In many organizations that deploy LSS, statistical tools are taught in either a green or black belt course, as part of a broader toolset that’s framed by the DMAIC methodology, an approach that divides projects into five phases—define, measure, analyze, improve and control. In these deployments, the use of statistical tools is framed solely around working through an improvement project. Buckman chose a different approach, recognizing that the statistical tools of LSS are useful for any role that analyzes data. If these tools were taught independently from the DMAIC model, they could be taught to a broader audience than just green or black belts.
“We took a Lean approach to the deployment of Lean Six Sigma, realizing that many of our associates who should be using statistical tools would not benefit from the full curriculum of a LSS belt course,” says Mohler. “As we looked at this expanded view, we realized that a key group who should be taught these tools were our sales associates.”
At Buckman, technical field sales associates who have backgrounds in chemistry, biology, or engineering work directly with the company’s customers to help them assess their processes and look for improvement opportunities. Analyzing customer data is a key part of Buckman’s selling process.
“Using Buckman’s chemistry solutions, our technical sales teams work to make our customers’ systems better,” Mohler says. “In essence, they function as process engineers for our customers.”
Mohler and his colleagues developed two separate Lean Six Sigma courses. The first course, a yellow belt course, focused on the traditional DMAIC process and the “soft” tools of quality improvement. This is the course Buckman teaches associates who will be leading simple improvement projects. The second course is a data analysis and statistical tools course targeting the organization’s sales associates.
Instead of using the DMAIC framework as the backbone of the statistics training, Buckman took the selling process and linked the appropriate statistical tools to each step. This framework broke the sales flow into more manageable pieces and looked at data analysis activities that are used to:
- Gain knowledge of customer processes
- Plan, run, evaluate and sell new chemical programs
- Manage ongoing chemical programs
- Solve problems within the account
“The end goal is to have our sales associates comfortable using practical statistical tools, so they’ll be able to make better recommendations—data-driven recommendations—to help our customers,” notes Mohler. “We believe that focusing our efforts on improving customer satisfaction will make Buckman more profitable and sustainable.”
In the statistics class, associates are trained on the tools they need for their job activities. Concepts such as control charting, hypothesis testing, capability analysis, and correlation are taught with practical examples that use the data analysis tools available in Minitab Statistical Software.
To perform statistical analyses such as process capability—which can help determine whether a process is capable of producing output that meets customer requirements—associates use the Minitab Assistant. The Assistant is a menu-based tool that guides users step-by-step through their analysis. It includes decision trees that make it easy to choose which analysis to use to examine data.