Why Strategic Planning Needs to Focus on Certainties Not Just Uncertainties

Rethinking Scenario Planning: Balancing Certainties and Uncertainties

In December 2025, Cynthia Selin published a piece in MIT Sloan Management Review that challenges conventional wisdom about scenario planning. Her central argument is simple: strategic planning should focus as much on identifying certainties as exploring uncertainties. After two decades observing how organizations approach strategic planning, I find this argument both refreshing and incomplete.

Selin contends that scenario planning has become too fixated on unknowns at the expense of knowable constraints. She argues that physical, temporal, institutional, and cultural boundaries shape what's possible in the future, and recognizing these limits provides essential scaffolding for strategy. This perspective deserves serious attention, but it also demands critical scrutiny.

The Seductive Danger of Certainty

Selin writes that "the future is not a blank slate" and that "certain constraints shape the terrain of the future, delimiting what is possible." This sounds reasonable. After all, gravity still works, humans still need sleep, and institutional inertia is real. But history is littered with examples of supposed certainties that dissolved faster than anyone expected.

Consider Blockbuster in 2000. The company's leaders could point to numerous certainties: Americans loved watching movies at home, video rental was a $16 billion market, physical media offered superior quality to streaming technology, and Blockbuster operated 9,000 stores with established customer habits. These weren't wild speculations. They were observable facts supported by decades of data.

Yet by 2010, Blockbuster filed for bankruptcy. Netflix, which Blockbuster declined to acquire for $50 million in 2000, reached a market capitalization of $13 billion. What happened? The certainties proved less certain than they appeared. Technological constraints fell away faster than expected. Customer behavior shifted more rapidly than historical patterns suggested. Institutional advantages became liabilities.

This isn't an argument against Selin's thesis, but rather a necessary complication of it. The challenge isn't choosing between analyzing certainties or uncertainties. It's developing the discernment to distinguish genuine constraints from assumptions masquerading as facts.

When Certainties Actually Matter

Despite these risks, Selin identifies something important. Jeff Bezos famously built Amazon's strategy around things that wouldn't change: customers would always want lower prices, faster delivery, and more selection. He told investors in 2001, "I very frequently get the question: 'What's going to change in the next 10 years?' I almost never get the question: 'What's not going to change in the next 10 years?' And I submit to you that that second question is actually the more important of the two."

Bezos was right, and Amazon's success validates Selin's core insight. The company invested billions in logistics infrastructure and pricing algorithms based on assumptions about unchanging customer preferences. Meanwhile, it remained flexible about how to deliver those benefits, experimenting with everything from drones to cashierless stores.

This points to a more nuanced framework than Selin provides. Some types of certainties are more reliable than others. Human needs and desires change slowly. The laws of physics and mathematics are truly constant. Network effects and infrastructure lock-in create real path dependencies. But institutional arrangements, cultural norms, and technological capabilities can shift with startling speed.

The global response to COVID-19 illustrates this complexity. In February 2020, most organizations operated on certain assumptions: office work required physical presence, major supply chains were stable, governments wouldn't implement extended lockdowns, and consumer behavior patterns were well-established. By April 2020, every single one of these "certainties" had collapsed.

Yet other constraints held firm. Humans still needed social connection, even if delivered virtually. Supply and demand still governed markets. Organizations still required coordination and communication. The companies that survived best identified which certainties were genuine and which were merely conventional wisdom.

The Four Types of Constraints Worth Examining

Selin mentions physical, temporal, institutional, and cultural constraints but doesn't elaborate on how to analyze them systematically. Let me propose a framework based on my observations of successful strategic planning processes.

• Physical constraints include the laws of nature, resource limitations, and infrastructure dependencies. In 2024, Breakthrough Energy reported that battery storage costs had fallen 89% since 2010, but energy density remains constrained by physics. This creates genuine limits on electric vehicle range and charging time. Automotive manufacturers planning for 2030 must account for these boundaries, even as they remain flexible about other aspects of electrification.
• Temporal constraints involve demographic trends, generational shifts, and long-cycle patterns. McKinsey's 2024 workforce analysis showed that by 2030, millennials and Gen Z will comprise 75% of the global workforce. This isn't speculation. These people are already alive and in the labor market. Their preferences and expectations will shape workplace dynamics regardless of technological or economic uncertainties.
• Institutional constraints include regulatory frameworks, legal structures, and organizational arrangements. The European Union's AI Act, finalized in 2024, creates compliance requirements that will shape technology development for years. Companies can't simply wish away regulatory constraints, even as they work to influence or adapt to them.
• Cultural constraints involve deeply rooted values, social norms, and identity formations. Despite predictions that globalization would homogenize culture, research from Pew Research Center in 2024 showed that cultural distinctiveness has actually increased in many dimensions. Companies operating globally must navigate genuine cultural differences, not assume convergence.

The key question is: How do we distinguish genuine constraints from false certainties? I've found three tests useful. First, examine the underlying mechanism. Is this constraint based on physics, biology, or human nature, or is it based on current technology and institutions? Second, look at historical precedent. Have similar "certainties" proved malleable in the past? Third, consider contrary evidence. What examples challenge this apparent constraint?

The Danger of the Missing Framework

Selin's article promises "a framework that outlines five types of certainties" but never delivers it. The summary mentions this framework, yet the published piece only alludes to four types of constraints without systematic elaboration. This omission matters because without a concrete framework, her argument remains abstract.

This pattern recurs throughout the article. Selin writes that "certain constraints shape the terrain of the future" and "offer a clearer basis for planning," but provides limited guidance on how to identify these constraints in practice. She references "obduracy" and "long-wave trajectories" without explaining how leaders should distinguish between forces that will persist and those that will dissolve.

The risk is that managers will latch onto the appealing idea of focusing on certainties without developing the analytical rigor to identify them correctly. In my consulting work, I've seen executives mistake industry conventions for immutable laws, confuse current technological limitations with permanent constraints, and assume their own cultural preferences reflect universal human nature.

A robust framework would need to address several questions Selin leaves unanswered: How do we systematically identify potential certainties? What evidence confirms or challenges these constraints? How do we weight certainties versus uncertainties in strategic planning? When should we invest in overcoming apparent constraints versus accepting them as boundaries? How do we update our understanding as new information emerges?

Learning from Scenario Planning's Evolution

Selin positions her argument as an enhancement to scenario planning rather than a replacement. This is wise. Scenario planning, developed at Royal Dutch Shell in the 1970s, has evolved significantly over five decades. Pierre Wack and his colleagues never intended scenario planning to predict the future. They designed it to challenge mental models and surface hidden assumptions.

The best contemporary scenario work integrates both uncertainties and certainties. When the Bank of England conducted scenario planning in 2023, as documented in the same MIT Sloan Management Review issue, they identified fundamental trends (aging demographics, climate change, technological acceleration) while exploring uncertain variables (policy responses, social adaptations, technological breakthroughs). The power came from examining how uncertainties might play out within the boundaries set by certainties.

Rafael Ramírez, a leading scenario planning scholar, has written extensively about how predetermined elements and critical uncertainties interact. His research from 2024 shows that effective scenarios identify the "inevitable" trends and examine how different responses to uncertainties could unfold within those constraints. This integration is more sophisticated than simply cataloging certainties or uncertainties separately.

The challenge is that identifying genuinely predetermined elements requires deep analysis. When Shell's scenario planners in the 1970s recognized that oil production would eventually peak, they weren't making a wild guess. They analyzed geological surveys, production data, and basic arithmetic. When they explored uncertainties around OPEC behavior and geopolitical responses, they were examining variables that could genuinely vary within those physical constraints.

Practical Applications and Limitations

How should leaders actually apply Selin's insights? Let me offer three concrete practices I've seen work effectively, along with their limitations.

• Conduct a constraints audit before developing strategic scenarios. Gather your planning team and systematically examine physical, temporal, institutional, and cultural factors in your industry. For each potential constraint, demand evidence. Challenge assumptions. Look for counterexamples. This process often reveals that fewer things are truly certain than initially assumed, but those that remain become powerful anchors for strategy.
• Distinguish between constraints you must accept and those you might overcome. Amazon accepted that customers would always want low prices and fast delivery, but rejected the constraint that retail required physical stores. Tesla accepted physical limits on battery energy density but rejected assumptions about electric vehicle market size and infrastructure requirements. This distinction separates genuine strategic thinking from passive acceptance.
• Use certainties as stress tests for strategic options. When evaluating potential strategies, ask whether they're compatible with genuine constraints. A strategy requiring physics to change won't work. A strategy assuming demographic trends will reverse probably won't either. But a strategy betting on regulatory change or cultural evolution might succeed with the right approach and timing.

The limitations here revolve around biases, judgment, and the potential conservatism that stress testing may inspire if not viewed through a lens of strategic innovation.

The Organizational Politics of Certainty

Selin's article ignores a crucial dimension: the political function of claims about certainty within organizations. In my experience, debates about what is or isn't certain are rarely purely analytical. They're often proxies for conflicts about resource allocation, strategic direction, and organizational identity.

Executives defending existing business models tend to emphasize certainties that justify current approaches. Innovators challenging the status quo tend to question apparent certainties and emphasize uncertainties requiring new responses. Both perspectives carry insight and bias.

Consider how automotive executives discussed electric vehicles between 2010 and 2020. Legacy manufacturers pointed to certain constraints: battery costs, charging infrastructure, consumer preferences for long range, dealer network investments. These weren't fabrications. They were genuine factors.

But some executives used these certainties to justify minimal EV investment, while others used them to guide ambitious programs accounting for constraints. By 2024, companies like General Motors and Volkswagen had committed over $100 billion to electrification, while others lagged. The difference wasn't access to information about certainties. It was interpretation and response.

This political dimension means that any framework for identifying certainties must include mechanisms for surfacing and challenging assumptions. Red team exercises, devil's advocates, and structured debate can help. But there's no purely technical solution to what remains partly a judgment call inflected by interests and perspectives.

What's Missing from the Conversation

Selin's argument would be stronger if it engaged with three bodies of research she overlooks.

• Work on discovery-driven planning by Rita McGrath and Ian MacMillan shows how to make strategic commitments while preserving flexibility as uncertainties resolve. Their research from Columbia Business School demonstrates that in highly uncertain environments, treating too many factors as certain leads to brittle strategies. The answer isn't ignoring certainties, but structuring investments to allow learning and adaptation.
• Research on complex adaptive systems from the Santa Fe Institute reveals that in highly interconnected systems, small changes can cascade unpredictably. What appears certain at one level may be contingent on factors at another level. Stuart Kauffman's work on fitness landscapes shows how the strategic value of any position depends on a context that's constantly shifting.
• Scholarship on infrastructure and path dependence by Paul David, Brian Arthur, and others illuminates when and why certain constraints persist. Their research shows that lock-in effects are real but not permanent. Understanding the mechanisms that create and dissolve lock-in is essential for applying Selin's insights effectively.

A More Nuanced Framework

Building on Selin's foundation, here's a more complete approach to integrating certainties and uncertainties in strategic planning.

Start by mapping your strategic landscape across two dimensions: the degree of constraint (from fully determined to completely uncertain) and the locus of constraint (from environmental factors beyond your control to organizational choices within your influence).

• Fully determined environmental factors include things like physical laws, completed demographic trends, and locked-in infrastructure. These set hard boundaries for strategy. Don't waste energy fighting them. Instead, find opportunity within or around them.
• Partially determined environmental factors include things like regulatory trajectories, technological learning curves, and cultural trends. These show strong directional momentum but aren't fully locked in. Monitor them closely and plan for multiple paths.
• Uncertain environmental factors include competitor moves, policy changes, and demand shifts. Traditional scenario planning addresses these well. Develop robust strategies that work across multiple scenarios.
• Organizational choices include capabilities you might develop, business models you might adopt, and markets you might enter. These are within your control but constrained by environmental factors and path dependencies.

The strategic art lies in finding the intersection between genuine constraints and meaningful choice. As Peter Drucker wrote in 1973, effective strategy "converts the isolated actions of individuals into a purposeful team effort." That team effort must respect real constraints while exploiting genuine opportunities.

Recommendations for Leaders

Based on this analysis, I offer five specific recommendations for leaders engaged in strategic planning.

• Explicitly identify your assumptions about what is and isn't certain. Write them down. Assign probabilities if possible. Too often, implicit assumptions drive decisions without scrutiny. Making them explicit enables testing and updating.
• Invest in intelligence gathering about potential constraint-breaking developments. Assign someone to monitor technologies, social movements, and innovations that might dissolve constraints you've accepted. Kodak's failure wasn't inevitable. The company invented the digital camera in 1975 but didn't challenge its own assumptions about film-based constraints.
• Structure investments to preserve optionality where genuine uncertainty exists while committing to areas where certainties are clear. Amazon committed heavily to logistics infrastructure based on certain customer preferences but experimented with dozens of business models for monetizing those capabilities.
• Build organizational capabilities for distinguishing types of constraints and updating beliefs as evidence accumulates. This requires intellectual humility, analytical rigor, and decision-making processes that incorporate diverse perspectives. Companies that do this well outperform those that don't, according to research by Paul Schoemaker published in Organization Science.
• Challenge your certainties as rigorously as your uncertainties. The most dangerous strategic assumption is the one you don't realize you're making. Red team exercises, pre-mortems, and structured contrarian analysis can surface hidden assumptions before they prove costly.

For more nuanced insights on scenario planning and strategic frameworks, explore this article from MIT Sloan Review: Explore Further on Scenario Planning.