Tool/Decision Theory/No. 0886
Scenario Planning
Scenario planning is a method for testing plans against several plausible futures rather than predicting one outcome. Developed by Herman Kahn in defense research and adapted by Pierre Wack at Shell, it reveals assumptions and weaknesses in strategy under uncertainty.
- Evidence
- Useful, modest evidence
- Read
- 6 min
- Links
- 13 connections
01You've seen this when…
- in life
You can afford the mortgage on two full-time salaries. Before buying, you work through futures where one of you changes careers, takes parental leave, or needs to move.
- at work
Your hiring plan assumes next year’s customers behave like this year’s. The team also sketches a future where a competitor cuts prices and another where new regulations bring a surge of demand.
- out in the world
A city needs water infrastructure that will last decades. Planners compare a slowly growing city with reliable rainfall against a rapidly growing city facing repeated droughts.
02The idea
A plan often contains a future nobody has said out loud: customers keep buying, financing stays available, regulations stay put. Scenario planning makes those assumptions visible by building several different futures and asking how the same decision would fare in each.
A scenario is a coherent account of how conditions could develop. It connects events and responses: energy prices rise, shipping gets expensive, customers change what they buy, and competitors adjust. That connected story gives a scenario more depth than optimistic and pessimistic versions of a single number.
By default, scenarios are possibilities to explore, not predictions with assigned odds. Their job is to expose vulnerabilities and identify choices that hold up across different conditions. They also help you prepare moves you would make only if certain changes occur. This is particularly useful under deep uncertainty, when even the right model or probabilities are disputed.
Focus on a small set of futures chosen to challenge the assumptions carrying your decision. All the stories may turn out wrong, yet the exercise can still reveal where your plan is fragile.
03How to use it
- Start with a decision and a horizon. Specify what you must choose, by when, and how long the consequences last. Planning a warehouse lease for three years needs different scenarios from planning a retirement.
- Separate firm constraints from uncertain drivers. List what shapes the decision: demand, technology, regulation, financing, weather. Distinguish existing commitments and well-supported trends from things that could move in different directions.
- Choose a few contrasting futures. Select uncertainties that could materially change the decision. Three or four scenarios are often manageable. Crossing two uncertainties on a grid can help, but don’t force everything into four boxes or assume every combination makes sense.
- Explain how each future develops. Write a short causal story, not a collection of adjectives. Include how customers, competitors, governments, or family members respond. Use second-order thinking to follow those responses beyond the first change.
- Test the same options in every scenario. For each option, record what works, what fails, and what must be true for it to succeed. Look for common strengths and scenario-specific weaknesses. This supports robust decision-making, rather than optimizing for one assumed future.
- Separate commitments from contingent moves. Decide what to do now, what to defer, and what flexibility is worth buying. A smaller initial investment with room to expand may preserve real options, but that flexibility has a price.
- Choose signals and assign follow-up. Identify observable changes that would justify reconsidering the plan: sustained order growth, a proposed regulation, supplier lead times. Use leading indicators where possible. Give someone responsibility for checking them and revising the scenarios.
04A worked example
Consider an illustrative online retailer shipping 30,000 orders a month. Its warehouse is nearly full. The team must choose between a large inland facility on a three-year lease and a smaller facility near customers, with temporary overflow space available at a higher unit cost.
What it looks like A capacity calculation. The sales forecast shows growth, so the larger warehouse appears to offer the best cost per order.
What’s actually going on The calculation relies on both demand growth and affordable delivery. The team develops three contrasting futures:
- Cheap delivery supports expansion. With shipping still affordable and household spending growing, orders reach 60,000 a month. The large inland facility performs well.
- Two other futures change the trade-offs. In one, shipping gets expensive while customers postpone purchases. Orders fall to 20,000 a month. The large lease becomes a burden; the smaller facility limits fixed costs. In the other, a rival offers rapid delivery, making faster service the competitive standard and pushing the retailer toward smaller, more frequent shipments. Orders grow, but proximity to customers matters more than warehouse size.
The smaller facility’s advantages depend on the conditions. The exercise reveals what each option needs to succeed. The team can now compare the cost of overflow space against the cost of being locked into the wrong location.
What made it work Every scenario tests the same two choices. The stories produce a decision: the team will start smaller with overflow capacity reserved and revisit expansion after sustained demand growth. The team accepts higher costs in the expansion scenario in exchange for lower exposure in the other two.
05When to reach for it
06When it misleads
- A vivid story starts sounding likely. Detail makes a future easier to imagine while leaving its probability unchanged. Assign odds only with evidence beyond a convincing story, and treat scenarios as equally likely only when that judgment is justified.
- The exercise merely adjusts a spreadsheet. Sensitivity analysis examines how results change when inputs vary. Scenario planning combines conditions into coherent sequences and traces responses. Both methods are useful. Each answers a different question.
- Every scenario becomes a disaster. A stress test deliberately examines adverse conditions. Scenarios can also reveal favorable changes and opportunities. A pre-mortem starts from assumed failure; scenario planning can explore a range of outcomes.
- Flexibility becomes an unlimited expense. Preparing equally for every imaginable future can cost more than the risks warrant. Compare the price of keeping options open with the exposure it reduces.
- The stories leave the plan unchanged. A polished presentation supports preparation when it leads to action. Each important vulnerability should lead to a changed commitment, a contingency, or a signal somebody monitors. Revise the stories when their assumptions stop fitting.
07Roots
At RAND in the 1950s, Herman Kahn worked on a problem ordinary forecasting could barely touch: nuclear conflict. There was no history of repeated nuclear wars from which to estimate a dependable trend. He explored alternative sequences of escalation and response, tracing their consequences so planners could examine choices across several possible outcomes. Kahn later carried this style of thinking into broader futures work. His 1967 book with Anthony Wiener, The Year 2000, explored alternative futures thirty-three years ahead.
At Shell in the early 1970s, Pierre Wack and colleagues faced a commercial version of the problem. Oil companies were making long-lived investments in a world where dependable supplies of cheap oil could no longer be taken for granted. Their scenarios explored changes in producer power and possible supply disruptions. When the 1973 oil crisis arrived, managers who had engaged with those possibilities had a framework for interpreting events that challenged their usual assumptions.
That episode became the technique’s best-known success story, sometimes retold as Shell predicting the crisis. Wack’s later accounts emphasized a subtler purpose: changing how managers understood the world so they could recognize change and respond. The method spread through corporate strategy and public planning. The durable lesson is about preparation: rehearsing different conditions can make today’s commitments less dependent on one unquestioned future.
08How solid is this?
A developed planning method whose evidence for better real-world outcomes is largely case-based. Shell’s experience illustrates preparation but does not isolate the method’s effect from other factors or establish predictive accuracy.
09Connections
- Often confused with Backcasting, Sensitivity Analysis, Stress Testing
- Helps counter Risk vs. Uncertainty, Overconfidence Effect, Slippery Slope Fallacy
- Can follow fromDeep Uncertainty
- Part ofRobust Decision-Making
- Includes Counterfactual Reasoning
- See alsoReal Options, Second-Order Thinking, Leading vs. Lagging Indicator, Pre-Mortem
+ 3 more in the list
10Origin and sources
Herman Kahn developed scenario methods in defense research in the 1950s and 1960s. Pierre Wack and colleagues adapted them for corporate strategy at Shell in the early 1970s.
- [1]Kahn, H., & Wiener, A. J. (1967). The Year 2000: A Framework for Speculation on the Next Thirty-Three Years. Macmillan.
- [2]Wack, P. (1985). Scenarios: Uncharted Waters Ahead. Harvard Business Review, 63(5), 73–89.
- [3]Wack, P. (1985). Scenarios: Shooting the Rapids. Harvard Business Review, 63(6), 139–150.
- [4]Schoemaker, P. J. H. (1995). Scenario Planning: A Tool for Strategic Thinking. Sloan Management Review, 36(2), 25–40.
- [5]Bradfield, R., Wright, G., Burt, G., Cairns, G., & van der Heijden, K. (2005). The origins and evolution of scenario techniques in long range business planning. Futures, 37(8), 795–812.
Suggest an edit· Updated 2026-10-02