A Six Sigma Case Study Tutorial for IT – Call Center Part 4 of 6 – February 26, 2010 0 of a Six Sigma DMAIC project This combination “case study and tutorial” tracks the inception by an IT support business. The project is aimed at helping the company become more competitive and profitable. Each part follows the project team as it works through another stage of the DMAIC methodology. Click to read the rest of the case study: , , , and . Having refined the defined performance standards for project project’s key outcome measures, and defined measurement systems, the Six Sigma project Y‘s, identified segmentation factors team of the IT services business began to focus on the Analyze phase. The DMAIC (Define, Measure, Analyze, Improve, Control) roadmap called for work in these areas during the Analyze phase: A1. Measure Process Capability: Before segmenting the data and the to look “peeling onion” for root causes and drivers, the current performance is compared to standards (established in step M2 of the Measure phase). A2. Refine Improvement Goals: If the capability assessment shows a significant departure from expectations, some adjustment to the project goals may need to be considered. Any such changes will, of course, be made cautiously, supported with further data, and under full review with the project Champion and sponsors. A3. Identify Significant Data Segments and Patterns: By segmenting the data based on the Y factors (X‘s) identified during the Measure phase the team looks for patterns that shed light on – what may be causing or driving the observed variation. Y A4. Identify Asking why the patterns seen in A3 are as observed highlights some Possible X’s: factors as likely drivers. To sort out the real drivers from the A5. Identify and Verify the Critical X’s: “likely suspects” list built in A4, there is generally a shift from graphical analysis to statistical analysis. A6. Refine the Financial Benefit Forecast: Given the of the real driving the “short list” x’s, may need to be adjusted. financial model forecasting “how much improvement?”
A Six Sigma Case Study – Tutorial for IT Call Center – Part 4 of 6 February 26, 2010 0 This combination “case study and tutorial” tracks the inception of a Six Sigma DMAIC project by an IT support business. The project is aimed at helping the company become more competitive and profitable. Each part follows the project team as it works through another stage of the DMAIC methodology. Click to read the rest of the case study: , , , and . Having refined the project’s key outcome measures, defined performance standards for project Y‘s, identified segmentation factors and defined measurement systems, the Six Sigma project team of the IT services business began to focus on the Analyze phase. The DMAIC (Define, Measure, Analyze, Improve, Control) roadmap called for work in these areas during the Analyze phase: A1. Measure Process Capability: Before segmenting the data and “peeling the onion” to look for root causes and drivers, the current performance is compared to standards (established in step M2 of the Measure phase). A2. Refine Improvement Goals: If the capability assessment shows a significant departure from expectations, some adjustment to the project goals may need to be considered. Any such changes will, of course, be made cautiously, supported with further data, and under full review with the project Champion and sponsors. A3. Identify Significant Data Segments and Patterns: By segmenting the Y data based on the factors (X‘s) identified during the Measure phase – the team looks for patterns that shed light on what may be causing or driving the observed Y variation. A4. Identify Possible X’s: Asking why the patterns seen in A3 are as observed highlights some factors as likely drivers. A5. Identify and Verify the Critical X’s: To sort out the real drivers from the “likely suspects” list built in A4, there is generally a shift from graphical analysis to statistical analysis. A6. Refine the Financial Benefit Forecast: Given the “short list” of the real driving x’s, the financial model forecasting “how much improvement?” may need to be adjusted.
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