The DECIDE BETTER® method

Your gut is a data set. Audit it.

Intuition is compressed experience: reliable in familiar situations, unreliable in novel ones. Intuition and information are partners, and you need a method for when they disagree. When they do, that is the cheapest research you will ever get.

Five rules

The gut sets the bar. The data tests it. You stay accountable.

  1. 01

    Set the bar before you see the data.

    Make your gut testify. Before you open the report or run the model, write down what you expect and the result that would change your mind. Say it to your team.

  2. 02

    Check confirming data as hard as contradicting data.

    If the numbers agree with you, audit them as aggressively as the numbers that do not. We are just not wired to be contrarian to our own beliefs.

  3. 03

    Make sure the data answers your question.

    Every data set answers somebody's question. Make sure it's yours, or you end up precisely wrong and only generally right.

  4. 04

    Decide on the ingredients, not just the answer.

    Name the criteria and weigh them before you argue about the winner. Not everything matters equally; saying so is just not wanting to do the work.

  5. 05

    Never make a decision you can't explain.

    If you cannot say how you got there, the tool decided, not you. The gut sets the bar. The data tests it. You stay accountable for the call.

Match rigor to stakes

Mundane, Important, Epic.

Spend more time on decisions you cannot undo. Spend almost none on the ones you can.

Mundane

Set it, forget it.

Low stakes and easy to undo. Let system one handle it, use a template, and save your attention for what matters.

For example: Vendor renewals, routine scheduling, a team lunch.

Important

Measure twice.

Real consequences, partly reversible. Bring information to the table, weigh the criteria, and invite a second view.

For example: A key hire, a new program, a budget reallocation.

Epic

Measure twice, cut once, seek wise counsel.

Hard or impossible to undo: acquire, shut down, let a key person go. Spend more time on decisions you cannot undo. Run the premortem and the red team.

For example: Mergers, closures, decade-defining investments.

Premortem

Why wait for the postmortem? Run the premortem.

Before you act, imagine it is a year from now and the decision has failed. Each person writes down why. The reasons that surface are the risks you can still do something about. Some teams call it a before-action review.

Red team

Red team your decisions before they are made.

Give someone the job of arguing the other side, with real time and real authority. Those who are often quiet have the most to say: at the edges of the organization is where you will find the greatest signal to noise. Then disagree and commit.

The library

Biases, fallacies, razors and practices.

The canon of decision-making is available but locked up. The Volley library unlocks it: each entry has a meaning, an example and a mitigation. Search it here; save favorites and track completions in the app.

biases, fallacies, razors and practices in the library

Featured entries

Anchoring biasCognitive Biases · Perception
Meaning
Relying too heavily on the first number or idea you hear, then adjusting too little from it.
Example
A board sets next year's budget by nudging last year's figure up 3 percent instead of asking what the work actually needs.
Mitigation
Set the bar before you see the data: write your own estimate first, then compare it with the anchor on the table.
Read more on Wikipedia (opens in a new tab)
Availability heuristicCognitive Biases · Memory
Meaning
Judging how likely something is by how easily examples come to mind.
Example
After one vivid donor complaint, a team concludes donor satisfaction is falling, though the survey says otherwise.
Mitigation
Ask for the base rate. Count the cases instead of recalling them.
Read more on Wikipedia (opens in a new tab)
Confirmation biasCognitive Biases · Belief
Meaning
Seeking out and favoring information that confirms what you already believe.
Example
A leader checks the numbers that contradict the plan line by line, and waves through the numbers that support it.
Mitigation
Check confirming data as aggressively as contradicting data. Assign someone to argue the other side.
Read more on Wikipedia (opens in a new tab)
Decoy effectBehavioral Economics · Perception
Meaning
Adding a clearly worse third option changes which of the original two people pick.
Example
A middle pricing tier looks like a bargain only because a lopsided premium tier sits next to it.
Mitigation
Remove dominated options and compare the real alternatives head to head.
Read more on Wikipedia (opens in a new tab)
Devil's AdvocateBest Practices · Learning
Meaning
One person deliberately argues against the prevailing view to test it.
Example
In a hiring decision, one panelist argues the case for the runner-up candidate.
Mitigation
Rotate the role so dissent is expected, not personal.
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Dunning-Kruger effectCognitive Biases · Perception
Meaning
People with limited skill in an area tend to overestimate their ability in it.
Example
A new manager is certain the vendor selection is simple, while the procurement lead sees six open risks.
Mitigation
Ask the people closest to the work to rate your plan. Compare self-ratings with outcome data.
Read more on Wikipedia (opens in a new tab)
Endowment effectBehavioral Economics · Money
Meaning
Valuing something more simply because you already own it.
Example
A team rates its homegrown tool far above an equivalent product it would never have built.
Mitigation
Ask what you would pay to acquire it today if you did not already have it.
Read more on Wikipedia (opens in a new tab)
Framing effectCognitive Biases · Perception
Meaning
Reaching different decisions from the same facts depending on how they are presented.
Example
"90 percent of grants succeed" wins approval where "1 in 10 grants fails" would not.
Mitigation
Restate the option in the opposite frame before you decide.
Read more on Wikipedia (opens in a new tab)
GroupthinkCognitive Biases · Social
Meaning
A group's desire for harmony overrides a realistic look at the alternatives.
Example
Nobody objects in the meeting; three people raise concerns in the hallway afterward.
Mitigation
Collect inputs privately before discussion. Invite the quiet voices at the edges first.
Read more on Wikipedia (opens in a new tab)
HALT: Hungry, Angry, Lonely, TiredEmotional Biases · Emotional
Meaning
Hungry, angry, lonely or tired: four states that quietly degrade decisions.
Example
A late-night email approving a vendor change goes out after a 14-hour day.
Mitigation
Before an important decision, check HALT. If any apply, set a time to decide tomorrow.
Hindsight BiasCognitive Biases · Memory
Meaning
After an outcome is known, believing you saw it coming all along.
Example
After a launch fails, everyone remembers having doubts that no one wrote down.
Mitigation
Journal your expectation and your reasons before the result arrives, then compare.
Read more on Wikipedia (opens in a new tab)
Hyperbolic DiscountingBehavioral Economics · Money
Meaning
Preferring smaller rewards now over larger rewards later, more than reason supports.
Example
A program skips the data cleanup that would pay off next year for a quick dashboard this month.
Mitigation
Put the later payoff in today's terms and commit in advance.
Read more on Wikipedia (opens in a new tab)
Imposter SyndromeEmotional Biases · Emotional
Meaning
Doubting your own competence despite evidence, and fearing you will be found out.
Example
A capable new director defers every call to the board rather than trust her own analysis.
Mitigation
Write down the evidence for your competence and decide on the ingredients, not on your nerves.
Read more on Wikipedia (opens in a new tab)
Loss AversionBehavioral Economics · Money
Meaning
Losses feel about twice as painful as equal gains feel good.
Example
A foundation turns down a promising program to avoid a small chance of a public misstep.
Mitigation
Frame each option as both a gain and a loss, and compare expected values.
Read more on Wikipedia (opens in a new tab)
Optimism biasEmotional Biases · Emotional
Meaning
Believing you are less likely than others to experience a bad outcome.
Example
A team assumes its data migration will be the one that has no surprises.
Mitigation
Run a premortem and assign a probability to each failure path.
Read more on Wikipedia (opens in a new tab)
Overconfidence effectCognitive Biases · Perception
Meaning
Being more sure of your judgments than the evidence justifies.
Example
A team gives a 90 percent chance of hitting a date it has missed three times before.
Mitigation
Think probabilistically and speak probabilistically: give ranges, then check your track record.
Read more on Wikipedia (opens in a new tab)
Post-mortem analysisBest Practices · Learning
Meaning
A structured review after an outcome to learn what happened and why.
Example
After a grant cycle, the team compares what it expected with what happened, criterion by criterion.
Mitigation
Review the process, not just the outcome; good decisions can still meet bad luck.
Read more on Wikipedia (opens in a new tab)
Pre-mortem analysisBest Practices · Learning
Meaning
Imagine the decision has already failed, then explain why it failed, before you act.
Example
Before a migration, the team lists the five most likely reasons it would be a disaster in six months.
Mitigation
Why wait for the postmortem? Run the premortem. Assign an owner to each failure path.
Read more on Wikipedia (opens in a new tab)
Red TeamingBest Practices · Learning
Meaning
Assigning people to attack a plan the way a skeptic or adversary would.
Example
A red team argues that a new portal will overwhelm the two staff who must approve submissions.
Mitigation
Red team your decisions before they are made. Give the red team real time and real authority.
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Scenario PlanningBest Practices · Learning
Meaning
Building several plausible futures and testing a decision against each one.
Example
A ministry tests its five-year plan against a currency shock, a leadership change and a giving surge.
Mitigation
Pick scenarios that would change your choice, not just ones that are easy to imagine.
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Status Quo biasCognitive Biases · Belief
Meaning
Preferring things to stay as they are, even when a change would serve you better.
Example
A ministry keeps a spreadsheet process that costs a full day a week because switching feels risky.
Mitigation
Score the current state as one of the alternatives, with the same criteria as the others.
Read more on Wikipedia (opens in a new tab)
Straw Man fallacyCognitive Biases · Belief
Meaning
Misrepresenting someone's argument so it is easier to knock down.
Example
"So you want to stop funding the field entirely?" in reply to a request for one more site visit.
Mitigation
Restate the other person's argument until they agree it is fair, then respond.
Read more on Wikipedia (opens in a new tab)
Sunk Cost fallacyBehavioral Economics · Money
Meaning
Continuing an effort because of what you already spent, not because of what it will return.
Example
A failing system stays in place because "we already paid for three years of licenses."
Mitigation
Ask: if we were starting today, would we choose this? Judge only future costs and benefits.
Read more on Wikipedia (opens in a new tab)
Survivorship biasCognitive Biases · Memory
Meaning
Drawing conclusions only from the cases that made it through a filter, and ignoring the ones that did not.
Example
A grant committee studies its five most successful projects and copies their traits, never looking at the projects that failed.
Mitigation
Ask what the missing cases would show. Pull the full list, including the failures.
Read more on Wikipedia (opens in a new tab)
The IKEA effectBehavioral Economics · Perception
Meaning
Placing extra value on things you built yourself.
Example
A custom intake form survives every review because the team assembled it by hand.
Mitigation
Have someone outside the build team score it against the alternatives.
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The Mom TestBest Practices · Learning
Meaning
Ask people about their past behavior, not their opinion of your idea, so even your mom cannot lie to you.
Example
Instead of "Would you use a donor portal?" ask "How did you last check on a gift you made?"
Mitigation
Ask about specifics in the past. Listen for what people already spend time and money on.
The Ulysses ContractBehavioral Economics · Money
Meaning
A decision made in advance that binds your future self against a known temptation.
Example
A board agrees before the cycle opens that no grant skips due diligence, however urgent it feels.
Mitigation
Write the rule down while calm, with a named person to hold you to it.
Read more on Wikipedia (opens in a new tab)
Zeigarnik effectCognitive Biases · Memory
Meaning
Unfinished tasks stay on your mind more than finished ones.
Example
An open decision about a key hire crowds out attention for everything else on the agenda.
Mitigation
Close the loop: decide, or set a dated check-in so the decision can rest.
Read more on Wikipedia (opens in a new tab)

All 116 entries

  • Actor-Observer bias
  • Ad hominem
  • After-Action Review
  • Anchoring bias
  • Appeal to Authority
  • Attribution bias
  • Authority bias
  • Automation bias
  • Availability heuristic
  • Backfire effect
  • Bandwagon effect
  • Barnum effect
  • Base Rate fallacy
  • Begging the Question
  • Belief bias
  • Ben Franklin effect
  • Blind Spot bias
  • Blue Teaming
  • Broken Windows theory
  • Bystander effect
  • Choice-Supportive bias
  • Circular reasoning
  • Clustering Illusion
  • Composition fallacy
  • Confirmation bias
  • Conservatism Bias
  • Courtesy bias
  • Cryptomnesia
  • Curse of Knowledge
  • Decision Trees
  • Decoy effect
  • Delayed Gratification
  • Devil's Advocate
  • Discounting Positive Feedback
  • Dunning-Kruger effect
  • Egocentric bias
  • Embrace Diverse Perspectives
  • Endowment effect
  • False Consensus effect
  • False Dilemma
  • Fear of Success/Failure
  • Framing effect
  • Fundamental Attribution Error
  • Gambler's fallacy
  • Groupthink
  • Halo effect
  • HALT: Hungry, Angry, Lonely, Tired
  • Hanlon's Razor
  • Hindsight Bias
  • Hot Hand fallacy
  • Hyperbolic Discounting
  • Illusion of Control
  • Illusion of Validity
  • Illusory correlation
  • Implicit bias
  • Imposter Syndrome
  • In-group bias
  • Just-World fallacy
  • Law of the Instrument
  • Listen Mode
  • Loss Aversion
  • Matthew effect
  • Mere-Exposure effect
  • Negativity bias
  • Neglect of Probability
  • Occam's Razor
  • Optimism bias
  • Ostrich effect
  • Out-group homogeneity bias
  • Outcome bias
  • Outgroup bias
  • Overconfidence
  • Overconfidence effect
  • Parkinson's law
  • Perfectionism
  • Pessimism bias
  • Placebo effect
  • Post hoc ergo propter hoc
  • Post-mortem analysis
  • Post-Purchase Rationalization
  • Pre-mortem analysis
  • Pro-Innovation bias
  • Reactance
  • Reactive Devaluation
  • Recency effect
  • Red Herring effect
  • Red Teaming
  • Risk Compensation
  • Scenario Planning
  • Selective Perception
  • Self-Deprecating Humor
  • Self-Serving bias
  • Serial-Position effect
  • Slippery Slope fallacy
  • Social Comparison bias
  • Spotlight effect
  • Status Quo bias
  • Stereotyping
  • Straw Man fallacy
  • Sunk Cost fallacy
  • Survivorship bias
  • The Arena Razor
  • The Feynman Razor
  • The Google effect
  • The Gratitude Razor
  • The IKEA effect
  • The Lion Razor
  • The Lunch Razor
  • The Mom Test
  • The Optimist Razor
  • The Rooms Razor
  • The Ulysses Contract
  • Third-Person effect
  • Tu quoque fallacy
  • Zeigarnik effect
  • Zero-Risk bias