Decision Making With Incomplete Information: How Entrepreneurs Do It
Waiting for better information is also a decision, and it has a cost.
Every entrepreneur eventually reaches a moment when a choice has to be made before the facts are in. Right now, that moment feels more common. In the NFIB’s September survey, the Small Business Uncertainty Index rose to 90, well above its historical average of 68, and only 7% of owners said it was a good time to expand.¹
Here is what research and well-documented practice say about how entrepreneurs handle that.
Decision Making With Incomplete Information Starts With the Type of Decision
Amazon’s shareholder letters offer a useful starting point. In 2015, Jeff Bezos separated decisions into two types: Type 1 decisions are consequential and nearly irreversible, like one-way doors, and deserve careful, slow deliberation. Type 2 decisions are changeable and reversible, like two-way doors, and can be made quickly by high-judgment individuals or small groups.² His 2016 letter warned that as organizations grow, they tend to apply the heavy Type 1 process to most decisions, and added a rule of thumb: most decisions should be made with around 70% of the information you wish you had, because waiting for 90% usually means being slow. He paired it with a condition: you have to be good at recognizing and correcting bad decisions quickly.²
A caution: the 70% figure is a rule of thumb from a shareholder letter, not a research finding. The more durable idea is the sorting question: is this decision reversible?
Figure 1: "Which kind of decision is this?”
What Expert Entrepreneurs Actually Do
The best-known research on entrepreneurial decisions under uncertainty is Saras Sarasvathy’s. In a verbal protocol study of 27 expert entrepreneurs, who were asked to think aloud about a single new product, she found a pattern she called effectuation: a logic of control rather than a logic of prediction.³ ⁴ The experts she studied had founded multiple ventures and taken companies public.⁴
Instead of setting a goal and calculating the best path to it, they started with the means available and focused on what they could control. Her work describes five principles:³
Bird in hand: start with who you are, what you know, and whom you know.
Affordable loss: decide what you can afford to lose, instead of calculating expected returns.
Crazy quilt: build partnerships with people who commit to the venture.
Lemonade: treat surprises as material to work with.
Pilot in the plane: focus on the parts of the future you can influence.
Experts used both logics: effectuation was not a rejection of planning, and the research draws the boundary between the two.⁴ The takeaway for an owner isn’t to stop forecasting. It is to ask, for each commitment, what the most is that can be lost without ending the business.
The Gap Between Confidence and Base Rates
Confidence can stand in for information. In a classic 1988 study of 2,994 people who had recently become business owners, 81% rated their odds of success at 7 out of 10 or better, and 33% rated them at 10 out of 10. They saw the odds for similar businesses as lower, and the authors concluded that owners’ views of their own chances were detached from statistics on business survival and from peer businesses.⁵
Base rates give a reference point. The Bureau of Labor Statistics tracks every new private-sector establishment with employees. Through March 2025, about 78% of establishments born in the year ended March 2024 survived their first year, 51.4% of the 2020 cohort survived five years, and 34.7% of the 2013 cohort survived ten.⁶
Two cautions apply. The 1988 sample is old, and “success” in that study and “survival” in the BLS data are different measures. Establishment exits also include closures that were not failures.⁶ The two sets of numbers don’t prove a verdict. They do suggest that asking what usually happens to businesses like yours is a cheap form of information.
Figure 2: “Confidence vs. base rates.”
Tools That Make Incomplete Information Safer
Cap the downside. The affordable loss principle turns an open-ended bet into a bounded one.³
Run a pre-mortem. Psychologist Gary Klein popularized the technique in a 2007 Harvard Business Review article: a team assumes the project has already failed, and each person writes down why.⁷ It builds on a 1989 study that found imagining an event as already having happened increased the number of reasons people generated by about 30%. That study did not assess the quality of the reasons, and a review describes the academic literature on pre-mortems as thin, though later work found it reduced overconfidence.⁷
Stage the commitment. Reversible steps, such as a pilot or a limited launch, convert a one-way door into a series of two-way doors.²
Check the base rate. Before deciding, ask what usually happens in situations like this one.⁶
What Remains Unclear
The evidence has limits. Sarasvathy’s sample of 27 is small and made up of successful founders, so it cannot show that effectual reasoning causes success. Cooper’s study dates to the 1980s. The 70% rule is a practitioner’s heuristic. Pre-mortem research is thin, and BLS data measure establishment exits, not business failure.² ³ ⁵ ⁶ ⁷ None of these frameworks predicts outcomes. They help an owner structure a decision, and they don’t replace judgment.
Questions to Ask Before You Decide
Is this decision reversible, and how quickly can I tell if I’m wrong?
What is the most I can lose, and can the business absorb it?
What would have to be true for this to work, and what is the cheapest way to test it?
If this failed a year from now, what would the most likely reason be?
What usually happens to businesses like mine in this situation?
What am I waiting for, and will it arrive before the window closes?
What I find interesting is that waiting is also a decision, and it carries its own risk. The goal isn’t certainty. It is knowing which risks you can afford, and which information is actually worth waiting for.
Sources
¹ National Federation of Independent Business, “Uncertainty Grows and Optimism Fades Slightly on Main Street in September,” October 13, 2026, and Small Business Economic Trends, September 2026.
² Amazon.com, 2016 Letter to Shareholders; 2015 Letter to Shareholders (Type 1 and Type 2 decisions).
³ Saras D. Sarasvathy, “Causation and Effectuation: Toward a Theoretical Shift from Economic Inevitability to Entrepreneurial Contingency,” Academy of Management Review 26(2), 2001.
⁴ Saras D. Sarasvathy, “Effectual Reasoning in Entrepreneurial Decision Making: Existence and Bounds,” Academy of Management Proceedings, 2001 (study of 27 expert entrepreneurs); effectuation.org, “Effectuation 101.”
⁵ Arnold C. Cooper, Carolyn Y. Woo, and William C. Dunkelberg, “Entrepreneurs’ Perceived Chances for Success,” Journal of Business Venturing 3(2), 1988.
⁶ U.S. Bureau of Labor Statistics, Business Employment Dynamics, Table 7 (“Survival of private sector establishments by opening year”), data through March 2025.
⁷ Gary Klein, “Performing a Project Premortem,” Harvard Business Review, September 2007; Deborah Mitchell, J. Edward Russo, and Nancy Pennington, “Back to the Future: Temporal Perspective in the Explanation of Events,” Journal of Behavioral Decision Making, 1989; Jason Collins, “The premortem”
John Jezzini
Business Leader, Investor & Philanthropist
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