Showing posts with label VP. Show all posts
Showing posts with label VP. Show all posts

Friday, March 20, 2020

Life on the Edge: A Reactive Stimulator Story


By: Gary J. Salton, Ph.D.
Chief: Research & Development
Professional Communications, Inc.
 
INTRODUCTION: 
The Reactive Stimulator (RS) style has permeated all aspects of my life—from the most trivial to the most consequential. To map all of the effects of the style over my 77 year life span would fill bookshelves. What can be done here is to sketch how my dominant Reactive Stimulator decision strategy affected the course of my career path. The trajectory of that path begins in early childhood.


THE EARLY YEARS 
My earliest memory was as a 5 year old running along the top of a brick pier at Lake Tippecanoe. My mother casually commented to my father that I was “a real risk taker!” What effect did that remark have on my life? I do not know. But just the fact that I remember the episode after 70 years suggests that it had some effect.

Fulfilling my mother’s prophecy was easy. All you had to do to create risk was to act before fully thinking through an issue. This reduces the cost of decision making. No thinking means that less effort needed and things can get done faster.

This strategy works best when focused on near-term outcomes. The dangers lurking in a longer term horizon were simply risks that could be handled as they became visible. Since issues were not thought through, there was no way to figure out how close I was to perfection. Thus adequacy rather than optimality became my standard of acceptance.

The pattern of behavior described above is what I would later come to define as a Reactive Stimulator or RS style (i.e., a style is a characteristic manner of doing something). This is one of four basic styles that people typically use to navigate life. Did my mother’s off-hand comment set the course of my life down this least traveled road? It is possible but not likely. There is much evidence that a large part of our life orientation is set at birth or soon thereafter. But whatever was the ultimate “cause” of adoption the RS strategy has proven to be durable enough for me to continue to use it over a very long lifetime.

The RS strategy had a lot to offer. It was cheap, fast, exciting and can produce an impressive volume of outcomes. With adequacy as the standard the quality of those outcomes was uneven. In most cases good enough is good enough and optimal solutions are not a required condition. While it is low cost, the RS strategy comes with serious downside exposures. These risks can disrupt a life path before that path is even launched.

In my case that serious exposure occurred in my early education. During this time in history (the 1940’s) classroom order was a primary goal of elementary education (at least at the school I attended). My RS orientation caused me to center my attention on “doing” thing (versus thinking about them). A short-range horizon (measured in minutes at this age) blinded me to potential future consequences. Using adequacy as my standard meant that things were never quite right in the teacher’s eyes. This was not a formula for educational success.

These and other RS generated tendencies caused me to disregard rules. I did not intentionally go about trying to disobey rules. I just did not notice the rules even existed. My teachers interpreted my behavior as willful disobedience and applied their favored method of restoring order—corporeal punishment. A ruler forcefully applied to the palm of the hand was intended to impart a new pattern of behavior. It did not work. My short-term orientation came into play. I simply forgot to remember about the punishment.

The end result was that my behavior persisted unchanged. The result was that I flunked 4th grade (or maybe 5th, I’m not really sure which). I do not know if I flunked due to a shortfall in my cumulative learning or as a disciplinary strategy. Whatever was the motive another year in 4th grade did not result in any visible behavioral maturation. I suspect that social promotion powered my progress through the remainder of my primary grades—I was just getting too old to keep around.

My behavior in high school followed the same trajectory as my primary school years—just at a much more accelerated rate. I dropped out of high school after the first semester of my freshman year. I had flunked almost all classes during that first semester (I got a “D” in shop) and I saw little point in hanging around for more of the same. Fortunately life in the 1950’s had advantages for high school dropouts that are not available today.

Those advantages centered on the need for a lot of unskilled labor. Primary among them for a high school dropout was the military. The armed forces still needed to enlist people to serve as cannon fodder (soldiers considered as expendable war material). If you were warm and breathing, you had a potential home in the military. I qualified.

Overall, my years in the military were colored more by alcohol and youthful indiscretions than by the strategic styles that guided behavioral choices. Those indiscretions resulted in rank reduction. I left the service honorably but at the same rank as when I joined. However, something had happened that I did not notice at the time.

That unnoticed life-changing event was basic training. For some unknown reason no one in my early years—parents or teachers—were able to show me the value that discipline can have on performance. Drill Sergeants did not have that problem. They have ways of getting and keeping your attention whether you want it or not. They were able to introduce and instill the practice of discipline—obedience to rules and codes of behavior.

For military purposes that obedience was focused on the chain of command. If a superior told you to leave the foxhole, you did it without thought or question. The training focused on physical activities. The value of discipline on the physical outcome was obvious. However, I generalized that learning and applied it to life in general. I interpreted discipline as focused energy. I then figured that if I applied enough focused energy to a subject—any subject—I could do almost anything. This belief was going to be a key to my future life course.


THE DEVELOPMENTAL YEARS
Luck played a significant role in my RS oriented life. The short-range opportunistic orientation created a lot of negative exposures such as those of my early educational experience. But it also presented me with unplanned opportunities. One of these opportunities arose when a friend asked me to accompany him. He was planning to sign up for classes at a local junior college. Like me, neither his family nor friends had any experience with higher education. I presume that he wanted my company to provide him some reassurance in the face of the unfamiliar.

I did accompany him and milled around the college office waiting for my friend to complete his registration. From casual discussions with the staff I found that the newly opened junior college (they are now referred to as Community Colleges) had just opened its doors. I also discovered that they were desperate for students to fill the seats. Their standard of acceptance at the time was the same as it had been for the military. You had to be warm and breathing. I again qualified.

Without a lot of forethought and with no particular plan in mind I signed up for a class in general speech. The $45.00 I paid for the course would be about $385 in 2019 dollars. This was a significant commitment for me at the time and the commitment had a positive effect. I now had to get “value” from my investment. The only way to get value was to attend class and do the work.

This is where the learning from my basic training in the military kicked in. I faithfully attended the speech classes and dutifully completed assignments. The demands of a general speech class do not sound like much. But for a person who had met nothing but failure in academic pursuits it was material. The ability to do the course work demonstrated to me that I was intellectually no different from my classmates. I could compete with “smart, college educated” people.

The “C” grade that I earned in that first college level class confirmed that I was capable of heretofore impossible things. This was the highest grade I had earned up to that time. It opened the doors of possibility in my mind. A two-year Associate of Arts degree became a realistic prospect. That possibility provided the motive for signing up for two 101 level classes for the next trimester. The dollar commitments were getting bigger.

I chose economics and sociology. These choices again show the influence of my RS style. Keep in mind what I knew at the time. I knew that economics had to do with the study of money. I did not even consider that the subject would demand at least a high school math background that I did not have. But using my basic training focus and energy I believed that the relevant math could be searched out and acquired. It was and it could.

I knew that sociology had something to do with the study of societies. I came to find out that it was not mathematically demanding but it involved an awful lot of reading. I knew how to read but did not have a lot of practice actually doing it. Comprehension demanded much re-reading and a slow pace. Again basic training discipline came into play. I simply applied myself without regard of whether that reading took one hour or ten.

In both subjects I simply “hit the books” with everything I had. I read and reread assigned readings until I felt I understood them completely. I ran and reran calculations in economics until I was sure that the results were correct. It was a clumsy, inefficient and a personally costly method. But it worked. Grades of “A” and “B” confirmed that if I was willing to expend the energy, it could meet the demands of academia.

As I progressed through my undergraduate courses at the community college I evolved a pattern of study that worked for me. I took copious notes in classes. I then recopied them in an organized format. I constructed lists of questions that might be asked in a test and prepared the answers. Required papers were written and edited. This process resulted in acquiring study skills but it also had another outcome.

I came to appreciate the value of understanding. There was a real pleasure to be gained in understanding the “what causes what and why” of a subject. I would later define the information processing pattern focused on pursuit of understanding as a Hypothetical Analyzer (HA) style. My new found appreciation did not cause me to come to use HA as my “go to” default approach to life. It did, however, create an appreciation of learning and knowledge creation that would remain with me for a lifetime.

It is worth noting that my RS orientation benefited from the simplicity of the academic success formula. Grades determined whether certifications (e.g., degrees) are awarded. Grades were awarded primarily on the basis of tests. Tests typically involve regurgitation of course learning's or the successful application of predefined patterns (e.g., formulas, writing formats, physical skills like dissection, etc.). This kind of transparent formula fit the RS strategy of targeting immediately visible outcomes. Educational efforts targeted at groups with high RS commitments should probably incorporate highly visible, step-by-step elements leading to explicit, visible outcomes into their designs.

My grades continued to hold at the “A” and “B” levels throughout my community college years. This was the era before grade inflation came to grip colleges. A grade of “C” really denoted an adequate level of performance. My stream of A’s and B’s provided me with a solid certification of competitive academic adequacy. The increased confidence this created had motivational consequences. My academic ambitions rose from an Associate to a Bachelor’s degree.

After about 30 semester hours in a Community College I felt confident enough in my abilities to apply to a 4-year degree granting college. The college was in Chicago—about a 35 minute train ride from the suburbs where I lived. I had a full time job working nights from 11PM to 7AM. That meant that I was available to attend ordinary day classes. Again focus and energy applied without concern for efficiency carried the day. I was able to carry a full academic load and still support my family.

I earned my bachelors with a reasonably strong grade point history. I had a job that paid enough to support my family. I had demonstrated the stamina needed to hold a full time job and full time school registration. Graduate education was a viable option,

My motive for majoring in business administration was that it promised the quickest return on educational investment. This also was the time of the space program, integrated circuits, computers and advances in the biological sciences (e.g., birth control, vaccines, etc.). The value of advanced education was being highlighted everywhere and business was no exception. The MBA was the “hot” degree and held promise of high demand and premium salaries. I decided to “give it a shot.”


THE MBA
True to my RS leanings, I applied to only one school—Northwestern University. It was (and is) a top ten business school with very restrictive admissions requirements. My travel from high school drop out to college graduate had given me an exaggerated sense of self-worth—a “fat head” in colloquial terms. I did not even consider the possibility that my application would be declined. That turned out to be a mistake.

The Graduate Record Exam (GRE) was a mandatory requirement at the time I applied to grad school. I did not do well. My grade fell in about the 40th percentile. This would have been a “red flag” to most people. However I figured that my grades would be enough to carry me over the hurdle. I was wrong again.

I received a letter from Northwestern declining my application. Again true to my RS style I was physically on my way to the school within minutes of reading the rejection letter. No thought, no plan, just reaction (the style is called a “Reactive” Stimulator). Upon arrival I by-passed the secretary and literally barged into the Admission Officer’s office. The RS style tends to cause a person to favor asking for forgiveness rather than for permission.

This level of assertiveness was apparently not common experience at Northwestern. The Admission Officer was a little taken aback by my assertiveness and allowed me to make my case. I proceeded to do so with considerable animation. I told him that I had taken the exam after working a 16 hour shift and with no preparation. I claimed that this made the GRE results unrepresentative. I maintained that my grades and personal situation confirmed that view. I acknowledged my misjudgment but I argued that I was the kind of person Northwestern wanted as an alumnus. A degree of arrogance is a common RS attribute which I did not lack.

The GRE was a “one strike and you are out” test at the time of my application. My plea to the Admissions Officer plea caused him to take the unusual step of authorizing a retake of the exam. This was not a home run I had hoped for but it did keep me in the game. This time I had a better idea of the stakes involved.

I immediately signed up for the next GRE exam. Again the discipline of basic training was applied. I went out and bought every GRE test preparation book I could find and went through them page by page. I do not remember my re-take score but apparently it was high enough to merit admission. I received another letter from the school this time it welcoming me as a student.

A realistic look at my MBA experience suggests that it was not my grades, GRE score or intellectual “brilliance” that earned my admission. It is more likely that the immediacy, forcefulness and logic of my response to the poor GRE score that got me admitted. It can reasonably be argued that my arrogant RS strategy was the cause of the initial rejection. It is also likely my grades alone did not warrant acceptance. Rather it was probably the speed and forcefulness of my RS response that turned the trick. Styles can work in both positive and negative directions on the same subject at about the same time.

My progress through the MBA was a reasonably straight forward. The same strategies as used in my undergraduate years continued to apply. There were instances where my RS style may have influenced some minor adventures. For example, I helped initiate a parade of students into the Dean’s office complaining about the competency of a mathematics professor. Or the time Norman (another student) and I figured out how to use the punch card duplicating machine to satisfy an assignment involving programming the quadratic equation in the FORTRAN language. While it can be spiced up with these anecdotes the MBA experience was really just a two-year slog.

Upon graduation employment opportunities arrived as predicted. I interviewed 60 firms on campus before joining an automotive firm in Detroit Michigan. The choice was simple. They offered the most money, the most generous fringe benefits and multiple avenues for advancement on a worldwide basis. It was time to get that “return on investment” that had underpinned my educational efforts.

CORPORATE AMERICA
Education gave me a command of intellectual matters. It did not give me knowledge of the culture that I would encounter upon graduation. At the time that I joined the automotive firm it had about 400,000 employees and was probably at the peak of its bureaucratic organizational discipline. For example, the three ring binders holding the Comptroller’s Manual occupied an entire wall in the finance department. The likely implications of a highly structured environment on my somewhat unruly RS tendencies had completely escaped my attention.

It turned out that first job at the new firm set the course of my career. That first job was to maintain bank balances in multiple banks worldwide in a way that optimized the interest income while satisfying line of credit deposit requirements. The job was tedious, exacting and provided little action based satisfaction. It was likely among the worst jobs a strong RS could encounter. Things did not look good but chance once again intervened.

The banking department had a Telex terminal in the backroom (a kind of an old fashion teletype machine that you might see in the old black & white movies). It was ordinarily used to exchange information with various banks. I discovered that it also connected to the GE time-sharing computer network—a brand new innovation at the time. No one in finance knew how to program so management was not concerned with machine access. It was ignored by everyone but me.

The programming language on the GE timeshare machine was called BASIC. It resembled the FORTRAN of my graduate school years so I came in with a bit of “how to” knowledge. There were also programming manuals on the wall behind the Telex. These provided the remainder of the “how to.” But the system itself offered a bit of a challenge. It only allowed 2K programs (2,048 bytes of memory) but those programs to be linked in kind of a chain. I figured that if we could put a person on the moon under these size constraints, I could probably figure out how to program a banking report. So I began programming after working hours.

Working after hours meant that I did not get any annoying questions about what I was doing. This mitigated the need to advise anyone of what I was doing or to ask anyone’s permission to do it. Things tend to move faster that when you choose to ask for forgiveness rather than permission. Over the course of a month I managed to program my job out of existence.

About the time I finished programming GE sent the firm a bill for about $550 (about $4,000 in 2019 money). A visit to my manager’s office soon followed. I was told that junior analysts should not be spending that kind of money without first obtaining permission. I apologized and claimed to be unaware of the cost (which was true, I did not know the exact cost). I also pointed out that they could now permanently save the cost of one professional staff member. On the whole, the firm was ahead of the game. I was chastised by management but forgiven.

The fast response RS orientation served me well in this situation. Had I moved at a slower pace the bill from GE would have arrived before I finished. It is virtually certain that my efforts would have been stopped. That could and probably would have dramatically changed the course of my career. If you are going to engage in questionable activities it is probably best to move quickly rather than deliberately.

My Banking Department adventure had inadvertently created a personal “brand.” Managers looking to improve their areas of responsibility began to recruit me as a person who could initiate change. Even in a highly bureaucratic firm, change required that I be given a bit of discretionary latitude. This made the firm a tolerable environment for a young man with strong RS tendencies.

Life was good but not great. Interesting assignments and access to advanced technology insulated me from bureaucratic drudgery. The money, a lot of “pats on the head” and regular promotions kept me interested. Getting a new car of my choice every 6 months was a strong reminder of which side my bread was butter on. However, the intellectual adventure I enjoyed in college was absent. It turned out that the answer for filling the mental gap was down the street.

MORE SCHOOL
There was a university about 4 miles from the office. One of the generous fringe benefits that had lured me into joining the firm came into play. The firm offered full tuition reimbursement for any university level class on any subject. I do not know what the firm had intended to accomplish with this policy but it gave me a way to keep my mind engaged.

Intellectual boredom was the underlying motive powering my return to graduate education. My choice of economics as a subject of that study is not that clear. It may have involved gaining “bragging rights” among my peers in the finance organization. Or it may have been an insurance policy against future employment difficulties. Or it may have been born of my favorable initial experiences in the junior college. But whatever the reason I signed up for the Master’s degree program in Economics.

The time spent in the economics program was largely unremarkable. It is worth noting that my interest was in microeconomics. This area is focused on how people make economic decisions on a small, local scale. I did not know it at the time but the area would come to influence the future development of “I Opt” technology. In any event, I graduated with a straight “A” grade point. That pumped me up a bit so I signed up for the economics PhD program. Things did not work out as well at this level.

The higher level classes focused heavily on detailed particulars. The program tended to focus on esoteric questions, intricate details and exhaustive mathematics. I recall being frustrated over the minutiae. Patience is not an attribute typically associated with the RS strategic style. A lack of intellectual satisfaction a focus on trivial matters called for a reaction. It was not long in coming.

My response was simple and direct. One day I spontaneously walked out of the Economics and into the Sociology department. There was no plan. I had an interest in sociology since those early classes at the junior college. I knew that the subject was unlikely to involve the minutiae I had encountered in economics. Since I had no specific end use agenda for the PhD degree sociology as a subject was as good as any other. What mattered was that my mind remained engaged.

I found the Department Chair in Sociology to be very willing to facilitate the change. I think he was tickled pink over having someone from economics petition to enter the sociology program. But whatever the reason, the move was quick and effortless—it was an optimal RS outcome.

Strategic styles do not affect everything but they do influence how a lot of things get done. An example is the way I handled the formal requirements of a PhD in Sociology. One of these was that PhD candidates were required to demonstrate of basic competence in a second language. This was a problem for me since I avoided language in my undergraduate years as a way of preserving my grade point average.

A “logical” strategy for meeting the language requirement would be to take a class. A PhD normally takes between 5 and 7 years to complete. There was plenty of time to do language classwork. However, the RS strategy tends to look for the easiest rather than the most logical way. Since adequacy rather than excellence was my standard of acceptance all I needed was to pass the test, not to speak the language. The testing procedure seemed to offer a solution to my problem.

The Princeton Placement Test was used to gauge language proficiency. The test was a multiple choice written exam offered every quarter at the cost about $15 (about $100 in 2019 money). The first time I took the exam I fell short of the required score by only 50 points. I figured it was virtually certain that if I retook exam every quarter, sooner or later I would pass simply by chance alone. I had created an RS type of option.

My RS orientation kept me looking for easier ways even after I had isolated the “easy” Princeton strategy. As it turned out I came up with another even easier way. I had gained a command of computer programming in the course of my job. At the time (the late 1970’s) programming was not a widely available skill—especially in a “soft science” area like sociology. I figured that there was a probability that I could use programming to satisfy the language requirement. It was worth a shot. If it did not work I could always fall back to my Princeton option.

The department chair had the authority to declare that the language requirement as satisfied. So he became my focal point. I produced several large 3-ring binders of working programs to prove my capability. I then made the case that computer programming had a grammar, syntax, context and semantics. I argued that it was a reasonable substitute for French or Spanish in terms of difficulty and potential scholarly value. The department chair agreed and declared the language requirement to be satisfied. One down!

The second stumbling block was a residency requirement. PhD applicants were required to have at least 1 year in full time residency. Full time was defined as 12 semester hours during the Applicant phase of the PhD program where actual classes had to be attended.

I was able to satisfy part of the attendance requirement with evening classes. However, there were not enough advanced classes offered in the evening to fully meet the requirement. I had to attend some day classes if I was going to meet the residency requirement. This meant that I had to convince my managers to allow my absence for a few hours during the working day a couple of times a week.

This does not sound like much of a challenge today. But in the 1970’s manufacturing was a rigid environment. Compounding this was the fact that my direct manager was a rigid accountant. For him, how the work was being done was as important as the purpose of the work itself. Even if I were to seek permission, it was unlikely I would get it from him.

Fortunately the RS strategy tends not notice rules to which most people subscribe. This opens the door to many of additional options. In this case the relevant rule to be overcome revolved around the chain of command. Violating the chain of command was considered a major organizational offense at the time. And so that is exactly what I did.

My computer programming skill had got me involved in modelling a major at a United Kingdom facility. While not part of my regular job the assignment required me to meet with the VP of area on a somewhat regular basis. In one of those meetings I mentioned to him that I wanted to take a course in statistics that only met in the early afternoon 3 times a week. I never actually said that it was going to help my modelling but neither did discourage him from arriving at that conclusion. The upshot was that the VP said it was okay with him for me to take a few hours off a few times a week.

Now armed with explicit permission of the VP I promptly relayed his message to my immediate manager. I left the impression that this was a general permission rather than merely applicable to one course. In any event, my manager’s respect for rules and his respect for the chain of command caused him to take directive as a mandate. I had no further problem in meeting the PhD residency requirement. Two down!

The final aspect of the PhD meriting notice is dissertation approval by a committee of five professors. My PhD advisor headed my committee and the remaining people were from various other academic areas. The usual practice was that you presented drafts of your dissertation; the committee reads them, meets and offers criticism. You then go back and do it again. There were stories of this process going on for years. This possibility did not sit well with my RS inclinations. So I developed a “quick cycle” strategy.

The committee would meet at my request whenever I had something to review. They expected that the “something” would be excerpts from the dissertation which they had criticized in the prior meeting. I decided that if I could change the “cost” of review I could expedite dissertation approval. Fortunately technology had just provided me with a tool that facilitated the execution of this strategy.

Word processors had just been introduced to replace typewriters. I had access to them at work. They were not yet generally available in universities and so professors were unfamiliar with their power. My committee members were used to just getting the changes that resulted from their criticisms. That meant they had only to reread a part of the draft dissertation.

My “quick cycle” strategy involved using my strong RS capabilities to quickly make the changes required by their criticisms. I would then use word processors to introduce those changes, retype the entire dissertation and deliver completed draft back to committee members. This all happened over about a month.

While I always referenced the general area of change I made no effort to highlight them in the text itself. This meant that committee members had to re-read large sections of a rather dull and ponderous work. This was undoubtedly a tedious, taxing and painful process. The criticisms began to drop off sharply after about the second cycle. Dissertation approval came soon thereafter. Three down!

The RS is not typically seen as a dominant style favoring academic pursuits. Using this strategy to overcome challenging PhD requirements shows the flexibility of strategic styles. Any style can do anything but how they go about doing it will be very different. In this case it is fair to see my efforts as “gaming the system.” But that “gaming” did actually satisfy the requirements. It was just not in a manner that the creators of those requirements had expected. In final analysis I was awarded the PhD and neither it nor I suffered any enduring harm from “bending of the rules.”

WRAPPING UP CORPORATE AMERICA
Over the course of my early career I made steady progress climbing up the organizational chain of command. I rose to manager level in the automotive industry, to director level in food processing and to a Vice President level in a Fortune 500 Real Estate firm specializing in shopping malls. The theme running through all of these positions was change. People hired and promoted me to do something different than was then being done.

My career in corporate America ended with a stint in at a small private investment bank in Boston. A leader of a six person private firm had found a way to make an awful lot of money financing barges and tug boats using other people’s money. RS's like shiny objects and this was a shiny green object (i.e., money). This looked to me like a great opportunity so I took it.

My timing could not have been worse. Investment bankers live on commissions. Commissions are paid on deals that get done. Deals in investment banking require access to credit. Credit access depends on a permissive Federal Reserve discount window. On the very day I landed in Boston the Federal Reserve took action to severely restrict credit. They effectively announced that they were slamming shut their discount lending window. Poof! No more money.

I lasted for about a year. I did do some interesting stuff. For example, one potential deal involved trying to buy all of the garbage trucks of multiple cities in England from the UK Post Office. Another involved financing multi-million dollar tug boats. However, not a single deal closed. No deals, no money. I did not need the PhD to figure out that things were not going well.

After about a year it became obvious that I was failing as an investment banker. I figured that I did not need help to fail—I could do it all by myself. So I returned to my original home base in Ann Arbor, Michigan where I still owned a home. This was not a fun time. Initially I sat around wondering what I was going to do with the remainder of my life. I was 50 years old at a time and considered way “over the hill” for employment in corporate America.

The RS style uses emotions as the key component of its decision strategy. Rational methods take too long to be useful as a guide to an opportunistic strategy. Unfortunately emotions do not confine themselves to just guiding decisions. They tend to permeate the life stance of an RS. During this period where my future hung in the balance those emotions began to exert a heavy negative and painful force on my attitude.

Fortunately the RS strategy also provides methods to handle the emotional swings. The severity and persistence of my present situation called for the “nuclear option”–act directly and forcefully on the matter causing the emotions stress. The matter that needed to be addressed was just what I was going to be doing with the rest of my life.

My experience with a small investment firm gave me a roadmap. The formula was easy. Sell something for more than it cost to make or buy it. So after several months in gut wrenching torment I finally just decided to start a company, look for something to sell and get on with my life. This is not the kind of planning taught in school but it did the job of relieving the emotional stress.

LAUNCHING THE FIRM
My launch of a new firm began with naming it. The company’s name had to be totally benign since the firm was being created without a commitment to any particular product. However, I knew that whatever I ended up doing was going to be done in a professional manner. I also knew that selling was going to require communicating with buyers. Hence arose the name “Professional Communication Inc.” No matter what I ended up doing, the name was going to fit.

The next step was incorporation. That turned out to be easy. I bought a book on starting a company in Michigan, tore out and completed the forms and mailed them into the State of Michigan with a $65 fee. My certificate of incorporation arrived within a few weeks. The firm had been born. The only remaining issue was what to do with it.

The firm flopped around for about a year. I tried instructional video tapes, referrals, ISO 9000 quality training and a little product that provided an individual analysis similar to Myers-Briggs, Kersley-Bates and other similar diagnostic products that were being offered by established, well-entrenched firms.

The little analysis was later to be named “I Opt”. At this time it was assembled by hand using measurements created by a 24 question survey form. The clumsy preparation process; an entrenched competition and a minimal 8 page report made the little analysis the least promising of the products being tested. But it was also the most interesting. It was consistently accurate and always resonated with the people who tried it. I could not help wondering why.

I spoke to the report’s creator. He and one other person had developed the little analysis as a tool in response to a consulting gig they had secured. I was told that there was no specific theory or methodology guiding its creation. Rather the product was born out of their decades of experience. It worked and they saw no need to explain why. In the course of these conversations I managed to acquire usage rights for no upfront cost. There was now no reason not to keep “fiddling” with it.

Programming was one of the early “fiddles.” I wrote a program that automatically generated the report. This moved the little report a step closer to becoming a viable product. It was not a big revenue generator but neither was it a big cash drain. My intellectual curiosity could continue to be indulged without financially damaging the firm.

As I “fiddled” insights that explained one facet or another of why the little analysis worked began to accumulate. For example, I was able to identify information processing as the item that was being measured by the survey. I also found that the measure was being made on a ratio (i.e., like a ruler) rather than ordinal (i.e., big, bigger, biggest) scale. These and many other similar insights began to pile up as did my interest.

In the early 1990’s the telephone was still the principal method of communication. I made a practice of calling everyone who had purchased the “I Opt” individual analysis. These conversations provided the challenges, insights and observations that helped build, broaden and deepen the insights into the technology. A theory was being born and fleshed out once conversation at a time.

The above approach is an example of the RS style being applied to an academic subject. The typical academic process involves fully specifying a theory, subjecting it to “peer review” and only then deploying it in a filed setting. This produces reliable, verifiable knowledge at a high cost, slow speed and much tedious effort.

The RS approach is to iterate incremental improvements. The field setting becomes the laboratory where opportunities are identified and deficiencies corrected. Issues are addressed one at a time until there are none left. The RS strategy iterates to excellence rather than demanding excellence from the onset. Conducted with appropriate rigor the end result of both the academic and RS process is the same level of excellence. The outcome is just obtained by two different routes. 



REFINING THE THEORY
Important advances regularly arose in the course of conversations with clients. For example, a rubber supply company in upper Michigan applied the individual report to their management team. When I did my follow-up call the in-house consultant said the reports were accurate but “so what?” He felt that they did not help improve group functioning. My reply was that “I’ll call you tomorrow and show you “so what!” At that point I had no idea what I was going to “show” him. Impetuous commitments are standard fare for the strong RS.

The rubber supply initial contact phone call happened about 3 PM. I immediately began work assembling a new report using what I had on hand. The bits and pieces of insight that I had been gathering were some of the tools at hand. My programming skill provided other tools. By 3AM I had constructed a new report using these bits and pieces as well as some insights that arose in the construction process.

I delivered the report as promised. A phone call with the client confirmed that the new report was an accurate group assessment. The prescriptions it offered also appeared to be on target. The client then added that it was “too bad it wasn’t available when we were having meeting about it.” So the effort had not gained a new customer. But it did create a new product—TeamAnalysis. Over the course of the next year or so the report was refined into a core product and remains such today.

The growing pile of insights and tools highlighted the fact that long-term, detailed memory is not one of my strengths. I kept reinventing things that I had already invented. The obvious need was to capture the knowledge externally. Programming solved part of the problem by embedding knowledge in code. However, many other insights, discoveries and random bits of knowledge were in danger of being lost. .

The obvious answer was to capture the knowledge in an organized manner. I was educationally well equipped to write a book that could also serve as a marketing tool. So that is what I did. The book was written over 6 weeks and self-published in 1996. It did its job. It codified a lot of the insights and operations. It also helped demonstrate that “I Opt” was a viable alternative to existing products.

My RS based memory issues and client insights were not the only thing influencing the development of “I Opt.” Technology itself also played a role. For example, in 1998 I attempted to put a TwoPerson report on line. The idea seemed sound. Providing an analysis of a relationship rather than of an individual would differentiate “I Opt” from the others in the field. Instant results of online access would further enhance the differentiation.

Sound ideas sometimes do not work. This was one of those. At this juncture the internet was changing rapidly. Competing browsers came and went with some frequency. The browsers that remained were always being revised to correct bugs and add features. I got the report running on-line but found that program worked on some browsers and not on others. I did not have the resources to continually update the programming to keep up with the browser changes. Failure was the only option. So I took it.

However, that failure had a silver lining. Programming the Two Person Report gave me an in-depth command of Visual Basic for Application (VBA)—a programming language native to Microsoft’s Office suites (i.e., Excel, Word, PowerPoint, Access, etc.). In the coming years I would use these tools to create a variety of new reports (e.g. coaching, career, sales, learning and leadership among others). Each of these reports caused me to focus deeper into one or another aspect of “I Opt” technology. Step by step they helped to refine the theory as well as contributing some revenue to the firm.

“I Opt” technology rested on a totally new foundation (i.e., information processing) and was growing in its reach and complexity. During this time seminars were the principal way of getting operationally relevant information to clients. So I began to offer seminars on the use of “I Opt” technology in the mid to late 1990’s. Marketing was the primary motive but it turned out that the event also served as a major product development function.

The seminars were usually attended by between 10 and 20 people. Attendees were not passive recipients of knowledge. They tended to be people with a deep interest in organizational studies. They actively interrogated as well as absorbed. I was challenged when I attempted to “gloss over” and issue. Elaborations were demanded when my explanations were foggy. The seminar process forced refinement of both theory and practice.

The third leg of theory refinement was research. Beginning in the mid 1990’s we began to supported client submissions to various publications—in both juried and professional publications. Again, the main motive was marketing but a strengthening of the theory was inevitable. For example, we were able to gather evidence-based proof that the benefits provided by “I Opt” were durable and had a multi-year life span.

About the year 2000 we began a research publication labeled “JOE” (Journal of Organizational Engineering). “JOE” ran for about 5 years. It was intended as a permanent and transparent idea forum. It served as both a marketing tool and a means to develop, refine and extend the theoretical underpinnings of the technology. The publication was intellectually valuable but economically hopeless. Technology came to the rescue.

In about 2006 the research publications moved to Google Blogger. This accelerated the research pace since we no longer had to wait for typesetting and printing. In addition, distribution was much wider. To date about 250,000 people have accessed the research and over 50 scientifically grounded studies have been published. Each one of these served to both extend the knowledge base and insure knowledge retention.

The new reports, seminars and research combined to create a strong theory that now under-girds “I Opt” technology. None of these efforts involved extended periods of “blue sky” thinking typical of academic research. In one form or another they were all response based. This strategy of directed reaction is not applicable to all areas. But where it does apply it is a fast, inexpensive and adaptive way of creating a knowledge base.

There is one added factor that contributed to the development and refinement of “I Opt” technology—the staff members. Over the course of 25 or so years many people have left their mark on the technology. They assembled report packages, executed computer programs, edited articles and consulted with clients. But their contribution did not stop there.

They contributed ideas that improved both the graphics and textual content of the reports. They were also in a position identify problems and had a motive for seeing them corrected. I may have been willing to dismiss glitches, they were not. They acted as an ongoing control function directing, editing and restraining my RS tendencies.


END GAME
My working life began to change in a subtle manner with our telephone protocol. It was practice for anyone to pick up a ringing telephone. About my 72nd year the staff asked that I let others answer the phone. Various “reasons” were given. But the likely motive was obvious. I remained a strong RS even as I aged. An RS “reacts” to input. Phone calls represented potential input. Less phone interaction, less input, less reaction.

The next restraining initiative involved attempts to direct my energies. For example, past publications—textual and video—were judged to be dated and in need of revision. This was true. But it was also true that working in those areas kept me confined to matters that promised the possibility of least damage. The online certification was revised, multiple articles were “cleaned up” and an index of past research was produced. It was a worthwhile effort.

Somewhere around my 75th year still more efforts emerged. The staff began to encourage me to reduce my “in office” time. It started with suggestions that I move up my starting time by an hour. It was then suggested that I leave a bit early. The net result was steadily decreasing “in office” time. The strategy is obvious. Less time in the office reduced the opportunity for reactive responses.

The notable aspect of all of these efforts is that no one is trying to change my strategic style preferences. I continued to use the RS strategy as my primary navigation tool. Staff efforts focused on controlling the environment in which my somewhat impulsive tendencies are expressed. Adjusting environments is always easier than changing people. This approach has the highest likelihood of producing the desired result. “I Opt” insights apply universally—including to the creator of the technology.

So how am I taking all of this? I relinquished the CEO title a number of years ago. The current CEO is an experienced woman who has 20 years of experience with the technology. Her preferences for resolving issues are totally different than mine. She uses the methodical LP strategy as her primary navigation tool. She is sensitive to different variables, acts at a more methodical pace and plans over longer horizons.

This change in perspective is needed. The technology itself has matured. Like the Pythagorean Theorem “I Opt” has been shown to work regardless of where, when or with whom it is applied. There is no longer any question of if it works. The battles I fought 20 years ago have been won. There is no need to keep fighting them.

But the environment within which “I Opt” is being applied is changing rapidly. Text and email has replaced voice as the principal communication media. The internet has substantially replaced seminars as the favored method of learning about a technology. Younger people who are sensitive to current issues, variables and circumstances are needed to carry the firm and the technology into the future.My challenge is to keep my mouth shut and let them do it. So that is what I will try to do. 


And what does a 77 year old RS do while letting others guide action? This is something I have yet to find out. This paper is the first attempt to continue to contribute under the new circumstances. My work in maintaining the firm’s database is another. The possibility of updating the 1996 book is still another option. The good part of my current condition is that there is always something to do. The bad part is that these things do not carry many reactive opportunities that lend the excitement and energy that power much of a Reactive Stimulator’s  life. Whether I will be able to confine myself to these non-RS type activities remains to be seen.

Friday, May 18, 2018

Organization: A Fact-Based Profile



By: Gary J. Salton, PhD
Chief: Research and Development
Professional Communications, Inc.



INTRODUCTION 
This study considers the entire “I Opt” database of 76,442 individuals domiciled in 115 countries and who occupy positions in 5,549 unique organizations. The study is able to define the organization as an ecosystem with specific, quantifiable relationships between its elements. The resultant model can be used as a framework for both micro and macro organizational analyses.

Jump to YouTube Video
A companion video augments the explanations and analysis offered here. Clicking the icon on the right directly accesses the YouTube video.  Alternatively you can access the video from our website at www.iopt.com  in the “from the I-OPT blogs” scroll-down listing on the home page.



SUMMARY 
As with any large evidence-based study, the data and logic can be somewhat tedious. Below are the conclusions for those who wish to avoid this tedium:

  • The conclusions describe an “ecosystem” with both autonomic and rational components interacting to sustain the system at the cost of some tension between the internal components
  • A majority (58%) of the sampled population strongly favors stability in addressing new situations
  • The balance of the population (42%) offers a capacity for adjustment to new situations.
  • Contaminated input disproportionately threatens the majority (i.e., misdirection or paralysis)
  • Over the longer term, the focus on stability drops from 58% to 43%
  • Over the long-term the change-oriented tendency roughly balances long-term stability tendencies (43% stability versus 42% change)
  • The long-term change-orientation (42%) is equally divided between analysis and experimental strategies. This division weakens the thrust toward change but increases flexibility
  • The “average” person relies on their primary or secondary style 70% of the time. This consistency is one of the foundations for the high predictive accuracy of “I Opt” technology.
  • The management hierarchy is the “conscious” change agent (versus the “automatic” style elections)
  • The style orientation of management changes by organizational level at a moderate 5 to 15% 
  • Top management has the strongest focus on new ideas and options
  • 1st Level management favors certainty, stability and reliability
  • Senior management (i.e., VP, SVP, EVP) is the primary change agent in both ideas and action
  • Mid-management acts as a bridge that is slightly bias towards upper management positions 
The research finds the parallel to biological systems to be obvious. Like biological systems the organizational system can accommodate disruptive changes up to some undefined point. That undefined point likely occurs where the certainty and stability required by the base orientation is seriously threatened. After that point the majority population will tend to look to an increasingly decisive management to re-impose predictable order. The direction of that order will likely be secondary to the establishment of order itself.


THE SAMPLE 
There is no such thing as a truly random sample for any large scale research in the social sciences. Society has too many dimensions. There is virtually a zero chance that all can be simultaneously balanced. A viable strategy is to identify the data sources used and leave it to the reader to assess whether it is adequate for their purposes.


Table 1 
SAMPLE DISTRIBUTION

  The total 76,442 people are used in the analysis as the sampled population to which various subsets are compared. This is deemed legitimate since all of the categories in the sample participate in the general organizational framework. As such they both influence and are influenced by the whole population.


Table 2 
UNIQUE ORGANIZATIONS IN SAMPLE


Table 2 shows the number of unique organizations in the sample (see footnote #1 for more detailed listing).  Subsidiaries were collapsed into the parent organization. Thus an organization with multiple subsidiaries and thousands of employees is counted as one unique firm.

Table 3 
GEOGRAPHIC DISTRIBUTION OF SAMPLE


Table 3 describes where people were domiciled at the time they took the “I Opt” Survey. It does not necessarily represent their nationality. However, it is reasonable to expect that many if not most of the people are nationals of the countries cited.


The sample is not purely random. However, the large sample size and its wide distribution at least mitigates some of the concerns. The range of titles cited in Table 1 limits the effects of rank based bias. The wide scope of organizations cited in Table 2 reduces the possibility of industry based bias. The fact that the data captures about 60% of the countries on earth dampens the possible effects of a national culture bias. It is reasonable to accept the sample as being indicative if not definitive. However, final judgement is left to the discretion of the reader.


 “I Opt” technology is the lens that will be used to make the macro-level assessment of our sampled population. It is based on the classical information processing model shown in Graphic 1. Each component of that model has a role to play in nature of interactions and the character of the decisions likely to be made.

Graphic 1 
CLASSIC INFORMATION PROCESSING MODEL

 


OVERVIEW ANALYSIS 
Input is a key component determining the behavior that can and will be emitted. One measurable aspect of input is the degree of acceptable ambiguity in input data. Some people require fact-based detail when confronting new issues. This provides them with the exact, precise evidence they require to execute their preferred decision strategy.

Other people tend to use a more probabilistic stance. They are prepared to infer needed information. This inference can be applied to the base data itself as well as “filling in” missing data elements. For example, it might be inferred that a commodity price is being manipulated even without specific evidence. Or the effect of an apparently unrelated variable might be assumed to be affecting the commodity price. An inferential strategy is less precise but considers a broader range of options since explicit connections are not required.

Everyone can and does use both inferential and detailed factual data in conducting their life. Common issues that we confront everyday can effectively be pre-decided whether they be inferential or fact based. New unfamiliar issues are a different story. If the issue does not carry a “label” defining a resolution method people must choose a way of addressing it. They will tend to use a way that has worked for them in the past. “I Opt” registers that experience as a level of strength with which they are committed to a particular stance—inferential or explicit.

Graphic 2
DIRECTION OF INPUT ORIENTATION 

(Sample Size = 76,442)


Graphic 2 shows that 61.9% of sampled population favors explicit detail and “facts.” Facts can take time to gather. They typically do not come with certifications of their veracity or relevance. They take time to assess and evaluate. In addition, “facts” can conflict. Reconciliation of factual discrepancies can add to the time demands. The dominance of fact-based methods means that we can reasonably expect the sampled population to be a bit slow to react to unfamiliar issues.

Graphic 3
OUTPUT DIRECTION OF ORIENTATION 

(Sample Size = 76,442)
 

Graphic 3 shows another basic component of our model—output. A person can be oriented toward either thought or action as the targeted outcome of the decision process. Thought in our terms is a preparatory activity. It involves things like plans, assessments, projections and the like. Action is the other option. It involves directly affecting the issue in question. Action causes the “real world” condition of that issue to be changed. Action output can change thought activities, thought output cannot change actions already taken. Thought is conditional. Action is final.


The dominance of thought-based output reinforces the measured pace tendencies noted in Graphic 2. Preparatory activity takes time. It also presumes that time will be available to deploy the knowledge that was created by thought—more time. The combination of detailed input and thought output makes it reasonable to expect that our sampled population will not be fast “out of the blocks.” The combination is not a formula for a responsive posture on new unfamiliar issues.


‘I Opt” connects input and output elections with the “Process” component as shown in Graphic 4. Process is an activity rather than an event. It tells input what to look for in order to satisfy the output objectives. It informs output of the range of possibilities given the input that is available. It is an iterative process. It proceeds toward issue resolution in a step-by-step fashion (see footnote #2 for references to more detailed explanations)

Graphic 4
 PROCESS COMPONENT OF THE MODEL 
(Sample Size = 76,442)



The process activity is not “free.” It takes mental effort. People typically do not reinvent “process” for every new issue that arises. Rather they tend to settle on a general process that seems to work within their particular environment. This reinforces the stability of the system. That stability helps make people predictable. This fact has been empirically validated in research studies on both the validity and reliability of “I Opt” (see footnote #3 for detailed references)


The population does have a change component. The 38.1% favoring inferential input and the 41.9% action output components are not inconsequential. However these are secondary inclinations that will most likely be engaged in the face of a recognized threat not well addressed by the dominant strategies.


In general our sampled population is inclined to seek certainty in both thought and action. A reliance on trusted methods provides a level of this certainty in action outcomes. Rigorous logic, reliable methods and thorough analysis provides the certainty assurance on the preparatory thought side. This posture is a trade off. Reliable, efficient performance is being purchased at the cost of a certain level of sluggish behavioral caution when confronting new issues. Since we all want the lights to go on when we flip a switch and water to flow when we turn the facet this may be a near optimal social posture.

STRATEGIC STYLE DISTRIBUTION 
The above analysis is useful for overview purposes. However, predictive accuracy needs more precise delineation of the variables involved. “I Opt” technology is able to do this by combining the macro components into discrete strategic style combinations as shown in Graphic 5.
Graphic 5 
STRATEGIC STYLES

Table 4 shows the labels “I Opt” has assigned to each strategic style. “I Opt” technology actually measures these more precise variables rather than the generalized concepts (i.e., inference and “facts") used in the macro review. The formal “I Opt” concepts are shown in red italics and are included in deference to those readers already familiar with “I Opt” technology.

Table 4 
“I OPT” STRATEGIC STYLES

The style measurements of the sampled population are shown in Graphic 6. The summary level data of the previous section has been refined to gain increased behavioral specificity.

Graphic 6 
DISTRIBUTION OF PRIMARY STRATEGIC STYLES 
(Sample Size = 76,442)
Thought (i.e., preparatory activities) remains the dominant approach to a new issue. But it has been divided. The Hypothetical Analyzer (“HA”-34.9%) uses detailed thought-based analysis to assess and plan. The Relational Innovator (“RI”-23.2%) uses inferential input to generate thought-based options, ideas and alternatives. The result is an increase in the range of options considered. Both styles favor thought output but approach it differently.


Similarly the earlier action based output of 42% has been divided between the Logical Processor (“LP”- 27%) who favors detailed “facts” to guide precise action and the Reactive Stimulator (“RS” -14.9%) who tends to use inference as an action guide and is prepared to act on that inference. Again the range of options “automatically” considered by our sampled population is increased.


The dominant HA and LP styles share a common detail oriented “fact based” approach. Together they account for the 61.9% inclination toward fact-based input. But they produce different behavioral outcomes. The HA produces a plan or assessment. The LP produces conclusive action. Both HA and LP strategies see a measured, cautious approach as the best way to confront our environment—whether in thought or action.

A STYLE BASED RISK 
At the time of this writing the world is attempting to digest a new technology which directly affects the information flow entering the decision process. The internet and wide availability of smart phones has created the ability to publish “news” of all types without edit or attribution.


News is by definition “new” and unfamiliar. Strategic style strategies are the vehicle used to initially assess “new” information. Misinformation will affect everyone. But it has a disproportionate effect on the analytical HA and process oriented LP styles. Both styles depend on accurate detailed input to engage their preferred resolution strategies. 


The effect of misinformation depends on its design. Faulty conclusions are a general exposure to all styles. However the HA and LP styles have an incremental exposure. They will tend to see matters as “settled” once a conclusion is reached. Their initial reliance on “solid” evidence provides them with a level of confidence that is not easily shaken even in light of subsequent contrary information. Faulty decisions will tend to persist. There is also the possibility of frustration paralyzing the HA and LP’s strategic processes. Confused data generated by misinformation can render an issue unsolvable and cause it to be set aside or ignored.


A majority of the sampled population subscribes to the HA/LP styles (61.9%).  This means that the population as a whole has something of a bias toward increased risk exposure from misinformation. This risk is embedded in the structure of the sampled population. Methods to offset the increased risk are beyond the charter of this paper but merit the attention of those in a position of influence.



STRATEGIC PATTERN DISTRIBUTION 
Strategic styles describe the likely approach to a new issue that does not give a clear signal as to the “right” resolution method. However, most issues of consequence involve a series of interrelated decisions. Each step in this process can require a radically different style-based response. To meet this challenge people develop a style “fall back” strategy. The “fall back” is merely the style with the next highest strength. The combination of primary and secondary (i.e., “fallback) style strength commitments are designated by “I Opt” as strategic patterns.  Table 5 outlines the strategic style combinations for each of the four “I Opt” patterns.

 Table 5 
 “I OPT” STRATEGIC PATTERNS
Graphic 7 shows the distribution of strategic patterns in the sampled population. The Conservator Pattern (HA/LP) is dominant. Over twice as many people chose this rigorous, detail oriented pattern over the next most used patterns. This means that interactions in organized settings will most likely be the examination of the “facts” through the lens of well-understood analytical methods (HA) and will favor execution elections using a disciplined, exacting approach (LP).
Graphic 7 
STRATEGIC PATTERN DISTRIBUTION OF THE POPULATION 
(Sample Size = 76,442)


It might be noted that the tendency toward the 61.9% cautious measured approach in Graphic 6 (the combination of HA and LP considered independently) has declined to 43.4% in Graphic 7. The reason is that people do not always select the HA or LP as their secondary approach. They can choose the RI and RS both of which accept inferential input. This longer-term stance diminishes rigidity seen in the initial response style profile.

This distribution described in Graphic 7 makes societal sense.  A majority of the functions, conventions and practices of a society are established and well-tested. Keeping them running is the prime requirement. Employing standard procedural practices (LP) or well-tested analytical approaches (HA) are probably the best way to ensure that the lights stay on, the supermarket has groceries available and the toilet has water to flush.

But environments do occasionally change. These changes can require new approaches. The “I Opt” distribution accommodates this ability to change with the Perfector and Changer Patterns. Both are focused on new options (both have an RI component). The Perfector uses analysis to assess the RI options, the Changer validates them with experimentation. The combined strength of these two change-oriented patterns about equals that of the stability-oriented Conservator pattern (42.6% versus 43.4%).

However, this apparent equality probably overstates the change orientation. The 42.6% change orientation is the strength of two combined strategies (Perfector 21.1% + Changer 21.5%) which can compete. This competition is likely to diminish their overall thrust toward change. On balance the long-term orientation of the sampled population continues to favor cautious stability.


STYLE EQUALITY AND USAGE 
 “I Opt” technology maintains that no style election offers any particular advantage or disadvantage on an absolute basis. Graphic 8 confirms the validity of that assertion.

Graphic 8 
AVERAGE STYLE DISTRIBUTION BY PRIMARY PATTERN

Graphic 8 measures the “average” style strength distribution for all of the people subscribing to each of the four “I Opt” patterns as their primary approach. The proportional representation of the styles is roughly the same across all patterns. It is consistent whether a particular “style” component holds a primary or peripheral position within a pattern. If a particular style were inherently better or worse than another we would expect to find that condition reflected in its proportional representation. There is no visible distortion. It is reasonable to conclude that all styles of equal organizational value when applied in the domains to which they are applicable.

Graphic 8 is also telling us that the “average person” is able to navigate the “real world” about 70% of the time using their primary and secondary styles. When they do have to fall back to a peripheral style, they are equally likely to choose either one of the two remaining styles at about a 15% rate. The consistency of these ratios across the four patterns also argues for the validity of measurement. The intervals measured will be the same regardless of the pattern to which they are applied.

It is worth reiterating that Graphic 8 is an average. It is not a standard of comparison. For example, Graphic 9 shows the distribution of styles of the author. Yours will likely be different. Different environments generate different style elections. “I Opt” reliability studies have statistically demonstrated that our style and pattern elections are stable for periods as long as 18 years (see footnote 3c and 3d for reference to those studies). This means that the consistent averages shown in Graphic 8 are not a statistical fluke. They are founded on the consistency of our individual behaviors.
Graphic 9 
Dr. GARY SALTON STYLE DISTRIBUTION
This style consistency also accounts for a portion of the “I Opt” technology’s high predictive power. The average reliance on two principal strategies means that the character of decisions is likely to be consistent over time. An “I Opt” assessment made using person’s current style and pattern preference is likely to persist into the future. This stable correlation is one foundation for “I Opt” predictive accuracy.


HIERARCHICAL EFFECT 
The foregoing analysis is akin to the autonomic nervous system in biology. It describes the probable behavior of the population in the absence of any overarching authority. Modern organizations typically superimpose some form of merit based bureaucracy on these basic capacities. The authority resident in the hierarchy allows it to “call out” specific attributes of the population as a response to the particular issues being confronted.

The large size of the current sample gives us the opportunity to examine the information processing preferences of each level of the hierarchy. The large sample size limits then need for esoteric statistics. We can simply graphically overlay the ‘I Opt” style curves for the population segments. The areas under each curve can be measured and differences calculated. The result is a quantified, visually obvious degree of similarity and difference.

First Level Management 
First level management consists of both Supervisor and Assistant Managers (see footnote #4 for a test of title equivalency). They typically manage functions with narrow areas of responsibility. The position is ordinarily seen as the first rung of the management ladder. Graphic 10 compares current occupants of this position with the rest of the sampled population (i.e., all other ranks both above and below 1st Level).

Graphic 10
 1st LEVEL MANAGEMENT STRATEGIC STYLE DISTRIBUTION 
(1st Level Sample n= 2,765 - All non-1st Level n= 73,677)

The blue area on the chart is the area where the curves for 1st Level and that of all of the others in the sample population overlap. In other words, people whose profiles lie in the blue area are using the same information processing approach regardless of their hierarchical position.

The red area represents the portion of 1st Level managers who are more inclined in a particular direction than are others in the population. For example, the red RS area in Graphic 10 (upper left quadrant) shows the amount that 1st level managers are more inclined to use less RS strategy than is the rest of the population. The red area in the LP graph (upper right quadrant) shows the portion of 1st Level managers more inclined to use this LP approach.

The green area shows the amount by which the general sample population (non-1st Level) exceeds 1st Level managers. The simple mechanics of overlaying two charts dictate that the green area always lies opposite that of the red. However, how that distribution is spread across the range of strength commitments can tell you something. In our sample RS reference (upper left quadrant) the green area is spread across a wider range of strengths. Clumps of strength are likely to be more noticeable than are this kind of diffuse distribution. The low RS will likely be noticed and may come to characterize the 1st Level group. The fact that others in the population are more RS inclined is unlikely to be remarked upon—it just “is.”

1st Level management generally has about a 90% overlap with the general “I Opt” population. Almost everybody’s profile can fit somewhere within 1st Level management without the need for any change in approach. “I Opt” profiles do not appear to offer any significant impediment or advantage to advancement at this level.

1st Level management “pulls” the organization toward restraint. They are 8.0% to 9.3% less inclined to use the change-oriented RS (red area upper left) and idea-oriented RI styles (lower right). They also “pull” the population toward a greater reliance on traditional methods (LP-upper right) and more analysis and planning (HA-lower left). But the strength of this incremental pull toward stability is a modest 3% to 5%.

Overall, 1st Level management appears to be discouraging spontaneity rather than advocating for greater detail and depth. This makes some sense. 1st Level management’s role is to keep things running. Spontaneous ideas (RI) and actions (RS) can cause glitches. Glitches can disrupt “running” operations.


Mid-Management 
Mid-management consists of people with responsibility for a functional area. They typically have multiple supervisory level subordinates and usually carry the title of Manager or Director. 

Graphic 11 shows that the 90% overlap with the rest of the population is about the same as 1st Level management. In both cases, if any style penalty to advancement exists it can probably be easily offset by education, experience or other such job relevant factors.

Graphic 11
 MID-MANAGEMENT STRATEGIC STYLE DISTRIBUTION 
(Mid-Management Sample n= 21,750 - All non-Mid-Management n= 54,692)
There is a directional shift from 1st Level. Mid-Management is “pulling” the organization toward more new ideas (lower right—positive 5.8% versus minus 8% for 1st Level) and responsive RS (upper left—positive10.4% versus minus 9.3%). At the same time they are lessening the influence of the analytical HA (lower left—minus 5.5% versus positive 3.5%) and the established process LP (upper right—minus 5.3% versus positive 5.3%).

The difference between 1st Level and mid-management is substantial in statistical terms. However, it is of marginal practical significance in absolute terms. A majority of the sampled population (the common area) shares mid-management’s profile preference. Any stress arising from the difference is likely to be confined to 1st level managers reporting to the 5% to 10% of mid-managers who differ from the general population.

In addition, mid-Management continues to have a high respect for traditional methods (e.g., mid-management “pulls” toward the center of the LP distribution—Graphic 11, upper right). The RS inclination (Graphic 11, upper left) is material. But it is offsetting about an equally strong 1st Level inclination  in the opposite direction (see Graphic 10, upper left). The overall direction of mid-management can probably be best described as cautiously inclined toward a more adjustment-oriented overall posture.


Senior Management 
Senior management consists of people who have policy making authority for major components of the organization. They typically carry the general title of Vice President, Senior Vice President and Executive VP. They also include “C Level” chief tiles such Chief Financial officer, Chief Operating Officer, Chief Information Officer and the like.

Graphic 12 
SENIOR MANAGEMENT STRATEGIC STYLE DISTRIBUTION 
(Sr. Management Sample n= 2,840 - All non-Sr. Management n= 73,602)
Graphic 12 shows a marked change. The senior management common area falls to 80%. This is likely due to two factors. First, gaining a senior management role is a highly competitive process and small differences may carry heavier weight. Secondly there is less content variety than there is at lower levels. This narrower skill set may place higher value on specific strategic style profiles. It is worth noting that the 80% absolute level of the common area remains large in absolute terms.

But the directional “pull” is substantial. Senior management doubles the rate of de-emphasis of the precise action LP and analytical HA styles (about 11% lower for Senior versus about 5% lower for mid-management in both cases). Senior management’s RI style inclination stands out at 14.4%; almost triple mid-management’s 5.8% pull. The one consistency between the mid and senior levels is that the fast responding RS style remains roughly the same at about 11%. This suggests that a threshold limit to spontaneous RS actions has been reached. This is consistent with what Ashley Fields discovered in his 2001 doctoral dissertation using a much smaller “I Opt” sample (See footnote #5 for reference).

The picture painted by this analysis is of Senior Management as the major organizational change agent. It is not impulsive change. Rather it is a measured but aggressive push toward adjusting to meet current conditions. 


Top Management 
Top Management consists of Presidents, CEO's, Board Members, and similar titles that have the ability to influence the direction of the organization as a whole. 

Graphic 13
TOP MANAGEMENT STRATEGIC STYLE DISTRIBUTION 
(Top Management n=1,048: Non-Top Management n=75,394)
Graphic 13 shows that the Common Area remained in the same order of magnitude as for senior management at roughly 80%. The exception is in the innovative RI category where the common area fell to roughly 70% (Graphic 12, lower right). The smaller common area is caused by a 22% increase in RI strength over senior management (14.4% versus 17.6%). This makes some sense. Issues that could be resolved at senior management levels have been resolved. What is left is for top management is likely to be the even more uncertain and less well-defined issues. The RI style offers ideas with nonthreatening thought as its output. However, it is also worth noting that while the common area in RI distribution is diminished, it remains large at about 70%. There appear to be many roles in top management that do not particularly favor a strong RI stance.

The drop in the RS difference from 11.1% to 7.2% (a 35% drop) between senior and top management is also notable. The broader nature of the issues confronted by Top Management makes quick, simple actions less probable. The organization wide scale of potential consequences associated with the risky RS strategy is also likely to play a role. The consequences of error can be organizationally threatening.

The overall picture painted by the Top Management numbers is that of a long-term advisory role. However, this may be due to the inclusion of board members who do not have executive responsibilities. The inclusion of top managers of non-profits may also influence this result. Their dependency on external agencies for funding may limit their behavioral options. It is likely that if these types of influence were factored out, Top Management could more closely resemble the posture of senior management.


OVERALL ASSESSMENT 
The general organizational structure of the sampled population has capacities for stability and change built-in at all levels. The portion of the sampled population operating without supervision favors stability over change at about a 60%-40% ratio. This 60% majority acts to limit the possibility of being “whip-sawed” over potentially transient issues. But the 40% minority remains as the option for near-term adjustment “just in case.”

Over a longer-term series of transactions (i.e., “I Opt” patterns) our sampled population shifts to about equal stability versus change inclinations (43.4% for stability, 42.6% for change). The longer time span provides “room” for deeper consideration as well as giving the opportunity for more “evidence” to accumulate.

In both the short (i.e., “I Opt” style) and long-term (i.e. “I Opt” pattern) situations the general sampled population retain about a 15% capacity for fast response using minimal analysis. This is the RS “firefighting” capacity. Firefighting can bring spontaneous change as collateral condition but it is change without strategic direction. Sometimes it is positive, sometimes negative; sometimes durable, sometimes transient.

The consistency of the system is sustained by a stable behavioral predisposition among the participants. About 70% of the time they can (as a group) be expected to respond to a situation using their primary or secondary styles. This makes them predictable. Predictability is a necessary condition for coordination. Coordination is the essence of organized activity.

The autonomic system described above is a system with the capacity to accommodate a fluctuating environment. But it will be optimal only when those fluctuating conditions conform to the 60%-40% ratio embedded in the population. Unfortunately, real world fluctuations can vary from this optimal ratio. An additional overarching mechanism is needed to call out specific population capacities that match unpredictable environmental changes. That mechanism is the organizational hierarchy.

The organizational hierarchy is itself a system. The 1st Level base of the hierarchy acts something as like a shock absorber. It reinforces the basic stability tendencies of the sampled population. It interprets and dampens initiatives generated at higher levels. It “buys time” for management initiatives to be absorbed and incorporated at operational levels.

Mid-management appears to function as a managerial bridge. Its major style effect is a 10.4% accent toward the responsive RS strategy. Effectively this posture serves to incentivize lower levels toward action. The remaining three mid-management styles (HA, LP, RI) are in directional support of the senior management position but at a modest 5% strength level.

Senior Management is the major change agent. The combination of a 14.4% greater inclination toward new ideas (RI) combined with a strong 11.1% greater willingness to take responsive action (RS) is a prescription for initiated change. Their reduced 11% stress on the cautious HA and LP strategies lessen the likelihood of restraint.

Finally, Top Management’s heavy 17.6% inclination toward new ideas and options (RI) casts them in something of an advisory role. The positive 7.2% pull toward responsive action (RS) suggests that the advice given will be accompanied by an action imperative.

The above structure is sustained by a pool of commonality. Between 70% and 90% of the participants in the population share a common “I Opt” profile with the various levels of management. This means that most of the time the position of management and the general population will be in accord with the approach being taken—even if they differ on the specific actions taken using that approach.

The large Common Area also signals that Strategic Styles are important but are not everything in terms of individual advancement. Intelligence counts—you can be a genius while subscribing to any of the four styles. Education matters—no one is going to hire an accountant for an engineering position and vice versa. Experience is relevant—a person with in-depth, successful experience in an area can have an “edge” offsetting that of any style. There are many other such factors. Any of these other factors can and have been leveraged to offset any “I Opt” style-based advantage. However, knowledge of the style advantage is a useful signal alerting a person to the need to invest in one or another of these other factors.

In final analysis the sampled population has sufficient diversity of styles to provide resilience to disruptive events and the directional energy to maintain the system on an ongoing basis. This is a definition of a social ecosystem. Organizational science may have more similarity to biological systems than is currently recognized.




FOOTNOTES AND BIBLIOGRAPHY

1.  Organizational citations are for unique organizations. Subsidiaries were collapsed into their parent as were multiple location wholly owned entities.


2. A general orientation to the “I Opt” paradigm can be found by viewing the 8 minute YouTube video "I Opt" Strategic Styles and Patterns at: https://www.youtube.com/watch?v=KVOyznCCWB8
An explanation of the dynamics of the input>process>output model can be found in the YouTube video Team Tension—Causes and Management.
http://www.youtube.com/watch?v=xQ_5b4BUUB0&feature=youtu.be.

3. “I OPT” VALIDATION:  “I OPT” technology has been extensively validated both in terms of theory and operation.  The major publications on the subject include:

a)      A book has been published which covers all eight accepted tests of validity is available from Professional Communications at a modest cost. The book is available free of charge at the Organizational Engineering website at:  http://www.oeinstitute.org/articles/validity-study.html. An included resume outlines the extensive professional qualifications of the author.
Soltysik Robert (2000), Validation of Organizational Engineering: Instrumentation and Methodology, Amherst: HRD Press. 

b)      A doctoral dissertation titled A Study of Intuition in Decision-Making using Organizational Engineering Methodology was approved by Nova Southeastern University in 2000. The dissertation used “I Opt” as both a subject and research instrument. The dissertation was subject to review by an independent doctoral research committee headed by a Ph.D. focused on research methods and found to meet all academically accepted standards of validity. The complete dissertation is available free of charge at   http://www.oeinstitute.org/articles/ashley-fields.html. The dissertation is also available in book form as: Fields, Ashley (2001). The Effects of Intuition in Decision-Making, ISBN-13: 978-3639368185, Germany: VDM Verlag Dr. Müller (August 18, 2011). Available from Amazon.com.


c)        “I Opt” Style Reliability Stress Test: A sample of 171 surveys applied a classic test-retest design covering a period of 18 years to test the reliability of the “I Opt” instrument on styles (i.e., short term decision responses). The results far exceed the reliability of traditional instruments (i.e., MBTI, DiSC, Firo-B, 16PF). The research is available of the Google research blog in textual form at: http://garysalton.blogspot.com/2011/03/i-opt-style-reliability-stress-test.html. 
A 10-minute video of the study is available on YouTube at: https://www.youtube.com/watch?v=Vs6eoIsqVkc


d)       “I Opt” Pattern Reliability Stress Test: The same data as used for style reliability was applied to patterns (i.e., long-term decision sequences). The change between test-retest was found to be negligible. The research is available of the Google research blog in textual form at: http://garysalton.blogspot.com/2011/03/i-opt-pattern-reliability-stress-test.html.
A 15-minute video of the study is available on YouTube at:
https://www.youtube.com/watch?v=0SLg28BhNHU


e)      Operationally “I Opt” has been validated through continued worldwide use at all levels from hourly workforces to Board of Director levels of Fortune 50 organizations in the profit, non-profit and government sectors. An outdated (last updates 15 years ago) listing of the organizations involved can be found at http://www.iopt.com/corporate-information.html.  Many of the clients cited have continued to use the technology for decades and many more pages of new clients could be added if the list were to be updated to today. 

4. Combining Assistant Managers with Supervisors raises the question as to whether the two types of jobs may have different strategic style demands put on them. A statistical test found only one marginally significant difference (p=.0166) of 4.2% difference in average LP strength. This difference is one of degree and not direction as shown in Graphic below. For present purposes this small difference in LP can be safely ignored.

SUPERVISOR vs. 1st LEVEL MANAGER LP STYLE DISTRIBUTION

 
Project Managers were also considered for inclusion in the analysis. They occupy a level between the professional and management levels. The typically have more authority than does the professional staff. But have a narrower range of options than do people at full managerial levels. Also, analysis revealed that Project Managers were statistically indistinguishable from others in the organization. The combination of these factors lead to the decision to exclude Project Managers from this study.

5. Fields, Ashley. A Study of Intuition in Decision-Making using Organizational Engineering Methodology. Ph.D. dissertation, Nova Southeastern University, 2000. The complete dissertation is available free of charge at http://www.oeinstitute.org/articles/ashley-fields.html.