As a Lean Six Sigma Master Black Belt for many years I get why many organizations have a focus on Lean. The idea of many people working on many projects is compelling in terms of the value it can generate, the high level of involvement of the workforce and the intuitive nature of the toolset that is easy to teach and learn. On the downside, because the projects tend to be smaller in nature, they tend not to be tracked, aggregated or leveraged; therefore, the net impact is not as noticeable as it should be.

In today’s workplace we are seeing Lean and Six Sigma being applied as much, if not more, in transactional environments than where they developed – in manufacturing. When explaining this to folks undergoing training I ask them to substitute “people” for “equipment.” If I use overall equipment effectiveness as an example of this and translate it to overall people effectiveness, you still have the three components of availability, rate and quality. Consider – do you have enough employees? Are your resources balanced? Are they working at full speed? Are they producing quality, defect-free work?

Other tools such as fishbone diagrams need a little translation as well. The machine category can be looked at as the systems we use to transform information and data into a final product/service and materials can be forms and fields that we fill in while performing transactions.

Using these simple analogies helps people make that leap toward understanding how these highly successful methodologies, that have stood the test of time in manufacturing, can help us improve transactional processes.

Keeping on the transactional theme, the other big difference we tend to see is that we are using more time-based measures than we have perhaps seen in the manufacturing world where we have tended to use normal data sets. In a transactional world we see more binomial or Poisson-type distributions due to time starting at zero and more skewed distributions. I believe that this is one reason why Six Sigma is not being used enough in organizations – people are less comfortable with non-normal data as they are not used to working with it. But we actually have many tools to deal with these data types and distributions and we should not be afraid to work with them.

In the transactional, non-normal world we can still do hypotheses testing but instead of working with comparisons of means we compare medians, which address issues with highly skewed data. We can also work out process capability and estimate the number of defects likely to be produced based on customer specifications or service-level agreements. Control charts can also be used with discrete data and be a useful method of analyzing current performance to get a baseline and be of great use in displaying and maintaining improvements to a process.

I believe that Six Sigma is still a big requirement for step/breakthrough changes – it just seems that many people have forgotten that for now.