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Leantensify Learn

Lessons

Grouped by unit. If you want them in the order to take them, the course page resolves the prerequisites for you.

30 lessons, about 403 minutes of work. Every one ends in a tool you operate on real data — not a screenshot of one. All free, no account needed to read.

Reading numbers honestly

Before any method, the skill everything else rests on: telling whether a number that moved actually means anything, and saying so out loud when it does not.

  1. Signal or noise: reading a number that movesFoundation · 14 min · 2 tools
  2. The average that describes nobodyFoundation · 13 min · 1 tool
  3. Work is a process, and somebody is waiting at the end of itFoundation · 12 min · 1 tool
  4. The difference between what hurts and what caused itFoundation · 11 min · 1 tool
  5. Two people, one measurement, different answersFoundation · 14 min · 1 tool
  6. The best worker, and why they are notFoundation · 13 min · 1 tool

Seeing waste

Learn to look at work the way an improvement practitioner does: as a flow of value interrupted by things nobody would pay for.

  1. The eight wastes: what you are actually looking atWhite Belt · 13 min · 1 tool
  2. The 4% problem: how much of your process is actually worth paying forWhite Belt · 12 min · 1 tool

The method

DMAIC is a sequence, not a checklist. Learn what each phase produces, why the order is load-bearing, and how to state a problem without smuggling a solution into it.

  1. DMAIC: what each phase produces and why the order holdsWhite Belt · 12 min · 1 tool
  2. Writing a problem statement that does not contain its own answerWhite Belt · 12 min · 1 tool
  3. The hidden factory: why every step passes and the process failsWhite Belt · 13 min · 1 tool
  4. Mapping the gaps, not the boxesWhite Belt · 12 min · 1 tool
  5. Go and see: what a walk gives you that a report cannotWhite Belt · 12 min · 1 tool
  6. Scoping a project you can actually finishWhite Belt · 13 min · 1 tool
  7. PDCA: the Check is the part everybody skipsWhite Belt · 14 min · 1 tool
  8. 5S: why the tidy area keeps going backWhite Belt · 12 min · 1 tool

Finding causes

Most problems get solved by treating a symptom. These are the two cheapest tools for getting past that, and the judgement to know when each has gone far enough.

  1. Pareto: finding the few categories that carry the problemWhite Belt · 12 min · 1 tool
  2. 5 Whys: knowing when you have reached a cause you can act onWhite Belt · 11 min · 1 tool
  3. Fishbone: widening the search before you narrow itWhite Belt · 13 min · 1 tool

Control and capability

Two questions that get confused constantly: is the process behaving consistently, and is consistent good enough? They have different answers, different charts, and different consequences when you get them the wrong way round.

  1. Control limits are not specification limitsYellow Belt · 15 min · 1 tool
  2. Capable, or just in control?Yellow Belt · 15 min · 1 tool
  3. Measuring the gauge before you measure the processYellow Belt · 15 min · 1 tool

Comparing things honestly

Every change ends with the same question: is this difference real? The arithmetic is one line. Almost every failure in practice is in what the number gets taken to mean.

  1. Is this difference real? And is it big enough to care about?Green Belt · 15 min · 1 tool

Relationships between measurements

A regression always returns a slope, an intercept and an R-squared — whether or not a straight line was ever the right shape. The residual plot is the part that tells you which.

  1. Two things move together. Now what?Green Belt · 15 min · 1 tool
  2. What the fitted line is hidingGreen Belt · 15 min · 1 tool

More than two groups

A significant F says at least one group differs. It says nothing about which — and finding out by running every pair is how a study with no real differences produces one anyway.

  1. Four suppliers, one answer, and the question it does not answerGreen Belt · 15 min · 1 tool

Experiments that change everything at once

One factor at a time feels careful and cannot see interactions — the factors whose right setting depends on each other. A factorial runs every combination, and every run informs every effect.

  1. Change everything at once, carefullyGreen Belt · 15 min · 1 tool

Screening designs, and the price of a fraction

A full factorial doubles with every factor. A fraction buys breadth with confounding — and the bill is computable to the letter, before a single run is booked.

  1. Half the runs, and knowing exactly what you gave upBlack Belt · 15 min · 1 tool

Finding the setting, not just the factor

Two levels cannot describe a curve. Adding the third finds where the gradient is zero — and the harder question is whether that point is a maximum, a minimum, or a saddle that is no optimum at all.

  1. The gradient is zero here. That is not the same as best.Black Belt · 15 min · 1 tool

How many, and what it could show

The difference worth detecting, the sample size, alpha and power are one equation — so a study whose size nobody argued about has already settled one of them by accident. Solving it in whichever direction the project has left open is what stops a real improvement being written up as "no significant difference".

  1. The study you can afford, and what it can actually seeMaster Black Belt · 15 min · 1 tool