Two questions are in the end.

about 2-3 pages. double space

The Institute for Marketing Deployment (IMD) is a non-profit organization that assists small startups in developing countries with marketing their goods and services. The organization is often associated with microlending, where relatively small amounts are loaned to individuals to start small enterprises in communities where traditional financing is unavailable. IMD’s headquarters is located in Toronto Canada. It has subsidiaries in many countries, most notably India, Kenya, Chile, and South Africa. As such, IMD requires strong information technology (IT) to facilitate the movement of information across great distances.

The IT department at IMD (IMD-IT) supports the organization by overseeing the purchase, training, and service of all IT resources. Their responsibility encompasses hardware, software, and associated devices, such as printers, scanners, projectors, and other peripherals. IMD-IT supports all internal business units, with its main internal customers residing in three departments: operations, finance, and human resources. The operations department has personnel in locations around the world. Each week, IMD-IT is available 6 days (Monday through Saturday) from 0900-1900 (9 am to 7 pm, Toronto time zone), for a total of 60 hours per week.

IMD-IT is led by 58-year-old Randy Albright, who has worked at IMD since its founding in 1992. Originally a political scientist, Randy took over IT responsibilities because no one was available with significant IT expertise. Randy was somewhat of a computer hobbyist and he welcomed the challenge. Over the years, his IT expertise has grown and he enjoys his work. The department includes three functions: one devoted to purchasing hardware and peripherals, one devoted to purchasing and updating software, and one devoted to troubleshooting (which handles both hardware and software issues). The troubleshooting function operates a help desk through which all customer requests are processed. Customers contact the help desk by e-mail, telephone, or walk-in.

Every customer contact with the help desk generates a help ticket. Each ticket is immediately routed to a technician. Two groups of technicians currently exist – one group devoted to hardware problems and one group devoted to software problems. No preference is given to customers based on how they contact the help desk. Once the help ticket is written, jobs are assigned to technicians on a first-come first-served basis. The help ticket provides formal documentation of the request, how the issue is solved, and the responsible technician. Therefore, it provides a history of each job handled by troubleshooting.

Recently, troubleshooting customers have been complaining about long waits for getting their problem solved. An analyst from the business analytics department (Mimi Li) is assigned to work with IMD-IT and find a solution. Mimi is a 27 year-old graduate, among the first to earn an applied business analytics master’s degree. Her undergraduate degree is in mathematics. This is her first professional job. Mimi’s first task was to collect performance information from previous troubleshooting help tickets to determine the source of the complaints. According to data collected last year, about 40% of tickets had a turnaround time of less than 45 minutes, but about 10% of tickets were closed after 4 or more hours. Because a turnaround time of 4 hours constitutes about half of an internal customer’s work-day, many tickets were closed on the day after they were opened. The turnaround time is working hours not real time. For example, a ticket opened at 3 PM on Tuesday and closed at 9 AM on Wednesday would be recorded as a 6 hours turnaround time. The average turnaround time was about 55 minutes.

When interviewing customers, it became evident to Mimi that the main problem was not the length of the wait, especially for those customers whose problems were complex, but the variations that cause uncertainty among its customers. As one customer, Natalie Sutera, noted: I am a frequent user of printing and scanning devices. I make a lot of requests for minor problems, especially network connection issues. Most times, the problem is addressed and solved in less than an hour. But, other times, I have to wait until the next day for the problem to be resolved. These delays can cause my clients to wait and become dissatisfied. In some cases, the days caused them to miss important deadlines. I wish the IMD help desk were more consistent.

Other customers were happy because the variations resulted in unexpected short turnaround times, even for seemingly complex requests. However, it was clear to Mimi that IMD-IT needed to have better control of customer turnaround times for their troubleshooting service.

Randy was not entirely convinced that Mimi’s help was needed. In his opinion, some technicians were not working as hard as others. He suggested that a system be initiated where long lead times are flagged so that he could talk with the responsible technician. In response, each month Mimi generated lists of technicians and dates associated with the longest 10% of turnaround times. The lists, however, showed that long turnaround times occurred about equally among the technicians. It also showed that almost all technicians appeared on the list in some months but not in other months. Hence, Mimi believed that the problem was systemic (i.e., a natural result of the way the system was managed) rather than being caused by “bad” technicians. She decided to pursue this capacity planning issue in more detail.

After creating a better system for creating shift schedules for technicians at the IMD Help Desk, Mimi Li set out to determine the specific staffing levels for various work shifts. For each work shift, two options will be considered. The first option (Figure 1) is similar to the current system, where jobs are segmented. Hardware problems are solved by hardware technician and software problems are solved by software technicians.

The second option would consist of a common set of servers that handle both hardware and software problems. Because much of the training and knowledge base of software and hardware technicians are common, the amount of retraining would be manageable if this system were implemented. However, in the long run it is anticipated that all-purpose technicians will be paid 10% more than technicians that specialize in either hardware or software problems. In both options, problems will continue to be solved on a first-come, first-served basis. Due to the number of reasons, it would be impossible for servers of the segmented option to switch to solving other types of problems (e.g., hardware technicians cannot be temporarily be reassigned to solve software problems).

Figure 2: Common Option General Technicians All Problems Hardware Technicians Hardware Problems Software Technicians

1. Explain to Randy why his estimate of four workers needed during the early weekday period is flawed. Remember that his background is in political science with acquired IT expertise. Create an explanation that he will understand.

2. List up to six important assumption required to apply the M/M/s queueing model at the IMD help desk for evaluating the two alternative presented in this analysis. For each assumption, write 1-2 sentences explaining why it is a valid assumption.