Systems Wisdom

DESIGNING AN IDEAL DOCTORAL DEGREE

In 2014, Philadelphia University (PhilaU) a 130 year old institution with a mission to develop the model for professional university education in the 21st century asked Systems Wisdom to design ( we provided project leadership[i] and facilitation[ii]) a new kind of professional doctorate for their institution.  Based on their deep understanding of the past and ample evidence of the current realities of the changing role of the university in society, they assigned project governance to their remarkable and supportive Executive Dean of the College of Science, Health and the Liberal Arts, and to their equally remarkable and supportive Vice-President of Innovation. 

We imposed two project requirements.  First was the adoption of a systems thinking framework or mindset including expansion rather than only reduction thinking.  A new doctoral program, we posited, is a social system contained within the university system.  Both were contained within the much broader system of other universities, as well as for profit, non profit and government organizations all of which vary in geography (local, national and global) and delivery channels.  In addition, the doctoral faculty and students as working professionals would have purposes and obligations not only to the program and the university but also to other workplaces and social communities of which they remain integrated parts.  The implication of a systems thinking mindset is that the environment and contexts are interdependent and varied. 

The second related requirement was that the expert knowledge for the design was presumed to reside in many places and with many people beyond the customer and consultant.  To create the design for a new doctoral program, therefore, requires direct involvement by internal and external communities, stakeholders, and users.   For this project, the consultants would be process experts; the customer, stakeholders and users would be the content experts who would directly incorporate their own interests and values resulting in a program “designed by” the customer, stakeholders and users.

Email invitations for a “Design an Ideal Doctorate” project were sent to a broad community from within PhilaU as well as from other external communities of stakeholders and users.  Voluntary participation was requested in one of several available workshops held on Saturday mornings at the University.  For those unable to attend, separate group meetings were arranged (also at the university). 

More than 100 people participated: academic leaders (e.g., deans of schools, directors, chairs of departments and programs, faculty members from PhilaU and from other universities); leaders and members of administrative functions (e.g., registrar, finance, library, development, and other roles from PhilaU and from other universities); alumni of PhilaU graduate degree programs; current graduate students (Master and Doctoral) from PhilaU and attending other universities; leaders and thought leaders from professional organization and leadership societies; executive level leaders from corporate in-house universities and training departments; government and nonprofit training leaders; senior HR administrators; and representatives from organizations where there was no support for graduate education. 

In the workshops and meetings, participants were challenged to generate characteristics of an ideal doctorate that “you would personally want to teach in; you would want to administer via your professional work; you would want to be a doctoral student in; you would recommend colleagues apply to; your organization would support if colleagues were admitted as doctoral students, faculty or mentors; you would want to join for professional and community support; your organization would want to partner with for consulting and research projects; and you would want to be acknowledged as a co-designer.”  These were not specifications for the future or for others; rather, these were what the stakeholders and users wanted right now and for themselves.  The only limitations were that elements must be technological feasible and that the program must be capable of thriving in the existing environment, as well as be sustainable in the future as the environment may change. 

As a guide, the following topics were available (all other topics were accepted):  Vision and mission; Admission (student demographics, requirements, pathways); Staffing (faculty demographics, requirements, pathways); Channels and learning environments (locations, travel, virtual); Brand (“type” of degree, “kind” of program, PR/marketing); Size/time (students/faculty, timelines, FT/PT, weekend); Curriculum/courses (topics, obligations, opportunities); Learning experiences (to develop capacities, competencies, connections or integrations); Deliverables (academic and practice); Finances/tuition (including support mechanisms); and Relationships (university and workplaces). 

The workshops and meetings produced hundreds of specifications (with many overlapping elements) for the ideal doctorate that would be appropriate for working professionals.  This became the content for the detail work completed by a core representative Design Team of 17 people (facilitated by the consultant).  This team worked online to prepare the final program design.  A Full Proposal document required by PhilaU for all new academic programs was written that contained the proposed program’s vision, mission, and descriptions of functions, processes and structures including courses.      

Workshops and meetings were held in October and November 2014.  The Design Team worked in December and early January 2015.  The Full Proposal was delivered January 30 and immediately began working its way through the required academic committees shepherded by the Executive Dean and Vice-President of Innovation.   In April 2015, the Doctorate in Strategic Leadership was approved.

Some Program Characteristics

Those admitted would be motivated to develop themselves as strategic leaders who effectively navigate situational, organizational and dynamic complexity, and apply tools leading to creative and innovative outcomes.  Graduates would be able to astutely identify new opportunities, help solve complex organizational problems, and meet the leadership needs of employers and society in the United States and abroad.

An important premise of the program design is that the information, knowledge, understanding and wisdom[iii] necessary to become a strategic leader is not located merely in the University or its faculty; it is in the workplace and beyond which means learning exchanges must take place broadly and among many situations and communities of people.   Instructors, mentors, advisers, and others who support learning and practice must also be drawn from broad communities of knowledge and practice.  To support this, the means of learning would be beyond instructor-led coursework; it would include varied cognitive experiences, action learning experiential experiences held in a variety of locations, and coach-and-mentor reflective experiences.  

The design called for two doctorates:  The first is a Doctor of Management (DMgt)[iv] completed in three years while working full-time.  Requirements include delivery of a Doctoral Thesis, a systematic review paper of a topic of the student’s choice.  This is also a requirement of the DMgt degree from University of Maryland University College.[v]  The second degree, if desired, is a Doctor of Philosophy (PhD) which expands the Doctoral Thesis into a Dissertation Project.  This 3-year Doctor of Management followed by a 4^th year Doctor of Philosophy is also available from Case Western Reserve University Weatherhead School of Management.[vi]   

 

For more information on the project or the program design contact Larry M. Starr, PhD at [email protected]

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[i] This was my third academic program design for working professionals.  In 2001, I had designed then directed the Master of Science in Organizational Development and Leadership degree program for Philadelphia College of Osteopathic Medicine.  Between 2002 and 2014, I had radically redesigned and directed the Master of Science and Master of Philosophy degree programs in Organizational Dynamics at the University of Pennsylvania. 

[ii] Appreciation is extended to the facilitators: Erica Wexler, Steve Freeman, Jason Magidson and  John Pourdehnad

[iii] Ackoff, R. L.(1989). From data to wisdom. Journal of Applies Systems Analysis, 16, 3-9.

[iv] Professional Executive Doctorates are globally recognized degrees preferred by working professionals who do not wish to commit to the deep discipline of a research doctorate.  Examples of professional applied degrees include Doctor of Education (EdD), Doctor of Psychology (PsyD), Doctor of Business Administration (DBA), and Doctor of Management (DMgt).  To support the increasing number of such programs, the (global) Executive DBA Council (http://www.executivedba.org/) holds conferences and publishes an academic journal.   

[v] Dinauer, L., Booth, B., Nadasen, D., DeFraia-Colee, L., and Paramasivan, V. (2012). Educating and engaging managers: The value of the systematic review method in professional doctor of management programs. Proceedings of the Second International Conference on Engaged Management and Scholarship, Bedfordshire, UK, June 21-23.  See: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2084807

[vi] https://weatherhead.case.edu/degrees/doctorate/doctor-management/ 

KISS AND LAWS

This essay is not about illegal kissing.  If you are interested in that topic, read the report in the UK’s Daily Mirror[1] which describes that “lovers face fines for kissing on Austria’s trains…after moans that amorous passengers were losing track of common decency.”  Rather, this essay is about problem solving and decision making.

Here are my conclusions:  First, one size does not fit all. Second, different situation contexts demand different approaches. Third, for some contexts the best approach is to reduce and KISS, and for others it is to expand and LAWS.  KISS is a mnemonic, a memory device, for “keep it simple stupid” and LAWS is an acronym for “look at whole situations.”    

In the course of our personal and professional experiences we encounter varying contexts.  Contexts according to Google dictionary are “circumstances that form the setting for an event, statement, or idea, and in terms of which it can be fully understood and assessed.”

In 2007 Dave Snowdon and Mary Boone[2] described a contextual framework and challenged readers: before deciding what to do when confronted with a challenge or opportunity, ask, what is the nature of the context? And, in what kind of context is this problem or opportunity embedded?  The framework proposes that there are differing context types which require differing problem solving and decision making approaches.  My first conclusion, therefore, is that to understand a problem or to make a decision one size does not fit all. 

The authors called their framework cynefin (pronounced ku-nev-in) a Welsh word translated as habitat or place.  An obvious context is one in which we believe a problem or opportunity is simple and the recognized approach is to use a previously identified “benchmark” or “best practice” solution.  A complicated context is one where we may need an expert to do an analytic diagnosis to understand what is occurring and then to apply a “good practice” solution.  A complex context is a qualitatively different state because the nature of the problem or opportunity and what to do cannot be understood or determined in advance.  It is only after the challenge has been addressed that the real problem becomes clear.   The appropriate approach for this kind of context is to facilitate and generate “emergent practice.”  In a chaotic context there is no discernible cause-effect or correlation-relationship among elements.  The approach is to try to discover an effective “novel practice.”  The final context is disorder.  In this situation there is no rational approach either to understand the situation or to intervene because events and outcomes are random.   My second conclusion, therefore, is that to understand a problem and to make a decision one must be aware that different situation contexts demand different approaches. 

How to determine which of the contexts best characterizes your particular problem or opportunity?  This is a very important question that I address in a subsequent essay.  For now, I present a table co-created with my colleague John Pourdehnad that lists problem and opportunity characteristics that depend on context.  I focus on the last three; the first five have been described in previous blogs.[3] 

TABLE OF KISS AND LAWS

Characteristic	Obvious or Complicated	Complex or Chaotic
Governance	Management	Leadership
Mindset (thinking framework)	Analytic and rational	Systemic and intuitive
Control	Predict and forecast	Anticipate
Focus	Parts and details	Relationships
Perception	Data analysis (collect the dots)	Pattern recognition (connect the dots)
Problem solving	Analytic, deductive and inductive	Design and abductive
Approach	Reduce	Expand
Mnemonic	Keep it simple stupid – KISS	Look at whole situations- LAWS

 

When a context is obvious or complicated, the appropriate problem solving approach is research and evidence-based.  It is appropriate to apply the prevailing methodologies that generate a solution that is best or good (enough).   Analytic thinking is fundamental because reducing the problem or opportunity to an explanatory root cause enables appreciation of the most critical elements and how each can be managed going forward.  Indeed, keep the problem simple is reasonable advice.  Inductive and deductive reasoning – approaches where one seeks an optimal solution for a defined problem in an orderly manner by testing optional hypothesis – imposes control within obvious and complicated contexts. 

When the context is complex or chaotic the challenge cannot be simplified or reduced to critical elements without losing the meaning of what is occurring or what to do. For such challenges a best or good practice may not exist.  Indeed, complexity cannot be readily reduced or simplified.  Those who study such contexts agree that “A complex system is defined more by relationships than by its constituent parts … (furthermore) there are different kinds of complexity and each has different and sometimes conflicting assumptions and conclusions.”[4]  What is needed in this complex or chaotic contexts is to perceive the whole challenge in terms of relationships and patterns.  This involves abductive reasoning which is central to design thinking and is sometimes called inference to the best explanation or what might be.  Abduction is used in addition to deduction (what should be) and induction (what is).

Rather than reductionism, to understand a complex challenge it is appropriate to apply expansionism.  This involves looking beyond the situation and into the containing system in which it exits.  A complex car challenge may be better understood by understanding the transportation system.  Expansionism involves understanding how changes in the environment, e.g., the competitive context may impact the problem or opportunity, and how the problem or opportunity may influence forces or competitors in the environment.   It is only by looking at the whole situation – the problem at hand and its relationships in broader contexts - that a complex or chaotic challenge can be appreciated, and the appropriate problem solving methodology can be selected.   The third conclusion, therefore, is that to understand a problem or to make a decision in differing contexts, it is sometimes appropriate to “keep it simple stupid” and for other contexts it is appropriate to “look at whole situations.”  In other words KISS and LAWS. 

 

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[1] http://www.mirror.co.uk/news/weird-news/worlds-weirdest-laws-20-bizarre-2284278

[2] https://hbr.org/2007/11/a-leaders-framework-for-decision-making

[3] http://systemswisdom.typepad.com/my-blog/

[4] Manson, S. (2001). Simplifying complexity: a review of complexity theory. Geoforum, 32, 405-414: http://www1.fee.uva.nl/cendef/upload/76/2001_Manson_Simplifying_Complexity.pdf

ICEBERGS, PATTERNS, AND SYSTEMS

Derived from the Dutch word ijsberg (ice mountain), an iceberg is a large mass of freshwater ice that floats freely in open water.  The expression “tip of the iceberg” is applied to a perceived event or situation that is believed to be only a small manifestation of something much larger and often hidden.   An iceberg metaphor has been widely applied including to the architecture of situations, experiences and cognitive processes.

The prevailing cognitive approach to understand an event or situation is analysis.  Derived from the ancient Greek word análusis(break down, unravel), the analytic process has three steps: 1. Take the situation apart; 2. Understand (function, role, behavior) what the parts do; 3. Assemble the understanding of the parts into understanding of the whole. 

The mindset or world view of analysis and its iceberg analogy is that a situation, challenge or problem on the surface may seem to be minor, but hidden below may be large and difficult.  To understand or address the situation, one can deconstruct it.  Since the whole problem is considered to be equal to the sum of its parts, a rigorously conducted diagnosis will lead to understanding that one or more independent causes are at the root of the whole problem.   Another assumption is that by changing or improving one or more of the root causes, a solution will result. 

Snowdon and Boone (2007)[1] argue that one size does not fit all; there are different kinds of situations or contexts, and different perspectives and responses needed to effectively understand and navigate them.  According to the Cynefin framework (from the Welsh meaning habitat or place), an analytic-root-cause approach is appropriate for situations that are complicated because in such situations the many unknowns can be identified, understood and managed with expert knowledge and skills.  After clearly defining the situation, applying diagnosis for causes, an evidence-based set of best practices may be implemented and can be expected to remedy the symptoms and to solve the problem. 

Complex situations, however, are characterized by unknown unknowns such that the whole problem and its risks cannot be fully defined.  Some characteristics may be dynamic and change in unpredictable ways, and little relationship may exist between causes and effects.  When a context, situation, opportunity or challenge is volatile, uncertain, complex and/or ambiguous (VUCA), a better cognitive approach is systems thinking. 

Derived from the Greek word, súnthesis, meaning to put together or combine, systems thinking applies synthesis.  The steps of systems thinking are opposite to those of analytic thinking: 1. Rather than deconstruct, expand the situation to its containing systems; 2. Rather than understand behavior and properties of the parts, understand the behavior of the whole containing system; 3. Rather than understand how the parts fit together, identify and understand how the situation you are trying to understand fits within the whole system in which it is contained.  The mindset or worldview of systems thinking is expansionism.  The focus is on relationships and interactions among events, situations and experiences. 

The systems approach has also been portrayed with an iceberg metaphor.  In this architecture, a surface event or situation may be perceived, and below are the cognitive processes that provide how one gains its meaning.  This begins when it is connected to other events to form a pattern.   When one recognizes associations among two or more patterns, a template or structure is acknowledged.   Structures are supported by deeply embedded mental models – representations of the world based on personal experiences, organizational and social beliefs, values, and expectations - that influence reasoning.  

Pattern Recognition and Errors

Systems thinking and its metaphors posit that a single perception may have little independent meaning and may be ignored as noise.  It is when at least two situations are associated, i.e., connected as a pattern, that we become attentive to the meaning of a possible relationship between events, objects, people, and ideas.  When we connect events into a pattern we transform the scattered and seemingly unrelated pieces of information into a meaningful image or situation.  As there are millions of events, there are many millions of such relationships and of “patterns of patterns” (structures) that far exceed the sum of the parts.   Michael Shermer (2011)[2] defines patternicity as the tendency to perceive meaningful patterns in the scattered elements and events of the environment.  He notes that our brains are hard-wired to be “evolved pattern-recognition machines that connect the dots and create meaning out of the patterns we think we see in nature” (p. 59).

While we may be developmentally predisposed to see patterns, it is not always easy to identify, describe or understand what we experience.  In other words, to perceive a pattern, we must first collect the appropriate dots from the scattered facts, events, relationships, meanings, and interpretations (Libicki & Pfleeger, 2004).[3]  Some events and information may be withheld purposefully by others to retain power or because the holder is not aware of the informational relevance.  Surface information may also be in a poor state of articulation; one may recognize intuitively that something is occurring, but may be unclear about its importance.   This means that meaningful pattern recognition may not occur until enough information of certain types and configurations are perceived, or until additional similar or supporting connections can be identified. 

Shermer (2011) argues that we have a second evolved cognitive process which he calls agenticity, the tendency to infuse patterns not merely with meaning but with purpose or intention.  He cites research that evolved neural networks allow us to be sensitive to the mental states and desires of others and to determine their intentions in order to plan goal-directed actions and responses. 

Seeing a pattern when it exists is important, but for some the perception of inter-connectivity may be symptomatic of mental illness.  Described in 1958 by Conrad (in Brugger, 2001),[4] apophenia is the clinical diagnosis of finding abnormal meaning or significance in random experiences.  Brugger described apophenia as the "pervasive tendency … to see order in random configurations … an unmotivated seeing of connections … the experience of delusion as revelation … and the tendency to be overwhelmed by meaningful coincidences." 

The extension of agenticity into clinical illness is pareidolia the misperception of a vague or obscure stimulus into something clear, distinct and personal. Examples include perceiving the face of Jesus in the discolorations of a burnt tortilla,[5] the image of Mother Teresa in the folds of a cinnamon bun,[6] or the image of Vladimir Lenin in the soap scum of a shower curtain.[7]   Perceiving that a pattern of lights in the sky is an alien spaceship from Planet J1407B may be apophenia; that you have been personally selected to be Planet Earth’s special envoy is probably pareidolia.

Despite the assertion that we have evolved into “pattern-recognition machines” and apart from those with evidence of clinical illness, pattern recognition cognitive processes and associated decisions of many people are often in error.  Consider the following: You become aware that a colleague with whom you are working on a project (and who reports to the same supervisor as you) is suddenly no longer employed at the organization.  You also learn that among the many activities and events requiring your participation on this day, an appointment with your supervisor has been unexpectedly scheduled for you.

If the sudden appointment with the supervisor is not related to the loss of your colleague’s job or to retaining your job, but you perceive a connection or pattern such that you anticipate you may be laid off, you would be making a Type I error: a false positive, perceiving a pattern when it does not exist.  When the perceived cost of an error is high (missing a real pattern of threat or danger can be very serious), most people will tend to be safe by responding as if a pattern exists.   Therefore, most people make many Type I errors of commission.  They perceive connections between situations; they lump together many possible relationships into patterns of events and activities some with personal purposes. 

If the scheduled appointment is a signal that you are about to be informed that your position has been eliminated, but you perceive no connection or pattern and treat the upcoming meeting as innocuous, you would be making a Type II error:  a false negative, not recognizing a real pattern when it exists.  Type II errors of omission occur for many reasons including that one may be cognitively naïve.  Others may miss a real pattern because relevant information is withheld or there is inadequate sharing or the noise of massive amounts of information is so great it overwhelms detection of a signal.  The true pattern may be missed when there are multiple and conflicting patterns perceived from the same set of collected dots and when the templates/structures one applies based on previous personal experience may be inadequate or misleading.    

As discussed previously, context is relevant to pattern recognition: In epidemiology and in military affairs the operating situation is expected to be volatile, uncertain, complex and ambiguous.  Health investigators and military counter-terrorism personnel anticipate that information may be difficult to collect or connect, in some cases because of purposeful deception.  The current business environment is similar.  It is characterized by increasingly dynamic complexity[8] with increasing rate of change, widespread connectivity, globalization, and innovation.  Sudden disruptions occur despite well-formulated planning and without obvious anomalies in key performance indicators. 

Cognitive Capacity and Competencies

The cognitive capacity to detect patterns early and accurately when they exist offers advantages for organizational effectiveness and survival similar to its human developmental value.[9]   But challenges abound in the form of Type I and Type II errors resulting in ineffective decisions and poor performance.   Notwithstanding these, another significant reason for poor pattern recognition may be because the mindset or worldview of the person attempting to connect the dots is not up to the challenge.  In 1994, Henry Mintzberg wrote[10] that strategic thinking is more about synthesis (i.e., "connecting the dots") than analysis (i.e., "finding the dots").  Ram Charon (2008)[11] agreed: "When a leader tries to connect the dots, linear, analytic thinking is useful and important, but sometimes it’s incomplete.  Leaders of substance can take mental leaps in order to make sense of incomplete or seemingly unrelated pieces of information.  They can use their imaginations and go beyond charts and graphs to connect the dots (p. 49)."

How are such leaps for sense-making done in the dynamic and complex environment?  The pathway seems to be with improved systems thinking capacities and competencies.  To the already powerful analytic approaches and tools should be added an equally powerful systems thinking competency in order to enable a more complete understanding of an organizational challenge or opportunity and to make available more methodologies for addressing them. 

Executive education in systems thinking and pattern recognition are needed immediately.  One reason is that those entering the workplace from the US education system are not adequately acquiring the cognitive processes relevant to operate in the complex environment.  Bloom (2010)[12] noted that the US continues to lag behind many other countries in student achievement in reading, writing, mathematics, science and other areas because the processes of learning are limited in relevance, meaning and applicability.  He calls for an educational redesign that includes systems thinking, pattern thinking and abductive (design) thinking.  In higher education, there are also challenges.  Too often programs teach by presenting cases of how problems encountered by people and organizations were addressed based on the analytic assumption that a best practice can be identified and followed.  To improve systems thinking and pattern recognition, to increase the number of recognizable patterns of patterns/structures, and to broaden mental models, there should be more effort and content devoted to learning how to recognize unusual, unexpected and paradoxical patterns, and how to cope with new, unanticipated and uncharacteristic events.   

In a proposal submitted to the US Army Research Institute which was soliciting ways to measure systems thinking in order to improve the competencies and capacities of the Department of Defense cyber (security) workforce, Blane Després (2014) noted, "Systems thinking … is often described as a capacity to connect dots, see patterns and structures that may be outside the usual scope of vision.  It is described as a framework in which the whole is greater than the sum of its “obvious” parts (p. 8)."[13] 

To improve pattern recognition there must be increased cognitive capacity, competency, understanding and application of systems thinking taught in an environment that integrates cognitive learning, action learning, and reflective learning.   

 

References and Notes

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[1] Snowdon, D. L. and Boone, M. . 2007. A leader’s framework for decision making.  Harvard Business Review: https://hbr.org/2007/11/a-leaders-framework-for-decision-making

[2] Shermer, M. 2011. The believing brain: From ghosts to gods to politics and conspiracies – How we construct beliefs and reinforce them as truths. New York: Times Books

 

[3] Libicki, M. C. and Pfleeger, S. L. 2004. Collecting the dots: Problem formulation and solution elements.  Occasional Paper OP-103-RC. Santa Monica, CA: RAND Corp.

 

[4] Brugger, P. 2001. From haunted brain to haunted science: A cognitive neuroscience view of paranormal and pseudoscientific thought, in J. Houran and R. Lange (Eds), Hauntings and Poltergeists: Multidisciplinary Perspectives. North Carolina: McFarland & Company, Inc. Publishers.

 

[5] http://www.roadsideamerica.com/story/10166

 

[6] http://www.indiana.edu/~jkkteach/P335/nunbun.html

 

[7] http://www.badastronomy.com/bad/misc/lenin.html

 

[8] Pourdehnad, J. and Starr, L.  2014. Rethinking executive education: A program for responding to sudden disruptions caused by dynamic complexity.  University of Pennsylvania Scholarly Commons, #14-03: http://repository.upenn.edu/od_working_papers/22/

 

[9] Cook, C. L. 2012. A review of Michael Shermer, The believing brain: From ghosts to gods to politics and conspiracies – How we construct beliefs and reinforce them as truths. Evolutionary Psychology, 10(1): 29-34.  See also Hastelton & Buss (2000) and Haselton & Funder (2006).

 

[10] Mintzberg, H. 1994. The fall and rise of strategic planning, Harvard Business Review: https://hbr.org/1994/01/the-fall-and-rise-of-strategic-planning/ar/1

 

[11] Charon, R.  2008. Developing leaders of substance (pp 45-50).  In James L. Noel and David L. Dotlich (Eds), The 2008 Pfeiffer Annual Leadership Development. San Francisco: Wiley.

 

[12] Bloom, J. W. 2010. Systems thinking, pattern thinking, and abductive thinking as the key elements of complex learning. Paper presented to the annual meeting of the American Educational Research Association, Denver, CO, May.

 

[13] Després, B. 2014. Systems thinking and its measure: Using the FoRSE Matrix: A proposal to the US Army Research Institute, July.

 

 

 

 

RETHINKING EXECUTIVE EDUCATION: A PROGRAM FOR RESPONDING TO SUDDEN DISRUPTIONS CAUSED BY DYNAMIC COMPLEXITY

John Pourdehnad and I have been writing about and teaching how to help people to understand and more accruately formulate organizational problems, challenges and opportunities, and to make better decisions.  We believe these lead to improved individual and organizational performance. 

For the past few years, we have been particularly attentive to the impact on decision making and performance of dynamic complexity.  We believe that executive education programs – those offered by academic and professional groups, and in graduate degree programs - are inadequate for the present business environment which is characterized by increasingly dynamic complexity characterized by increasing rate of change, widespread connectivity, globalization, and innovation.   While many education programs acknowledge that sudden disruptions occur and that environments may be VUCA – volatile, uncertain, complex and ambiguous - the recommended approach is to apply a well-formulated strategy conceived through advance planning as a means of “controlling complexity.” 

We hold that complexity cannot be controlled. Rather, preparation of leaders should be based on two underlying propositions:

 1: Each state of dynamic complexity is unique and requires unique responses.  A standardized checklist, algorithm or preformed set of procedures or processes is inadequate. 

 2: Proficiency to generate appropriate responses and navigate dynamic complexity is an art, an expression of creative competencies and imagination, based on rapid integration and deployment of a portfolio of competences and capacities.   

 Acknowledging that a single person may be responsible for a critical decision does not mean that proficiency is a unitary or singular attribute.  Indeed, we believe that proficiency to make effective decisions for improved performance in dynamic complexity is a property that emerges from the interaction of five elements: relevant skills; accessing previous experiences; accurate knowledge and understanding of the situation; practical wisdom and sound judgment;, and leadership attributes.  Each is explained.

Relevant skills refer to cognitive and performance abilities that are domain-general and domain-specific.  General skills include collaboration, cooperation and communication; specific skills include use of specific software or technology in response to relevant stimuli or in appropriate environments.  These include the ability and willingness to develop new platforms for opportunity beyond the current horizon as well as the diversity of talent and resources necessary to envision that world before those events actually occur.

Accessing experience refers to recalling from memory requisite and relevant past experiences that apply to the current situation but not to be hamstrung by them.  Accessing these requires that the decision maker has accumulated over time and in varied circumstances through conceptual/intellectual learning, experimentation/action learning, and reflection/emotional learning a broad set of experiences from which to draw when confronted with sudden dynamic complexity.  

Knowledge and understanding of the situation lead to efficiency compared to effectiveness (which is efficiency multiplied by measured value).   We propose that the accuracy of perceiving a situation characterized by turbulence is significantly increased when using an appropriate perception model and methodology.  Leaders in the Internet Century⁹ must be comfortable with its messiness and uncertainties and be able to identify emergent phenomena and the linkage they have or do not have with the current system and business model.

Practical wisdom and sound judgment refer to an intellectual and moral virtue that ensures selection of the right end by the right means – cognitively and behaviorally - across situational contexts.  Unlike a state of science but similar to art, it is concerned with both producing outcomes and with the experience of doing the action itself.  It includes study of humanities in addition to technology.

Leadership attributes are the individual capacities, competencies, styles, traits and states that are sought and developed for leadership.  Over the centuries, thousands of philosophers, researchers, practitioners, and writers of military, political, human drama, and more have offered theories and models which in thousands of books, education programs and training workshops purport to improve leadership decision making and performance.  For dynamic complexity, few of these are relevant, and none alone is sufficient for the new era of business and the thinking approaches it requires.  As Peter Drucker noted, the new knowledge worker requires a new cognitive and social tool kit.

Based on the above, we have created and tested in the US and abroad a model which underlies a new executive education program for making effective decisions for improved performance in dynamic complexity.  The model depicts a multi-layered approach to executive education.  It displays how the ability to rapidly assimilate, sort through, and comprehend vast amounts of data/information in order to make the right decisions depends on approaches to learning, knowledge of critical concepts particularly systems thinking as a mindset/filter, and knowledge of enabling IT.   It constantly asks the participant to recalibrate and adjust to unforeseen circumstances and to corporate assaults on the status quo.

For an expanded version of the ideas and outcomes expressed here, see the Position Paper by John Pourdehnad and Larry M. Starr available here: http://repository.upenn.edu/od_working_papers/22/