Readiness for Lean Six Sigma: The Good, the Bad, and the Ugly

Left to right: data-rich and capable; primitive; data or talent starved.

In a recent presentation to a group of executives, we discussed the readiness of organizations to deploy “Lean Six Sigma.” For the purposes of this note, let us define “Lean Six Sigma” as the application of a range of tools and concepts including but not limited to those developed as part of the Toyota Production System and documented in books such as “Lean Thinking” by James Womack as well as statistical and analytical tools such as control charts and design of experiment. In addition are various change and project management tools.

One of key considerations in whether and how to go about deploying Lean Six Sigma in an organization the degree to which an organization has a culture that embraces data-driven decisions and insights and possesses the skills to interrogate complex data sets. In my experience there are generally three archetypes:

A primitive organizational culture that is data poor, lacks the skills to analyze data, and is culturally antagonistic to analysis is not ready for most of the analytical tools of Lean Six Sigma (for example design of experiment). Such an organization is best served through a LSS deployment that develops an appreciation of what analysis can do and gradually muscle-builds analytical skills through basic projects that graduate to more advanced analytical problems as skills and data are acquired.

An organization with lots of data but little idea how to mine, interpret or focus its efforts analytically will also require cultural and skill changes but there is the possibility for a few high-impact, breakthrough projects that use advanced analytical tools to demonstrate the latent value of the data the organization sits upon.

In some organizations, or parts of organizations, lie highly educated professionals with analytical skills unused by the company because there is a lack of structured data. A combination of projects (which build data in the service of specific, high-impact projects) and top-down initiatives (such as gathering customer transaction data) builds data even as it is put to use by these under-used analytical resources.

As for the good, the bad and the ugly, it is no surprise that the “good” and the goal, is the combination of analytical skills and rich data; the “bad” are organizations with neither data nor analytical abilities; the “ugly” however are organizations wasting either talent (data-starved) or a treasure-trove of data for lack of skills and a supportive culture.

The deployment and nature of Lean Six Sigma clearly varies significantly in each case.