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Case Study : An It Service Business 's Attempt For Improve Its Business Potential And Decrease Support Costs Per Call

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The case study in hand focuses on an IT service business’s attempt to improve its business potential and decrease support costs per call by incorporating six sigma DMAIC process. The process will aid the managers to identify key problems that are adversely affecting the company’s growth. Based on the data purchased from the clearinghouse, management team noticed that improving the process measures especially wait time in call center could significantly increase new account growth. A champion was assigned to take responsibility for the new project and a team leader and key team members were identified. Define: The goal and scope of the six sigma project is to increase the call center’s industry-measured customer satisfaction rating …show more content…

Analysis: In order to decide whether to reject or accept the hypothetical causes for higher support costs, the team used multi-vari charts to test. The chart, call type is X and support costs is Y, revealed that problems and changes criteria looked more expensive to service. In the chart, where call type and day of the week are X’s and support costs is Y, showed Mondays and Friday standout as more costly. With these insights, the next step for team was to discover lower factors which were really driving the Y. Fish bone tells the team that the driving factor of staff availability and why the variation on Mondays and Fridays is so wide. Y-to-X tree highlighted that the team should view the staffing/call volume as a ratio. Cause-and-effect matrix raises web-to-phone issue that was not measured initially. Having deeper understanding about what might be the driving factors for Y, the team is going to use statistical tools to verify the critical X’s. The charts where day of the week is X and call volume/staffing ratio is Y indicated that Fridays and Mondays are understaffed. The ANOVA table showed that the influence of callbacks on a call’s wait time is statistically significant. Improve: The team identified staffing, web service percentage, transfers and callbacks as areas where improvement could be

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