Applying Problem-Solving Theory to Engineering Project Team Leadership
Improving Collaboration, Communications, and Trust
Dr John Walker & Prof Kathryn Jablokow
Roberts Wesleyan College, NY; Penn State University, 2010
In this article, the application of a problem-solving theory to engineering project team leadership will be presented in order to improve collaborations, communications, and trust within the project team with the goal of improving project team performance. This paper discusses the boundaries of project leadership. Boundaries are determined by project objectives, organizational relationships of team members, the team charter, and team roles. In addition, the timeframe and development of the team determine the boundaries of team leadership.
An overview of Kirton’s (2003) Adaption-Innovation (A-I) problem-solving theory will be presented. The focus of this overview will be to distinguish between the problem the project team has been assembled to solve and the problem of managing the project team members who have been assigned to solve the problem. The relationship of the project team leader to the team, with regards to problem-solving preferences, will be examined. The knowledge of this relationship may promote improved collaboration, effective communications, and trust among the team members plus reduce the effort required by the project leader to manage team members. Application of A-I theory provides an approach to the project leader to harness more effectively the cognitive diversity of the team in an effort to produce superior problem solutions, remembering always that large, complex problems need a diversity of problem solvers to solve them–as long as that very needed diversity does not cause the team to fall apart. The team’s management of such wide diversity is the theme of this paper.
Three diverse engineering project leadership styles will be described. Problem-solving leadership is described by Jablokow (2008), servant leadership as described by Greenleaf (1991), and micro leadership as described by Nicholls (1988). The similarities and differences of these styles will be examined and when the application of these styles may be more advantageous to the engineering project team leader will be discussed within the structure of defined project boundaries and the cognitive diversity that exists in a given team.
Scenarios will be presented examining various combinations of project team boundaries, the relative problem-solving preference of the team leader versus the group, and the project leadership style in use with the idea of creating a model that would assist engineering project team leadership in the future.
II. Structures of Project Team Leadership
According to Kirton’s (1994) A-I theory, “cognitively driven change implies structure. Without structure there can be no analysis of the past and no learning; no projection to the future, no prediction and no theory; no classification of events, no abstraction of principle, no order in the universe; no language and no thought” (p. 3). In a project team, the leader needs to understand the cognitive structure that optimizes the problem-solving effectiveness of the team. Structure is not fixed throughout the life of the project team and so should be adjusted during different development phases. The phases described in this article are the pre-team, new team, and mature team phases.
In the pre-team phase, a critical structure is a clear definition of the problem the team is being formed to solve. This will require varying amounts of dialogue between the project team leader and the decision-makers who are chartering the team. Although no set amount of dialogue is required, Kirton’s (2003) A-I theory would suggest that the greater the difference of problem-solving gap between the project team leader and the decision-makers, the greater the effort to effectively understand the problem required.
After clearly identifying the problem the team is chartered to solve, the team leader must develop a communications plan that will articulate the team’s objectives to distinct audiences or stakeholders. There may be many stakeholders depending on the problem, but in general, there will always be three major stakeholders: the decision-makers who chartered the team, the team members, and those who will benefit from the solution to the problem.
Dialogue will let each of the major stakeholders provide additional structure to the problem definition; through their involvement, additional buy-in to the potential solutions will be increased. Before proceeding to the creation of the new team, project leaders should communicate the defined problem to both the decision-makers and those who will be impacted by the solution. The pros and cons and possible unintended consequences should be discussed with the intended outcomes being emphasized. The team leader is now prepared to enter into the next phase—creating a new project team.
New Project Team
The type of relationship among team members is another structure the project team leader should consider. According to Katzenback and Smith (1993), the team structure needed is dependent on the ability and knowledge of the team members and the level of ability required to solve the problem. If, for example, sharing of existing knowledge is all that is required to solve the problem, then a workgroup is sufficient. If, however, new abilities and knowledge must be learned through synergistic group development and output, then a real or high-performance team may be required. Katzenback and Smith (1993) define a real team as “a small number of people with complementary skills who are equally committed to a common purpose, goal(s), and working approach for which they hold themselves mutually accountable”. The awareness of the problem to be solved is one structure that may help the project leader in selecting team members. Once the members are selected for their abilities, the project leader may enhance the team’s performance further by assessing the preferred problem-solving style of each of the members. The identification of preferred problem-solving styles for the team members and the team overall will facilitate improved communication, trust, and the ability to work well together.
Understanding the team’s problem-solving preference can also give insight into refining the team charter rules of conduct and mission of the team. The team charter should clearly state what kind of decision-making authority the team has. For example, will the team be making a recommendation to other decision-makers or will the team be charged with reaching consensus on implementing the solution to the problem? The team charter should identify the roles of the team members and key indicators of progress in solving the problem.
Mature Team Phase
The project team leader is now ready to enter into the mature team phase. The mature team phase is where the performance of the team becomes evident. In addition to the challenge of recognizing various structures mentioned in the article, the advent of technology and increasing complexity of problems adds an additional structural concern for some team project leaders. The project team leader will need to anticipate the impact of whether the team will work virtually, in close proximity, or in some combination of both.
III. A Cognitive Framework for Problem Solving
The cognitive framework for problem solving embraced here was introduced by Kirton [2, 43], a British industrial psychologist who has spent nearly four decades developing both its theoretical foundations and its practical application across disciplines (including, e.g., management, education, and science). In this section, we will explore a condensed summary of Kirton’s framework for problem solving, incorporating the work of others whose contributions add support as well as depth and breadth to Kirton’s original views. We begin by recalling the greater context for problem solving and change in today’s world, driven by the challenge and complexity of our current problems, the catalytic nature of change, and the implicit need for collaboration. In responding to all of these, our understanding must begin with the cognitive processes of individuals – where all problem solving begins.
Key Variables of Cognitive Diversity
All humans solve problems, and at the core of every individual’s problem solving efforts (according to Kirton) are four principle elements or key variables: opportunity, motive, level, and style. While these elements are common to all humans, small but significant variations in them help define the differences in our problem solving efforts. As for opportunity, the environment is its general source, however a particular opportunity may come to our attention (as Kirton notes, opportunities may be revealed, sought, or made [2, p. 7]). Without opportunity, no problem solving can occur; when it exists, opportunity must be perceived by the individual (perhaps from among many opportunities), who must then manage and exploit it successfully – or recover from bad (e.g., inappropriate) decisions.
Next, motive is needed to drive our problem solving efforts; it is the means by which we channel energy in a particular direction, at the necessary intensity, for the required duration, in order to solve a given problem. Motive is also the underlying process that enables us to filter through all the possible problems (oppor¬tunities) available and helps us choose those that we wish to address (and in which order) . Having chosen an opportunity (problem) upon which to act, we plan, find, and implement a solution. To do so, we need two cognitive facilities: level (capacity) and style. We know a good deal about cognitive level, which refers to an individual’s inherent potential capacity (such as intelligence or talent) and manifest capacity (such as technical competence or managerial skill). Cognitive style, on the other hand, describes the manner in which we solve problems [2, 20, 30, 44]; more precisely, cognitive style is the “strategic, stable, characteristic, preferred way in which people respond to and seek to bring about change” [2, p. 43], including the solution of problems. Kirton’s particular contribution here is to make clear (backed with evidence) that cognitive style is independent from cognitive level ; knowing something about an individual’s style tells us nothing about that person’s level, and vice versa, although the two are often confounded in practice [44, 45].
From this discussion, note that our definition of problem solving is very broad; in essence, it is the act of bridging a gap (of cognition and resource) between “what you have” and “what you want or need”, with variations in how (and where – as in “which discipline”) that occurs encompassed in the four key variables described above. On this point, our approach differs from some others, where problem solving (as opposed to, say, “exercise solving” [33, 34]) is constrained to include only those situations “that the problem solver has not encountered before” and/or in which “the procedure to be used is unclear” [33, p. 75]. The general definition for problem solving we have adopted, which subsumes these cases, is not new or unusual; it forms the basis for many problem solving process models in use today [34, 46] and can be found in the classic works of Wallas , Guilford , and Gagné , among others [e.g., 26, 27].
The concepts and definitions presented above all feed into a number of key assumptions. First, by virtue of adopting a broad functional model for human cognition, we can link creativity, problem solving, and decision making together: the brain uses the same fundamental cognitive process for all of them. Since all humans utilize this process, we can assume that all humans are creative and solve problems – with differences in their problem solving and creativity explained through variations in level, style, motive, and (perception and selection of) opportunity [2, 13]. Among these variations (i.e., this diversity), no style, level, or motive is better than any other in general, only more or less effective (appropriate and efficient) for finding the required solution to a specific problem and implementing it. Every style and level has advantages and disadvantages, in which the style and level of the problem, not one’s preference, is the key [2, 17]. This is a vital element of Kirton’s theory that moves us from allowing popular trends (e.g., “Innovate or die!”) to determine the so-called “best” approach to problem solving, to the more reasonable approach of determining what the problem actually requires for its resolution – regardless of what the trends say. In actual practice, a team member may not fit the current trend, but he or she may be most helpful (given that person’s particular level and style) with the present problem, at the present stage!
With these principal elements and assumptions in place, we now have a model of cognitive diversity at the individual level, which (while basic) is rigorous and useful. In summary: all humans are creative and solve problems, at different levels and with different styles, driven by different motives, and exposed to different opportunities (which they also view differently). In problem solving, we must – at a minimum – manage this individual diversity in order to manage change; to manage wider change, we must manage wider social diversity (i.e., that of the group) as well.
Style and Structure
Next, we explore the concept of cognitive diversity (and its relationship to problem solving) from another perspective, with a particular focus on cognitive style. Personality can be defined generally as the sum of all the stable cognitive influences on, and stable patterns of, behavior; it is a structure, as are all its elements (e.g., attitude, motive, potential level, style, etc.) [2, 50, 51]. Differences in personality result from variations in these patterns, to which we, as humans, are particularly well attuned (“I can readily tell that you are not like me, even if I cannot explain why!”). According to Kirton, one of the main patterns that differentiates us from each other is the characteristic way (as distinct from characteristic level) in which we, as individuals, manage structure.
In general, cognitive style (like cognitive level) has multiple dimensions, which can be assessed by many different means. To assess cognitive style, Kirton developed and validated the Kirton Adaption-Innovation Inventory (KAI), a straightforward psychometric assessment that does its job neatly and compactly [2, 43]. As measured by KAI, cognitive style differences lie on a bipolar continuum that ranges from strong Adaption on one end to strong Innovation on the other. In general, individuals who are more Adaptive prefer to solve problems using more structure, and with more of this (cognitive) structure consensually agreed. In contrast, more Innovative individuals prefer to use (be confined by) less structure when solving their problems and are less concerned with gaining consensus around the (cognitive) structure they use. Note that individuals are most accurately described as “more/less Adaptive” or “more/less Innovative” in keeping with this continuous range of styles, although the terms “Adaptor” and “Innovator” are sometimes (but cautiously) used for linguistic convenience.
A-I continuum + sub-scales
In general, more Adaptive individuals prefer to approach problems from within the given frame of reference (or paradigm – a conceptual structure) and strive to produce solutions that are more immediately efficient, sound, and reliable. They are especially good at refining the current standards, rules, and procedures in order to make them operate as effectively as possible. The value of these individuals is obvious: they provide the consistency, stability, and efficiency necessary to keep a system running smoothly in the long term. Their advantage lies in their preference for finding ways to enable and create change within a structure, making best use of its defining properties and resources; they also change the structure as an outcome of solving a problem. Their disadvantage is their tendency to stay with a (even the main) structure “too long” – i.e., after its usefulness has played out .
The more Innovative person, on the other hand, tends to detach a given problem from its customary frame of reference, searching for “unusual” solutions in unexpected places . These individuals are particularly good at bending the current rules and procedures in order to move a system into different (often riskier) territory. The value of the more Innovative is also clear: they provide more radical shifts in structure when these are required. They may, from time to time, alter elements of (even) the main structure in order to solve the problem – a riskier approach. Their advantage lies in their preference for manipulating boundaries and juxtaposing views that may not be obvious to their more Adaptive counterparts. Their disadvantage is their tendency to leave a structure “too soon” – i.e., when it is still enabling and delivering value. For additional descriptions of commonly observed traits of individuals with different Adaption-Innovation (A-I) cognitive styles, see Kirton [2, 43, 52] as well as Buffinton , Lopez-Mesa and Thompson , and Jablokow [1, 54].
The Paradox of Structure
Within these variations of style and their corresponding impact on problem solving, we can see a paradox: the style (preference for structure) that enables problem solving in one instance may hinder it in another [1, 2, 30]. For example: while Leonardo da Vinci devised many “futuristic” designs that spanned and combined a wide variety of disciplines, he frequently left projects unfinished due to his apparent lack of focus . In contrast, Thomas Edison – who was very focused – found it difficult to shift away from a particular design solution, even when superior alternatives existed . When applied to structure in general (whether it be technical, social, conceptual, etc.), Kirton refers to this phenomenon as the Paradox of Structure [2, pp. 126-134]; that is: every structure, by its very nature (including one’s own brain), is both enabling and limiting at the same time. In fact, a structure limits (i.e., focuses our efforts) in order to enable, but it must enable more than it limits, or the structure cannot function well. The limits must be focused, sharp, and stable enough to enable “now”, yet flexible enough to change when currently-required enabling is blocked. The trick is to find a good balance in each circumstance, i.e., we must find ways to maximize the enabling factors and minimize those that limit in order to reach ground where there is payoff for all.
One difficulty is that the proponents of any structure will play down its limiting side and play up its enabling side, whatever that structure might be. Here we must take care: within much of the literature devoted to “creativity”, breaking down or shedding structure (i.e., Kirton’s Innovation) is considered better (i.e., “less structure is more creative”) – which, from a cognitive perspective, blatantly confounds level and style by falsely assuming that structure only limits. The careful distinction between level and style (and its practical implications) is a key element of Kirton’s theory that makes sure we see Adaption-Innovation as a continuum, not a dichotomy.
As noted previously, no particular style (level, motive, etc.) is better than any other in general; only in the face of a particular problem might one be more effective (by being more appropriate) than another. As engineers, we know the truth of this from practical experience: there are times when maintaining or fine-tuning the current structure (product, idea, design) is the best solution, while at other times, the current structure must be rebuilt or replaced in order to succeed. In complex problem solving, both approaches are needed overall, at different times, and applied toward different parts of the “larger” problem. There is more than one style of creativity and problem solving, and within that diversity, more Adaptive and more Innovative approaches are equal in intrinsic value, with their complementary contributions wrapped around the management of structure.
We can find many historical examples of the catalytic nature of change and the Paradox of Structure in science, engineering, management, and other disciplines [1, 2, 12, 57]. Classic case studies include the Copernican Revolution [58, 59], the development of the Periodic System of the Elements , and the invention of the telephone , among others. In each case, it is evident that multiple problem solvers were necessary to resolve these complex problems – individuals with different levels, styles, motives, views of change, and per¬ceptions of opportunity. And so we generalize: a diversity of problem solvers using a diversity of approaches is needed to solve a diversity of problems (as we have noted before, we must collaborate in order to survive). What is equally obvious is that these diversities of problems and people need to be managed and facilitated; they do not generally “take care of themselves”. If the current, required diversity is not managed well, it will reduce (not enhance) the team’s problem solving effectiveness. The question is: how do we take the essence of this multi-faceted diversity of problems, people, and processes, which we have tried to capture here using a few key variables and principles, and apply it to collaborations in a systematic and practical way? How can we come to some understanding of the implications of cognitive diversity (and the beginnings of its management) in a group setting?
Cognitive Diversity in Teams: Problem A and Problem B
And so we come to teams: in problem solving, we must manage our own individual diversity to manage our personal impact on change; we must manage the diversity of teams to manage wider change. Kirton describes this practical challenge in a simple, yet elegant way [2, p. 5, also p. 205]: every time a person shares a problem with another person (i.e., in every collaboration), each person automatically acquires two problems. The first is Problem A – the original problem around which the team was formed (even if it is a team of only two), and the second is Problem B – the problem of managing each other’s differences (i.e., managing the collective diversity). In the end, Problem A should take up more of the collective energy than Problem B, or the team will eventually fail. We are repeatedly faced with this situation and must ultimately make a choice in each case: do we collaborate or clash?
Problem B can take many forms, for the potential differences between two individuals (much less, two groups) in level, style, motive, and perceptions of opportunity are countless. In addition to these person-to-person variations (which can create considerable friction between team members), the problem of managing the differences between our problem solving resources and the requirements of Problem A is an additional challenge – in essence, another form of Problem B. We can come to a better understanding of Problem B and its resolution by considering the notion of cognitive gap.
The Problem as a Moving Target
Framed in the Paradox of Structure, Kirton describes the management of change (done well) as “managing structure, by adjustment and readjustment, so as to set just sufficient limits that will achieve maximum enabling” [2, p. 287]. How can we make this information useful in an immediate and practical way? As one strategy, consider the following: when teams are first formed, a good deal of time is spent assembling the best possible combination of people in style, talent, knowledge, moti¬vation, etc., for the current problem in its current form. But any team, by virtue of its own success in solving the original problem, creates new condi¬tions, and these new conditions can create needs that the present team is not well equipped to han¬dle.
In essence, every large and complex problem (at least) is “a moving target” [2, pp. 290-292], and we must learn how best to track it. One solution is to identify competent, experienced people who, although currently at a disadvantage and seemingly out of favor in the present environment, will be needed at the appropriate time and stage to adjust and help con¬trol the change trajectory (avoiding the pendulum of change, seeking a spiral) in due course. In other words: identify what will be needed when the current phase of problem solving has changed the operating conditions and what will be needed in the next phase of problem solving; it helps if the entire team shares in these insights and assists in the process. So, to manage change widely and well, a team needs to manage diversity (both of problems and its own internal array) equally widely, wisely, and well.
IV. Diversity of Engineering Project Leadership Styles
Upon review of the top 15 articles on leadership and management by Harvard Business Review, it was observed that very little literature focused on problem A defined by Kirton. Most of the articles dealt with managing the structures, systems or leading people with almost a complete focus on problem B. this lack of emphasis on Problem A in the literature may explain why Problem A is often poorly defined or not defined at all in team projects. According to Kirton (Kirton, 2003) failure to articulate Problem A may cause the team to work on multiple Problem A’s, thus creating a certain Problem B right from the start. Project team leaders may be well served by having awareness of the following leadership approaches of: Problem Solving Leadership, Servant Leadership, and Meta, Macro and Micro in their toolbox for leadership. Below is a brief overview of the three styles
Problem Solving Leadership
In essence, all the elements described above represent the knowledge required by a problem solving leader in order to manage successfully the efforts of a problem solving team. They also represent the knowledge required by each member of that team in order to help a leader be successful; there are no ideal leaders who can “do it all”. In the past, considerable time was spent in the search for such an “ideal leader” – a notion Kirton and we reject. This past leader was selected (or took command) because it was deemed (especially by the leader) that he or she had outstanding knowledge of the problem area (what we might call the “technical content”). This leader was expected, with whatever resources of people and materials were available, to dominate the problem solving process, leading and commanding while others “followed” (i.e., did the work).
In our framework, a leader is the (any) person holding the role in leadership that will facilitate the team in solving a particular problem, over a specific time, with the currently available resources, within the available team. We seek to be pragmatic rather than aim for an unattainable ideal. As such, today’s problem solving leader needs a new array of attributes to be successful and remain acceptable; these are composed of two general parts. First: he (or she) still needs knowledge of the original problem (Problem A) – not in order to dominate it completely, but enough to be able to “hold his own” as an expert in an appropriate team. This is now a more modest requirement, but it is only half of what is needed. The other half is an understanding of the problem solving process and the problem solver (i.e., knowledge related to Problem B). This combination will allow a leader to help the team direct their combined energy efficiently towards the collective solving of Problem A, with as little hindrance from any potential Problem Bs as possible [2, pp. 308-313; 21]. So, it is the team that solves the problem, under knowledgeable leadership, given that “knowledgeable” has been redefined. The leader is now a conductor of the orchestra, interacting with each player, rather than the lead player on every instrument.
Greenleaf (1970) posited that being able to answer the following questions affirmatively is the best test and the most difficult to administer for the servant leader:
• Do those served grow as persons?
• Do they, while being served, become healthier, wiser, freer, more autonomous, more likely themselves to become servants?
• What is the effect on the least privileged in society; will they benefit or, at least, not be further deprived? (p. 7)
The servant leadership philosophy provides a framework for the development leadership skills that minimize problem B that inevitably occur with collaboration according to Kirton (2003) , it also provides a frame work for development of each of the team members collaborating on the project and those who will be served upon the completion of the project. The servant leader abandons preconceptions of how best to serve, by listening first to the needs of others, engages in ongoing dialog with the team members. From this conversation a shared vision emerges for the team.
Spears in On Becoming A Servant Leader (1996) identified ten critical characteristics of the servant leader: listening, empathy, healing, awareness, persuasion, conceptualization, foresight, stewardship, commitment to the growth of people, and building community (p. 4). Each of these characteristics deal with problem B described in the KAI theory.
The competencies that engineering project team leaders have—their knowledge and skill set—are increasingly valuable in today’s organizations. Expertise is not limited to a person’s place in an organizational chart and does not depend on how many employees a person supervises or the office size.
Today’s engineering project team leaders also face a more difficult set of challenges. The global marketplace is much more complex than the largely local or national economies of years past. Consumers are more demanding; they not only want the latest technology, but they want it at the lowest price with the highest possible quality. The quest for quality is changing. Mere product quality is insufficient; quality is required in processes, services, and in problem solving. Additionally, the process owner must consider the impact of potential solutions on various stakeholders and the ethical ramifications of those solutions when solving problems.
Today’s engineering project team leaders, therefore, have to accomplish more while having fewer sources of traditional power. One of the primary implications of these trends is that engineering project team leaders may need intentionally to evaluate and develop the ten critical characteristics listed above were themselves and their project team members. Those who are able to provide excellent servant leadership may provide positive outcomes for the stakeholders impacted and will be able to answer affirmatively to test for servant leadership.
Meta, Macro, Micro Leadership
Nicholls (1987) asserts that the study of leadership suffers from too many definitions, not too few. This results in confusion due to two different perspectives on leadership and three common usages of the word, leadership. The first perspective views leadership as influence on individuals without using power or authority. The second perspective views leadership as the shaking and moving of organizations to face the future and cope with change (p. 16). The first perspective most closely applies to much higher level engineering project team leadership and will be discussed in greater detail.
Nicholls (1987) describes three aspects of leadership viewed as influence on individuals are meta, macro and micro and develops a framework that posits the following:
Meta leadership links the individual to the environment through visioning and talent and creates enthusiastic followers.
Macro leadership links the individual to the entity be it the whole organization, a strategic business unit, or a project team by answering key questions about roles and expectations and creates committed members of the business unit.
Micro leadership links the individual to the job or task creating willing performers. (pp. 20-21)
Nicholls (1987) states, “. . . This sheds light on the way in which many of the current studies overlap and relate to one another. The framework has also been found to be of great value in helping managers to understand the variety of leadership skills that are needed to draw the most out of people at work” (p.18).
Applying Theory to Project Team Leadership
Problem Solving Leadership
The Venn diagram below shows the interaction of the project team leader and team members with the business plan or technology plan, which forms a structure in which they are problem solving:
Awareness of preferred problem solving style of team leader
The engineering project team leader would greatly benefit from gaining insight of his/her problem solving skills. Kirton (Kirton, 2003) states, “Knowledge of A-I theory has been found useful to engender insight not just into a specific event but also in to this class of problem generally. P. 248”. Gaining this insight is analogous to providing lubricant to a high performance engine. This insight enables the team leader to develop high performance project teams with regards to the well defined Problem A while minimizing team friction (Problem B) and avoiding excessive coping and possibly break down of the collaborative function. This insight for the leader can be gained by taking the KAI inventory and receiving feedback from a certified KAI practitioner. Based on this feedback the team leader can intentionally plan to improve collaborations, communications, and levels of trust between current and future team members.
Application of the test of servant leadership adds another dimension in the planning process for the team leader. By answering the questions, “Do those served grow as persons? Do they, while being served, become healthier, wiser, freer, more autonomous, more likely themselves to become servants? What is the effect on the least privileged in society; will they benefit or, at least, not be further deprived?” provides a framework to intentionally seek improvement for team members and stake holders that will solve Problem A and those who will be impacted by its solution. This philosophical approach my help the team leader to understand his own motivation for the solution produced and why various stake holders may view the solution with very diverse perspectives which may actively seek to resist the solutions.
Meta, Macro, Micro Leadership
Applying the leadership style posited by Nicholls (Nicholls, 1987) provides the leader with a wholistic perspective that identifies critical links and potential previously unknown stake holders that may be impacted by unintended consequences of solving Problem A. By creating enthusiastic, motivated team members that are linked to the environment, the entity, and the task at hand, the team leader will develop team members that will be more invested in the successful solution of Problem A and in the development of team members.
Katzenback and Smith (Katzenback & Smith, 2002) state that high performance teams are concerned about the development of team members and hold each other accountable. Greater understanding of the intended impact of the solution to Problem A and provides greater acceptance and motivation to assist in the successful implementation of the solution.
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