01 — Programme Outcome Map & Business Diagnostic
Programme: Lean Management & Factory Productivity
1. What you will learn
In this lesson you will learn to set ninety-day factory outcomes and test them with arithmetic before committing, and to run a diagnostic across the eight capabilities that determine whether a small factory can improve at all.
2. The idea explained
Factory outcomes should be expressed in the units the floor already counts: parts per week, minutes of changeover, percentage first-pass yield, days of lead time, weeks of work in progress. Expressed that way they can be verified by anyone standing at the machine, which is what makes them credible to the people who must deliver them.
The backward arithmetic is what separates a plan from a wish. Take the output you need, convert it into the cycle time and available time it requires on the constraint, and then list the specific changes that would produce it, each with its own measured contribution. If the changes you can name do not add up to the target, you do not have a plan, and you have discovered that on day one.
This is unusually easy to do in a factory, because everything converts into seconds on the constraint. A changeover improvement converts into run time. A yield improvement converts into good parts from the same run time. A layout change converts into either. Adding them up is straightforward arithmetic, and it prevents the common failure of a programme with five workstreams and no idea whether they collectively reach the goal.
The diagnostic covers eight capabilities. Measurement: are output, stoppages, rework and cycle times recorded daily? Constraint management: is the constraint known and is effort concentrated there? Changeover: is it measured and being reduced? Quality at source: are defects caught where they are made rather than at final inspection? Flow and layout: does material move a short distance in one direction? Standard work: does a documented, verified method exist for key operations? Visual management: can a stranger tell from the floor whether today is going well? People involvement: do operators raise and solve problems, or wait to be told?
Rate each from one to five on evidence. The last one, people involvement, is the one that determines whether any of the others survive, and it is the one most often scored generously.
Honest statement: lean work reliably reduces lead time and defects. Whether it raises profit depends on selling the freed capacity, and many factories improve substantially while their order book does not move.
Apply it
3. How to apply it in your own business
Write three outcomes in floor units, with a baseline, a target, an owner and a review date.
Do the backward arithmetic on the main one, listing each named change with its measured or estimated contribution in seconds or parts.
Run the diagnostic and give the first month to the two lowest, and be especially honest about people involvement.
Worked example
4. Worked example
Suresh's main outcome is to meet demand of one thousand two hundred parts a week without overtime.
His available time is two thousand two hundred minutes, which is one hundred and thirty-two thousand seconds. To produce one thousand two hundred parts in that time, his constraint would need an effective cycle of one hundred and thirty-two thousand divided by one thousand two hundred, which is one hundred and ten seconds. It currently runs at one hundred and forty-eight seconds, so the gap is thirty-eight seconds, or about twenty-six per cent.
He now lists what he can name.
The changeover improvement already measured releases three hundred and sixty minutes a week of run time, which is twenty-one thousand six hundred seconds. That does not change the cycle time but adds available seconds, so his capability becomes one hundred and thirty-two thousand plus twenty-one thousand six hundred, which is one hundred and fifty-three thousand six hundred seconds, divided by one hundred and forty-eight, which is about one thousand and thirty-eight parts.
That leaves him one hundred and sixty-two parts short of one thousand two hundred.
The second change is a tooling and method revision on the constraint operation, which his machinist believes will bring the cycle from one hundred and forty-eight to about one hundred and thirty-two seconds. At that cycle, one hundred and fifty-three thousand six hundred seconds produces about one thousand one hundred and sixty-four parts.
Still thirty-six short.
The third change is eliminating the sixty-two minutes a week the machine spends waiting for material, which is three thousand seven hundred and twenty seconds, giving about twenty-eight more parts at the improved cycle, taking him to about one thousand one hundred and ninety-two.
Three named changes reach about one thousand one hundred and ninety-two against a target of one thousand two hundred. He is eight parts short, which is within the noise of his measurements, and he writes it that way rather than declaring the target met.
The value of the exercise is that he now knows his plan is roughly sufficient rather than hoping it is, and that the tooling revision, which is the least certain of the three, carries the largest share. If it delivers only half of what the machinist expects, he will be about seventy parts short and will need a fourth change, which he starts thinking about now rather than in month three.
5. Common mistakes and how to fix them
The first mistake is setting outcomes in percentages the floor cannot verify. Fix it by using parts, minutes, days and pieces.
The second is running several workstreams without adding up their contributions. Fix it by converting each to seconds or parts on the constraint and totalling them.
The third is treating the estimated contribution of an unproven change as certain. Fix it by noting which change carries the most uncertainty and planning a further one in case.
The fourth is scoring people involvement generously. Fix it by asking when an operator last raised a problem unprompted, and scoring the honest answer.
Key takeaways
6. Board summary
Express factory outcomes in units the floor already counts, so anyone at the machine can verify them. Convert every named change into seconds or parts on the constraint, and check that they add up to the target. A plan whose named changes fall short of the target is a discovery worth making on day one. Note which change carries the most uncertainty, since that is where a shortfall will come from. People involvement determines whether any other capability survives, and it is the one most often scored generously.
Check your understanding
7. Practice and self-check
Question one: What effective cycle is needed for one thousand two hundred parts in one hundred and thirty-two thousand seconds? Answer: one hundred and ten seconds.
Question two: What is the gap from one hundred and forty-eight seconds, in seconds and per cent? Answer: thirty-eight seconds, about twenty-six per cent.
Question three: Adding twenty-one thousand six hundred seconds of run time at one hundred and forty-eight seconds gives what output? Answer: about one thousand and thirty-eight parts.
Question four: At a cycle of one hundred and thirty-two seconds with the same time, what is the output? Answer: about one thousand one hundred and sixty-four parts.
Question five: Adding three thousand seven hundred and twenty seconds at that cycle adds how many parts? Answer: about twenty-eight.
Question six: What is the total, and how should it be reported? Answer: about one thousand one hundred and ninety-two, reported as roughly sufficient and eight short rather than as the target met.
Question seven: Which change carries the most uncertainty? Answer: the tooling and method revision, which is unproven and contributes the largest share.
Question eight: How should people involvement be scored honestly? Answer: by asking when an operator last raised a problem unprompted and scoring that answer.