How to define what is good and what is bad?

How to explain GOOD and BAD so that everybody can understand?

What has a company and a household in common?

Can we use things we know from our home to improve our working environment and efficiency in a company?

Can we use things we learn in a company to improve our homes?

The most changes are applied to processes because there was a problem happening or the need to make "it" better.

So what means better?
Who or What indicates that something is better now?
How to measure that something is better now?

and who cares?

Lets see and lets start where we need to start.
Lets figure out at first, what is a symptom and what is a problem.

Implementing a "new" kind of methodology into an "old" environment
or start doing changes in a given environment or structure can cause misunderstanding, fear, aversion, defensive postures.

To me, it makes pretty much sense, not to hide methodologies behind a few characters, instead, those characters already have to show the way to go,
to be the methodology itself and to be part of a clear guideline how this methodology is working like "the G-C-E-C-P-C methodology of root cause elimination".

Each letter has a specific meaning, each letter stands for a specific task.

The G-C-E-C-P-C methodology of root cause elimination is part of a statistical "tool set" called "Structured Improvement with Strategy" used for business process improvement and training for process engineers, process owners and process developers.

G...Get Data: Measure, Monitor, Record,......

C...Compare Data: Perform comparison between defined, specified,standardized information or measurement values (comparison between: instantaneous value; actual value & set point value; specified value)

E...Evaluate / Analyse / Trace: Evaluate all measured
or recognized deviations (anomalies, irregularities) in a systematic and structured way.

C...Correct: the largest found issue at first

P...Perform: Perform a further test run:

C...Control: Keep your applied action under tight and careful control and check how the process, machine, parameters, any other value or situation responds to your applied action.

The cycle, starting from G have to be repeated step by step, until the root cause is eliminated. It is explained very clearly that there is the basic need to understand the difference between a symptom and a problem and how to define what a symptom is and what a problem is. To understand that a high scrap rate is a symptom and not the problem for the technicians, that is one key aspect.

The idea behind is, to understand that sometimes a change is an improvement and sometimes a change is called improvement
and a so called improvement is just a change and the success is temporary and might be only the sum of all done experiments.
The alleged and short-term success is simply the sum of all experiments and not reproducible and repeatable.

If the problem can be reproduced and the same symptoms are shown again, then the root cause is found.

During the "most important" data collection process, every single finding needs to be recorded.
N E V E R think about, that this specific tiny item could not have an influence on my problem because if you do so, you could be lost already.

During building correlations between your findings and men, machine, method, material, environment, accessories,........ you can exclude the findings, one by one but never exclude anything in th early stage of data collection.

I hope my way of thinking can add value to process failure elimination and also help to eliminate the natural fear from "new" management methodologies.

Feel free to download the free version "Your home factory" (.pps) from www.martin-kolinsky.com - Sourcing & Supply - Intro Download, further the "Intro Version" of Structured Improvement with Strategy - SI³wS - G-C-E-C-P-C methodology of root cause elimination.  Martin