When organizations want to develop strategies around potential changes in their operating environment, they often turn to scenario planning. But are they utilizing its full power? Countervailing forces analysis offers a structured way to integrate the unexpected into scenarios and prepare an association for a wide array of possible futures.
Planning would be easy if we could take a look at a trend line and simply extend it out into the future. But if reality worked that way, housing prices would be much higher today than they were five years ago, and many a startup company would still be in business.
All planning begins with research into environmental conditions—a look at "what's going on." In times of relative stability, it was much easier to take that data-driven foundation and extrapolate plausible future scenarios. Today, however, such scenario analysis is significantly more challenging.
But while times of pervasive uncertainty make scenario planning more difficult, these are also the times when the true power of scenario analysis becomes most apparent.
In its simplest form, scenario analysis is spinning a story about a future state. It anticipates future economic, social, and political directions and develops responses accordingly. It is a tool for monitoring the environment in support of decision making and action, a key competency to cultivate in uncertain times.
|5 Scenario Pitfalls to Avoid|
|To ensure successful scenario analysis, avoid the following five pitfalls.
1. Treating scenarios as simple forecasts. Forecasts are normally extrapolated trends that are internally derived and driven; they usually offer a specific prediction. Scenarios address shifts in the industry's environment and as such are more externally derived. Scenarios are not about predicting the future but rather offering multiple distinct, plausible outcomes.
2. Falling into the strawman trap. Many users of scenario analysis do not generate equally plausible scenarios but instead develop one plausible scenario and two or more "strawman" scenarios that simply serve to make the first one seem more plausible. This approach is not useful for planning or future environmental monitoring.
3. Ignoring relevant factors. Scenarios sometimes overlook areas of potential real impact on a profession or industry. It is easy to focus on trends for which data is available rather than the ones that really matter. This can be a result of faulty research analysis or simply not interpreting the research correctly.
4. Drawing inappropriately early conclusions. Do not accept an outcome before all the factors have had a chance to play out. Scenario analysis should support development of current strategies, but scenarios' real impact is in monitoring over time as a basis for assessing strategic direction and making modifications based on real-time environmental change.
5. Not engaging the most senior staff and decision makers. To be effective, scenario planning must have senior management ownership and involvement.
Scenario analysis is not about predicting the future or identifying a "most likely" scenario. Rather, it is about developing several plausible outcomes, monitoring them, and trying to influence the one(s) that are most desirable.
What Makes Scenarios Work
There is no magic in crafting good scenarios; the four building blocks listed on page 34 are enough to get you started. But when instability is significant, as we're experiencing today, there are several key factors to keep in mind.
Clarity of purpose. What is driving the need to develop scenarios? As Kristel Van der Elst put it during a recent World Economic Forum, "What is the central question of the specific strategic issue that requires a decision in light of trends or potential development?'
Clarity of time horizon. A big hurdle to overcome in scenario planning is getting one's thought process beyond the next couple of years. Using at least a 10-year time horizon is a good starting point, but it is also important to realize that different factors require different time horizons. For changing workforce trends, 10 years is a good time horizon. For public-policy issues, a much shorter horizon may be relevant. A mix of factors, with varying effective time horizons, will likely be part of most scenarios, with the overall time horizon for the total scenario pegged to the decision process the scenario is being constructed to support. So, if an organization is developing a five-year plan, the overall scenario should be constructed to monitor the environment in that timeframe, but within the scenario specific variables may play out in less or more than five years.
Plausibility. Each scenario should have a reasonable likelihood of outcome. Don't craft two polar extreme scenarios and one "midrange" scenario; the art of scenario analysis is blending the known and the unknown into profiles of alternative futures that have equal or similar plausibility. In uncertain environments, because no single outcome can be assured, it is prudent to develop plans on the assumption that several different futures are possible.
Evidence based. Anyone can guess about the future. The key is to eliminate guessing as much as possible and craft scenarios that take into account the joint effect of the many factors in your environment. Research, both primary and secondary, is the best way to get at this. It is important to recognize, however, that hard data will not be available for all the relevant factors in the environment, and the scenarios should take into account important "soft" variables as well. (A technique for doing this is covered below under the subheading "Countervailing-Forces Analysis.")
Appropriate breadth. It is important to engage all stakeholders in the scenario-planning process. If you are an association of homebuilders trying to craft a plan for the future in light of the 2008 economic meltdown, it is necessary to go beyond the inner core of the organization and include input and perspective from all of the stakeholders in your environment: bankers, mortgage brokers, buyers, landowners, suppliers, and so forth. The key is to cast a wide net.
Action oriented. Scenarios can be used passively to describe the anticipated environment or more actively. But scenarios can also drive strategies to influence the environment and not just accept it as a given with which the organization must cope.
Trackable metrics. Once scenarios are developed, you must monitor the environment to determine which is playing out in reality. Define each metric clearly and then determine the basis and unit target to track it. For example, if an important environmental factor for your scenario is housing starts, one metric might be the 10-year U.S. Treasury note, which has a current rate of 3.5 percent. The target to watch for as a key environmental trigger could be any rate more than five percent.
The biggest challenge when weaving together scenario stories is to incorporate behavioral factors that your research does not adequately cover. It is important to be data driven, but reliable data is often not available for certain critical factors.
|The Four Building Blocks of Scenario Analysis|
|1. Identify multiple relevant factors active in the environment and for each major factor identify direction, intensity, pace of likely change, and the key players.||2. Construct several scenarios around those factors that are as equally plausible as possible.|
|3. Identify desirable scenario(s) and develop strategies and action plans to influence outcomes.||
4. Identify indicators to use in tracking which scenarios are actually emerging over time and adjust strategies accordingly.
Countervailing-forces analysis can help in these situations. It is a tool for factoring in "soft" variables such as likely political trends, shifts in societal values, and other behavioral influences.
The healthcare sector provides an example. Starting in the mid-1980s, the growth of "managed care" was the big trend in health delivery and was the target of many forecasts, including scenario analyses. Almost all of the scenarios developed at that time extrapolated growth data of HMOs (the dominant form of managed care at the time) into forecasts of managed care dominance of the healthcare sector.
To some degree, those forecasts were on target, because managed care did become the major factor in the healthcare environment. However, the direction in which managed care developed and its impact on health delivery, patient care, and healthcare costs turned out to be quite different from what most of the scenarios envisioned. Why?
The reason the early scenarios were so far off target was that they failed to take critical soft variables into account. The scenario that played out in reality started with strong media and political support for HMOs, including considerable public funding of HMO demonstration projects. As public and professional backlash grew over concerns about restriction of choice and denial of coverage, the media reaction began to become more mixed and over time turned generally negative. Political pressure started to develop in response to negative media coverage and constituent feedback to legislators' offices at both the federal and state levels.
Insurance companies and health plans sponsoring HMOs responded by making modifications in the plans, and eventually what began as the HMO movement broadened to the more general managed-care trend. However, the generally negative image of managed care prevailed, and the term has become emblematic of much of what is widely perceived to be wrong with the health-delivery system.
What does all of this mean for scenario analysis? The scenarios of the early 1990s were generally on target with regard to the broad direction of the system. The HMO movement did grow rapidly and became a major driver of health-delivery trends. However, almost all the scenarios missed the potential for backlash and thus the potential for the evolution of HMOs into the broader managed-care phenomenon and the negative image that developed around it. Instead of becoming the solution to healthcare issues that was originally envisioned and forecasted, the HMO movement became emblematic of what is wrong with the healthcare system and has been a major factor leading to the push for broader health-system reform.
Countervailing-forces analysis could have been used to construct scenarios that anticipated this shift in direction and impact, taking into account those "soft" variables that can substantially shift a trend line.
Incorporating Countervailing Forces Into Scenarios
Countervailing-forces methodology is by its nature more speculative than data-based forecasting, so it is important that it be as specific and reality based as possible and used in combination with more data-based trend identification. Follow these steps:
1. Start with data-based trends. The key drivers in most environments are relatively apparent, and usually there is some data to support extrapolation of the trend in question. In the example above, there was data available by the early 1990s about the growth of HMOs and their early impact on controlling healthcare costs.
2. Ask who will be most affected. Be sure to consider both direct and indirect stakeholders. Generally, the direct stakeholders are relatively easy to identify; in the HMO example, they might include patients, healthcare providers, and people and institutions that pay for health insurance and healthcare. Indirect stakeholders are those affected by or sensitive to the direct stakeholders, such as the media, political bodies, nongovernmental organizations representing key stakeholder groups, and the public at large.
3. Ask how stakeholders will be affected. Starting with the direct stakeholders, consider the direction, intensity, and pace of the likely impacts and each group's likely response. This is, of course, speculative since it involves anticipating human behavior. However, applying the "why" test can help reality test the possible alternatives that are identified. For each potential stakeholder response, ask the question "why," and in response to the answer ask "why" again. Two to three iterations of this technique generally gets the analysis down to fundamentals that either make sense or don't. In cases where the technique produces results that don't make sense, disregard the potential stakeholder response you originally subjected to the "why" analysis and look for others that better withstand the test.
For each of the direct-stakeholder responses that are plausible, ask whether any indirect stakeholders will likely be drawn into the response. Will the direct-stakeholder response be strong enough to attract attention among indirect stakeholder groups, and will the indirect-stakeholders tend to be supportive or resistant?
Once both direct and indirect stakeholders' likely responses are identified, look at them and ask whether they collectively constitute a significant force for potential change.
For a more in-depth discussion on the basics of scenario analysis, see Barton Tretheway's presentation "Scenario Planning: Not a Passive Forecast" from the 2009 ASAE & The Center Annual Meeting.
4. Identify the intensity of stakeholder response. For the anticipated stakeholder responses that are accepted for the analysis, ask follow-up questions: Is the collective anticipated stakeholder response likely to be widespread enough to be apparent within the industry or more broadly in society? If so, is the impact of the response likely to be strong enough to shift the trajectory of the original trend? If so, in what direction?
Anticipating a shift in trajectory should avoid the traditional "pendulum premise." One often hears of "the pendulum swinging back" in discussing trends. This can be limiting and misleading, because pendulums swing on a predictable trajectory and human behavior almost never moves that way. A stakeholder response strong enough to shift the trajectory of a trend is unlikely to send it back in exactly the direction from which it came. The countervailing movement created by a strong stakeholder response will likely be in some other direction. The "why" technique discussed in step three above can be useful in reality testing the alternative trajectories of a trend shift.
5. Revise the original scenarios. Countervailing forces that are identified as potentially significant can be incorporated into the alternative plausible scenarios as key factors to be monitored over time to determine which direction the environment is actually tracking.
Following these five steps will result in scenarios that include a more complete reflection of the environment, including both hard and soft variables.
Many associations are talking about when their environment and the economy will "get back to normal." Back to normal no longer exists; the new paradigm is pervasive uncertainty. Advanced scenario analysis can assist organizations in navigating through these uncharted seas. Done properly, it can be a very powerful planning tool.