Productivity Improvement using DMAIC: A Service Industry Case Study

This paper presents usage of DMAIC (an acronym for Define, Measure, Analyze, Improve and Control) approach of six sigma process and its tools to identify various root causes which influences productivity in engineering services industry. Effort variance is identified as major measure of productivity which is defined as difference between actual effort spent on the task and estimated effort of the task. Difference of actual and estimated effort was studied for variety of tasks over specified period to identify root cause for the benefit of revisiting of estimated effort for the future tasks. The improvement was to contain effort variance of around 5% for repeated tasks and of around 15% for new kind of tasks. The paper further studied about productivity and learning curve enumeration of effort after implementation of selected six sigma tools. Prioritized root causes which affect effort variation are considered for Design of Experiments (DoE) with two levels each. Myth on selected root causes is unlocked with results and its interpretation out of DoE. Analysis of results yielded basic outcomes which needed further attention in engineering service industry.