Comparing by fit
Two ways of thinking, side by side. There is no winner here — read across each row and choose the one that fits your situation.
Decision Making
Strip a problem back to what must be true, then rebuild — instead of copying what exists.
By 6days
Decision Making
Observe, orient, decide, act — and win by cycling faster than the situation changes.
By 6days
When to use — First-Principles Thinking
Use it when an industry's costs or practices have been stable for a long time without obvious justification, when you are entering a field as an outsider and lack the incumbents' assumptions, or when repeated incremental attempts have all failed and the problem may be framed wrongly.
When to use — OODA Loop
Use it in genuinely competitive, fast-changing situations — an incident, a live negotiation, a competitor's surprise move, a crisis. It suits environments where information is incomplete by nature and waiting for completeness means losing.
When not to use — First-Principles Thinking
Avoid it for routine decisions — it is slow, effortful, and analogy is right most of the time. It is also a common vehicle for arrogance: reasoning from first principles while lacking domain knowledge tends to rediscover why the convention exists, expensively. If experts cannot explain why a practice exists, that is worth investigating; if they can, listen.
When not to use — OODA Loop
Avoid it for decisions that are expensive to reverse and slow-moving: a factory site or a pension scheme does not want tempo, it wants analysis. It is widely misread as 'decide fast', which drops the orient step and produces speed without judgement. It also has little to say where there is no adversary and no clock.
Most reasoning is analogy: we do it this way because that is how it is done, because the incumbent does it, because we did it last time. Analogy is efficient and usually right, which is exactly why it is dangerous — it carries forward constraints that were real once and quietly expired. Whole industries hold assumptions nobody has tested in decades, because testing them was never anyone's job.
In fast-moving situations the quality of a decision decays with time. A team gathers information, builds consensus, and commits — and by the time it acts, the situation has moved and the decision addresses a world that no longer exists. Meanwhile a less careful competitor has already acted three times, learned from each, and is operating against a picture of reality that is simply more current than yours.
First-principles thinking decomposes a problem to the things that must be true — physics, arithmetic, contract terms, hard constraints — and reasons upward from there, deliberately ignoring how the problem is currently solved. The hard part is not the rebuilding; it is telling a real constraint from an inherited convention. 'Water boils at 100°C at sea level' is a principle. 'Enterprise software is sold through channel partners' is a convention wearing a principle's clothing. The method is expensive and usually unnecessary — its value is concentrated in the rare cases where a load-bearing assumption is simply wrong.
The OODA loop describes decision-making as a continuous cycle: observe what is happening, orient by making sense of it against your models and experience, decide on a course, act, then observe the results and go again. Its central claim is comparative — in a contest, whoever cycles faster and more accurately accumulates an advantage, because their opponent is perpetually responding to a stale picture. Orientation is the pivot and the part most often skipped: it is where prior beliefs distort what the observations mean, and a fast loop feeding a broken orientation just produces confident errors at speed.
Write the problem so that no current approach is embedded in the wording. 'How do we make our call centre more efficient' has assumed a call centre. 'How do customers get their question answered' has not, and the two questions have very different answer sets.
Write down everything you believe about the problem, especially what feels too obvious to state. The load-bearing assumptions are always the ones nobody thought worth writing down, because obviousness is what protects them from scrutiny.
For each, ask what would happen if it were false, and demand evidence for why it holds. Laws of physics, arithmetic, and binding contracts survive. Industry practice, precedent, and 'the customer expects it' usually turn out to be conventions that someone chose, under conditions that may no longer apply.
Construct a solution using nothing but the constraints that survived. Do not check it against the existing approach yet — the comparison will pull you back toward the familiar before the new idea has finished forming.
Not specified
An ordered process with 4 phases.
Gather what is actually happening — raw signals, unfiltered.
Make sense of it, and challenge the frame you are imposing.
Commit to a course while information is still incomplete.
Worked example — First-Principles Thinking
A team is quoted £40,000 for a piece of lab equipment and treats it as fixed. Decomposed: what is it actually made of? A precision stage, a camera, a light source, a controller, an enclosure, and software. Priced as components, roughly £6,000. The remaining £34,000 is not physics — it is certification, low production volume, support, and margin, all of which are real costs but not laws. For a regulated clinical setting the £40,000 is justified and the analysis ends there. For an internal research rig that needs no certification, most of that gap is avoidable, and the team builds it for £9,000.
Worked example — OODA Loop
During a partial outage, one team convenes a call to establish full root cause before acting. Another observes that errors are concentrated in one region, orients on a recent config change to that region's load balancer, decides to roll it back despite not having proven causation, and acts within nine minutes. The rollback resolves it — and had it not, the negative result would itself have eliminated the leading hypothesis. The first team is still on the call, assembling a complete picture of a situation that the second team has already ended.
The idea is ancient: Aristotle described reasoning from first principles, and the method underpins mathematics and physics as disciplines. Its modern circulation in business owes much to engineering culture and to founders who have publicly credited it for cost-structure decisions. It is common intellectual heritage rather than anyone's proprietary framework.
The loop was developed by John Boyd, a United States Air Force colonel and military strategist, from the 1970s onward, initially to explain air combat outcomes and later generalised into a broader theory of competition and adaptation. Boyd published little formally, working mainly through briefings, so the model circulates through interpreters — and popular versions often flatten the orientation stage he considered central.
Set the rebuilt solution against the status quo. Often the status quo wins, which is a real and useful result: you now know why it is right rather than merely inheriting it. Occasionally the gap is enormous, and that is what the whole exercise was for.
Gather what is actually happening — raw signals, not the summary someone assembled to support a position. Most organisations observe through reporting layers that have already discarded the anomalies, which are precisely the observations that matter.
Interpret the observations against your models, and deliberately ask what frame you are imposing and what it might be hiding. This is the step that determines everything downstream and the one under time pressure that gets skipped. A fast wrong orientation is worse than a slow right one.
Commit to a course knowing you do not have everything. Waiting for certainty is itself a decision — usually the worst one available, because it hands the tempo to whoever is willing to move.
Execute in a way that generates information. A well-chosen action resolves uncertainty as well as making progress, which means the next observation step starts from a better place than the last.
Feed results straight back into observation, and treat cycle time as a metric in its own right. The advantage does not come from any single pass; it comes from the rate.
Execute so the action itself teaches you something, then loop.