The Lean Six Sigma Diet for Big Business Bloat

Large organizations suffer from what’s known as big business bloat. With each added process there is unintentionally added complexity and variability that ultimately affects cycle times, service levels, scalability, capacity, compliance, and defects among other things. In some estimates, complexity is attributable for as much as 15 – 30% of large business costs. This article from the WSJ written by Deloitte further explains how these process variations and potential savings are greatly underestimated by executives.

What complicates the issue is that sources of complexity are inherently difficult to trace and identifying root causes requires a foundation of metrics from end-to-end processes that are scarcely available. In addition, investigators are often thrown off the trail when subjective evaluation techniques are employed such as collecting estimates from interviews or surveys. The real root cause is hidden in the analytical data that make up the front-end and back-end processes. This is where Lean Six Sigma methodologies come into play where the effectiveness of which depends on the accuracy and reliability of the source information in order to make correct process evaluations. Knowing this information therefore, is the first step to combating this problem.

What organizations need to know is that in order to take effective actions, the process needs to be well mapped and understood. This includes identifying all stakeholders, inter-related processes, standard work hours and quality criteria. Likewise, as Six Sigma practitioners it is equally important to recognize these opportunities in the organization and to advocate for more accurate performance metrics of end-to-end processes.  There is often pressure to move forward with incomplete or subjective data that would ultimately result in ineffective solutions; classic garbage in, garbage out scenario. Therefore, a rigorous approach that includes validating hypothesis through Design of Experiments (DOE) is always recommended. This helps to weed out wrong assumptions or confirm subjective data. Process evaluation is always a time consuming endeavor but must not be taken lightly as relying on estimates alone will lead even the well-intentioned astray and make any extrapolations wildly inconsequential.