The Near Impossibility of Objectivity and Neutrality When Dealing with Human Beings
This characteristic is a cautionary note. From 1924–1932, a study of lighting conditions was done at the Hawthorne Works, a Western Electric factory outside of Chicago. One experiment was to examine the effect of better lighting on productivity. It sounds simple enough. The control was based on increasing wattage of the light bulbs weekly and then noting the results in productivity. It was expected that productivity would increase as lighting got better every week, and sure enough, it did.
However, one week some joker decreased instead of increased the lighting intensity, removing all objectivity and neutrality. Guess what? Productivity improved anyway. It was hardly a miracle or an error in measurement. What had happened was that workers expected the lighting intensity to increase and this motivated them to work harder, more efficiently, and hence more productively. Today this is known today as the “Hawthorne Effect”.2 It demonstrates that the novelty alone of having research conducted, along with the increased attention to the measurement results, can cause at least a temporary increase in productivity. And it means that, as Drucker said, “Controls are not applied to a falling stone, but to a social situation with living, breathing human beings who can and will be influenced by the controls themselves.”
Focusing on the Real Results
It is relatively easy to measure effort or efficiency, but much more difficult to measure real results with a control. Drucker explained that it was of no value to have the most efficient engineering department, for example, if the department was efficiently designing the wrong products. In somewhat the same fashion, Drucker differentiated leadership from management. Others have since similarly adopted his formula: that management was doing things right – read efficiently – while leadership was doing the right things, that is, the effective things to get the job done. So one could be very efficient as a manager, using whatever measurement you choose, and still not be a good leader.
Measuring efficiency is usually not so difficult. For example, one can measure the number of times a leader recognizes subordinates for accomplishing good work. That’s considered a sign of good leadership. Think of the “One-Minute Manager”, who was told to catch his people doing the right things more than catching them doing something wrong.3 However, “good work” can be done on the wrong things, as well as the right things. Maybe salespeople are doing a marvellous job selling the wrong product. Is this “good work”? To complicate controls further, how do we know what are “the right things”? This is much harder to know when so many factors and multiple humans are involved. Since leadership is an art, in observation, its quality may most definitely be in the eyes of the beholder.
Focusing on the Right Results
Battle gives some real examples of what this means. Marine Corps Gregg “Pappy” Boyington was a World War II fighter pilot. He later wrote the book, Bah, Bah, Black Sheep. About 20 years ago they made a TV series about his experiences, under the same name. As a young pilot he had resigned his commission as a Marine Corps pilot and volunteered for General Chennault’s “Flying Tigers” in China. He scored several victories as a fighter pilot. But his senior leadership thought that he drank too much, and he was so despised as a leader by his military superiors that when he left China to re-join the Marine Corps, he was not given a very good recommendation.
Although a superior pilot – and even when fighter pilots were badly needed during World War II – he was assigned a desk job with minimum responsibility in operations and no subordinates other than a secretary. It was only through luck that too many fighter aircraft were shipped to his location with no pilots to fly them in combat. He proposed to be given the job of squadron commander and that he would find and train his own pilots somehow. After all, the basic idea was to fight the enemy!
Boyington was given “temporary” command of a makeshift squadron and the authority to train a group of any pilots he could find and put them together in a squadron with a temporary unit designation under his leadership. Only in wartime could such a thing happen! He found pilots from wherever he could who were in non-flying jobs but were eager to volunteer for this “new squadron”. He trained transport pilots to be fighter pilots, and pilots who were “grounded” for having done something wrong were allowed back in the cockpit on probation. He trained them hard, and when he felt that they were ready, he took the squadron operational and they began to fly combat missions.
They called themselves the “Black Sheep” Squadron. However, that Black Sheep Squadron shot down more enemy aircraft in a few weeks than most did in months. The responsible senior commander made the unit a permanent squadron and it became the highest-rated Marine Corps fighter squadron in the Pacific theatre of operations. Boyington finished the war with a Congressional Medal of Honour, and a reputation as one of the finest fighter squadron commanders of any American service in the war. This once-despised leader who was barely trusted to command a secretary, retired from the Marine Corps with the senior rank of full colonel.
As in Boyington’s case, the eyes of the beholder are not always very objective measurements. As Drucker said, you don’t staff organizations because potential members don’t have any weaknesses, but because they have the right strengths.
Moreover, Drucker would have said that the commander allowing Boyington to form this squadron of semi-misfits took the right risk. It could have failed, and planes and lives might have been lost. It was the correct risk and it paid off.
When Conditions Change, the Real Results May Change, Too
This chapter seems to have a lot of military examples, but here is another. When I was a cadet, I remember we studied the case history of an infantry officer who had been commissioned, barely got through commissioning training and, before his unit entered combat, his commander had already instituted paperwork to have him decommissioned and “busted” back to the rank of private.
This lieutenant was overweight and slovenly, his uniforms were rarely pressed, his shoes weren’t shined, and he didn’t shave properly. Then the entire division went into combat. This officer didn’t change much, but he had a knack for leading under difficult circumstances and making the right decisions in combat. As the case description indicated, his men confidently followed in his “pudgy” footsteps. In combat, where it counted, he was a great success. Conditions had changed, and so did the real results upon which risks should be taken.
So one doesn’t always measure leadership by appearances or even the lack of weaknesses, but by absolute results depending on the organization’s mission. The failure or success of a leader is determined not so much by how hard a leader tries or how efficiently he or she works, but by the success or failure of the event or endeavour. This is a very crude measurement when we consider that so many factors are frequently not under the leader’s control: resources available, quality of personnel, difficulty of the task, acts of nature, judgment, and a lot more. But that’s all we have!
Non-measurable Events, Too
Controls are also difficult because some events in an organization, important to risk, simply aren’t measurable. We already noted that you don’t have true facts about the future. You don’t know what may suddenly happen on the way to the future, either. The ubiquitous slide rule, once on the person of every engineer worthy of the name, disappeared almost overnight when the pocket electronic calculator hit the market in 1972.
The Seven Control Specifications
Drucker investigated further and determined that all controls must satisfy certain specific specifications, of which there were seven:
1. They had to be economical – the less effort required to gain control, the better.
2. They had to be meaningful – in other words, they had to be intrinsically significant or symptoms of significant developments.
3. They must be appropriate to the nature of what you are measuring – absenteeism of a yearly average of 10 days per employee sounds acceptable, but you coul
d have only two employees and one was never absent while the other was absent frequently.
4. Measurements must be congruent to the phenomenon measured. As a writer, I’m always interested in book sales.
I once read a book by a famous entrepreneur who had written a best seller. He had bought a well-known company and promoted the company’s product frequently on television, stating he liked the product so much, he had bought the company. His advertising promotions were great. However, when I read his book, I found it was at best fair. Yet it became a bestseller and sold two million copies, surpassing many better books on entrepreneurship in sales, including Drucker’s Innovation and Entrepreneurship, which came out at about the same time. Not to mention several that I had written, the best of which had sold a little less than 100,000 copies.
One day it was revealed that the author had spent almost $2 million of his own money promoting the book. Now, book royalties are a lot less than you might think, frequently about 15% of the net amount received by the publisher. The net to the publisher may be only roughly 50% of the price of the book. Since this entrepreneur was not the publisher, I estimated that he had earned about $1 million in royalties for his total book sales. So he personally lost a million dollars selling his book. He may have been willing to pay a million dollars to have a two-million-copy bestseller just for bragging rights. But as a control measurement, book sales alone – the most frequent tool used to measure public demand for a particular book by readers – is probably a poor tool without other factors being noted and compared.
Control requirements 5, 6, and 7 are much easier and intuitive. They need to be timely. They are an expensive waste of time if the information received arrives too late to be of use. They need to be simple. As Drucker noted, complicated controls just don’t work. They frequently cause confusion and lead to other errors. Finally, they need to be oriented toward action. Controls are not something instituted for academic interest. They are for implementing strategy once actions with the right risks are chosen.
The Final Limitation
The final limitation on controls is the organization itself. An organization operates with rules, policies, rewards, punishments, incentives, resources, and capital equipment. But its success comes from people and their daily, frequently unquantifiable, actions. The expressions of their actions, such as an increase in salary, may be quantifiable. However, their feelings, motivations, illnesses, drive, and ambitions are not. As an operational system, the organization cannot be accurately quantified.
What It All Means
Risk is essential and, as a consultant, this is what Drucker taught his clients. The key is to pick the right risks and then control those risks considering the many factors that make this control so difficult to comprehend and use. But knowledge is power, or at least stored power. Selecting the right risks and monitoring the seven important aspects of the risk controls identified by Drucker means effective risk management. One cannot do more, nor should the consultant consider doing less.
1 Drucker, Peter F., Management: Tasks, Responsibilities, Practices (New York: Harper Business). p 512.
2 No Author Listed, “The Hawthorne Effect” in The Economist (November 3 2008). This article is adapted from The Economist Guide to Management Ideas and Gurus, by Tim Hindle (New York: Bloomberg Press, 2008,) assessed at http://www.economist.com/node/12510632, 12 February 2015.
3 Blanchard, Kenneth H. and Spencer Johnson, The One-Minute Manager (New York: William Morrow, 2003).
Chapter 11
How to Think Like Drucker, Einstein, and Sherlock Holmes
I’ve written earlier that perhaps Drucker’s greatest legacy was in teaching us to think. His valuable insights and theories, both published and in the classroom, did not come from scientific methods or mathematical calculations, but by the straightforward method of observation and using his brain and reasoning to logical conclusions. Like another genius of note, Albert Einstein, he did not arrive at his theories in a laboratory surrounded by microscopes, computers, and white-coated scientists, but in the laboratory of the mind. It is a fact that Einstein’s most productive period was in 1905, during which he produced four ground-breaking theoretical papers, one of which eventually won him the Nobel Prize. None of the four were conceived and written in the sterile atmosphere of a laboratory, or even at a university, but while he was working at the Swiss Patent Office.1
The Development of the Theory of Relativity
Einstein himself described the first step in the development of one of his most famous theories, the Theory of Relativity, as conceived while he imagined himself traveling along the side of a beam of light. It is also distinctly possible that it was Einstein who provided Drucker with the example of developing his own methodology of reasoning and thinking, which in turn resulted in his many theories of management. Drucker observed companies in action. Collectively he described these companies as “his laboratory”. He used his analysis and development of what he observed in this laboratory to develop his theories in his mind.
Einstein Revealed the Common Process
Although Drucker only gave us clues about the process, Einstein actually described it. In an article in the London Times written in 1919, Einstein wrote about what he called “Theories of Principle”. He stated that these theories “…employed the analytical, not the synthetic method. Their starting point and foundation are not hypothetical components, but empirically observed general properties of phenomena, principles from which mathematical formulae are deduced of such a kind that they apply to every case which presents itself”.2
I do not know whether Drucker actually read Einstein’s article. Drucker was only 10 years old at the time and did not speak English. However, Drucker did refer to Einstein, and it is possible that he read the article later. This article motivated me to better investigate the difference between synthetic and analytical research. To simplify some rather complex definitions, synthetic research starts with the known and proceeds to the unknown. Thus, one starts with a hypothesis or hypotheses and tests this hypothesis to prove or disprove it, usually by examination of a sufficient number of examples and testing mathematically for significant difference. Analytical research starts with the unknown and proceeds to the known. There is no hypothesis. One definition of analytical research is, “A specific type of research that involves critical-thinking skills and the evaluation of facts and information relative to the research being conducted.”3 The analytical process is how Einstein and Drucker arrived at their theories. This also extended to Drucker’s consulting practice, both in his use of what he observed and his reasoning in considering a client’s issues.
Enter the World’s Greatest Fictional Detective
Sherlock Holmes, the great fictional detective of yet another genius, Sir Arthur Conan Doyle, also enters into this discussion of Drucker’s thinking. I’ve already noted that Drucker likely used Doyle’s definition of Holmes as a “consulting detective” to determine the definition of a management consultant. The dictionary and other sources were of little help in providing a definition at a time when neither Drucker nor his military supervisor understood the duties for which Drucker had been mobilized during World War II. It is likely that Drucker’s insight as to this definition was helped by reading some of Sir Arthur’s stories or novels after he fled Germany for England during the rise of Hitler in 1934.
While Sherlock Holmes had the amazing ability to deduce facts, his assistant, Dr John Watson, complained of his own inability to see all the facts that Sherlock seemed to see. To explain this, Sherlock stated: “On the contrary, Watson, you can see everything. You fail, however, to reason from what you see. You are too timid in drawing your inferences.” In other words, it was not only that one must observe, but one must analyse and draw conclusions from these observations.4
Academic Research is an Analytical Process, But...
Is academic research itself not an analytical process? It is. However, note that the theories developed by the three genius
es – Einstein, Sir Arthur Conan Doyle’s famous detective (Sherlock Holmes), and Peter Drucker – did not start with hypotheses until after observation, and their resulting theories did not evolve from the scientific method as it is commonly understood, a process in which many subjects are surveyed and analysed through mathematical techniques and equations. Their analytical approach came from a simple model:
1. Observation, either real or, as in Einstein’s case, imagined.
2. Analysis of what was observed.
3. Conclusions.
4. Construction of theory based on these conclusions.
Ed Cooke, a Grand Master of Memory, is a graduate of Oxford University in psychology, as well as the author of books on memory. He was the memory coach who convinced Joshua Foer that anyone could be trained to have a world-class memory in a year. Though Foer’s tested memory was only average at the beginning, he was trained by Cooke to become the United States Memory Champion in about one year to prove Cooke’s claim that he could train anyone in one year of concentrated study. In case you’re wondering what concentrated study entailed, it took about one hour a day of training, and then several hours a day prior to the championship competition. (If you want to know more, I recommend Moonwalking with Einstein by Joshua Foer, Penguin Books, 2011).
Discussing what the mind was capable of, Cooke wrote that there were two ways of doing brain research: “The first is the way that empirical psychology does it, which is that you look from the outside and take a load of measurements from a lot of different people. The other way follows from the logic that a system’s optimal performance can tell you something about its design.”5
Consulting Drucker Page 16