When the Fog Won’t Lift: Making Smart Decisions with Half the Picture
It was 2:30 AM when Sarah’s phone jolted her awake. The voice on the other end belonged to her operations manager: “The Singapore server is down. The whole APAC region is offline. We need a decision on whether to roll back yesterday’s update or try the emergency patch.”
Sarah, the CTO of a growing fintech company, felt that familiar knot in her stomach. She had maybe 70% of the information she needed. The patch might fix everything—or it might corrupt their database. Rolling back was safer but would erase a day’s worth of transactions that would need manual reconciliation. Thousands of customers and millions in transactions hung in the balance.
We’ve all been there—maybe not with servers crashing at 2 AM, but facing decisions where the full picture is frustratingly out of reach. The promotion offer that requires an answer before you’ve finished interviewing elsewhere. The house you love that has multiple offers coming in by tomorrow. The medical treatment option that needs a decision now, despite conflicting expert opinions.
The Illusion of Certainty
“I just need a little more information, then I’ll decide,” says everyone, everywhere, all the time. It’s the most natural human response to uncertainty. But as Charlie Munger, Warren Buffett’s late business partner and the philosophical genius behind Berkshire Hathaway, often pointed out: “Acknowledging what you don’t know is the dawning of wisdom.”
I learned this lesson the hard way during my first startup. We delayed launching our product for months, constantly tweaking features based on endless customer interviews. “Just one more round of feedback,” became our mantra. Meanwhile, our competitor launched a simpler version, captured the market, and rendered our “perfect” product irrelevant before it even debuted.
The truth is, certainty is usually an illusion. Even decisions we think are based on complete information often aren’t—we just don’t recognize what we’re missing.
Learning from Those Who Decide in the Dark
Navy SEAL commander Mark Divine describes making life-or-death decisions with severely limited intel as “standard operating procedure.” During one particularly harrowing mission in Afghanistan, his team had to decide whether to proceed with an extraction based on satellite imagery that was 12 hours old and reports from sources of questionable reliability.
“We developed a saying,” Divine told me during an interview for this article. “You’ll never have all the information you want, but you usually have all the information you need.”
Divine’s team uses a framework called the OODA Loop (Observe-Orient-Decide-Act), developed by military strategist John Boyd. The key insight isn’t just making the best decision with available information—it’s making it faster than your opponent can respond, then adjusting based on results.
This approach translates remarkably well to civilian life. When Jessica Chen launched her marketing consultancy, she faced entrenched competitors with deeper client relationships and bigger budgets. “I couldn’t outspend them on market research,” she explains, “so I had to outmaneuver them with speed.”
Jessica implemented rapid two-week experimental campaigns for clients rather than the industry-standard three-month strategies. “We’d get real data quickly, adjust, and improve. By the time competitors finished their perfect plan, we’d already found what actually worked through three iterations.”
The 70% Solution
Marine Corps leadership teaches what they call the “70% Solution”—when you have 70% of needed information and 70% confidence in your analysis, it’s time to act. Waiting for the remaining 30% often costs more in opportunity loss than occasional mistakes from acting on incomplete information.
This principle saved Miguel Fernandez’s construction business during the pandemic. When supply chains first showed signs of disruption, Miguel had incomplete information about how bad things might get. Rather than waiting for clarity, he secured extended inventory at the 70% confidence threshold.
“Some thought I was overreacting,” Miguel recalls. “But six months later, when competitors couldn’t get basic materials and their projects stalled, we were still operating. The information wasn’t perfect, but it was enough.”
Bayesian Thinking: Your New Best Friend
Thomas Bayes was an 18th-century minister and mathematician who developed a framework for updating beliefs as new evidence emerges. While the math can get complex, the core insight is simple and powerful: start with your best guess (prior probability), then systematically adjust as new information arrives.
Rachel Wong, a venture capital investor, applies this approach to startup funding decisions. “For each investment, I assign an initial confidence level based on available information—maybe 60% confidence this company will succeed. Then I identify the specific pieces of missing information that would most change my assessment.”
Rather than trying to resolve all uncertainty (impossible), Rachel focuses on the highest-value information gaps. “If user retention data would move my confidence from 60% to 80%, that’s where I focus my due diligence. If the founding team’s previous experience would only shift me from 60% to 65%, that’s less important to verify.”
This prioritization of information gaps is something intelligence analysts at the CIA call “collection requirements”—identifying precisely what missing information would most improve your decision.
Munger’s Mental Models
Charlie Munger famously advocated building a “latticework of mental models” from various disciplines. This approach is particularly valuable when information is limited, as it allows you to view problems through different lenses.
When Lakshmi Desai needed to decide whether to accept a job across the country, she applied multiple mental models to her incomplete information:
- Opportunity cost (economics): What alternatives am I giving up?
- Regret minimization (psychology): Which choice would I more likely regret at age 80?
- Expected value (mathematics): Multiplying potential outcomes by their probabilities
- Inversion (problem-solving): Instead of asking “Will this job make me happy?” she asked, “What would make this job decision a disaster?”
“No single model gave me a definitive answer,” Lakshmi explains, “but together they highlighted aspects of the decision I was overlooking. I realized I was overweighting salary and underweighting the value of being near family as I started thinking about having children.”
Overcoming the Psychological Barriers
Our brains evolved to crave certainty. Neuroscience research shows that uncertainty activates the same brain regions associated with physical pain, explaining why we find it so uncomfortable.
David Ramirez, an emergency room physician, deals with this discomfort daily. “In the ER, you’re constantly making high-stakes decisions with limited information. A patient arrives with chest pain—is it a heart attack or indigestion? The full test results won’t be back for hours, but you need to decide on treatment now.”
David’s approach: “I explicitly acknowledge the uncertainty to myself and sometimes to the patient. ‘Based on what we know right now, this is the best course of action.’ This mental framing prevents decision paralysis.”
For non-medical decisions, David recommends a technique called “premortems”—imagining your decision has failed and working backward to identify what might have gone wrong. “This helps identify information gaps you might be overlooking and prepares contingency plans.”
Type 1 vs. Type 2 Decisions
Amazon founder Jeff Bezos distinguishes between “Type 1” decisions (irreversible, high-impact) and “Type 2” decisions (reversible, less consequential). Most decisions, he notes, are Type 2 but we often treat them like Type 1.
When Raj Patel was considering whether to invest his savings in a friend’s startup, he initially approached it as a Type 1 decision, agonizing over incomplete financial projections and market analyses. Then he realized: “I could start with a smaller investment amount. If things went well, I could invest more later. If not, I’d learn an affordable lesson.”
By reframing it as a Type 2 decision, Raj found a way forward despite incomplete information. He made a modest initial investment, established clear milestones for increasing his stake, and created a decision path that could adapt as new information emerged.
Building Your Decision Journal
Professional poker player Annie Duke recommends keeping a decision journal to improve decision-making under uncertainty. For important decisions, record:
- The situation and constraints you faced
- The information you had available (and what was missing)
- Your decision and reasoning
- Your confidence level
- The eventual outcome
- Reflections on what you learned
Michael Torres, a real estate investor, credits this practice with transforming his business. “I was making gut decisions on properties and had mixed results. The journal helped me see patterns—I was overvaluing cosmetic features and undervaluing structural issues because the former were more visible in limited viewing time.”
After six months of journaling, Michael’s confidence calibration improved dramatically. “I now know when my ‘80% confident’ actually means 80%, not 60% or 95%. That alone has been worth thousands.”
The Paradox of Wisdom
Perhaps the most profound insight about decision-making under uncertainty comes from ancient wisdom. Socrates was declared the wisest man in Athens not because he possessed all knowledge, but because he recognized the limits of his knowledge.
This paradox remains true today: those most capable of making good decisions with limited information are precisely those who most clearly recognize the limitations of their knowledge.
As Charlie Munger put it: “It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent.”
In my own career, I’ve found this humility to be the foundation of good decision-making. When launching my second startup after the failure of my first, I began by explicitly listing what I didn’t know about the market. This acknowledgment of my information gaps led to focused research questions rather than paralysis.
The startup succeeded not because I had perfect information—I didn’t—but because I made reasonable decisions with the information available, built in feedback mechanisms to learn quickly, and remained adaptable as new information emerged.
In your next fog-of-war decision moment, remember: the goal isn’t perfect information (impossible) or perfect decisions (also impossible), but rather a thoughtful process that acknowledges uncertainty while still moving forward. As the old sailing wisdom goes: “We cannot direct the wind, but we can adjust the sails.”
The fog may never fully lift. Learn to navigate within it, and you’ll reach destinations others only dream about.