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Bat Case Report Essay

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Executive Summary
BAT is a technology that sells financial software to individuals and organizations. BAT’s success had attracted a number of competitors. BAT differentiated itself by committing to free tech support for the life of the product. BAT started its call center operations in 1987 with 6 technicians which grew to over a 100 technicians by 2002. However, the call center has been under pressure in terms of long waiting times for customers. Such poor service was beginning to take its toll on the company’s reputation.
We recommend that BAT should implement the Fast Track proposal in order to improve customer service and the company’s bottom line. We understand that free technical support is BAT’s value proposition and central to …show more content…

Please refer to Appendix 2 for details.

Fast Track

We considered different staffing plans and ran Queuing Macro for average wait time. We considered adding servers and keeping one queue, and other scenarios with dedicated Fast Track Servers. We ran Queuing Macro under five different staffing scenarios: (Please note that we have dedicated Fast track servers in Scenarios 4 and 5)

Scenario No | No of Standard Servers | No of Fast Track Servers | 1 | 8 | 0 | 2 | 9 | 0 | 3 | 10 | 0 | 4 | 7 | 1 | 5 | 7 | 3 |

The following results were observed:

Refer to Appendix 3 for spreadsheet calculations.
As observed in the data, Scenario 2 and 3 succeed in keeping Average waiting for track customers to less than 1 minute. Scenario 2 uses less number of resources. Scenario 2 (9 technicians) is the best staffing level, without dedicated servers for Fast Track.
Economics of Fast Track
We’ve now established that Scenario 2 and 3 keep average wait time to less than 1 minute to help meet the Fast Track Guarantee.
In Scenario2, The average server utilization is 75%, which is an adequate level. The additional yearly net revenue that can be obtained ranges from $54,325 to $376,300 depending if 10% or 40% of customers become Fast Track customers.
In Scenario 3, The average server utilization is 68%, which is not as good as in the previous scenario. The additional yearly net revenue that

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