When to Simulate

In general, simulation modeling is useful for understanding complex relationships, for developing and testing specific policies, and for understanding the implications of long time delays on a problem or issue (see “When to Simulate,” April 1995). While these general guidelines give you a sense of why modeling can be useful, they don’t tell you when a particular problem you’re working on can benefit from simulation modeling.

That is why experienced practitioners watch for certain signals that indicate when it is time to move into simulation modeling. One such entry point is to listen for organizational “dilemmas.”

A “dilemma” occurs when a group is aware of multiple consequences of a policy or strategy, but there is no clear agreement around which consequence is strongest at what point in time. In such a situation—where there are strong passions around a specific issue and the organization or team is “stuck” at its current level of understanding—simulation modeling has the potential to be very effective. The following six-step process describes how modeling can be used to resolve such dilemmas.

1. Identify the Dilemma

The first step is to listen for situations where there are two different theories about the consequences of a decision (for more on this process, see “Using Systems Thinking ‘On-Line’: Listening for Multiple Hypotheses,” August 1995). Dilemmas are often characterized by one party strongly advocating for a decision or strategy, followed by public disagreement or private mumbling about how that action will cause just the opposite of the intended outcome.

For example, the plant management team of a major component supplier wanted to “load the plant”—that is, continually push sales in order to maximize the plant’s capacity usage. But others expressed concern that loading the plant might create other problems that would affect both quality and service.

2. Map the Theories

Once you have identified the dilemma, it is important to clarify the issues involved by explicitly mapping out each of the viewpoints using causal loop diagrams or systems archetypes. For example, in the plant capacity issue, the strategy behind loading the plant was to increase sales in order to maximize the capacity utilization of the plant, until the available capacity falls to zero and no more sales can be filled (B1 in “Theory 1: Loading the Plant”). The benefit of this strategy is twofold: by increasing sales, the plant will boost profits (R3); and by increasing the capacity utilization, the cost per unit will fall, which increases profits and allows more investment in plant capacity (B2).

However, other people felt strongly that if plant utilization remained too high, the ability to respond to customer changes (flexibility) would go down, eventually hurting the company’s reputation as a supplier and leading to a decline in sales (B4 in “Theory 2: Unintended Side-Effects”). They also believed that loading the plant would cause the stress level in the organization to rise, eventually eroding quality and further hurting their reputation (B5).

3. Assess Dynamic Complexity

Some situations of “multiple hypotheses” resolve themselves when the different parties work together to map out each story and find that one is clearly more accurate. But in cases where both sets of interconnections are plausible and the uncertainty or disagreement still exists, further work is needed to resolve the dilemma. If the uncertainty is simply around a number (such as accurate cost data) or the probability of one outcome versus another, it is a static problem and techniques such as decision analysis may be appropriate. Simulation modeling, on the other hand, is most effective where there is some degree of dynamic complexity—where the link between cause and effect is subtle and the implications over time are not obvious.

To check for dynamic complexity, ask if the uncertainty or disagreement is around what feedback loop is dominant at what time—in other words, the long-term impact might be different than the short-term effects. If this is the case, then some degree of dynamic complexity exists and it is appropriate to move into simulation modeling. In the manufacturing example, a key area of uncertainty was the effect of various capacity utilization strategies on the company’s reputation (and therefore sales) over time. The importance of this time delay indicated a degree of dynamic complexity that could benefit from a simulation approach.

4. Developing the Simulation Model

At this point, you are now ready to move into the development of the model. First, you want to focus the model-building effort by asking, “What do we need to learn in order to be able to resolve the dilemma?” Stating the objective up front will guide the rest of the process.

Once you have established your objective, you can define the boundaries of the simulation model by identifying the key decisions (critical policies that the organization makes), the important indicators (what you need to see from the system to assess the decision), and the uncertainties (most fragile assumptions about the relationships or outside world) associated with the dilemma.

In the capacity utilization example, the parties recognized that the dilemma would be resolved when they knew both the short- and long-term impact of different capacity utilizations on sales and profits. Their primary decision was to select a particular utilization goal (desired production relative to capacity), which could be assessed by looking at the long-term behavior of sales and reputation. The company’s key uncertainties included demand and customer sensitivity, because they didn’t know exactly how the market would evolve, and the impact of different utilizations depended heavily on their assumptions about the customer’s sensitivity to price, quality, and flexibility.

Once you have established the focus and boundaries of the model, you are ready to build the simulation model by defining the relationships between important variables, such as the relationship between manufacturing flexibility and reputation in our plant capacity example. (For more on the actual mechanics of model building, see “From Causal Loop Diagrams to Computer Models—Part II,” August 1994).

5. Divergence: Testing the Assumptions

Once you have built the model, you can begin testing the different assumptions behind your causal theories to see the effect of those interrelationships over time. At this stage, you are attempting to be divergent—trying out many possible scenarios, any of which can lead to new questions and experiments.

Using the simulator they had developed, the management team was able to test different capacity utilization levels, using various assumptions about the market and customer “sensitivity.” In the first scenario, the group made two simplifying assumptions: that there would be no change in overall market size, and that the organization could not build new capacity. They then ran the simulator, testing four different capacity utilization “goals”: 70%, 75%, 78%, and 82% of maximum possible capacity.

When they ran the simulation, they discovered that when the plant is running at 70% or 75% of its maximum capacity, it is able to maintain a set level of production. Bur at 78% or 82%, an unexpected oscillation occurred after a short period of time, the number of orders began to drop dramatically, and then gradually rebounded (see “Scenario 1” in “Capacity Utilization Scenarios”).

From these results, the group hypothesized that at higher capacity utilizations the plant is less flexible in meeting customer demands, which affects the company’s reputation and leads to a decline in sales. Once the number of orders falls below the utilization goal, the plant then has time to improve flexibility and quality. Over tune, its reputation and sales gradually rebound until once again it is in a situation with high capacity utilization but low flexibility — and the cycle begins again.

In the second scenario, the group tested the same four capacity utilization goals, but with new assumptions: that the market would grow steadily, and that the company would expand capacity when the forecasted demand exceeded the current capacity (sec “Scenario 21. To their surprise, when they ran this simulation, they found that a lower utilization goal actually leads to far more sales in the long run. From this they hypothesized that at a lower utilization, there is a greater unfilled demand, which leads to more optimistic forecasting and investment, more plant capacity, and a better reputation as a growing reliable supplier.

6. Convergence: Resolving the Dilemma

Testing various scenarios allows you to explore assumptions and gather data. But understanding more about behavior over time is only useful if it helps move toward resolution of the dilemma. Therefore, the divergent phase should be followed by a convergent phase, in which the group closes in on the policies that produce the most desirable short-term and long-term behavior for the most likely future scenarios.

In the plant capacity example, the team discovered that there was an optimal capacity utilization level, above which the organization created undesired oscillation. The resolution to their dilemma was to set capacity utilization at a level that balanced the need to load the plant with the need u, maintain flexibility and a high company reputation. In this case, the use of a simulation model enabled the team to productively address an issue that had been a long-standing dispute in the plant, and to develop a policy that was acceptable to all of the involved parties.

Don Seville is a research affiliate at the Mir Center for Organizational Learning and an associate with GKA Incorporated.

Many of these ideas emerged from conversations with Jack Homer of Horner Consulting. Inc., who also collaborated on the design of the model.

Editorial support for this article was provided by Colleen P. Lannon.

The post Entry Points to Modeling: Listening for “Dilemmas” appeared first on The Systems Thinker.

A shared commitment to act toward a compelling goal.

Why do I like it?

• First, it emphasizes that strategy is about action – not about analyzing, forecasting, writing papers, filling out forms, compiling spreadsheets, but about action.
• Second, it speaks of a shared commitment – the kind of commitment that management needs so that they continue to act as a team, even when things get tough.
• Third, it recognizes the importance of a compelling goal – the objective, that, when realized, brings vision into reality.

I recognize that the statement makes no declaration about what the goal should be or about what actions should be taken, but I ask that you ride with that gap for the moment — all will be revealed in due course. I also recognize that are many ways of building a shared commitment to act and of defining a good strategy. Scenario planning, which I will focus on, is just one of them.

Gods, Gamblers, Grinders, and Guides

All organizations have their own dominant beliefs, and top managers have their own styles. Some people believe, for example, that it is possible to predict the future (if not in general, then at least as far as their own organizations are concerned); others prefer to believe that the future is uncertain and that the journey into the future is one of exploration. As regards style, some leaders exercise very strong control, while others seek to empower those in their organizations (see “Four Leadership Styles”).

Strong, controlling leaders who believe they can predict the future are much like gods: Not only do they know what they want, they know best, too. You don’t have to read Homer to learn that any mortal who incites the wrath of an angry god soon has an uncomfortable time. Such leaders need no tools and techniques to formulate a strategy: They know. From time to time, they might actually be right.

Strong, controlling leaders who are less certain of their powers of prediction often behave like gamblers: They place a bet that the future will evolve in a certain way and, if it does, fine; if it doesn’t, well, let’s throw the dice again and see what happens a second time. Gamblers, too, need few tools and techniques, but they might like some financial analyses to give them a feel for the odds.

Empowerers who believe they can predict the future are convinced that, somewhere out there, the “right” strategic answer exists, if only they can find it. These are the grinders, managers who are forever grinding away on more analyses, more research, more numbers. These people love tools and techniques, with their five forces, their value chains, their PERTS, and their SWOTS.

In many cases, the most successful leaders may be those empowerers who choose to serve as guides: They seek to carefully steer their organizations through the uncertainties that the future will inevitably bring. How can they steer the safest course? Well, to do so, they need a map. The problem is that no such map can be found, for maps exist in space, not in time.

It is in this last arena that scenarios can help, for scenarios are stories describing how the future might evolve. Scenarios therefore do a similar job in time to that done by maps in space. But because the future might evolve in many ways, there are many possible scenarios, each of which represents one possible view of what might happen over the next five, 10, or 20 years. Importantly, the emphasis within each scenario is not on the internal aspects of the business, but rather on the external context in which the business might operate; robust scenarios depict the future in terms of politics, economics, sociology, demography, technology, and industrial structures.

By imagining what such a future might be, you can test whether or not a particular strategy for your own business will be beneficial, should that future indeed come to pass. And by explicitly recognizing that there might be several different futures, any one of which might happen, you can test your strategy against each and see if some strategies are more robust than others. In essence, scenario planning is a form of simulation: It is the business manager’s equivalent of the jet pilot’s flight simulator. The scenarios project you and your organization into the future, and provide a realistic, rich context in which you can examine whether or not particular strategies – the development of new products, the entry into new markets, or whatever – are likely to be successful.

Scenarios also serve to heighten your understanding of risk, so that when you put your strategy into action, you will be much more aware of how changes in the external environment are likely to impact your business. Then if you notice that the world is in fact evolving in a direction for which your strategy is less appropriate, you will be able to change course easily and quickly, far more so than your competitors, who may not have noticed what is going on, or, if they have, may continue for some time in a state of denial.

But how does scenario-based strategic planning – to give it its full name – actually work?

Scenario-Based Strategic Planning

Scenario-based strategic planning comprises two principal activities:

• First, the development of a small number of scenarios – say, up to five – each of which describes a different view of how a future world might look.
• Second, the agreement on a strategy – a set of actions that the organization is committed to take.

As indicated by “Scenario Development and Strategy Formation,” the process of scenario development is divergent and strives to embrace as broad as possible a view of how the future might evolve, in order to encompass the future’s inevitable uncertainties. This is done through a series of group workshops, supported by research, and the gathering of expert opinions. The purpose of the scenarios is to provide a series of backdrops against which different strategies can be assessed. Questions such as “Should we enter the [whatever] market?”, “What are the risks of making [whatever] investment?” and the like are tested against each of the scenarios. Participants assume that, yes, they do enter that market, and that, yes, they do make that investment, and then imagine that they and their organization are projected into each scenario 10 years into the future. They can then assess, using “projected hindsight,” whether or not those decisions were “good” or “bad.” By exploring various decisions against each scenario in this way, team members can then determine that set of decisions that they collectively feel most comfortable taking now and therefore converge upon an agreed strategy.

The following pages describe the process in more detail. First, we need to introduce and define three terms that have a special role in scenario planning: worlds, levers, and outcomes.

Worlds. A world is a comprehensive description of the context in which a business operates. Worlds are therefore described in terms of (often long!) lists of adjectives and adjectival phrases, describing all aspects of the world of interest, including the political, social, economic and regulatory structures, nature of market competition, technology, and all the rest.

SCENARIO DEVELOPMENT AND STRATEGY FORMATION

The process of scenario development is divergent and strives to embrace as broad as possible a view of how the future might evolve, in order to encompass the future’s inevitable uncertainties. The purpose of the scenarios is to provide a series of backdrops against which different strategies can be assessed. By exploring various decisions against each scenario in this way, team members can then determine that set of decisions that they collectively feel most comfortable taking now and therefore converge upon an agreed strategy.

The most familiar world is today’s world, and an important part of the scenario planning process is to come to a shared view of just what it is. Different people see different things, and some lively workshops can be run focused on describing today’s world. Ultimately, any description of today’s world must pass the Martian Test: If the description were e-mailed to a group of Martians approaching Earth, on stepping out of their saucer, they must be able to recognize where they have landed.

If today’s world is defined in terms of a long list of descriptive phrases, then, by definition, a different world must have a different list. A major milestone in scenario planning is to generate a small number of different worlds – three to five is usually sufficient – that have self-consistent descriptions. These worlds should be significantly different from one another, and from today’s world.

Some of the different worlds might appear favorable, others harsh; some may appear to be relatively likely, other less so; some might be desirable, others positively repulsive. At the moment, though, such issues aren’t important; all that matters is that any different world must be believed to be, in principle, possible.

Levers and Outcomes. Levers represent the actions and decisions that managers can take. For example, managers can determine product range, target markets, staffing levels, skills, investments in infrastructure, level of R&D, location of manufacturing sites, amount spent on advertising, and so on. At any time, each lever has a setting – the numeric amount associated with that lever.

Outcomes represent the commercial results of the organization: levels of sales and profit, reputation, share price, market share, staff morale, and so on. At any time, each outcome has a numeric value.

Fundamentally, the job of strategic management is to determine the levers and assign their settings, so as to generate desirable outcomes. As every manager soon learns, however, levers are not directly connected to outcomes; there simply is no lever to allow managers to directly control profit, market share, or share price. Rather, the levers that managers can actually pull are only indirectly, and sometimes rather loosely, coupled to the outcomes, and managers act in the belief – or hope – that by cutting costs here and increasing staff there, shareholder value will be increased. To make matters worse, time delays occur before any change in a lever setting begins to take effect.

This process is, as we all know too well, very complex. A powerful tool in taming this complexity is system dynamics modeling. This kind of simulation goes far beyond the typical spreadsheet and can handle loosely coupled variables, time lags, and feedback loops. (For a more complete definition of system dynamics, go to http://www.systemdynamics.org.)

The Rules of Innovation

Many people feel that inventing new worlds is difficult, fearing not only that they lack the expert knowledge, but also – and far worse – that they just don’t have the imagination. In fact, inventing new worlds is easy and a lot of fun, provided, of course, that you do it in the easy, fun way – and that is to borrow from the techniques of innovation.

Briefly, two of the key rules that make innovation deliberate, systematic, and safe are:

• Rule No. 1: Don’t try to leap directly into the unknown – start from something or somewhere you know well.
• Rule No. 2: New ideas are best generated not by waiting for lightning to strike, but by challenging assumptions and asking, “How might this be different?”

A simple but nonetheless startling example of these rules in action is the familiar nine dots puzzle (see “Nine Dots Puzzle”). There are two questions:

• How can you join all nine dots with four straight lines, without taking your pencil off the page?
• And if that is too easy, how many different ways can you find of joining all the dots with just one line?

Most people tackle the first question by picking up a pen and drawing various alternatives; they usually don’t even know where to start with the second question. But then most people don’t know the two rules of innovation. Picking up a pen, drawing, and trying to solve the puzzle by trial and error breaks the first rule – you’re leaping into the dark. The first rule says “Let’s understand all we can about the nine dots.” There are nine, they are in a square array, they are an inch or so apart, and they are about a quarter-inch square. The second rule says, “Challenge the assumptions.” Is the shape the dots form a square? What would happen if the dots weren’t an inch apart? They might be a mile apart or close together. But if they were close, I could wipe a felt-tip pen across all nine at once. So, if they’re an inch apart, I need a thick pen – maybe a paint roller. Ah yes, that’s it, a paint roller. And the puzzle is instantly solved.

Inventing New Worlds

The easiest way of inventing new worlds is therefore to apply the two key rules of innovation defined above. In the context of scenario planning, if we follow Rule No. 1, our starting point is something we all know well indeed, namely, today’s world. In fact, we take the time to define today’s world not only to build a genuine, deeply shared view of where we are, but also as a springboard to innovation.

One observation about today’s world might be that “the current industrial structure is consolidating.” Rule No. 2 requires us to challenge assumptions and ask, “How might this be different?” How might the industrial structure be different? Well, perhaps it will concentrate even further into a global monopoly; perhaps it will fragment as a result of government intervention; perhaps new entrants will come in on the back of a new technology.

Applying Rule No. 2 thus results in many alternative possibilities. As a group begins to list these potential futures, people start associating characteristics together, so that a small number of self-consistent worlds emerge, each with its appropriate set of descriptions. Created by a process of deliberate challenge and deliberate and systematic innovation, these descriptions will be very different from today’s world. When you are in the middle of the process, it can appear to be something of a muddle, with hundreds of post-its all over the walls. But rest assured that it works: The human mind is quite adept at seeing patterns. Just as the solution to the nine dots puzzle emerged, seemingly out of nowhere, so the process of challenge, coupled with the interactions of a group and the human ability to see patterns, will create a compelling series of new worlds.

“Scenario Planning Summary” forms the heart of a scenario planning exercise. Each column represents a different world, the first being today’s world. The often extensive descriptions of each world are incorporated in the first row. The levers are named in the title box of the second row, and the corresponding lever settings are identified in the appropriate column. Similarly, the outcomes are named in the title box of the third row, and the outcome values, for the defined lever settings in each world, are assessed and entered into each column.

The question then becomes, What are the lever settings and what new levers might be required to give favorable outcomes in as many of the worlds as possible? Once the most favorable set of levers and lever settings have been determined, then your strategy is that set of managerial actions required to move the levers from their current settings to the desired ones.

Testing the Levers

By now, you will have:

• Defined today’s world.
• Defined up to five alternative worlds.
• Defined the levers and the outcomes.
• Seen how the lever settings in today’s world generate today’s outcome values.

It is at this point that the scenarios themselves are written, each scenario being a vivid story describing how each of the alternative new worlds evolved, in its own particular way, from today’s world. Well-written scenarios capture your imagination and are powerful vehicles for communication and training. Immersing yourself in the scenarios builds “a memory of the future,” so that as time passes and the future becomes reality, you recognize what you see. But the scenarios themselves are not the end of the exercise: The purpose of the scenarios, and the alternative worlds they describe, is to form a context in which your business might operate in the future.

To test out this method:

• Imagine that the levers and their settings are the same as in today’s world. What will the outcome values be in the different worlds? Are they favorable or unfavorable?
• If the outcome values in any alternative world are unfavorable, what would the lever settings have be to give rise to favorable outcomes? Do you need to invoke any new levers?

This process is best carried out through group discussion; it can also be supported by modeling and specific, well-focused analysis. The objective is to examine how robust different lever settings are to future uncertainty. Suppose, for example, you decide that the current lever settings give favorable outcome values in just one of the alternative future worlds. That analysis implies that, if you leave the lever settings as they are and that particular future does indeed come to pass, your business is likely to be successful. But if the future were to evolve toward any of the other worlds, things might not be so rosy.

Turning Scenarios into Strategy

As a result of the exploration of the lever settings in the various worlds, you will discover one of a number of things, for example, that:

• The current levers, and their settings, are indeed robust under future worlds, or
• The current levers, and their settings, are not robust under future worlds, or
• Some different lever settings are robust under many of the future worlds, including today’s world; or there are no lever settings that work well under many worlds, but several clusters of settings that work well in some worlds but not others; or there are no generally safe lever settings – each world has its own.

These insights are guides to strategy. How so? Let’s go back to our definition of strategy: a shared commitment to act toward a compelling goal.

A shared commitment to take what specific actions, toward which particular goal? Well:

• The goal must be defined in relation to one or more of the worlds, and
• The actions must be to move existing levers to new settings or to deploy new levers.

The process of strategy development is therefore that of deciding which levers need to be placed at what settings. And the strategy itself is the set of actions you decide to take to move the levers from their current settings to their new ones.

Scenario-based strategic planning has the objective of providing a framework to enable managers to make strategic decisions (see “The Scenario-Based Strategic Planning Process”). These decisions can relate only to levers and their settings; managers, quite literally, can do little else. As we all know, the problem with resetting the levers is that some of them are difficult to reset; some, once reset, cannot be reversed to their original settings; many require a long time to reset; and, once settings have been reset, it may be a long time before the results are actually achieved—time during which the world is fast evolving, often in such a way as to make the new settings no longer fit for their originally conceived purpose.

THE SCENARIO-BASED STRATEGIC PLANNING PROCESS

Scenario-based strategic planning has the objective of providing a framework to enable managers to make strategic decisions. As such, it comprises a number of activities, beginning with defining today’s world and the range of actions that managers can take to creating scenarios of different possible worlds to testing levers in different settings and, finally, identifying effective actions.

But the levers must be reset from time to time. Doing nothing, and so betting that the world will stay still, is often a worse bet than taking a gamble on one particular future. The process is exciting, challenging, stimulating, exhausting, amazing – and, most importantly, it works.

Dennis Sherwood is the author of nine books, including Seeing the Forest for the Trees: A Manager’s Guide to Applying Systems Thinking, Smart Things to Know About Innovation, and Unlock Your Mind. For 12 years, he was a consulting partner with Coopers & Lybrand and was subsequently an executive director at Goldman Sachs in London, a partner in Bossard Consultants, and vice president of SRI Consulting. He is currently with the Silver Bullet Machine Manufacturing Company. Dennis was educated at the Universities of Cambridge, Yale, and California, and is a Sloan Fellow, with distinction, of the London Business School. He is a well-known speaker at conferences, has written many journal articles, and has appeared on BBC Radio 4’s programs In Business, Shoptalk, and Nice Work.

The post Turning Innovative Scenarios into Robust Strategies appeared first on The Systems Thinker.

We live in an age of paradox, with every trend seemingly matched by a counter-trend.

These dynamics have helped to reshape the world well beyond the sphere of commerce alone. Our newspapers today are filled with momentous and as yet unanswered questions. Are we facing a terrifying “clash of civilizations”? Can China maintain its extraordinary growth as a major global power or will its internal political, social, economic, and environmental tensions lead to implosion? Is aging, polarizing Europe in terminal decline or on the brink of its next renaissance? Will technology standards globalize and converge, or regionalize and fragment? Will free trade continue to override growing protectionist instincts? Are we on the brink of a new flu pandemic and, if so, how severe will it be? How fast, and how dramatic, will climate change prove? With entirely new business models being forged by mighty upstarts like Google and eBay, do we even know where our competition lies? There are two additional twists that can be thrown into this mix. First, we live in an age of paradox, with every trend seemingly matched by a counter-trend. For example, the economy is becoming increasingly intangible as we sharpen our focus on services, experiences, and virtualization, yet the physical economy matters more and more with the need to update critical infrastructure. The Nobel prize-winning physicist Niels Bohr summed up this tension well when he wrote:, “The opposite of a correct statement is a false statement. The opposite of a profound truth may well be another profound truth.”

Second, information is ubiquitous and instantaneous. What is “known” is a diminishing source of competitive advantage, so successful futures will increasingly be forged through mastery of the unknown.

Yet paradox and the unknown are uncomfortable. Most of us have learned to present our bosses with answers and solutions, not questions and problems. But by adopting this approach and sticking to certain tried and tested strategies, we run the risk of using counterproductive coping mechanisms and ultimately moving backwards, rather than forwards. For example, we might try to:

• • Increase Control Through Centralization and Bureaucracy. Yet, was it really hard to predict that the formation of the U. S. Department of Homeland Security was unlikely to improve the effectiveness of any of the agencies swept under its monolithic umbrella?
  • Escape into “Busyness.”Are we becoming addicted to endless, relentless activity – empowered by the ubiquitous “Crackberries” and reinforced through constant, often unproductive meetings?All this motion seems to stem, at least in part, from a subconscious desire to avoid the discomfort of sitting in the mess and ambiguity of our times.
  • Rely on Metrics.But does boiling down the complexity of business realities into a few key numbers sometimes end up driving rather than measuring performance? As Einstein observed:, “Not everything that can be counted counts, and not everything that counts can be counted.”

• Look for Scapegoats. Do we too often apportion blame and punish others for failures that may have been inevitable?The highest-level victims of this syndrome have been CEOs – turnover at the top has never been higher as executives face intense pressure to achieve guaranteed short-term results in a volatile, uncertain world.

  The effect of all this is that uncertainty can prevent the very learning that it so profoundly requires. The western ideals of secular modernity are based upon core concepts of certainty, such as empiricism, rationality, objectivity, analysis, and measurement. These remain critical values, but they are only part of our future and must be integrated with ways of thinking that rely as heavily on intuition, collective insight, emotional and spiritual intelligence, morality, and wisdom. This will be a difficult journey, especially for the traditionally hard-headed world of business. But, provided they can embrace and understand uncertainty, corporations are well positioned to establish new paradigms of human organization and learning.

How might we proceed? Following are six concepts that every business should consider. Each requires consistent effort and commitment, but none involves rocket science or prohibitive expense.

Create a Dialogue Between Risk and Opportunity

Thirty years ago, it was commonplace for a company’s product development activity to be housed in silos that were insulated from sales and marketing groups. How could we have been so misguided? Yet most businesses replicate this error today by separating the functions of risk management from business innovation and development. Both activities are at the forefront of exploring uncertainty. Great opportunity can be found in the most “risky” areas, while new risks emerge from every innovative corporate endeavor. Bringing together the skills and focus of each of these disciplines in a new dialogue can help turn risk and uncertainty into a powerful source of advantage.

Forge External Networks and Internal Communities of Practice

Most companies acknowledge the need for better processes to make sense of situations and more powerful antennae extracting critical signals from external noise. It is difficult, however, to develop such a function inhouse because we quickly become captives of our organization’s acceptable boundaries.” To achieve the necessary multiplicity of perspectives and insights, organizations are increasingly nurturing external networks of thought partners and sensors – people who are attuned to the deep trends they see in the world around them and can help translate them for specific organizations.

Informal, self-organizing “communities of practice” housed within organizations can also be powerful sources of knowledge and learning in the face of uncertainty. These communities perform much the same function as guilds did for craftsmen 500 years ago or open source communities do for software developers today. Provided the organization can support, nurture, and empower these “communities of practice” without destroying their vitality and integrity by over-formalizing them, these communities can help to ensure that unexpected issues encountered (and successful adaptations made) are socialized and adopted as widely and quickly as possible.

Test Strategies and Decisions Against Critical Uncertainties

Whenever we develop a strategy or make big decisions, we habitually reference our “official future” – an implicit set of beliefs about how the world works today and should in the future. Mounting uncertainty renders this approach increasingly hazardous. There is proven merit in stepping back and considering the critical uncertainties surrounding our choices. One very well established method is to develop a set of alternative “scenarios” of the future – coherent logical stories that set out credible and very different alternative. Through these, we systematically “stress-test” and, hence, improve our decisions. Additionally, we can develop a deeper understanding of critical uncertainties by improving our appreciation of interrelationships, causalities, and potential outcomes, and then contrasting and comparing these against our most important options and choices.

Develop “Masters of Uncertainty”

In the past decade, practitioners of quality management programs, such as Six Sigma, have become acknowledged enablers of the drive toward excellence. In the coming decade, they will be joined by a new and arguably even more powerful force let us call them “masters of uncertainty.” These will be leaders and talented contributors in our organizations who manifest a range of increasingly essential capabilities, which include the ability to:

• Stay relaxed in the face of overwhelming disorder, confusion, and ambiguity
• Seek out multiple and conflicting views, while being aware of one’s biases and blind spots
• Focus on the future, the emergent as well as the planned
• Embrace risk taking
• Learn rapidly from failure
• Be open, flexible, and even, on occasion, playful

These are not necessarily the attributes we associate with our current generation of leaders – but they will characterize the next generation. The good news is that the capabilities required for these leaders can be developed in our existing high-potential talent using a range of tools and techniques, such as learning journeys, simulations, scenario and systems training, job rotations, cross functional and even cross-company mentoring, storytelling experiences, and uncertainty coaching. Uncertain times will demand and reward untraditional talents – and we must invest in the next generation as soon as possible.

Intentionally Evolve As an Adaptive Organization Just like the elusive “learning organization,” no one has ever seen a truly “adaptive organization” in the wild. But we can certainly identify the hazy outlines of some vital characteristics of the responsive, enduring, and evolving business of the future. It should be:

• Externally oriented
• Flexible and nimble
• Patient but opportunistic
• Capable of balancing exploitation of the known with exploration of the unknown
• Visionary but open to corrective feedback
• Attentive to stakeholders
• Capable of balancing both economic and moral wisdom

The question today is not whether we can see this vision on the horizon – we all can – but whether we decide to move toward it with conviction and sustained attention, or hold back in fear that we may only be glimpsing a mirage.

Add an “Uncertainty Mapping” Dimension to Strategic Decision-Making

We should also learn to explicitly acknowledge uncertainty as a matter of habit. In every conversation of consequence, we should acquire the discipline of asking what important uncertainties are in play and challenge our beliefs and default positions.

Over time, we can also learn about our deeply embedded assumptions, and come to understand better and improve our decision-making habits. This is a readily achievable and remarkably important tool; indeed, there is probably no single greater contribution to the mastery of uncertainty. Finally, we must appreciate that there are very different forms and sources of uncertainty. In business, as in life, every important decision is actually a bet that we understand the context of our choice and that our sense of the future is reasonably accurate. In an increasingly uncertain world, the odds are lengthening against each and every bet, and the need for new thinking and better decision-making processes is growing. The ability to rise to this challenge will be the defining characteristic of the successful, adaptive organization of the future.

Eamonn Kelly is the CEO of Global Business Network (GBN) and a partner in the Monitor Group. He is also the author of Powerful Times: Rising to the Challenge of our Uncertain World (Wharton School Publishing, 2005). Eamonn will be a keynote speaker at this year’s Pegasus Conference.

The post The Tall Order of Taming Change appeared first on The Systems Thinker.