Waiting lines are characteristic of many service-based companies. Indeed, we find them in supermarkets, auto-teller machines (ATM), gas stations, and practically all around most service centers. Therefore, the pervasive nature of waiting lines makes them a common feature in our everyday lives. However, as Serson (1) observes, they are undesirable, and managing them is one of the most important aspects of operations management, especially for service-centered companies and organizations.
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Managing long customer queues is akin to creating workable schedules, developing effective job designs, and workplace plans to improve the quality of service delivery (McGuire 4). Nonetheless, many organizations have not figured out the best way to adopt these strategies in line management. This is particularly true in the banking sector, where long customer queues are a permanent feature (McGuire 4). This paper proposes a research study to reduce the waiting times and the formation of queues in banks.
The research would be a case study of a local bank in my community – GT Bank. The significance of undertaking the proposed research is to improve the quality of service delivery and customer satisfaction in the banking sector. Indeed, the study would provide recommendations that would lessen customer discomfort when they are seeking financial services at their favorite banks. Similarly, by adopting the findings of the study, customers and bankers would experience less economic costs of undertaking financial transactions.
- How can we reduce the waiting time and the formation of queues at bank counters?
Banks and many other service-oriented companies often depend on good customer service to improve their brand names and make a profit. Therefore, the amount of time consumers spends while waiting to be served at these companies is an important aspect of their operational performance. “As is well known, waiting time depends on several quantities, such as the system arrival rate, service rate, type of services, time of the day, and efficiency of the servers” (Agyei 160).
The banking sector, which is the hub of the financial sector in many countries, has often experienced a high demand for banking services from people who want to carry out financial transactions (Ogunwale 97). However, many of them have experienced problems emanating from the inability of banks to match their service facilities to customer demand. Here, the common experience for many customers is the lack of adequate facilities (in banks) to meet the service demands of their clients. Therefore, there is always a delay in the provision of services and hence the creation of customer queues in banking halls.
Ogunwale (97) supports this assertion by saying banking queues often exist because the demand for services often exceeds the supply of the same. Relative to this finding, Agyei says, “Some customers wait when the total number of customers requiring service exceeds the number of service facilities, some service facilities stand idle when the total number of service facilities exceeds the number of customers requiring service” (160). The problem in this scenario is that, for a long time, most customers have had an age-old desire for spending the least amount of time in banking halls; equally, banks have always wanted to retain their customers by offering the best customer services.
Consequently, banks have often strived to create solutions that would address the mismatch in service delivery and demand for banking services. For example, the introduction of auto teller machines was aimed at reducing the number of people who go to banking halls to withdraw money (Agyei 160-161). However, this strategy has not yielded many positive returns because of fraudulent activities at ATM machines and the increased number of service outages and breakdowns at the same service points (Agyei 160-161).
Independent research studies have revealed that numerous psychological and environmental factors influence the success of such strategies (Serson 1; Ogunwale 97). For example, the perceived waste of time perceived control, perceived boredom, perceived neglect, perceived crowding, and delayed gratification are some psychological factors that have an impact on customer satisfaction standards and customer loyalty for banks (McGuire 4). However, most of these factors are only indicative of the problem and not the solution.
There are many suggestions for eliminating banking queues. Some of the most popular ones include determining an acceptable waiting time for customers, trying to divert customer’s attention when waiting, and informing customers of what to expect when waiting (Serson 1; Ogunwale 97). Making sure the customers do not see employees who are not serving them, segmenting customers, training servers to be friendly, encouraging customers to come during slack periods, and taking a long-term perspective towards getting rid of queues are other recommendations that some researchers have proposed to manage the problem (McGuire 4-7).
Nonetheless, the general quest for most bank managers in managing customer service issues has been to balance the cost of providing extra customer care and the potential benefit of delaying customer service (Kelly 93). In other words, the main goal of banks has been to strike a careful balance between minimizing the economic cost of providing efficient customer services and reducing system overloads. Nonetheless, a significant gap in research has failed to show how to apply these philosophies in some of the proposed recommendations for managing queues.
Collection of both Qualitative and Quantitative Data
The proposed study would use a mixed-method research approach, which incorporates both qualitative and quantitative techniques of data analysis. The motivation for using the mixed methods research technique is the probable inclusion of qualitative and quantitative aspects of analysis in the research process.
The qualitative aspect emerges from the understanding that service delivery is mostly a qualitative issue. The quantitative bit emerges from the fact that queues may include numerical attributes, such as time factor analyses and customer number analyses. Both metrics are important in devising methods to reduce customer waiting times. Their possible inclusion in the research process justifies the use of the mixed-method research approach (Onwuegbuzie 1).
Since the proposed paper would include the mixed methods research approach, Onwuegbuzie (1) says the researcher can use research designs from both the qualitative and quantitative research methods to undertake the study. Based on this assertion, the exploratory research design emerges as the best technique for use because the research issue is contextual, and only a few research studies are available for referencing the research topic. Moreover, through the proposed study, the researcher would gain insight and familiarity into the research issue.
The nature of the research question is also exploratory because it is unlimited to one framework of solutions, as it leaves it open to the researcher to find a technique that would work to reduce the waiting times and eliminate queue formations at banking halls. Therefore, the exploratory research design is the most applicable technique for the proposed study (Onwuegbuzie 1).
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The data collection tools for the study would include a blend of qualitative and quantitative data collection techniques. In line with the goal of collecting qualitative data, we would conduct focus group discussions to get the views of customers and bankers regarding the research issue.
The focus group would comprise of 40 respondents. Half the would-be number customers and the other half would be the service providers. The main motivation for using this data collection technique is to stimulate discussions and gain deeper insights regarding the research problem and its possible solutions. In this regard, the researcher could possibly get information regarding customer experiences (when queuing) and understand their idea of a possible “ideal situation” when seeking customer services.
Similarly, the bankers would give their views on the same matter. Thereafter, the researcher would have an opportunity of merging the two perspectives to develop a concrete solution regarding the research issue. The data collection technique would also involve a review of secondary research information as an auxiliary source of data. The aim of doing so is to contextualize the views of the respondents.
This proposed data analysis process would stem from the data analysis framework of Onwuegbuzie (6), which outlines four phases of data analysis. The first step would involve the data transformation technique, which is a statistical method for analyzing qualitative data. The process would mostly involve two techniques that include data mapping and code generation. These techniques would be useful in analyzing qualitative data from the focus groups.
The second step in the data analysis process is data correlation. Here, the researcher would investigate the presence of diverse relationships among the different variables of the research problem. Particularly, this technique would be useful in identifying variables that affect customer satisfaction, or that would lead to the reduction of queues in banking halls. The third step in the data analysis process would be the analysis of the inquiry method.
This step would be useful in drawing inferences about the research variables and their contribution to addressing the research problem. The information gathered in this step would be useful in formulating the findings of the research and developing a conclusion. The last step of the data analysis process would involve the use of analytical frameworks between different methodological traditions to establish areas of convergence or divergence. This step would be pivotal in understanding how the proposed research adds or contributes to existing research.
The use of the exploratory research design has a lot of bearing on the interpretation of the research findings. Since the exploratory research design is unstructured, the findings of the study would be useful in generating a formal hypothesis, which appears in the section below. Nonetheless, the proposed findings would mostly be applicable to GT Bank because the research would be a case study. The outcome would be useful in creating more precise research questions for other banks in the industry.
Conclusion and Recommendations
Based on the growing adoption of information technology tools in the financial sector, the researcher hypothesizes that reducing waiting times and eliminating queues at banking halls would center on embracing “smart” technologies to reduce the demand for services. In other words, the solution would probably come from adopting demand-side solutions, as opposed to supply-side solutions. In this regard, the proposed study would add to the growing body of knowledge surrounding the improvement of customer satisfaction standards in the banking sector.
Agyei, Wallace. “Modeling and Analysis of Queuing Systems in Banks: (A case study of Ghana Commercial Bank Ltd. Kumasi Main Branch).” International Journal of Scientific & Technology Research 4.7 (2015): 160-163. Print.
Kelly, Stuart. Running Successful Projects, New York, NY: Lulu.com, 2012. Print.
McGuire, Kimes. A framework for evaluating the customer wait experience. Ithaca, NY: Cornell University, 2010. Print.
Ogunwale, Olubiyi. “A Comparative Analysis of Waiting Time of Customers In Banks.” Global Journal of Science Frontier Research 10.6 (2010): 97-99. Print.
Onwuegbuzie, Anthony. “Data Analysis in Mixed Research: A Primer.” International Journal of Education 3.1 (2011): 1-25. Print.
Serson, Fernando. A study of queues and customer service in retail bank agencies. 2015. Web.