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  1. CMMI 1.3 and other standards CS 577b Software Engineering II Supannika Koolmanojwong

  2. Outline Six Sigma Lean Six Sigma ITIL

  3. What is Six Sigma?

  4. What is six sigma? • Sigma - a statistical term that measures how far a given process deviates from perfection. • if you can measure how many "defects" you have in a process, you can systematically figure out how to eliminate them and get as close to "zero defects" as possible • To achieve Six Sigma, a process must not produce more than 3.4 defects per million opportunities or 99.9997% perfect.

  5. Think about a pizza delivery • Not to deliver later than 25 minutes • If achieve 68% of the time, you are running at 1 Sigma • if achieve 99.9997% of the time then you are at 6 Sigma • Six sigma measures quality. • It measures the Variance and does not rely on the Mean.

  6. Examples of the Sigma Scale In a world at 3 sigma. . . • There are 964 U.S. flight cancellations per day. • The police make 7 false arrests every 4 minutes. • In MA, 5,390 newborns are dropped each year. • In one hour, 47,283 international long distance calls are accidentally disconnected. In a world at 6 sigma. . . • 1 U.S. flight is cancelled every 3 weeks. • There are fewer than 4 false arrests per month. • 1 newborn is dropped every 4 years in MA. • It would take more than 2 years to see the same number of dropped international calls.

  7. What is Six Sigma • This is accomplished through the use of two Six Sigma sub-methodologies: DMAIC and DMADV. • The Six Sigma DMAIC process (define, measure, analyze, improve, control) is an improvement system for existing processes falling below specification and looking for incremental improvement. • The Six Sigma DMADV process (define, measure, analyze, design, verify) is an improvement system used to develop new processes or products at Six Sigma quality levels. • Both Six Sigma processes are executed by Six Sigma Green Belts and Six Sigma Black Belts, and are overseen by Six Sigma Master Black Belts.

  8. Six Sigma DMAIC • DMAIC • Define the project goals and customer (internal and external) deliverables • Measure the process to determine current performance • Analyze and determine the root cause(s) of the defects • Improve the process by eliminating defects • Control future process performance • When To Use DMAIC • The DMAIC methodology, instead of the DMADV methodology, should be used when a product or process is in existence at your company but is not meeting customer specification or is not performing adequately.

  9. Six Sigma DMADV • DMADV • Define the project goals and customer (internal and external) deliverables • Measure and determine customer needs and specifications • Analyze the process options to meet the customer needs • Design (detailed) the process to meet the customer needs • Verify the design performance and ability to meet customer needs • When To Use DMADV • A product or process is not in existence at your company and one needs to be developed • The existing product or process exists and has been optimized (using either DMAIC or not) and still doesn't meet the level of customer specification or six sigma level

  10. Six Sigma DMAIC Roadmap

  11. Six Sigma DMAIC Roadmap

  12. A Six Sigma Case Study -Tutorial for IT Call Center • Benchmarking: • From data about a number of measures about customer satisfaction and call center technical and business performance. • Comparing their company to the benchmark average and to a select best-in-class group. • We can find that customer satisfaction with their support services was just average or a bit below. (see the following slides.)

  13. Figure 1: Customer Satisfaction for the Company, 2001-2003

  14. Figure 2: Customer Satisfaction for Average Companies, 2001-2003

  15. Figure 3: Customer Satisfaction for Best-in-Class Companies, 2001-2003

  16. A Six Sigma Case Study -Tutorial for IT Call Center • By analyzing the customer satisfaction data, we can find that Customer Satisfaction has positive influence to New Account Growth.

  17. A Six Sigma Case Study -Tutorial for IT Call Center • Transfer = Average number of transfers (to different agents and help systems) during a service call. • Wait Time = Average wait time during a service call. • Service= Average service time during the call (the time spent getting the answer to the question, problem solving advice, etc.). • From the regression model, we can find that the longer the wait time, transfer time and service, the lower the customer satisfaction.

  18. A Six Sigma Case Study -Tutorial for IT Call Center • From the data that gathered from industry, we found that the call center’s waiting time is lower than industry average; thus, there is space for improvement and it will help reduce the cost and increase customer satisfaction. • From the data, we can find that the call center’s cost is higher than average, so this project is doable.

  19. Define Phase • D1. Project Charter: • Problem Statement: "Competitors are growing their levels of satisfaction with support customers, and they are growing their businesses while reducing support costs per call. Our support costs per call have been level or rising over the past 18 months, and our customer satisfaction ratings are at or below average. Unless we stop – or better, reverse this trend – we are likely to see compounded business erosion over the next 18 months." • Business Case: "Increasing our new business growth from 1 percent to 4 percent (or better) would increase our gross revenues by about $3 million. If we can do this without increasing our support costs per call, we should be able to realize a net gain of at least $2 million." • 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."

  20. Define Phase • D2. Customer Requirements • A SIPOC table (Suppliers, Inputs, Process, Outputs and Customers) develops a detailed view of all the important customers, their requirements, and the related process step and supplier dependencies. • Voice-of-Customer (VOC) Interviews: Group interview the representative samples of the company's customers. • Summarizing Customer Requirements


  22. Define Phase • D3. High Level Process Map: • The process map will be 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.

  23. M1. Refine the Project Y(s) During this step the team considered exactly how the project Y(s) would be defined and measured: Measure Phase

  24. M2. Define Performance Standards for the Y(s) Measure Phase

  25. Measure Phase • M3. Identify Segmentation Factors for Data Collection Plan • How is Y naturally segmented • What factors may be driving the Y(s)? • Y-to-x tree • cause-and-effect diagrams • cause-and-effect matrices

  26. Measure Phase • M4. Apply Measurement Systems Analysis (MSA) • Questions Usually Posed for Measurement Systems:

  27. Measure Phase • M5. Collect the Data: A plan was formulated to gather data from the past year's database. • M6. Describe and Display Variation in Current Performance • How is the Y Distributed? • Variation above and below the chart's control limits suggested that there were "special causes" in play – worth understanding in more detail by the team in the Analyze phase.

  28. 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.

  29. Analyze Phase • 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.

  30. Analyze Phase • A4: Identify (Refined/More Detailed List of) Possible x's • Collecting the findings that came out of A3, the team posed strongest in the form of "why" questions: • 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?

  31. Analyze Phase • 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. • The figure shows that the influence of callbacks on a call's wait time

  32. Analyze Phase • 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.

  33. I1. Identify Solution Alternatives to Address Critical x's: Consider solution alternatives from the possibilities identified earlier and decide which ones are worth pursuing further. Improve Phase

  34. Improve Phase • I2. Verify the Relationships Between x's and Y(s) • What are the dynamics connecting the process x's with the critical outputs • Use regression analysis to verify the relationships • I3. Select and Tune the Solution • Using predicted performance and net value, decide what is the best solution alternative.

  35. Improve Phase • I4. Pilot / Implement Solution: • If possible, pilot the solution to demonstrate results and to verify no unintended side effects. • Preparation and deployment steps for putting the pilot solution in place. • Measures in place to track results and to detect unintended side effects. • Awareness of people issues. • Measure and compare the improvement of the solution

  36. Control Phase • C1. Develop Control Plan • The Control plans addressed two views • Management control: It often focus on the Y(s) or outcomes of the process and often some of the x's as well • Operational control: It concerned with the x's that are predictive of outcome Y(s). • Operational control information included both controllable and "noise" variables • Operational control information was provided more frequently than management control information

  37. Control Phase • C2. Determine Improved Process Capability • Use the same measures from Define and Measure in order to provide comparability and monitor impact in a consistent way. • C3. Implement Process Control • Create, modify and use data collection systems and output reports or dashboards consistent with the control plan.

  38. Control Phase • C4. Close Project • Prepare the implementation plan, transfer control to operations, conduct project post-mortem, and archive project results.

  39. Outline Six Sigma Lean Six Sigma ITIL

  40. Lean Six Sigma • Lean + Six Sigma • Six Sigma • recognize and eliminate defects and or low profit margins. • recognize that variations in analyzing and measuring can hinder or often block the ability to deliver high quality services. • Focus on data • Need a team of professionals (champion, black / green belts) • Lean Six Sigma • focus is on maximizing products or perform things faster by removing the wastes • seven forms of waste or "muda“ (Defects, overproduction, overprocessing, motion, transportation, inventory and waiting) • Six Sigma Quality + Lean Speed

  41. Lean Six Sigma Measurement activity of the 6δDMAIC takes a long time and lots of data Lean 6δ does not ignore measurement, will do as necessary

  42. Lean Thinking provides a sharp degree of focus on customer value, and provides mechanisms for rapid improvement Six Sigma is the statistical control and performance prediction capability associated with stable processes [Ref: CrossTalk2010]

  43. ITIL - IT Infrastructure Library • V3 - consists of 5 volumes: • Service Strategy • Service Design • Service Transition • Service Operation • Continual Service Improvement.

  44. The Service Lifecycle • Service Strategy • Strategy generation • Financial management • Service portfolio management • Demand management • Service Design • Capacity, Availability, Info Security Management • Service level & Supplier Management • Service Transition • Planning & Support • Release & Deployment • Asset & Config management • Change management • Knowledge Management • Service Operation • Problem & Incident management • Request fulfilment • Event & Access management • Continual Service Improvement • Service measurement & reporting • 7-step improvement process

  45. How the Lifecycle stages fit together

  46. Service Strategy

  47. Service Strategy has four activities

  48. Service Design

  49. Service Design • How are we going to provide it? • How are we going to build it? • How are we going to test it? • How are we going to deploy it?