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Six Sigma in the Contact Center

Prepared by Mike Stone. Agenda. Introduction to Six SigmaFull Life-Cycle Case Study. Prepared by Mike Stone. Introduction. Six Sigma was invented by Motorola, Inc. in 1986 as a metric for measuring defects and improving quality. Since then, it has evolved to a robust business improvement methodol

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Six Sigma in the Contact Center

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    1. Six Sigma in the Contact Center Northwest Call Center Professionals Help Desk Northwest May 17, 2006 Mike Stone

    2. Prepared by Mike Stone Agenda Introduction to Six Sigma Full Life-Cycle Case Study

    3. Prepared by Mike Stone Introduction Six Sigma was invented by Motorola, Inc. in 1986 as a metric for measuring defects and improving quality. Since then, it has evolved to a robust business improvement methodology that focuses an organization on customer requirements, process alignment, analytical rigor and timely execution.

    4. Prepared by Mike Stone Six Sigma, the GE Way Six Sigma - A vision of quality which equates with only 3.4 defects per million opportunities for each product or service transaction. Strives for perfection. DFSS (Design for Six Sigma) is a systematic methodology utilizing tools, training and measurements to enable us to design products and processes that meet customer expectations and can be produced at Six Sigma quality levels. (DMADV - Define, Measure, Analyze, Design, Verify) DMAIC (Define, Measure, Analyze, Improve and Control) is a process for continued improvement. It is systematic, scientific and fact based. This closed-loop process eliminates unproductive steps, often focuses on new measurements, and applies technology for improvement.

    5. Prepared by Mike Stone Other Quality Systems Total Quality Management (TQM) Toyota Production System (TPS) Kaizen Lean Theory of Constraints Agile PDCA Plan, Do, Check, Act Good Manufacturing Process Pharma ISO 9000

    6. Prepared by Mike Stone Key Concepts A process is all the activities involved in producing a product or service for a customer. It is cross-functional in nature Quality is defined by customer requirements for the chosen process Defects are defined and counted Inconsistencies in the process, known as variation, are studied Causes of variation are identified and addressed

    7. Prepared by Mike Stone Key Terminology

    8. Prepared by Mike Stone Key Terminology

    9. Prepared by Mike Stone DMAIC

    10. Prepared by Mike Stone Case Study

    11. Prepared by Mike Stone Project Selection Business strategy How important is customer satisfaction? How important is it to attract new customers? Competitive position How do we compare to our competitors? Benchmarking Best projects Issue is well-defined with supporting data Scope is well-defined Objectives are stated in business terms and are measurable

    12. Prepared by Mike Stone Project Selection Customer satisfaction Average Lower than best-in-class in industry Positive correlation with account growth Customer satisfaction and new accounts are statistically related to one another Business judgment No correlation with customer service spending Per call costs were not higher at strong competitors Goals: Reduce support costs while improving new account growth

    13. Prepared by Mike Stone Define Team Chartering Goal statement: "Increase the call center's industry-measured customer satisfaction rating from its current-level (90th percentile = 75 percent) to the target level (90th percentile = 85 percent) by end of the fourth-quarter without increasing support costs. Milestones, tasks, responsibilities, schedule and communication plan.

    14. Prepared by Mike Stone Define Customer Focus SIPOC diagram identify customers (stakeholders) Customers Staff Business Voice of the Customer interviews "What influences your level of satisfaction with our services?" Summarize customer requirements Identify measures for each requirement Next slide

    15. Prepared by Mike Stone Define

    16. Prepared by Mike Stone Define Process mapping Helpful during the Measure phase, as the project team considers how and where to gather data that will shed light on the root cause of the issues most pertinent to the project's goals.

    17. Prepared by Mike Stone Measure Define measures and how the data will be gathered Example: Customer Satisfaction By industry standard monthly survey The project will require additional, more frequent, case-by-case customer-satisfaction data. A measurement system that tracks with the industry survey will be devised and validated.

    18. Prepared by Mike Stone Measure Define performance standards Example: Customer Satisfaction Current Baseline 90th Percentile / 70-80% Satisfied Performance Target 90th Percentile / 85% Satisfied

    19. Prepared by Mike Stone Measure Identify segmentation factors for data collection plan Focus data collection effort Use cause-and-effect tools How is Y naturally segmented? Call center, product type? What factors may be driving the Ys? Take a guess at what your important Xs might be Call type, customer type?

    20. Prepared by Mike Stone Measure Assess measurement system Accuracy Does the measure agree with the truth? Repeatability Does the system always produce the same value? Reproducibility Will different people get the same results? Stability Is the system accurate over time?

    21. Prepared by Mike Stone Measure Collect the data Automated Manual New metrics may be needed Display the data Look for clues into causes of variation Simple charts and graphs

    22. Prepared by Mike Stone Analyze Measure process capability Compare current performance to standards Refine improvement goals Adjust goals if data shows departure from expectations Segment data Slice and dice data to look for patterns to find causes of variation

    23. Prepared by Mike Stone Analyze Identify possible Xs Likely suspect causes of variation Identify and verify the critical Xs Narrow down to most important causes of variation Why do Problems and Changes cost more than other call types? Why are calls processed on Mondays and Fridays more expensive? Why do transfer rates differ by call type? (higher on Problems and Changes, lower on others) Why are wait times higher on Mondays and Fridays and on Week 13 of each quarter?

    24. Prepared by Mike Stone Analyze Refine the benefit forecast Update the forecast of how much improvement can be expected Found that key support cost drivers (the delays and interruptions during call-servicing) were the same as those known to drive down customer satisfaction so a win-win seemed to be possible.

    25. Prepared by Mike Stone Improve Identify Solution Alternatives

    26. Prepared by Mike Stone Improve Verify the Relationships Between Xs and Ys Solution Selection Matrix Solution Alternatives Customer Requirements (CTQs) Regression Analysis Determine the strength of each solution against the CTQs

    27. Prepared by Mike Stone Improve

    28. Prepared by Mike Stone Improve

    29. Prepared by Mike Stone Improve Implement Solution Pilot, if possible Collect data during pilot Xs and Ys Watch for unintended impacts Report out and obtain approval for full implementation

    30. Prepared by Mike Stone Control Develop Control Plan Management control dashboards Ys Operational control indicators Xs Determine Improved Process Capability Business Growth Customer Satisfaction Support Cost per Call Days to Close Wait Time Transfers Service Time

    31. Prepared by Mike Stone Control Implement Process Control Ongoing data collection and presentation Close Project Roll out process changes Training Transition control to management Validate results Refinements Project post mortem

    32. Prepared by Mike Stone Tools

    33. Prepared by Mike Stone Tools ANOVA ANalysis Of VAriance (ANOVA), a calculation procedure to allocate the amount of variation in a process and determine if it is significant or is caused by random noise.

    34. Prepared by Mike Stone Tools Control Chart A graphical tool for monitoring changes that occur within a process, by distinguishing variation that is inherent in the process (common cause) from variation that yield a change to the process (special cause).

    35. Prepared by Mike Stone Tools Pareto The Pareto principle states that 80% of the impact of the problem will show up in 20% of the causes. A bar chart that displays by frequency, in descending order, the most important defects.

    36. Prepared by Mike Stone Tools X-Bar and R Charts This set of two charts is the most commonly used statistical process control procedure. Used to monitor process behavior and outcome overtime.

    37. Prepared by Mike Stone Resources http://www.isixsigma.com/ http://www.sixsigmainstitute.com/ http://www.motorola.com/motorolauniversity http://www.ge.com/sixsigma/ The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance by Peter S. Pande, Robert P. Neuman, Roland R. Cavanagh Fourth Generation Management by Brian L. Joiner Leading Six Sigma by Ronald D. Snee and Roger W. Hoerl The Pocket Idiots Guide to Six Sigma by Marsha Shapiro and Anthony Weeks

    38. Six Sigma in the Contact Center Mike Stone Mobile: (206) 779-3105 mgstone2020@yahoo.com

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