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The art and science of the possible

Category Archives: problem solving

It all depends: the art of problem solving

10 Friday May 2013

Posted by lnedelescu in consulting, design thinking, innovation, knowledge, learning, paradox, problem solving

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Chaos, complexity, Consulting, Dave Snowden, Disruption, Entrepreneurship, Globalization, Innovation, Intractable Problems, Introspection, Knowledge, Learning, Methodology, Open Mind, Relativity, Risk, Roger Martin, Russell Ackoff, Self-Awareness, Wicked Problems

It all Depends

Over the last decade, I’ve lived globalization, entrepreneurship, change and crisis, complexity and chaos. I must have run into at least a dozen intractable, impossible, show-stopper, nerve-racking, all-or-nothing situations and at least several orders higher magnitude wicked problems. I also ran into the entire spectrum of human behavior, what the Clint Eastwood character would call the “good, the bad, and the ugly” (I would actually add the “irrational”).

About five years ago I also started an in depth study of the cutting edge thinking related to complexity and disorder. Finally I also studied and noted my own behaviors and responses in such circumstances; like Hansel and Gretel I traced my steps into the wilderness in case I ever had to find my way back. This ability to not only act but rationalize the act has served me well, substantially increasing my awareness and lowering my stress when faced with the new and unfamiliar. It has also resulted in a problem solving and sense-making body of work which I think rivals the best of what’s available on the market. I have yet to capitalize on all this, but I have learned to be patient.

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A visualization of “discontinuous evolution”

08 Wednesday May 2013

Posted by lnedelescu in complexity, design thinking, knowledge, management, Organizational Development, problem solving

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complexity, Discontinuous Change, Innovation, management, phase transitions, strategy

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In my blog entry arguing for a unified theory of management, I proposed that most top management reference a fundamental distinction between exploration of new knowledge (i.e. innovation) and exploitation of existing knowledge (i.e. efficient operations).

Business and indeed the entire society is caught in an evolutionary dynamic that balances exploration and exploitation – see David Hurst’s ecological perspective. While the exploitation cycle is amenable to incremental thinking, exploration appears to be prone to discontinuities – hard to predict leaps of logic.

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A brief modern history of future predictions: engineers vs. social scientists

23 Tuesday Apr 2013

Posted by lnedelescu in complexity, future, problem solving, society

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Club of Rome, Cold War, Consumerism, Drucker, future, management, Management Cybernetics, philosophy, Philosophy of Science, Quantitative vs. Qualitative Predictions, Social Science, Society, Stafford Beer, System Dynamics, Toffler

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At the height of the Cold War predicting the future become serious business. A nuclear World War III was a real possibility and a literally cold and dark planet awash in radioactive ash a likely prospect. But communism wasn’t the only threat to the free world. Ideology aside, consumerism coupled with energy shortages and population growth provided good reason for questioning the very sustainability of our civilization. Ironically, communist propaganda pointed precisely to greed as capitalism’s Achilles heel.

So it isn’t surprising that by the 1970’s two schools of thought were already embarking on predicting the future. Since I have not come across this type of distinction between “futurists” in literature, I will proceed to describe it here. It is worth noting that by “distinction” I don’t mean opposition since both schools of thought can be regarded as members of the larger umbrella of systems thinkers.

First let’s loosely define the “engineers”, or better said, the engineering school of thought. Engineering had proven successful in World War II for a number of inventions, including rocket control systems. While Wernher Von Braun was working hard on getting us to the Moon, geniuses of the likes of Jay Forrester and Stafford Beer saw other uses for rocket control theory. Namely they had the insight to apply engineering thinking, particularly the mechanism of feedback, to social systems. This resulted, respectively, in the birth of two entirely new disciplines: system dynamics and management cybernetics. In parallel, Mihajlo Mesarovic, also an engineer emeritus with whom I’ve had the privilege of taking a graduate course at Case Western Reserve University, was also working on an elaborate mathematical model to predict the future state of the world. The Club of Rome, a new organization with an interest in humanity’s fate, saw the opportunity for these new methods to lend a degree of rigorousness to their own predictions about humanity’s long term future. This resulted in several publications in the early 1970’s. Limits to Growth and Mankind at the Turning Point received widespread attention since they discussed the “predicament of mankind”. The underlying belief of the engineering school of thought was that given a sophisticated enough computer model, the future could be more of less “mathematically” derived. Perhaps not surprisingly The Limits to Growth report was first introduced at a symposium in St. Gallen Switzerland, which remains a powerhouse for management cybernetics – Fredmund Malik and his consultancy continuing to this day the work started by Stafford Beer.  In essence Limits to Growth painted a pessimistic view for the world future where shortages were likely to stop and even revert human progress. Simply put, the Club of Rome’s prediction for the early 21st century, largely based in engineering thinking, spelled disaster.

At about the same time, a number of futurists emerged from the direction of the social sciences. Peter Drucker, Alvin Toffler, Charles Handy and others were by no means engineers and were not using models, at least not in the quantitative sense; however, this did not discourage them from looking into the future. The term that Peter Drucker eventually chose to describe himself, “social ecologist”, captures well this entire breed of futurists. What these futurists were is astute observers of the human condition and social ecology, the same “tools” employed by the ancient Greek philosophers whose insights still form the basis of western culture. Drucker and his peers did not use quantitative methods but made predictions derived from qualitative insights at the intersection of human psychology, technology and social constructs. Many of those predictions are still relevant today while predictions presented by the engineering school of thought had to be dismissed or significantly adjusted. In all fairness, in the Club of Rome’s 2012 update to the Limits to Growth, “2052 – A Global Forecast for the Next Forty Years”,  they have moved considerably away from hard quantifiable predictions. They have also moved in the direction of the social, describing their latest work as “educated guesses, combining data, modelling and hard science with an understanding of human nature and its systems and intuitions”.

Per this latest evidence, the two schools of thought can be said to be converging. Perhaps the best insight to be derived from the distinction presented in this piece is that we have much work to do in reconciling natural and social sciences. Until we do, and possibly even after, predicting the future will remain messy business. Elliott Jaques and Ilya Prigogine come to mind as two exponents of the social and respectively natural sciences that have made significant strides in reducing the divide between the two paradigms. I have always said that the universe preceded humans and so, the fact that we glean it through the reductionist lens of separate sciences suits our own convenience more than cosmological reality.

What about our ability to predict the future? Is it a legitimate undertaking or modern alchemy? Is the future clearly discernible through the lens of an all encompassing computer model, or does Lorenz’s and Feingenbaum’s Chaos Theory with its Butterfly Effect render any attempt at prediction hopeless? I would dare say that the work of Drucker, Toffler, and Handy among others has addressed both assertions: exact predictions of the future based in quantitative methods is indeed a hopeless undertaking, but a broad, nonspecific peak at the future is possible through the lens of qualitative thinking anchored in the constancy of human nature. But here’s the catch: only a select few appear to have the capacity for this type of undertaking, and they certainly aren’t employing a repeatable process or “best practice” in doing so. For the time being it appears that staring into the future is more art and science.

The Journey of an Idea: From Thought to Action

05 Tuesday Mar 2013

Posted by lnedelescu in problem solving

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Action, Design, Idea, Ideation, Innovation, Journey

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Have you ever thought how an idea takes shape and materializes? Here’s my personal experience!

The journey my ideas usually follow as they materialize into action is this: thought – explanation – visualization – implementation.

My ideas start as a fuzzy possibility in my mind. After an initial argument with myself, I usually find an interlocutor.

Discussion helps me to sharpen my own argument, forces me to come up with examples which drives associations. The ideal discussion partner walks the fine line between confrontation and participation.

In the course of the discussion, the examples I give in an effort to convince my counterpart often come associated with images. A nearby board and marker are often handy as I may use ad-hoc diagrams to make my points.

Following the discussion I usually take those incipient early diagrams and try to focus them to where I feel they capture the essence of the problem space associated with the idea. The first diagrams are usually notional, with subsequent diagrams adding concrete detail.

At the point where enough detail is present, an action plans naturally emerges. I am ready for implementation.

This process is neither linear nor smooth. There are qualitative discontinuities where, during any one of these steps I have “aha” moments where things suddenly and almost mysteriously connect. These become structural nodes in the idea’s architecture.

How to approach wicked, ill defined problems

17 Sunday Feb 2013

Posted by lnedelescu in complexity, problem solving

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causality, complexity, creative thinking, critical thinking, models, problem solving, relationships

I have been dealing with ill defined problems for quite some time.  In this post, I will try to capture the essence of my approach to wicked problems in a five step process.

1. ELEMENTS – THE BUILDING BLOCKS: mentally walk through or discuss scenarios associated with the problem and note key elements that pertain to the problem space as they emerge. At this point, elements can be loosely defined: it is better to have a larger list of elements that are vaguely defined than a smaller list of clearly defined elements.

2. LOGICAL CLARITY: conceptually strengthen the problem’s elements so as to reduce logical ambiguity. Explore and resolve overlaps, hierarchy. Categorize as much as possible. Reduce the original list of elements to the smallest possible set.

3. CAUSAL RELATIONSHIPS: walk through problem scenarios again, this time exploring the causal relationships between elements. This represents the “static” structural characterization of the problem.

4. MODEL: architect a model to capture the problem’s dynamics (the main difference between a static and dynamic characterization of the problem is the time dimension that exposes the evolution of the problem’s elements and their relationships). Validate the model by exercising a few “what-ifs” derived from the original scenarios. Based on the type of model that fits, categorize the problem type if possible.

5. EXPLORE: apply initial questions pertaining to the problem to the model and explore non-obvious insights. Exploring implications should increase the understanding of the problem.

In summary, the approach to wicked problem solving is: ELEMENTS – RELATIONSHIPS – DYNAMICS.  The more complex the problem, the more sophisticated the model, and more iterations likely required.

A key trick is that the process may not be followed sequentially; that is, one could jump between the various steps as necessary (for example, while working on the model in step #4, one may need to jump back to step #2 to additionally clarify a particular element, or to step #3 to re-evaluate a particular relationship).

Finally, the entire process requires a diversity of mental skills: creative thinking for scenario walk-through; critical thinking for logical strengthening; design thinking for model architecture.

How bureaucracies continue to grow or the second law of “organizational” thermodynamics

20 Thursday Dec 2012

Posted by lnedelescu in capitalism, democracy, future, human capital, management, Organizational Development, problem solving, society

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Behavior, bureaucracy, management, Organizational Development, thermodynamics

Is there a reason bureaucracies seem to always expand? Is there a reason why a committee that was set up to resolve a problem often time gets of life of its own and outlives the problem? Is there an organizational equivalent to the second law of thermodynamics in physics that says that the entropy or disorder of a system always tends to grow? What are the equivalent mechanics that fuel bureaucratic expansion?

I present in this blog entry a generic bureaucratic growth scenario that is inspired by real experiences. The scenario is organized in a number of steps and most steps are conceptually reinforced by the words of a few individuals who are held in high regard by society.

(Step 1) The bureaucracy’s leadership defines a grand and worthy-sounding vision that needs to be pursued.

Because the leaders don’t have a complete and clear understanding of all the implications of the vision they propose, there is usually some degree of ambiguity associated with an otherwise worthy-sounding pursuit. A sound vision requires a deep understanding of the context. And a prerequisite to understanding in complicated domains requires clear organization of the complete knowledge in that domain, or an ontology. But there are many bureaucracies which operate without an awareness of the total knowledge they are supposed to possess and manage. And there are many leaders within those bureaucracies who do not possess the understanding required. An applicable quote from Profession John Gero is: “ontologies provide a domain with a structure for the knowledge in that domain. Domains without ontologies are constantly inventing new terms for existing knowledge and find it difficult to develop foundations on which others can build.”

Nevertheless, even with an ambiguous or incomplete vision…

(Step 2) Planning the work to achieve the vision begins.

Because the true implications of the ambiguity and incompleteness of the vision are not thought-through, there is usually a disconnect between the vision and the time and budget allotted. This increases the pressure on executing the vision, decreasing the opportunity to question the context, the validity of the vision. Because the subordinates are judged by checking off the vision or goal, they concentrate on just that. In a strive for efficiency (get the product out, meet the deadline so we can check off the box) effectiveness (i.e. context) becomes skewed. An applicable quote from Peter Drucker is “efficiency is a matter of doing things right; effectiveness is a matter of doing the right things.” But doing the “right things” takes enough up-front thinking, and it also takes pushing back on a vision or goal that doesn’t make sense.

But it’s already too late for that…

(Step 3) The initiative/project/product gets a life of its own.

This happens because it starts being tracked in the operational systems of the bureaucracy. These are however by definition not designed to be sensitive to context. That is because context takes thinking, and it cannot be easily measured with simple metrics: there is no such thing as a kilogram of context. The chance for someone noticing a fault with the initial vision diminishes at this point exponentially. That is because these context-blind operational systems have a direct impact on the employee’s performance, and they don’t measure context and validity. So arguing that the work doesn’t make sense, can only get one in trouble, since “doesn’t make sense” is not something that operational systems track.

And so, Drucker’s “doing the right things” turns decisively into “doing things right”, or else!

(Step 4): The vision cannot be wrong!

The initiative/project/product is clearly out of tune with the initial vision. The results are just not conclusive and the output isn’t useful. But it has since acquired a life of its own, and even if its ineffectiveness is obvious, no one dares to take the blame for fear of punishment. The disconnect eventually becomes apparent to the leadership, but even the executives who initiated the vision don’t have the political courage or power to declare the vision erroneous.  Doing so would mean taking the blame for X millions/billions spent in vain. And so, attempts are made to fix the initiative/project/product from within rather than scrapping it altogether, acknowledging the financial loss, and re-examining the initial premises. The same thinking and methods that created the problem are used to attempt to correct it, which is a futile exercise. Albert Einstein has a powerful insight for this type of situation: “we can’t solve problems with the same type of thinking that was used to create them”.

(Step 5): Fear and stubbornness are good companions.

Stubbornly refusing to acknowledge blame and scrap the project, the organization continues to try to do the wrong thing righter. But Russell Ackoff rightly cautions against this approach:  “most large social systems are pursuing objectives other than the ones they proclaim, and the ones they pursue are wrong. They try to do the wrong thing righter, and this makes what they do wronger. It is much better to do the right thing wrong than the wrong thing right, because when errors are corrected, it makes doing the wrong thing wronger but the right thing righter”.

(Step 6): Outside intervention!

An outside intervention is eventually necessary, and this usually takes the incarnation of a new committee. New procedures and processes are set up to prevent this “type” of problem from occurring in the future. The new procedures and processes themselves get a life of their own and have to be maintained which means new job roles or at the very least new job responsibilities are added, and the bureaucracy expands.

(Step 7 and 1) A new bold vision is defined…

And the rest is…déjà-vu!

Manifesto against the “5 steps to [topic of your choice]” recipe to success

27 Saturday Oct 2012

Posted by lnedelescu in business, Communication, consulting, human capital, Organizational Development, problem solving, society

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business, business strategy, culture, personal success

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Let me start with a telling quote from Russell Ackoff: “the appeal of gurus lies to a large extent in the simplicity of the doctrines they put forth. They are simple no matter how complex the problems at which they are directed. They provide a life raft to those who are incapable of handling complexity.”

In today’s fast paced life, the “5 steps to…” recipe for success is pervasive. This type of headline template dominates both mass media and social media.

I will pick just one of the many examples to make a quick argument for the “5 steps to…” template being intellectual noise at best, and dangerous advice to follow at worst. One of the newly minted “thought leaders” on the LinkedIn social network recently posted the 6 lessons he lives by. Number one on his list is: “surround yourself with people who are smarter than you and move out of their way”. My assertion is that this basically tells us nothing. It is an incomplete statement devoid of context. It sounds great but doesn’t provide any meaningful path to wisdom.

I picked this one example because I usually take issue with the “people smarter than you” leadership anecdote. It’s insufficient in that it doesn’t tell what the leadership still adds to the mix. Your employees can be “smarter than you” in terms of information, knowledge, and even understanding. The leader still has to supply the wisdom, which is synthesized knowledge and understanding, and it is future oriented. Russell Ackoff proposes a clear hierarchy of mental content value going from data to information to knowledge to understanding and finally to wisdom, which is the hardest to acquire in life. These simple classifications of reality that start with “5 simple ways to…”, “the ten traits of…” and so forth are counterproductive to understanding the full beauty and complexity of life. In Ackoff’s words, they provide a false life raft. The modern world, not unlike the ancient world, is full of false prophets. The problem of calling their bluff remains.

Russell Ackoff: the Albert Einstein of Management

24 Wednesday Oct 2012

Posted by lnedelescu in consulting, knowledge, learning, management, problem solving, strategy

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Ackoff, business, Einstein, Leadership, Learning, management, problem solving, strategy

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Russell Ackoff is likely the Albert Einstein of management. The reasoning is this: he created what is in essence a Generalized Ontology of Problem Solving just as Einstein created the Generalized Theory of Relativity.

By comparison,  most management gurus, consulting principals and executives only master a special case problem solving heuristic. Lower level managers and consultants are only able to reproduce a priori defined special case problem solving algorithms.

Professor John Geto of Krasnow Institute of Advanced Study cautions that without an ontology we are liable to continually reinvent new terms for existing knowledge, making it difficult to achieve a strong foundation on which to build. Management in general and management consulting in particular can in large part be paraphrased as problem solving common sense; yet, the generalized problem solving ontology carefully crafted by the genius of Ackoff has not been widely adopted. In a hierarchy management masters Ackoff’s generalized and universal thinking pedestal is permanent and situated on significantly higher ground than the altars at which most of us currently worship: innovation and Clayton Christiansen, Design Thinking and Roger Martin, Gary Hamel and Management 2.0, etc.

As in the popular “Matrix” movies, Ackoff is “the one”. But, it appears we may need a Morpheus character like advocate within the management discipline. And we need to overcome our latest infatuation with progress only possible in teams; the Theory of General Relativity could not have been a crowd sourced innovation on Facebook. Sometimes it takes “the one”.

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