SERVICE QUALITY SIX SIGMA CASE STUDIES

SERVICE QUALITY SIX SIGMA CASE STUDIES Chris Bott Elizabeth Keim Six Sigma Black Belt Six Sigma Master Black Belt American Express Company Integrated Quality Resources, LLC 7701 Airport Center Parkway 4220 Pebble Beach Drive Greensboro, NC 27409 Niwot, CO 80503-8359 336-668-5799 lizkeim@netscape.net Sai Kim Lisa Palser Six Sigma Black Belt Six Sigma Master Black Belt American Express Company E.I. DuPont de Nemours, Inc. World Financial Center BMP 35-2315 200 Vesey Street P.O. Box 800035 New York, NY 10285-4525 Wilmington DE, 19880-0035 SUMMARY This presentation will discuss the effective use of Six Sigma tools to improve several service processes. Each case will cover the following five steps: Define the problem Measure the defect Analyze the data Improve the process Control the process KEYWORDS Case Studies, Service, Six Sigma INTRODUCTION Below are three cases studies, using the Six Sigma methodology for defect reduction using Define, Measure, Analyze, and Control, from American Express and DuPont. Each will discuss the nature and quantification of the problem and the benefits of resolving the problem. Then, each will describe the analysis done to determine the root cause and evaluate potential solutions to the problem. Lastly, each will discuss control mechanisms used to ensure sustainability and the results achieved. CASE STUDIES Reduce Closed Store Passive Suppression Uncallables at American Express Sai Kim, American Express Company

SUMMARY This presentation will discuss the effective use of the Six Sigma tools to improve external vendor processes. It will take you through a project American Express completed, Reduce Closed Store Passive Suppression Uncallables. This analysis will demonstrate how we applied Six Sigma techniques to reduce the defect rate from 8.0% to 2.8% with expected annual savings of $401,000. INTRODUCTION: Reduce Closed Store Passive Suppression Uncallables It is important that all American Express merchants place our point-of-purchase materials (POP) or decals on storefronts, cash registers, or check presenters. POP helps our card members, especially Corporate card members, identify service establishments that honor American Express cards. In addition to increased perception of coverage, POP increases merchant and card member satisfaction and revenues for both the merchant and American Express. Despite the benefits of placing POP, merchants place competitive POP and no American Express POP; we define these merchants as passive suppressors (merchants with at least 1 POP placed are defined as non-suppressors). To monitor passive suppression, we work with an external vendor. The vendor is responsible for placing POP in the market place and identifying passive suppressors, as well as, measuring placement and passive suppression rates. When we began our analysis, we learned that we had a 36% Uncallable rate, a rate at which we fail to visit merchants for various reasons such as the store is closed, address is incorrect, ownership has changed, etc. Applying Six Sigma tools, we focused on the largest factor contributing to Uncallables - closed stores. We were able to decrease our defect rate by 65%. DEFINE & MEASURE THE PROBLEM The objective of this project was to reduce closed store Uncallables (closed due to business hours), representing 27.4% of total Uncallables and 8.0% of 831,000 annual total attempted visits. The process represented a 2.9 sigma level and cost of poor quality of $615,000 annually. ANALYZE THE DATA We applied various Six Sigma tools to identify Vital X s or the root causes of the defect (critical to success). The Pareto Chart pointed to the Closed Store category, the number one reason for Uncallables. With the focus on closed stores, we identified the following potential Vital X s: Vendor Call Hours: By shadowing our vendor on merchant visits, we found that visits were completed from 8:00 AM to 6:00 PM. It was brought to our attention that 45% of closed stores fell in the retail segment and 16% in the restaurant segment. Since these two industry segments typically are not open for business at 8:00 AM (or even at 9:00 AM), we hypothesized that vendor call hours contributed to the high defect rate. Closed Store Inspection Process: After we mapped the vendor call process, we identified the second Vital X, the inspection process. The current policy states that a merchant with at least one POP placed is defined a non-suppressor. However, in spite of POP placement on the exterior of closed service establishments, the vendor was not collecting this information. In fact, the calls were immediately terminated without checking for externally placed POP and reported as Uncallable. As a

result, the same merchants were being pulled from our database and visited multiple times - all leading to rework. IMPROVE THE PROCESS After we identified two potential Vital X s, we had to test and validate our hypotheses. We changed the call hours for all visits to after 10:00 AM. Secondly, our vendor was required to continue the inspection process and audit exterior placement status (Amex POP only, Competitive POP only, All POP, etc.), regardless of regular business hours. As a result of new call hours, we were able to reduce the defect rate by 43.7%, from 8.0% to 4.5%. This reflects annual savings of $269,000. The second test, continued inspection, indicated that 35.4% of the remaining 4.5% closed stores had at least 1 American Express POP placed on the exterior of the establishment. We concluded that a little over a third of merchants in the closed store category were not suppressing American Express cards, information we did not collect in the past. Going forward, we can use this data to forecast the total number of attempts (merchant visits) needed to achieve a targeted number of Callables. The new inspection process is expected to save an additional $132,000 annually. In summary, the following chart outlines the combined test results: Closed Stores Baseline Test Results Defect Rate 8.0% 2.8% (Reduced by 65%) DPMO 80,000 28,000 COPQ $614K $215K Total Annual Savings - $401K Cost per Unit $9.25 $9.25 Sigma Level 2.9 3.2 CONTROL THE PROCESS To ensure that we perform within the acceptable limits on an on-going basis, it is important to monitor the new process. To achieve control status, we will be using the p chart, a tool that tracks proportions of closed stores over time. In addition, we have revised the vendor call report to reflect Uncallable rates by reason, which gives us the ability to monitor the defect rate on a monthly basis. CONCLUSION Later call hours and a continued inspection process for closed stores significantly enhanced efficiency. Moving forward, we can make 43,336 fewer vendor visits and still achieve the same absolute number of Callables as we did in past years. Also, we can expect $401,000 in annual savings with $0 project investment. In terms of key learnings, we found that it is important to shadow vendors periodically to identify areas for improvement or opportunities not readily evident to the vendor or the client. This will help us accommodate the changing marketplace and meet business objectives using more efficient processes. Eliminate Non-received Renewal Credit Cards

Chris Bott, American Express Company SUMMARY This presentation will discuss the effective use of Six Sigma tools to improve our plastic issuance processes. It will take you through a project American Express completed, Eliminate Non-received Renewal Credit Cards. This analysis will demonstrate how we applied Six Sigma techniques to reduce the defect rate with ongoing dollar savings. INTRODUCTION Eliminate Non-received Renewals - Returned Plastics Due to Change of Address. DEFINE & MEASURE THE PROBLEM On average (in 1999), American Express received 72,000 returned Renewal cards each month. Of these, 65% (47,356) are due to the fact that the card members changed their addresses and did not tell us (therefore the updated addresses are not in our database). The US Post Office calls these forwardable addresses. Please note: Amex does not currently notify a card member when we receive a returned plastic card. ANALYZE THE DATA We applied various Six Sigma tools to identify Vital X s or the root causes of the defect. The use of Chi Square indicated the following: By Type of Card/Plastic: we isolated significant differences in the causes of Returned Plastics between product types. Optimum, our revolving card product, had the highest incident of defects, but was not significantly different, in the percentage of defects, from the other card types. Issuance Reason: the tool proved overwhelmingly that Renewals had far and away the highest defect rate in the three areas in which we issue plastic - Replacement, Renewal and New Accounts. Validated Reason for Returned: Because we suffered scope creep early in the project, it was important for us to confirm what our initial data was telling us. After testing the five reasons for returns, returns with forwardable addresses were overwhelmingly the largest percentage and quantity of returns. IMPROVE THE PROCESS After identifying the potential Vital X s, we had to test and validate our hypothesis. An experimental pilot was run on all Renewal files issued. This bumping against the "The National Change of Address" service was implemented on all Renewal cards in mid August. This solution, due to the strict file matching criteria, will impact 33% of the remaining population (or 15,000 cards monthly). As a result of a successful pilot, we were able to reduce the defect rate by 44.5%, from 13,500 to 6,036 defects per million. This reflects annual savings of $1,228,000. In summary, the following chart outlines the combined test results:

Closed Stores Baseline Test Results Defect Rate 1.35%.6% DPMO 13552 6036 COPQ $3,360,000 Total Annual Savings $1,228,000 Cost per Unit $6.49 (weighted) Sigma Level 3.71 4.01 CONTROL THE PROCESS To ensure that we perform within the acceptable limits on an on-going basis, it is important to monitor the new process. To achieve control status, we will be using the p chart, a tool that tracks proportions of returns over time. In addition, our vendor has constructed reporting, which gives us the ability to monitor the defect rate on a monthly basis. The report will tell us if any credit cards that were bumped against the National Change of Address database were returned back to our warehouse. CONCLUSION Using the National Change of Address will enable over 180,000 card members to get their credit cards. Prior to this implementation, these card members would have never received their cards automatically. This will undoubtedly increase our revenue and customer satisfaction. Lisa Palser, E.I. DuPont de Nemours, Inc. Cycle Time Improvement for a Human Resources Process SUMMARY This presentation will discuss how Six Sigma was applied to improve cycle time for an employee s application for long-term disability benefits. This process was selected because the process owner was receiving customer complaints; the process's performance was not meeting customer expectations. The process starts at the time the application is sent to the benefit provider until an accept or deny decision is delivered. How Six Sigma was used with a third-party benefit supplier will also be discussed. INTRODUCTION Long-Term Disability Application Process The Long-Term Disability Application Process is initiated in the fifth (5 th ) month of the employee's six (6) month short-term disability leave of absence. The cycle time requirement of the corporation is to receive an approve/deny decision prior to the end of the short-term benefit. The financial cost of not having a timely decision is that the short-term benefit is extended, which costs the corporation more than the long-term benefit. The cycle time objective of this process is to perform within a 45-day upper specification.

MEASURE The project team included the process owner, subject matter experts, and the supplier's account managers. The project team mapped and documented the current process. Using the process map and experience, the project team and the supplier's claim processors developed a cause-effect diagram for the factors influencing the process outcome, the cycle time. The customers, represented by 12 randomly selected employment sites, were surveyed for their view of the process and the 45-day upper specification was validated. Their insights were added to the process map and the cause-effect diagram. In addition, they were asked about an 'ideal' outcome to determine other potential process improvements and potential future projects. Baseline data was collected from the selected sites. In addition to the overall cycle time measure for each application, the team gathered data related to the application at various milestone dates between the initial application and the decision so that we could assess where the significant breakdowns in the process occurred. ANALYZE The good news from the initial analysis was that mean cycle time was 30 days; the bad news was that there was significant variation resulting in a 0.83 Sigma value. Various analysis tools were applied to identify the root causes of the defects. We discovered that there is no significant difference in the cycle time at different DuPont sites, even though each site uses a slightly different process. The most significant factors affecting cycle times were: Incomplete medical and/or job information requiring frequent re-work to gather and process missing information. The benefit supplier's agent who processed the application. Delays in receiving objective medical information from the employee's physician. Substantiation of the employee s condition by an independent medical evaluation. Mail cycle time from the site to the benefit provider agent s desk. Note: The team identified opportunities to analyze data to determine if there is a similar rate of approval or denial for disability by business unit or site, if there are trends in disability incidence or diagnoses, etc, however these were not the focus of this project. IMPROVE There is no formal design of experiment being done in this project. Through the identification of the sources of variation and customer and benefit supplier feedback, several process improvements, training, and communications are underway. The process improvements addressing the sources of variation within the control of DuPont include: Electronic distribution of materials to employees and sites to reduce mail times. Implementation of fax server technology to process applications, eliminating mail times for new applications. Improvement of the application package, providing more complete directions and forms for the employee and site to complete when submitting the application. Improvement of the application package, providing more complete directions and forms for the employee s personal physician. The process improvements to address the sources of variation within the control of the benefit supplier include:

Staffing changes to reduce administrative burden on claims processors. Re-negotiation of contract terms for independent medical exam suppliers, to include tighter standards with financial penalties for poor performance. Implementation of e-mail confirmation and bi-weekly status reports on each case to the DuPont employment sites reminding all participants of required actions and preventing confusion over the status of a case. Addition of supplier and turn-around time reporting. Introduction of formal quarterly supplier process performance reporting to the DuPont process owner. CONTROL Several control mechanisms are being formally instituted to continually monitor and manage process performance. A new database is being established to track each application and to monitor the key sub-cycles. This database will be used by the process owner and be used to identify and react to 'out of control' cases before overall performance is affected. Supplier and total turn-around time reporting will be used to monitor and control case cycle times. In addition to the implementation training, periodic training will be provided to site HR personnel on benefits and benefit processing, particularly if there are benefit plan or process changes. In addition the training material will be add to and maintained in the corporate collaboration database, which is always available to site personnel for review, when personnel changes or refresher training is desired. CONCLUSION Applying the Six Sigma methodology provided factual information regarding the process performance and the sources of variation in a way that enabled rapid approval, from both DuPont and benefit supplier management, of the process improvements and information technology investments required to improve the process. The controls being implemented provide on-going measurement and managing by fact for the supplier services to specified service level standards and provide a clearer foundation for resolving any service issues. OVERALL CONCLUSION The Six Sigma problem solving methodology of Define, Measure Analyze, Improve, and Control can be used successfully in service processes to gain significant defect reductions. The use of data to guide decision-making ensures that the right root causes are identified and addressed. The Control phase ensures that the improvements are sustained. ACKNOWLEDGEMENTS American Express: Paul Winsick, Andy Cvitanov, Keith Siemek, Vickie Barefoot, Nick Apel, Jessica Shklar, and Chuck Aubrey DuPont: Don R. Linsenmann, Joanne M. Smith, and John P. McHugh