and trusted collaborators, can make a world of difference. Going beyond the three primary theories of motivation, a fourth theory of motivation includes three subsystems in systemic motivation – leadership, environment and personalities – linked by positive core values. In the case studied, factors of that fourth theory helped an underperforming work shift not only meet expectations, but shatter production records.
The role of engineers in manufacturing is critical for solving day-to-day production issues, but in the new economic era cited by W. Edwards Deming, it is imperative that engineers function as leaders who exhibit profound knowledge. To do this, they must become aware of a broader array of skills and knowledge. Deming cited part of the knowledge for the new economy as statistics and psychology. This article shows how both helped correct a $10 million dollar production shortfall. The technical issues at the root of the shortfall were not complicated and lost production was recouped quickly. But producing an extra million dollars of product on an annual basis was unanticipated. The reasons for the increased production were described as a new theory of motivation that I call the fourth theory of motivation.
Although academia includes numerous motivational theories, in general, the three theories of motivation are Theory X, which does not trust workers; Theory Y, which trusts workers; and Theory Z, a Japanese holistic management approach. The fourth theory described in this article is a model of how motivation factors interact to form systemic motivation.
In 2008, Towers Perrin consulting group published a white paper based on extensive international research of worker motivation and productivity. They found that 38 percent of the world’s workers are not engaged in their work, not motivated, and consequently not performing to their potential. Only 21 percent of the world’s workers were engaged fully. Millions, possibly billions, of dollars of productivity are wasted.
In early 2009, a published case study examined the motivation factors affecting a team of production workers trying to recover a significant production shortfall. Part of the team was an engineer supervisor who applied statistics and Deming’s principles such as driving out fear and removing barriers that rob people of pride of workmanship. These worked to correct the production shortfall, but after that something unanticipated occurred; the production workers began to break production records week after week until they were producing more than $1 million of additional product annually.
An analysis found that the engineer supervisor introduced several motivational queues during the problem solving process. When production was restored, another series of work environment motivation queues was introduced, and the queues interacted with the needs and personalities of the production workers to form a motivation system (see Figure 1), or systemic motivation. Workers became self-motivated and reached a tipping point where they eagerly devoted more thought, time, energy and self-sacrifice to attain production records week after week.
The engineer supervisor introduced leadership motivation factors that constituted one subsystem of the motivation system. The system is a hierarchical relationship with leadership responsible for establishing the guiding principles. Leadership is also responsible for maintaining a system of positive core values that link leadership to the other motivation subsystems of environment and the individual psychology of the personalities in an organization.
The engineer supervisor inherited a demoralized union shop production line where mutual suspicion and distrust existed between management and labor. It didn’t help that the first shift produced at 100 percent of schedule, the second shift production fell, and the third shift struggled to attain only 50 percent of schedule. There was no explanation for the differences. This is a classic situation where supervisors could blame the union and the union workers would unify to protect their members. One only can imagine how often this scenario has played out in industry.
The first night on the job, the engineering supervisor reviewed the process with the operator, the machine settings, control plan, control charts and general information. He then called the maintenance technician to begin conducting a factorial experiment following George Box’s evolutionary operation (EVOP) approach. According to Box, this approach normally is conducted by operators during full-scale production. Based on the engineering supervisor’s guidance, the technician and operators made adjustments, collected data and tracked progress. After a couple of days of EVOP, the throughput improved. Full production was reached in less than three weeks.
Somewhat unknowingly at the time, the engineering supervisor had introduced motivation queues such as intellectual stimulation, goal setting, clarifying task significance, participative decision-making and enabling formulation. Goal setting is one of the prepotent theories of motivation. Setting attainable goals has proven to motivate workers and improve productivity. In this case, the goal was full production. The first shift was at full production, so the goal was attainable. Concurrent with goal setting was clarifying the significance of recovering lost production to the technician and production workers. Not only would the company meet demand, but the workers could quit working a schedule where they were allowed only one day off every two weeks.
The engineering supervisor joined the technician and production workers to solicit their views, make them participants in solving the problem, and enable them as decision-makers. In motivation theory this is called enabling formulation. He made it their project. And he was one of the team, not the boss, not the supervisor, but a coequal participant where each member applied skills when needed. The technician made machine adjustments, the production workers monitored product characteristics and plotted them on control charts, and the engineering supervisor added statistical knowledge and a problem solving approach as intellectual stimulation. Intellectual stimulation is the capacity of a leader to exercise the appropriate skills and knowledge for the situation. Intellectual stimulation was the first motivational queue introduced.
In effect, the engineering manager had replaced Theory X authoritarian management, where managers act as if workers cannot be trusted, with Theory Y, which states that workers can be autonomous and trusted collaborators. Note that merely trusting and empowering workers would not have solved this problem. It took a skilled process engineer and statistician to present the proper skills in a manner that did not emulate a Theory X supervisor. In so doing, the engineering supervisor bought a bonus. By eliminating authoritarian supervision, an atmosphere of trust began to emerge. Trust is a principal motivation factor for creating a normative environment, and it is necessary when trying to get workers to explain how two shifts can run full production with different process control charts. Figure 2 shows a comparison of the product characteristic of weight between the first and third shifts. It was not possible to run 100 percent of production rate with two different weight distributions. Production workers might explain the mystery if workers trusted they would not be blamed.
The engineering supervisor presented the control chart anomaly to the first shift lead operator. She was hesitant to talk because she feared some form of trouble. After convincing her that she would not get into trouble, she told an interesting story. She had been with the production line since it was installed and knew what machine parameters made good parts. She also knew that the quality manager who set up the control charts chose artificial nominal target values that were inconsistent with actual working parameters. All of the operators were told to monitor and adjust the process to achieve the nominal targets. Every one complied but her.
Fearing the person who set up the charts, but wanting to do a good job, she devised a routine where she would tweak the machine to a location where the process characteristic hovered around the artificial nominal. She would grab some parts to measure for the control charts and quickly turn the machine back to where she knew it would make good parts. She had been doing this for several years.
Why she wasn’t forthcoming with this explanation to management is exactly why Deming admonished managers to drive out fear. He wrote that fear reduced performance. In other words, anything that invokes fear would deter positive motivation and cause aberrant behavior; invoking fear in the workplace is a motivation deterrent behavior. Peter Drucker echoed Deming’s perspectives. He wrote that fear was a demotivator. This brings us to a fundamental rule in the fourth theory of motivation. Leadership has the responsibility to institute behaviors that become positive core values from which positive motivation may emerge. This is what the engineering supervisor did, and this set the stage for other motivation factors to emerge.
Leadership is the first, and most important, subsystem in systemic motivation. The other motivation subsystems are environment and individual psychology.
It is also worth noting that Deming recommended hiring statisticians. Make sure they are experienced statisticians. In spite of the wave of statistical process control training and Six Sigma, statisticians are not made in seminars. A couple of weeks of Six Sigma training and a couple of projects do not make an experienced professional.
Environment and motivation
The second subsystem of the fourth theory of motivation is environment. Environment has seven motivation factors. Perhaps the most important is trust. As noted earlier, the engineering supervisor developed an atmosphere of trust between himself and the workers. This allowed more information to emerge that clarified the root causes for the problems on the third shift by being able to solicit information from workers on other shifts. Developing trust also stimulated social interaction and shared norms among the workers as they began to work as a team to solve the problem. The social interaction was enhanced by workers having the autonomy to leave their work areas to commiserate with others about the status of the line. Ultimately, the success of this process improvement resulted in the engagement of workers’ normative intrinsic motivation.
Normative intrinsic motivation is a dependency-based group bonding that nurtures and sustains social obligations. The strength of normative motivation hinges on the degree of association and identification with the organization. Organizational traits such as goals, norms and values influence normative motivation. The greatest motivational moments occur when the individual, the group and the organization become aligned. This is the ultimate goal for any group of workers.
Alignment also includes alignment of the organization with the personal needs of individual workers. Too often, organizations consider needs as a one-way street where individual workers must align exclusively with organizational needs at their own personal expense. When organizations view workers’ personal needs as important and create policies that give workers the freedom to take care of family needs, have adequate sick days, have the freedom to take vacations, and even enjoy the occasional wonderful day off at a moment’s notice, then the worker has something of value that acts as additional motivation to work and productivity.
Alignment also played out in this situation. This particular factory was in a rural agricultural area. It was fall, and the farmers were working long days harvesting crops. A number of production workers were farm wives who, during harvest season, had to pick up all of the normal chores done by their husbands during the nonharvest season. The wives had to maintain their normal tasks of milking cows, feeding animals, cleaning the barn and other daily farm tasks. By the time they got to work, they had little sleep and were exhausted. This was the season when it was not unusual for workers to be terminated for being late or missing work.
The engineering supervisor assessed the situation, called the team together, and worked out a plan to make sure that sufficient cross-training was in place so that the production lines could be started and maintained even if someone was late or absent. In return for their participation covering for each other, they would not be written up or reprimanded. Both company and union rules quietly were being ignored. This had a powerful effect on the workers that played out in an unanticipated way. The workers began to break production records. The first production record was an "atta boy" from upper management to the engineering supervisor. He passed it along to the production workers. This is where a motivation wild card – workers’ individual psychology – entered the process.
The wild card in any social and organizational group is the individual psychology of the individual members. Unlike companies like Toyota, most companies do not have the luxury of taking an extraordinary amount of time to evaluate potential employees for a cultural fit. Most rural workers come in off the street and are hired after a brief background check and interview. Factors that affect their motivation rarely are examined. But here are a few that existed among the workers involved in this situation. Being agreeable, having a positive mood and nurturing a prosocial disposition are significant personality factors for a motivated work force. These involve the capacity to want to help others beyond the normal working scope. When elements of goal regulation (the ability to make adjustments to accomplish the work) are combined with a sense of commitment, intrinsic motivation begins to mature and have a significant effect.
Another personality characteristic is self-determination. One or more workers at the production facility had this trait. They began tracking their own production output and, based on how the line ran, knew whether they had the potential to break a record. If the potential existed, they took advantage of the moment and did what was necessary to break the record. Whereas, the production line normally shut down for breaks, the workers covered for each other and kept the line running continuously. Some workers began to curtail their breaks, and the last production record was set when workers continued to work after their shift during the 20-minute cleanup transition between shifts. They actually intruded into the next shift to break a record.
Deterrence behavior and systems
The key to the success of this process improvement was to change management style from Theory X management to Theory Y management. The success of that transition is a theme that has existed since Western Electric’s Hawthorne Works productivity experiments between 1927 and 1932, where test room subjects had Theory Y supervision and engineers. Consequently, productivity increased. Abraham Maslow’s research noted that positive motivation works better than negative motivation. Deming concurred and called for management to drive out fear. Fear is antithetical to positive core values.
Other factors detract from positive core values. Managers who are not fact-based undermine morale and motivation. Nonfact-based supervision is like traveling without a roadmap, and when workers perceive that a plan does not work, their motivation is diminished. Nonfact-based decision-making is the opposite of intellectual stimulation. Overcomplicating or oversimplifying work also can demotivate. So can management that undervalues work. Research has shown that ineffective quality control systems lower motivation and productivity. These deterrent factors can and will undermine motivation and lose production.
Recovering the lost production on the third shift would have been sufficient to make this a good article about the use of EVOP, the misuse of statistical process control or the necessity of engineers to understand statistics. Those would have missed the real story. The fact that production workers found ways to create production records for a state-of-the-art, high speed production line is remarkable. Something very unique occurred – the workers became engaged because a large number of motivation factors were introduced into the work environment. If we were to plot a linear flow of motivation factors that emerged, it would look like Figure 3.
What emerged during this production improvement was an evolution and interaction of factors that affected worker motivation. It received its initial energy from a philosophy that Deming advocated and extends beyond Theory Y, and even Theory Z (Japanese style management). It gained impetus with a sound understanding and application of statistics. When the work environment was changed to achieve interest alignment – keep the production lines running while serving the needs of exhausted workers – an avenue opened for individual potential to emerge in the form of intrinsic motivation and goal regulation. The result was $1 million of extra production each year.
This problem is an example of how low skill sets can undermine well-designed state-of-the-art production lines. This is also an example of how an engineer grounded in statistics and Deming philosophy corrected the problem and engaged motivation factors that resulted in something unanticipated. It suggests that the role of engineers plays a crucial part in the new economic paradigm of knowledge value. Engineering skills need to extend beyond the traditional and encompass what Deming referred to as profound knowledge. Profound knowledge includes psychology, knowledge of a system, theory of knowledge and knowledge of variation.
This article has significantly examined more psychology than Deming could explain but encompassed all that he implied. Knowledge of systems explains how everything is linked and processes need to be managed as a system. Systems thinking is a guiding principle of ISO 9001:2008, TS 16949, ISO 13485 and other quality systems. This should not be a surprise to anyone. Knowledge of variation is based in statistics, and process control charts are an integral part of understanding variation in order to control processes. Lack of knowledge of variation is what caused the third shift’s problems.
Theory of knowledge from a scholar’s perspective answers the question, “How do we know what we know?” From an applications perspective it is the ability to generate theories about incidents, craft a plan to test theories, conduct the test, check the results and act on those results. You may recognize this as plan, do, check and act. These are the skills of engineering in the new economic era.
J.J. Haefner has worked for many years in industry to improve processes and launch new products such as automotive air bags and automotive cam phasing. He has taught statistics at the University of Wisconsin in the College of Engineering, and he led Credit Union National Association – Card Services Group to win the Wisconsin Quality Network Award by improving in every category of the Malcolm Baldrige criteria. He has a master’s degree in industrial engineering from the University of Wisconsin-Madison. He is completing his dissertation at Walden University in applied management and decision sciences with specialization in engineering management for globally competitive product and services. His research interest is improving worker productivity and well-being.