The Enriched Toolbox of Six Sigma Belts, from Data Science to Robotic Process Automation
Constantin Stan, Director, ENVISO, Bucharest, Romania
Co-Speaker: Alexandra Niculae
Keywords: Data Science, Robotic Process Automation, Six Sigma
The good feedback we had from the audience for our topic “How the Lean Six Sigma Belts Improve the Robotic Process Automation” during the last AQI Lean Six Sigma Conference, encouraged us to propose you the following topic.
When Six Sigma appeared in the 80s, the one-year duration for a black belt project wasn’t something unacceptable. Starting from 2000 the pressure on six sigma belts (no matter their certification level) increased, so the acceptable duration was considered to be around 6 months.
Nowadays there are industries where the standard duration for a six sigma project became 3 months. The customers have no more patience, the executives have no more patience, the time itself has no more patience.
How can we manage that? How can we assure that the DMAIC phases can be finalized in weeks?
Our presentation will show how a process map made using the BPMN 2.0 standard could improve the problem understanding during the Define phase, how the duration of Measure and Analyze phases could be dramatically reduced using Data Science and Machine Learning, and how the Improve phase can be finalized in weeks using the Robotic Process Automation solutions. We are going to bring real examples from 2 of our projects, one in a bank, one in healthcare.
The conclusion of our presentation will be that even if we are facing increased pressure, we have solutions and the best thing a six sigma belt can do today is to go back to school and enrich his toolbox with new instruments. This will also help the Six Sigma methodology to remain relevant for the years to come.