370 likes | 589 Views
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
E N D
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 ANOVAANalysis 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 ChartA 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 ParetoThe 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 ChartsThis 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