Team C Business Research Project Part 4
Joshna Basant, Ashley Gates, Melissa Khan, and Hanane Kilaouy
Applied Research and Statistics – QNT 561
Dr. Ross DePinto
March 2, 2015

Team C Business Research Project Part 4
Introduction
AHJMR Inc. has noticed that certain days the wait time is longer. AHJMR wants to identify if review of a sampling of the calls shows if the wait times are actually longer on certain days of the week, or if it a perception. If AHJMR Inc. can determine that the longer wait time is related to a specific day of the week, the company can begin problem solving around productivity or staffing issues.
Formulation of the Research Problem
Team C is the management team that will review and analyze the data to determine the outcome of the hypothesis. The team determined that the independent variable (IV) is the day of the week, and the dependent variable (DV) is the wait time of the sample calls. The team determined that the research question to begin the study is: Are call wait times the same on each day of the week (Monday through Friday)? The research question is formed into a hypothesis:
Ho: There is no difference in wait time (DV) attributable to the day of the week (IV).
H1: There is a difference in wait time (DV) attributable to the day of the week (IV).
Initially Team C will identify if there is a difference in the wait times on each day of the week, then determine an action plan if needed.
Literature Review
Jouini, Dallery, and Nait-Abdallah (2008), describe two ways to organize a call center to increase efficiency for the center’s performance and quality. One of the ways described is how the customers have a dedicated team of agents and the other is the agents are grouped by specialty. Atlason, Epelman, and Henderson (2008) also wrote a discussion on efficiency and quality by specifying a method to reduce cost while maintaining service level. Jun and Manru (2014) highlighted the importance of the duration of calls wait time in enhancing customer satisfaction.
Olukemi, Shanthi, and Sigun (2009) discussed a different stance on efficiency by outlining the challenges of finding qualified candidate in call center. Their study analyzed how the attitude of the employee can affect the quality of service at the center (Olukemi, Shanthi, & Sijun, 2009). Bekker, Koole, Nielsen, and Nielsen (2011) took a different approach by studying how different telephone systems affect the level of waiting time. One model researched is dependent on a single server that matches its service based on the duration of waiting time of the first customer. The second model uses as a backup for the first server to make sure that the first customers wait time does not go for very long (Bekker, Koole, Nielsen, & Nielsen, 2011).
Jaoua, L’Ecuyer, and Delorme (2013) posited how call centers can be multi-skilled ones versus single-skilled calls that categorized calls by call type pools. This paper used the “Markov-process model of a call center with two call types served by two groups of specialized agents and one group of cross-trained agents” (Jaoua, L’Ecuyer, & Delorme, 2013, para.6). The experiment showed the use of routing policies that handled impatient customers (Jaoua, L’Ecuyer, & Delorme, 2013).
Beyond making specific changes in the process of a call center, another option to increase efficiency is to outsource. Ren and Zhou (2008) provided information for not only outsourcing, but also how to coordinate the service level and staff. Gans and Young (2007), discussed how call centers route their calls as well as the systems in place to prioritize calls based on classifying “customers as high or low value, serving the former with their in-house operations and routing the latter to an outsourcer” (Gans & Young-Pin, 2007). Bottom of Form
Saltzman and Mehrota (2001) used a simulation activity to help understand the boundaries of a product, the efficiencies of the call center, number of callers even during peak