When a basic problem is being addressed in the DMAIC process, the 5-Why approach is a good method for exploring and documenting root causes. The idea behind the 5-Why approach is to ask “Why?” five times when exploring the reason for a problem, hopefully arriving at the root cause, on or before the 5th Why.
Here is an example:
Problem: We shipped the wrong item to our customer
Why? Wrong item picked from inventory
Why? Supplier put the incorrect part number on the box when it was shipped to our location
Why? The operator at the supplier placed the wrong part number label on the box
Why? The supplier is printing part number labels in batches of 20, and it is easy to pick up the wrong label
Why? Supplier did not anticipate this problem when they designed their packaging process
So in the above case, both the 4th and 5th Why’s can be addressed, and fixing the 5th Why would result in a strong preventive action for the future.
Below is a more familiar format for conducting a 5-Why analysis when multiple causes exist (link to Powerpoint® file ).
A Note on Data Collection
Generating a 5-Why analysis like the one above is usually straightforward, provided that the team has collected enough data to create a sound Pareto Chart to begin with.
It’s rare that meaningful data is readily available for a 5-Why analysis, so oftentimes the team must organize themselves to collect the data over a period of time. This is where team selection comes back into play – if one or more Six Sigma team members actually work in the process being studied, then the data collection phase is much easier to implement. Note that each of the first “Why?” blocks in the above example includes the contribution-percentage from the Pareto Chart – this can be very helpful in keeping the team focused on the top two or three causes from the beginning (which is crucial for achieving measurable results at the end of the project!).
Why Can’t We Use 5-Why on Everything?
If Six Sigma is about identifying and controlling the top causes behind costly variation, then why doesn’t the Analyze phase simply focus on the 5-Whys every time? The reason is that understanding the top two or three causes of a problem is oftentimes more challenging than simply collecting data and analyzing it. This is especially true when product variation is involved. For example, if a toy manufacturer needs to improve color consistency in a product, they will need to understand which factors influence color the most (otherwise they might not need a Six Sigma project to begin with). In cases like this, structured analysis methods like multi-vari, correlation analysis, and DOE may be necessary to actually learn the physical relationships between the input variables (process settings, raw materials, etc.) and output variables (in this case, color). If your team is attacking a number of product variation challenges, the read Keki Bhote’s World Class Quality for a highly effective approach.