The Scientific Method

Lean is a science based discipline that uses facts, data, processes, measures and analysis to manage company operations, , reduce cycle times, and eliminate defects.  Projects, which include corrective action preventive action (CAPA), design and development (DND), and continuous improvement, follow a process or, specifically, the Scientific Method.

Years ago, when I struggled through difficult science courses like chemistry and physics, I was taught this simple paradigm, repeated and ingrained.

It wasn’t until I became a Lean Sigma practitioner that I started using this method again, albeit, tacitly.  This meant working on projects that weren’t strategically thought through and properly measured and analyzed during implementation.  For example, a cable technician needed to fix a communication node on top of a telephone pole.  He needed to bring with him about eight to ten small tools with him.  He had a huge tool box in his truck.  One option was to haul the tool box to the bottom of the pole and climb up and down, as needed, to pull the right tool.  Another option was to stuff his pockets as much as he could.  Unfortunately, he could not stuff his pockets adequately. He requisitioned a tool belt that did the job but found it bulky and uncomfortable. Then on Christmas, his father, gave him a tool vest.


When he tried it on, he noticed that the vest not only had enough pockets and slots for tools, but it was comfortable and easy to use.

 In this example, a problem statement, scope, hypothesis, experiment, analysis, evaluation and conclusion occurred, but not formally.  As this example provided an adequate solution, strategy was not part of this process, and the solution (tool vest for Christmas) occurred as a stroke of luck.

Each day, I faced challenges, a lot of them small. They resolved themselves.  Most of what happened described a pattern I picked up through the course of my life and fixed or dealt with without thinking.  

It’s part of life.  It’s what I do daily.

            The Scientific Method has many forms.  It follows a basic sequential premise.

·         Problem Statement

·         Scope

·         Hypothesis

·         Experiment

·         Conclusion

            Since working with Lean Sigma, I’ve expanded this outline to look like this:

·         Problems Statement

·         Scope:  Ishikawa Diagram / Capacity analysis / VSM / Waste, constraint, variations and variable analysis / Cycle time and defects assessment

·         Hypothesis (If this…then that…)

·         Experiment (Who does what with what equipment, technology and material at a specific controlled location, following predesigned written steps, limited to a timeline, milestones and deadline).

·         Data is collected, measured and analyzed

·         Conclusion that includes outcomes, discoveries.  SWOT is factored in.

·         Plan Do Check Act (PDCA)

The PROBLEM STATEMENT represents an issue that needs to be solved.  For example, a doll company receives a list of defective product complaints. The potential of lost revenue is imminent.  A problem statement could look like this:  In the month of January, 45 Kung Fu Kick dolls were return due to the signature kicking feature not working.  The leg locks at the hip and does not return.

The next step is to draft up the SCOPE.  XYZ Doll Company in Anywhere, California, has been in business for over 50 years, manufacturing specialty dolls.  Its signature dolls take on mechanical characteristics.  Their products are well known for its life-like mechanical movements.  Each present dynamic roles unique to the model.  Due to the craftsmanship, these dolls are in high demand, sold throughout the word in retail outlets and online.  Manufacturing face challenges in meeting high order demands.

Since its beginnings, the doll company had not received complaints in this magnitude.  The Kung Full Kick doll is the exception.  A quick examination indicated that defects weren’t segregated to specific lot or serial numbers. (Ishikawa Diagram / Capacity analysis / VSM / Waste, constraint, variations and variable analysis / Cycle time and defects assessment).  Further analytics indicated a spread of dates and production runs that spanned the past two years.  Quality control and assurance records were within standards.  The root cause, which was assumed from the start, pointed towards design.

 A HYPOTHESIS was formed.  “IF the design was bad, THEN engineering could locate and fix the problem.’

The EXPERIMENT was then implemented (Remember…Who does what with what equipment, technology and material at a specific controlled location, following predesigned written steps, limited to a timeline, milestones and deadline.)

Data was then COLLECTED, MEASURED and ANALYZED.

The CONCLUSION verified the assumption that there was indeed a design issue.  Small adjustments were made, and the defective doll problem was solved.

Because of this engineering developed steps to mitigate future problems.  A CAPA was initiated and resultant processes provided a continuous improvement mindset in the design and development department.

This is just one example how this useful tool was used.  It can be used in almost any problem related issues, small or large, business or personal.  You can take formalized steps, like the example above, which is highly recommended, or you can go through this process in your head.

In your Lean toolbox, be sure to keep this handy at all times and at a moment’s notice!  You won't be sorry.