Hierarchy Influence on Team Leadership

By: Gary J. Salton, Ph.D., Chief R&D
Professional Communications, Inc.

INTRODUCTION
This research blog looks at team leadership at various organizational levels. The research draws on 976 teams from 236 unique organizations in which the rank of the leader was known. Table 1 summarizes this database.

Table 1
UNIQUE TEAMS AND FIRMS USED IN RESEARCH

The supervisor category includes titles such as leader or team lead. The managerial category includes director titles. The VP category includes General Managers of substantial organizational units. The categories are believed to reasonably reflect distinct organizational levels or ranks.

A host of different societal and economic sectors are represented in the research base. Table 2 summarizes these interest areas.

Table 2
TYPES OF ORGANIZATIONS USED IN RESEARCH

The wide distribution of categories, large number of teams and variety of firms suggest that this is a realistic sample. It can be trusted as reasonably representative of teams and their leadership.

TEAM LEADER PROFILE
“I Opt” strategic styles measure short-term decision preferences. Other entries in this research blog and www.iopt.com define styles in more detail. Generally, they represent different positions on the input>process>output continuum.

Table 1 identifies the leader’s dominant strategic style in terms of relative strength. In other words, it measures the relative reliance the leader puts on each “I Opt” style.

Table 3
STRATEGIC STYLE DISTRIBUTION
OF TEAM LEADER

Team leaders favor the Relational Innovator (RI) strategic style (see yellow highlight). But there are differences. Almost as many supervisors favor the Hypothetical Analyzer (HA) (see small red arrow) as the RI style. Both strategies appear to offer reasonable access points to entry level management.

Once access is gained, the game changes. The reliance on the analytical HA strategy drops from about 31% to 20% (p~.05 significance). It appears that a strategy that gains access may not be ideal for advancement.

The RI style seems to be the favored strategy for those moving from manager to Vice President. The move from 34% to 44% reliance on RI is highly significant at p<.001. This is no accident. Some systematic process appears to be operating.

In summary, the idea-oriented RI style dominates the personal preference of team leaders. The analytical HA is a close second for the entry-level supervisor. But the HA importance quickly evaporates with increasing rank. The option-generating RI would seem to offer a key competitive advantage in team leadership.

LEADER VERSUS OTHER TEAM MEMBERS
A leader’s preference for a particular style is a personal, not organizational quality. For example, a leader may prefer RI over other “I Opt” styles. But other team member’s RI strength might exceed that level. Is just a having a dominant RI style enough?

Table 4 answers this question by comparing the leader’s style strength to that of other team members.

Table 4
PERCENT OF TEAMS WHERE LEADER
HAS HIGHEST STRATEGIC STYLE SCORE

The average team size in this sample is 9.2 people. If chance alone were responsible for the leader having the highest strength in a style we would expect it to occur only about 1/9.2 = 10.8% of the time. The LP and HA styles fall within that range. The RI and RS styles (see red arrows) clearly exceed chance. The selection mechanism is operating on an organizational as well as personal level.

The next likely question is how important is this finding. In other words, how much does having the highest strength in a particular style improve the odds of gaining a leadership position?

The advantage is best measured by focusing on the big picture. Table 5 shows the actual versus expected number of teams whose leader had the highest “I Opt” style strength in any category (i.e., RS; LP; HA or RI).

Table 5
CALCULATING THE ADVANTAGE
LEADERSHIP POSITION BY NUMBER OF TEAMS

Table 5 says that in a group of 976 teams a person would have a 130-instance advantage if one or another of their “I Opt” strategic styles ranked as the highest within the team. This translates into a 13% advantage (130/ 976=13.3%). This is a conservative estimate. Using the RI and RS as a standard would yield a higher percent. But “do no harm” is a good principle. A conservative estimate minimizes any exposure.

In summary, team leaders tend to favor the RI and RS strategies on a personal level (see Table 3). They also tend to excel other team members in the strength with which they hold these styles (see Table 4). The degree and structure of the difference is enough to suggest that result is due to some kind of systematic competitive advantage.

The advantage is about 13%. This is enough to pay attention to but not enough to compel. There are other ways to gain and keep team leadership. Investing in them may yield an advantage equal to or greater than the gain from altering “I Opt” strategic styles. This research can be used to improve those odds even further. It is not a panacea but it can make a substantial contribution.

TEAM DIVERSITY
A question might arise whether there is some influence being exerted by the character of the teams at the various levels. One of these factors is the diversity of “I Opt” strategic profiles among team members. Chart 1 shows the diversity distribution by rank of the leader.

Chart 1
TEAM DIVERSITY BY RANK OF LEADER

The “I Opt” Diversity Index measures the range profiles represented on a team. High diversity suggests that the team will naturally consider a wider variety of options. The cost is more decision-making difficulty.

There is a statistically significant difference between managers and Vice Presidents (p<.01) but its magnitude is trivial. Team leaders at all levels face essentially the same level of diversity in the teams that they lead. Diversity does not appear to be a basis for the relationships discovered.

TEAM SIZE
The more people on a team, the more opportunity for diverse positions. The Diversity Index in Chart 1 adjusts for this condition. Chart 2 shows the team size distribution by rank more directly.

Chart 2
TEAM SIZE BY RANK OF LEADER

The differences between supervisors and managers are statistically significant (p<.001) as is manager and Vice President (p<.01). However, it is obvious that the team size differences are not of meaningful consequence. Team size seems to be reasonably constant across the ranks. It is unlikely to account for the relationships discovered.

LEADER/TEAM MEMBER COMPATIBILITY
The degree to which the leader and average team member share a common information processing perspective (i.e., “I Opt” style) is another aspect of teams. Chart 3 shows the average structural information processing compatibility between the leader and the average team member.

Chart 3
AVERAGE INFORMATION PROCESSING COMPATIBILITY
BY RANK OF LEADER

The similarity of the distributions is again striking. There is a statistically significant difference between manager and Vice President (p<.05) but it is of minimal consequence. This is perhaps better seen in Table 6.

Table 6
AVERAGE STRUCTURAL
INFORMATION PROCESSING COMPATIBILITY

A 30% to 50% overlap is in the moderate range of structural compatibility. This range has been repeatedly confirmed as “normal” across the many aspects of human interaction. The 45% compatibility found in here offers no basis to account for differences found.


MISSION ALIGNMENT
The first requirement for getting a leadership position is to be noticed. The spontaneous RI and RS styles tend to be more easily noticed that the more methodical HA and LP. Alternatively, compatibility with higher management levels might be seen as reason. Other entries in this research blog have shown that higher ranks tend to favor RI and RS styles. It could be argued that people appoint team leaders who are like them.

Both of the above positions may explain why people with certain strategic styles are given a chance at leadership. They do not explain why they endure in that position. The leaders of the large number of teams in this research are unlikely to be all new appointees. The source of team leadership preference must be found elsewhere.

Some insight might be gained by looking at the raw “I Opt” scores in each rank. The flow of the change in styles may provide a clue as to what is going on. This flow is shown in Table 7.

Table 7
AVERAGE RAW “I OPT” SCORES

At a supervisor level the RI strategic style is dominant. But the LP and HA styles are almost equal to it. These methodical styles are well suited to handling specifics in an accurate and timely fashion. The mission of most supervisory teams is either processing specifics or improving the methods by which they are processed.

If this is an accurate characterization the implications are clear. The strength of the LP and HA are just as important to supervisory success as a dominant RI. Leadership development initiatives that cause these disciplined strategies (i.e., LP and HA) to be diminished among aspiring leaders can do damage.

At the manager level, the action oriented RS absorbs a decline in the LP and HA strategic styles. The idea-oriented RI also increases but only by a small amount. Teams at this level tend to be focused on functional missions. Specifics tend to be subordinated to tactical directions. Functions often must be discharged within a defined time frame. This mission is well served by the action-oriented RS style.

Leadership development initiatives guiding supervisors toward managerial positions will do well by focusing on decisive action. The ability to act in the face of uncertainty will need to be fostered. A capacity to work with fewer specifics and less detail will become important. These and other aspects of RS behavior can and should be developed.

Table 8 focuses on the change in “I Opt” profile between manager and Vice President. The green arrows show a further decline in both LP and HA. However this time the shift to the idea-oriented RI is more pronounced.

Table 8
AVERAGE RAW “I OPT” SCORES
Manager vs Vice President

At a Vice Presidential level the manager’s functional interest gives way to a mission focus. VPs are concerned about long run postures and objectives. The number of decision variables, the level of uncertainty and number of options explode with the lengthening of the decision horizon. The RI strategy is ideally suited to navigate this environment.

The RI strategy is NOT “out of the box” thinking. That is an analytical exercise. It is “no box” thinking. The box is created along with the relationship between the dots that make up the box. The RI creates ideas totally outside of the boundaries of the known.

Leadership training can foster the development of this capacity. The ability to create theories “on the fly” is part of it. Exercises in relating unrelated things is another. Internships in strong RI environments are a third.

In summary, it appears that strategic style differences by rank are explainable. They probably rest on the nature of the job. The driving factors appear to involve lengthening decision horizons and diminishing level of specificity. The different “I Opt” strategic styles found in this research appear to align with the demands of these various levels.


SUMMARY
This research has shown systematic differences in strategic styles at different leadership levels. Overall, the Relational Innovator approach seems to be favored at all levels. But the relative strength differs.

Transitioning from one level to another is not a simple process of adding RI capacities. Different levels appear to require different mixes of the four basic “I Opt” styles. To be maximally effective, leadership development in both universities and corporate training groups should understand and accommodate these different needs.

This research has identified and traced the impact of these rank-based style differences. Recognizing and adjusting for them can produce better team performance from leaders who are better able to lead. It also serves the interest of the leaders themselves. They can better prepare themselves for the changes that will accompany their rise in rank.

The investment needed to adapt leadership training to the findings of this research is small. The return to both the organization and individuals could be large. This research is worth serious consideration.

Leadership, Diversity and the Goldilocks Zone

By: Gary J. Salton, Ph.D., Chief R&D and CEO
Professional Communications, Inc.


ABSTRACT
Leaders lead teams. Teams are a tool for getting things done. The leader must decide how to configure a team so that it best meets the needs of the task at hand. One important aspect of design is the size of the team. Another is the particular people chosen as team members. This Research Blog addresses these subjects using hard data rather than opinion and is set in language accessible to anyone.


INITIAL DATA
Actual data was drawn from 3,815 teams. All functions are represented including engineering, IT, finance, medicine and manufacturing among many others. They include profit, non-profit and government organizations. It is a reasonable sample of actual teams operating in the real world. The team size distribution is shown on Chart 1.

CHART 1
DISTRIBUTION OF TEAM SIZE

Chart 1 shows a “Goldilocks” zone. The area between 4 and 9 people is 25% of the distribution but contains 60% of the teams. This clustering effect suggests that there are forces causing leaders to create teams in the “Goldilocks” range as optimal for their purpose.


THE COST OF TEAMS
The first factor influencing optimal team size is cost. Every added person adds costs. From a leader’s viewpoint, this cost is framed in the difficulty of guiding and coordinating increasing numbers of people. But the cost is not confined to the leader, it is experienced by all concerned. The concept of Transaction Channel is central to its understanding.

A transaction channel is a relation between 2 people in which the actions of one are determined (at least in part) by the actions of the other. In other words, all parties have to pay attention to what the other is doing, assess it and then decide what to do about it. Communication channels are passive. Transaction channels are active and expensive for all involved.

GRAPHIC 1
TRANSACTION VS COMMUNICATIONS CHANNELS

Transaction channels increase exponentially with team size. Movie 1 shows the process. What starts out as a simple diagram ends up as a bowl of spaghetti. Leaders choosing team sizes that exceed maintenance capacity no longer have a team. They have a group. The advantages of teams will have been lost.

MOVIE 1
TEAM SIZE AND TRANSACTION CHANNELS

The "right" size of a team depends on the objective being pursued. Leaders set these objectives. They have a choice of pursuing them as a whole or breaking them into pieces. Small teams can pursue narrow objectives. Broad objectives usually demand big teams. If the leader sets too broad an objective excessive cost will have been “built in.” Everybody will pay.

The relation of team size and transaction channels is given by the Combination Formula. The result of applying it to team size is shown in Chart 2. The growth in complexity is geometric.

CHART 2
TRANSACTION CHANNELS VS TEAM SIZE

Firms who sponsor the teams in the database all have a history. It is likely that experience taught them to recognize team sizes that seem to work. The clustering of teams in the “Goldilocks” zone is the expression of this common judgment. At the upper limit it translates to about 40 transaction channels.

There are teams that lie outside the “Goldilocks” zone. But if a leader chooses to exceed the "Goldilocks" limits, there should be a very good reason. The increase in complexity (i.e., cost) is certain. It will be paid by the leader in terms of increased guidance and by the team members in terms of increased complexity. The leader should be confident that the expected value of a larger team size should be enough to offset this certain cost.


MEASURING DIVERSITY
Most kinds of diversity are obvious. Age, gender, race and occupational specialization (e.g., engineers, physicians, etc.) are examples. If these are deemed to be important, a diversity mix is easily fashioned. Physical appearance or standard corporate records are usually all that is needed to identify team candidates.

There is one form of diversity that is not obvious—thought diversity. Thought diversity is simply the different ways people can view and address a particular subject. This diversity is embedded in everyone. Engineers can be spontaneous, idea generators or they can be disciplined, methodical juggernauts. Every other category of diversity contains this veiled component. This “secret” form of diversity is what will determine the success of a team.

“I Opt” is a tool that measures the information processing preferences of people. The way we process information determines how we approach issues. For example, if you do not pay attention to detail you will not be precise. It does not matter what you think about it or how hard you try. You have not got the data. On the other hand, focusing on detail limits long-range planning since there are no “facts” about what has not yet occurred. A focus on relationships is a better strategy.

There are more dimensions to thought diversity (see other entries in this blog). However, the above is enough to illustrate the condition. Taking in different kinds of information and processing them in particular ways creates a valid perspective. The mix of these perspectives is what equips (or limits) a team’s ability to get a job done. “I Opt” has defined these thought perspectives as Strategic Styles. They are strategic in that they are a general approach to life's issues. They are styles in that they tend to be applied throughout a person’s life—not just at work but everywhere. They are dependable.

Information processing preferences (strategic styles) can be measured exactly. The maximum diversity any team can have is shown in Chart 3. The area covered can be considered 100%. No matter how many people you add, you cannot exceed these boundaries.

CHART 3
MAXIMUM POSSIBLE TEAM DIVERSITY

Chart 3 represents a real but theoretical limit. The highest level recorded in the 3,815 teams was 71.2% of that maximum. The reason is simple. If all possible perspectives were brought to bear on a particular issue, nothing would get done. In most real life situations, part of the leader’s job is to set a general direction. This limits the desired thought diversity. For example, if the leader’s goal is replacing a heart valve, there is little value in including people good at expedient action. Including that capacity on the surgical team would be dysfunctional. Diversity is not a universal "good."

Thought diversity is a characteristic of the individual as well as of a team. We all can get ideas, plan, react spontaneously or execute with precision. We tend to favor one or another style, but the capacity for doing everything is within us all. The “I Opt” profile as shown in Chart 4 shows a typical “I Opt” profile. You can note that the profile touches each of the four strategic styles.

CHART 4
INDIVIDUAL DIVERSITY: THE "I OPT" PROFILE EXAMPLE

The lower theoretical level of individual diversity is zero. However, the only place you would find such people is in mental institutions. In the practice of OD the most typical level will be 19.4% of the theoretical maximum (Chart 3). In other words, a person approaching an issue alone will only cover about 20% of options. This is one of the big reasons we work in teams. Working alone we will probably not see all of the relevant dimensions of an issue.

Adding one person does not double the diversity of a single person. The reason is that profiles overlap. Some portion of the thought diversity the added person brings will already have been covered by the first. This is not bad. This commonality is the basis of mutual understanding. It allows us to work together. This condition is shown on Chart 5.

CHART 5
DIVERSITY CHANGE: ADDING ONE PERSON

An example of an actual five-person team used in this study is shown in Chart 6. The outer boundary of all of the overlapping profiles defines the total diversity of the team as a whole. The gray area defines the majority, it is the area where common positions are most easily reached. Both pieces are needed for a team to operate effectively.

CHART 6
TEAM DIVERSITY AND COMMONALITY
A TYPICAL 5 PERSON TEAM EXAMPLE

The interest of this Blog centers on thought diversity rather than commonality. The outer boundary of the overlaid profiles sets diversity limits. It determines the range of options. For example, if there is no one with an appreciable level of Reactive Stimulator (RS) in the group, the possibility of an expedient solution will probably never arise. If this were relevant (it was not in the surgical example), the team would have been denied access to a valid alternative. Cost, effectiveness or both can be negatively impacted.

The availability of a right level of thought diversity is one of the major benefits of teams versus division of labor work groups. Part of a leader’s responsibility is to create the right level of diversity. Too little and viable options disappear. Too much diversity and the team can be paralyzed. The delays inherent in divergent perspectives can be just as costly as too few options.


THOUGHT DIVERSITY IN TEAMS
The initial 3,815-team dataset are real teams. However, they are a bit of a jumble. They can include transitory teams, “teams” of loosely associated people or teams with a less than well-defined purpose. It was decided use subset of this larger group. The subset includes 1,196 teams where the leader of the group was known. In many cases, the leader’s title was also available. The dataset is still large and does provide increased assurance that the teams were focused on serious purpose.

The diversity index of each team was calculated and set as an increase in diversity over a single person. Thus, 150% indicates that the team increases diversity by about one and a half times. Said another way, the team has the equivalent of 250% of individual diversity.

Movie 2 shows the distribution of diversity indexes by team size. The movie shows both the mid-point (i.e., median) and the distribution (i.e., range) of each size of group considered in this study. It also explains in more detail the forces that affect diversity as it is applied in a team context.

MOVIE 2
TEAM DIVERSITY BY TEAM SIZE

A more abstract but inclusive way of looking at team diversity in relation to size shown in Chart 6. The "Goldilocks" zone generated by team size is superimposed on these diversity levels.

CHART 7
TEAM DIVERSITY versus TEAM SIZE

Chart 7 shows that within the "Goldilocks" zone the increase in thought diversity rises rapidly. In other words, every increase in the number of people on the team yields a large increase in the diversity of perspectives. Beyond the "Goldilocks" zone, the diversity value of each additional member decreases. But the cost grows exponentially (see Chart2). The interaction of increasing cost and diminishing diversity value is what causes the "Goldilocks" zone to be created.

Does thought diversity vary by organizational level? Table 1 shows that a common process appears to drive all teams, from President to Supervisor. A diversity index of about 150% over a single person (i.e., 250% total) and a team size of about 9 people appear to be a common standard.

TABLE 1
TEAM DIVERSITY AND TEAM SIZE
BY ORGANIZATIONAL RANK

SUMMARY
The fact that transaction channels impose costs is beyond question. However, we cannot offer a causal (what causes what and why) formula for why about 40 transaction channels appear to begin to tax the upper limit. Similarly, it is beyond question that different perspectives can contribute to team success. However, why a diversity index of about 150% over an individual seems to signal a level of diminishing value is unknown.

While we lack exact formulas, the findings in this blog can be useful to actual and prospective leaders. Just becoming aware of the nature of the costs and benefits of team design is enough to prevent most catastrophic errors. Being able to attach a measure to both costs and benefits further enhances the probability of success. While not yet complete, this appears to be a useful step forward.