Leading Through Uncertainty: Decision-Making When You Don't Know
In March 2020, Airbnb CEO Brian Chesky faced the impossible. Within weeks, the COVID-19 pandemic evaporated 80% of Airbnb's business. Bookings plummeted. Hosts panicked. The company's planned IPO looked dead. Nobody knew if travel would ever recover, when lockdowns would end, or what "normal" would mean.
Chesky had no playbook for this. No precedent. No clear path forward. Every decision required judgment calls with insufficient information:
- Should they lay off staff? (Unknown: how long would crisis last)
- How much cash to preserve? (Unknown: burn rate in different scenarios)
- Which products to cut? (Unknown: what travel would look like post-pandemic)
- Whether to proceed with IPO? (Unknown: market conditions in 6-12 months)
Chesky couldn't wait for certainty—it wouldn't arrive. Instead, he had to lead through uncertainty: make consequential decisions with incomplete information, maintain team confidence despite personal doubt, and navigate ambiguity without paralysis.
His approach combined transparency (honest communication about unknowns), decisiveness (making hard calls quickly), and adaptability (willingness to reverse course as situation evolved). Within months, Airbnb had restructured for survival, pivoted to local travel and long-term stays, and eventually achieved successful IPO in December 2020.
The lesson wasn't that Chesky predicted the future correctly. He didn't. The lesson was that effective leadership through uncertainty requires different capabilities than leadership in stable times: comfort with ambiguity, decision-making despite incomplete information, maintaining team confidence without false certainty, and balancing conviction with flexibility.
This article explains how to lead through uncertainty: the mindset shifts required, decision-making frameworks when you lack information, communication strategies for maintaining confidence, techniques for distinguishing when to pivot vs. persist, ways to develop uncertainty tolerance, and real-world examples of leaders navigating ambiguous situations effectively.
Understanding Uncertainty in Leadership
Not all uncertainty is equal. Recognizing types helps tailor approach.
Type 1: Known Unknowns
Definition: You know what you don't know. Questions are clear even if answers aren't.
Examples:
- "Will this product launch succeed?" (Unknown but can test)
- "What will competitor do?" (Unknown but can monitor)
- "Will candidate accept offer?" (Unknown but can ask)
Approach: Research, analysis, testing, monitoring. Information gathering reduces uncertainty.
Type 2: Unknown Unknowns
Definition: You don't know what you don't know. Surprises you can't anticipate.
Examples:
- 9/11 attacks
- COVID-19 pandemic
- Financial crisis of 2008
- Technology disruptions (iPhone making BlackBerry obsolete)
Approach: Build resilience, maintain flexibility, scenario planning, avoid over-optimization that creates fragility.
Nassim Taleb's insight: Unknown unknowns have disproportionate impact. Can't predict them, but can prepare through antifragility.
Type 3: Radical Uncertainty
Definition: Situation so novel that probabilities are meaningless. No historical precedent.
Examples:
- First-time founder's journey
- Unprecedented market conditions
- Revolutionary technology deployment
- Major organizational transformation
Approach: Frame-breaking thinking, first principles, experimentation, accepting that you're learning as you go.
The Leader's Uncertainty Paradox
Team expectation: Leaders should know what to do, provide clarity, exude confidence.
Reality: Leaders often don't know, face massive ambiguity, and feel doubt.
Result: Pressure to project false certainty. This backfires:
- Teams detect inauthenticity
- Overconfident decisions prove wrong
- Lost trust when reality doesn't match promises
Better approach: Authentic uncertainty—acknowledge unknowns while maintaining clear direction.
Mindset Shifts for Leading Through Uncertainty
Effective uncertainty leadership requires mental model changes.
Shift 1: From Knowing to Learning
Old model: Leader as expert who knows answers
New model: Leader as sense-maker who learns fastest
Manifestation:
- "I don't know yet, but here's how we'll figure it out"
- Rapid experimentation over extensive planning
- Updating views based on evidence
- Asking questions vs. having all answers
Example: Amazon's leadership principle: "Leaders are right, a lot... because they are open to learning and changing their minds."
Shift 2: From Predicting to Preparing
Old model: Forecast future, make plan, execute plan
New model: Prepare for multiple futures, make reversible moves, adapt based on what unfolds
Manifestation:
- Scenario planning (best/base/worst cases)
- Option-creating decisions (preserve flexibility)
- Quick pivots when assumptions prove wrong
Example: Military concept of "Commander's Intent"—specify outcome desired, not detailed steps. Troops adapt to changing battlefield conditions while maintaining strategic objective.
Shift 3: From Certainty to Conviction
Old model: Only proceed when certain of success
New model: Act with conviction on best hypothesis, remain willing to adjust
Distinction:
- Certainty: "I know this will work"
- Conviction: "I believe this is right direction based on current information, and I'll adjust if proven wrong"
Jeff Bezos's framing: Type 1 decisions (irreversible—go slow, gather information). Type 2 decisions (reversible—go fast, learn from outcomes).
Shift 4: From Comfort to Capability
Old model: Avoid uncertainty, seek stability
New model: Build uncertainty tolerance as leadership capability
Reframe: Uncertainty isn't problem to eliminate—it's condition to navigate effectively.
Development: Like muscle, uncertainty tolerance strengthens through progressive exposure and deliberate practice.
Decision-Making Frameworks for High Uncertainty
When you lack complete information, how do you decide?
Framework 1: The 70% Rule
Principle: Decide when you have ~70% of information you'd ideally want.
Rationale:
- 100% information often never arrives
- Waiting has opportunity cost
- Can learn from action faster than from analysis
Application:
- Define what 100% information would look like
- Assess current knowledge (30%? 50%? 70%?)
- If 70%+, decide
- If <70%, identify critical missing information and time-box gathering
Example: Amazon's Jeff Bezos: "Most decisions should be made with somewhere around 70% of the information you wish you had. If you wait for 90%, you're probably being slow."
Framework 2: Reversibility Analysis
Question: If this decision proves wrong, how hard to reverse?
Reversible decisions (Type 2):
- Make quickly
- Lower information threshold
- Learn from outcomes
- Iterate
Examples: Pricing changes, feature priorities, marketing experiments, team structure
Irreversible decisions (Type 1):
- Take more time
- Gather more information
- Get more input
- Higher conviction required
Examples: Acquisitions, large capital investments, workforce reductions, fundamental business model changes
Insight: Most decisions are more reversible than they feel. Artificial sense of irreversibility causes paralysis.
Framework 3: Pre-Mortem Analysis
Process: Imagine decision has failed spectacularly. Work backwards to identify what went wrong.
Benefits:
- Surfaces hidden risks
- Overcomes optimism bias
- Identifies early warning signs to monitor
Steps:
- "It's 12 months from now. This decision was a disaster. Why?"
- Everyone writes down reasons independently
- Share and discuss
- Identify which risks are addressable vs. fundamental
Example: Before launching product, imagine it flopped. "Why?"
- "Feature set missed real need"
- "Pricing way off"
- "Competitors moved faster"
- "Technical complexity blocked execution"
Some risks addressable through mitigation. Others suggest reconsidering decision.
Framework 4: Scenario Planning
Process: Develop multiple plausible futures, test decision against each.
Steps:
- Identify critical uncertainties (factors you can't predict or control)
- Develop 3-4 scenarios combining different outcomes
- For each scenario, assess: Does our decision make sense?
- Choose decision that's robust across scenarios or creates options
Example: Company considering major investment
Scenarios:
- Boom: Economy strong, competition weak → Investment pays off big
- Bust: Recession, low demand → Investment strains cash flow dangerously
- Disruption: Technology shift changes landscape → Investment in wrong technology
- Status quo: Moderate growth continues → Moderate ROI
Analysis: Investment makes sense in boom/status quo, risky in bust/disruption. Either:
- Proceed if confident boom/status quo more likely
- Reduce investment size (less upside but manageable in bust)
- Wait for more information to narrow scenarios
- Find alternative that's robust across all scenarios
Framework 5: Kill Criteria
Problem: Sunk cost fallacy—persist with failing approach because already invested.
Solution: Define failure conditions upfront before emotional attachment.
Process:
- Before committing, specify: "We'll kill this if..."
- Define metrics and thresholds
- Set review date
- At review, objectively assess against criteria
Example: New product launch
Kill criteria:
- <1000 active users after 3 months
- <20% month-over-month growth
- Customer acquisition cost >$100
- Churn rate >10% monthly
Removes emotion: Clear criteria make pivot/kill decision mechanical, not agonizing.
Communication Strategies for Uncertain Times
What you say and how you say it matters enormously when navigating uncertainty.
Strategy 1: Honest Transparency
Principle: Acknowledge uncertainty explicitly rather than pretending to know.
What to communicate:
- What you know: "Here's what's clear..."
- What you don't know: "Here's what's uncertain..."
- How you'll decide: "Here's how we'll approach this..."
- When you'll update: "I'll share more information by..."
Why it works:
- Builds trust through authenticity
- Sets realistic expectations
- Enlists team in sense-making
- Reduces anxiety of pretending
Example: Brian Chesky's communication during COVID:
"I don't know when travel will recover. Nobody does. What I know: we have X months of runway, we're focusing on Y and Z, here's what each of you can control. I'll update weekly as we learn more."
Strategy 2: Frequent Over-Communication
Problem: In uncertainty, information vacuum fills with anxiety and speculation.
Solution: Communicate more frequently, even when nothing has changed.
Benefits:
- Creates shared reality
- Prevents rumor mill
- Demonstrates leadership presence
- Provides psychologically stabilizing routine
Format examples:
- Daily standups (brief check-ins)
- Weekly updates (longer context and direction)
- Monthly all-hands (strategic perspective)
- Open Q&A sessions (address concerns directly)
Key: Consistency matters more than length. 5-minute daily update beats 2-hour monthly meeting.
Strategy 3: Name the Reality
Principle: Acknowledge difficulty explicitly. Don't gaslight with toxic positivity.
Toxic positivity: "Everything's fine! Stay positive!"
Reality naming: "This is hard. I know you're feeling [anxious/exhausted/uncertain]. That's normal. Here's how we'll navigate together."
Why it matters:
- Validates feelings
- Builds psychological safety
- Enables productive discussion
- Prevents burnout from pretending
Example: Satya Nadella during Microsoft's culture transformation:
"We're asking you to change how you've worked for years. That's uncomfortable. It's okay to struggle with this. We're learning together."
Strategy 4: Focus on What's Controllable
Problem: Obsessing over external factors you can't control creates helplessness.
Solution: Direct attention to factors within sphere of control.
Framework:
- Circle of concern: Everything that affects you (economy, competitors, pandemic)
- Circle of control: What you can influence (strategy, execution, culture)
Focus on control circle: "We can't control X, but we can control Y and Z. Let's put energy there."
Benefits:
- Restores agency
- Channels anxiety into productive action
- Prevents victim mentality
Strategy 5: Create Islands of Stability
Problem: Uncertainty everywhere is paralyzing.
Solution: Create predictable rituals and routines even when strategy shifts.
Examples:
- Consistent meeting schedules
- Regular 1-on-1s
- Transparent decision-making processes
- Familiar communication channels
- Maintained team norms
Why it works: Routine in execution provides psychological anchor when direction is uncertain.
Maintaining Team Morale Through Extended Uncertainty
Short-term uncertainty is manageable. Long-term ambiguity drains teams.
Tactic 1: Celebrate Small Wins
Problem: In uncertain times, big wins are rare. Waiting for them demoralizes.
Solution: Recognize and celebrate small progress markers.
Examples:
- Shipped feature on time
- Positive customer feedback
- Problem solved creatively
- Team member went above and beyond
Why it matters: Creates sense of progress and momentum even when ultimate outcome unclear.
Implementation: Weekly shoutouts, visible recognition, team celebrations.
Tactic 2: Provide Individual Clarity
Problem: Strategic uncertainty doesn't mean individual roles should be ambiguous.
Solution: Even when company direction is uncertain, provide clarity on individual contributions.
Framework:
- "Here's your focus for next [week/month]"
- "Here's how your work contributes to current priorities"
- "Here's how I'll measure success"
- "Here's how you should spend your time"
Why it works: People can execute confidently on clear individual goals even when broader direction is uncertain.
Tactic 3: Support Well-Being Explicitly
Problem: Prolonged uncertainty causes burnout.
Solution: Actively support recovery and boundaries.
Actions:
- Encourage time off (and take it yourself)
- Respect work-life boundaries
- Watch for burnout signals
- Reduce low-value work to conserve energy
- Provide resources (mental health support, flexibility)
Why it matters: Burnout teams can't navigate uncertainty effectively. Resilience requires recovery.
Tactic 4: Model Authentic Leadership
Problem: Leaders who project false confidence create cynicism.
Solution: Show authentic human response to difficulty while maintaining resolve.
What to share:
- "This keeps me up at night too"
- "Here's what I'm worried about"
- "Here's how I'm managing stress"
- "I don't have all the answers"
What to maintain:
- Commitment to mission
- Confidence in team capability
- Focus on controllable factors
- Belief in eventual success
Balance: Authenticity about difficulty + resolve about navigating it.
Tactic 5: Make Decisions to End Ambiguity
Insight: Sometimes best morale move is making a decision—any decision—to end prolonged uncertainty.
Problem: Indefinite ambiguity drains teams more than bad news with clarity.
Example: Team doesn't know if project will continue or be canceled. Weeks drag on without decision.
Better: Make call either way. "We're proceeding with X plan" or "We're killing this project and moving resources to Y." Clarity enables moving forward.
Principle: Don't let ambiguity linger unnecessarily. When decision is makeable, make it.
Pivot vs. Persist: Knowing When to Change Course
One of hardest uncertainty challenges: determining when to keep pushing vs. when to change direction.
Indicator 1: Core Assumption Validation
Question: Have fundamental assumptions been validated or invalidated?
Process:
- At start, list core assumptions (customer need, willingness to pay, technical feasibility, market size)
- Identify what would prove each assumption wrong
- Actively test assumptions
- Track which have been validated/invalidated
Decision rules:
- Assumptions validating: Persist, improve execution
- Assumptions invalidating: Pivot or kill
Example: Slack started as gaming company. Core assumption: "People will play our game." Tested through launch. Invalidated—nobody played. BUT: Internal communication tool they built was popular. New assumption: "Teams need better communication tool." Tested—validated. Pivoted successfully.
Indicator 2: Rate of Learning
Question: Are we learning and improving quickly, or stuck?
Persist signals:
- Clear progress with each iteration
- Understanding customer better each cycle
- Product improving measurably
- Growing organic pull
Pivot signals:
- Same problems recurring
- Customer feedback not improving
- No clearer on product-market fit after months
- Pushing uphill constantly with no momentum
Framework: If learning velocity is high, persist. If stuck in same place despite effort, pivot.
Indicator 3: Unit Economics Trajectory
Question: Are economics improving toward viability or stuck at unsustainable levels?
Persist signals:
- Customer acquisition cost declining
- Lifetime value increasing
- Gross margin improving
- Path to profitability visible
Pivot signals:
- CAC staying high or increasing
- LTV flat or declining
- Margin not improving despite scale
- No path to unit economics working
Nuance: Early stage can tolerate bad unit economics while testing. But trajectory matters—should be improving.
Indicator 4: Opportunity Cost
Question: What else could we do with these resources?
Framework:
- Current path: Expected value if persist
- Alternative paths: Expected value of other opportunities
- Switching cost: Cost to pivot
Decision: Pivot if (Alternative EV - Switching Cost) > Current EV
Caution: Beware "grass is greener" bias. New paths also have uncertainty.
Indicator 5: Team Energy and Belief
Question: Does team believe in mission and feel momentum, or is energy draining?
Persist signals:
- Team engaged and motivated
- Volunteering ideas and effort
- Pride in what's being built
- Excitement about progress
Pivot signals:
- Team demoralized
- Going through motions
- Nobody believes this will work
- Energy flat despite effort
Nuance: Team energy follows but also leads results. Sometimes pivot needed to restore belief.
Decision Framework: Persist vs. Pivot
Persist when:
- Core assumptions validating
- Learning and improving rapidly
- Unit economics trajectory positive
- Clear organic pull emerging
- Team energized and committed
Pivot when:
- Core assumptions invalidated
- Stuck despite repeated efforts
- No path to viable economics
- Better opportunities identified
- Team belief fundamentally broken
Time-box uncertainty: Set decision point: "We'll decide by [date] based on [metrics]." Prevents indefinite ambiguity.
Developing Uncertainty Tolerance
Leading through uncertainty is skill, not innate trait. How to develop it?
Method 1: Seek Uncertain Experiences
Principle: Uncertainty tolerance grows through exposure.
Actions:
- Volunteer for ambiguous projects
- Take on stretch roles
- Work in new domains
- Accept assignments without clear playbook
Why it works: Each uncertain situation navigated builds confidence and capability for next one.
Caution: Progressive challenge—don't jump to extreme uncertainty before building foundation.
Method 2: Decision Journaling
Process:
- Before major decision, write: Context, options, reasoning, prediction
- After outcome known, review: What happened? What did I learn?
- Quarterly, review patterns: When am I right? When wrong? Why?
Benefits:
- Calibrates confidence (Are you overconfident? Too cautious?)
- Identifies decision biases
- Improves pattern recognition
- Builds intuition over time
Example: Note when you were certain but wrong (teaches humility) and uncertain but right (teaches trust instincts).
Method 3: Build Mental Models
Principle: Frameworks reduce cognitive load in uncertain situations.
Frameworks to internalize:
- First principles thinking
- Second-order effects
- Reversible vs. irreversible decisions
- Base rates and priors
- Expected value calculations
- Scenario planning
Application: When facing uncertainty, pattern-match to framework. "This is a Type 2 decision—reversible—so decide quickly."
Development: Read case studies, analyze decisions, discuss with peers, apply frameworks deliberately.
Method 4: Practice Cognitive Flexibility
Skill: Argue multiple perspectives, update views based on evidence.
Exercises:
- Steel-manning: Argue strongest version of position you disagree with
- Perspective-taking: Explain situation from different stakeholder views
- Devil's advocate: Identify flaws in preferred option
- Premature commitment: Notice when you're defending position vs. seeking truth
Why it matters: Cognitive flexibility enables adaptation—key uncertainty capability.
Method 5: Manage Your Own Anxiety
Reality: Uncertainty triggers stress response.
Strategies:
- Self-awareness: Notice anxiety without being controlled by it
- Regulation: Breathing, exercise, sleep, boundaries
- Perspective: "Is this actually high stakes or does it just feel urgent?"
- Support: Advisors, peers, therapy
Why it matters: Can't lead team through uncertainty if personally overwhelmed by it.
Case Studies: Leaders Navigating Uncertainty
Case 1: Andy Grove's Strategic Inflection Point
Context: 1980s, Intel faced memory chip business collapse. Japanese competitors dominated with better, cheaper products. Intel's core business dying.
Uncertainty: What business should Intel be? Memory chips failing, future unclear.
Grove's approach:
- Reframed question: "If we got kicked out and board brought in new CEO, what would they do?"
- Answer: Exit memory chips, focus on microprocessors
- Decision: Painful—laid off 30% of employees, abandoned 15+ year business
- Communication: Honest about difficulty, clear about direction
- Result: Intel became dominant in microprocessors, defining next era of computing
Lesson: Sometimes uncertainty requires frame-breaking decision despite lack of certainty about outcome.
Case 2: Bob Iger's Disney Bet on Streaming
Context: 2017, Disney faced existential threat. Cord-cutting eroding cable business (ESPN, Disney Channel). Netflix dominating streaming.
Uncertainty: Should Disney enter streaming despite:
- Cannibalizing highly profitable cable business?
- Uncertain if could compete with Netflix?
- Massive investment required?
- Technology and expertise lacking?
Iger's approach:
- Scenario planning: Future with streaming vs. without—without looked worse
- Decisive commitment: Announced Disney+ would launch in 2 years
- Acquired capability: Bought BAMTech for streaming technology
- Content strategy: Pull content from Netflix to make Disney+ must-have
- Result: Disney+ reached 100M subscribers in 16 months, becoming #2 streaming service
Lesson: Sometimes uncertainty requires bold, irreversible bet. Waiting for certainty means competitors move first.
Case 3: Satya Nadella's Microsoft Cultural Transformation
Context: 2014, Nadella became Microsoft CEO. Company declining, culture toxic, missing mobile/cloud revolutions.
Uncertainty: How to transform culture of 100,000+ person company? What products to prioritize? How to regain growth?
Nadella's approach:
- Cultural diagnosis: Identified "know-it-all" culture killing innovation
- New mindset: "Learn-it-all" replacing know-it-all
- Strategic clarity: Cloud-first, mobile-first
- Honest communication: Acknowledged problems openly
- Persistent effort: Culture change took years, not months
- Result: Microsoft market cap grew from $300B to $2T+ under Nadella
Lesson: Cultural transformation is inherently uncertain. Requires persistent vision, authentic leadership, and long-term commitment.
Conclusion: Uncertainty as Leadership Laboratory
The most important leadership moments happen when the path isn't clear.
The key insights:
1. Uncertainty is normal, not exception—stable times are anomalies. Most consequential leadership happens in uncertainty. Those who navigate it well create disproportionate value.
2. Acknowledge uncertainty authentically—false confidence backfires. Teams respect leaders who honestly acknowledge unknowns while maintaining clear direction and resolve.
3. Decide with incomplete information—waiting for certainty means never deciding. 70% information often sufficient. Make reversible decisions quickly, irreversible decisions carefully.
4. Communicate frequently and honestly—information vacuum fills with anxiety. Over-communicate what you know, what you don't know, and how you're approaching decisions.
5. Focus on controllable factors—obsessing over external factors you can't control creates helplessness. Direct energy toward what you can influence.
6. Distinguish pivot from persist—validate core assumptions, track learning velocity, monitor unit economics, assess opportunity cost. Don't pivot too early (shiny object syndrome) or persist too long (sunk cost fallacy).
7. Build uncertainty capability deliberately—seek uncertain experiences, journal decisions, build mental models, practice cognitive flexibility, manage anxiety. This skill develops over time through deliberate practice.
Brian Chesky didn't have certainty when COVID hit Airbnb. He had resolve, authenticity, decisiveness, and willingness to adapt. That proved sufficient.
The paradox: You don't need certainty to lead through uncertainty. You need capability to navigate ambiguity effectively.
As Andy Grove wrote: "In times of uncertainty, bold action is often safer than inaction."
The future always uncertain. Leaders who wait for clarity wait forever. Leaders who act despite uncertainty, learn faster, adapt continuously, and communicate authentically navigate successfully while others remain paralyzed.
The question isn't "How do I achieve certainty?" It's "How do I lead effectively despite uncertainty?"
Answer that, and you've developed capability separating consequential leaders from those who only lead in stable, predictable times. The latter are administrators. The former are leaders.
References
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Nadella, S., Shaw, G., & Nichols, J. T. (2017). Hit refresh: The quest to rediscover Microsoft's soul and imagine a better future for everyone. Harper Business.
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