QUICK GUIDE

Measure to Save

An interactive infographic for leaders who want measurable results.

1. Define the Problem and Why It Matters

Don't say "we have a lot of scrap". Say "scrap on line 3 costs us €250,000 a year in material and rework, and it delays deliveries to customer X". Quantifying the pain makes it real and urgent.

2. Use the Right Framework

A good framework forces you to think clearly. Instead of jumping to solutions, define how you will measure success and which mistakes to avoid.

Mistakes to Avoid

  • Optimizing the symptom, not the cause.
  • Not measuring the final impact (€).

Success Metrics

  • Number of validated hypotheses.
  • Time to first result.

3. Learn from a Numerical Example

Abstract data doesn't motivate. A numerical example shows that change is possible and profitable.

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Scrap reduction in 10 days

Illustrative example: the scrap-reduction target to hit in 10 days with 3 micro-experiments.

4. Create a Simple Action Plan

You don't need a 100-page plan. Start with three clear steps and defined deadlines to build momentum.

Your Quick Action Plan

Today: Pick a recurring problem and quantify it.
In 7 days: Define a clear hypothesis and how you will measure it.
In 30 days: Run the first mini-experiment and measure the result.

5. Get the Template and Act

Ideas are the first step. The right tools help you execute them. Ask for our experimentation template to get off to a good start.

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💡 Quick Savings Calculator

Adjust the values and see the result in real time. The preloaded values are examples.

€500€3,000€20,000
5%15%40%
13 months12

Estimated annual savings

€5,400

Cumulative savings by month 3

€1,350

Progress towards the first year

Summary and Next Steps

You've learned why measuring matters. Now focus on these points to turn theory into real savings.

Common Mistakes to Avoid

  • Skipping the diagnosis and acting on the symptom.
  • Measuring for the sake of it, with no clear improvement goal.
  • Not communicating the "why" of measurement to the team.

Metrics that Matter

  • The quantified cost of the problem (€).
  • Number of validated root-cause hypotheses.
  • Time to get the first result from an experiment.

Illustrative example

Picture a production line with an intermittent scrap problem: instead of a lengthy analysis, you launch 3 micro-experiments in 10 days and quickly validate the real cause. That's the mechanic this method proposes.

Your Action Plan

  • Today: Pick a recurring problem and put a clear, visible cost (€) on it.
  • In 7 days: Define a root-cause hypothesis and design a micro-experiment to validate it.
  • In 30 days: Run the experiment, measure the result and decide the next step based on data, not opinions.