Process Improvement in a Contact Center

Process Improvement in a Contact Center

Introduction

In 2008, the state inaugurated the Abu Dhabi Government Contact Center. The purpose of the center is to improve the public’s access to relevant information originating from the government, an initiative expected to improve service delivery and accountability. It serves as a portal for all government services in the country. As of 2018, the contact center had listed 3730 services, both from the federal and local levels of government (The United Arab Emirates’
Government portal, 2020). It serves as a repository for all information (and how to access more information) and services necessary for living, working, studying, or investing in the country. Essentially, it reduces the bureaucracy often associated with the provision of services and access to information from the government.  It acts as an eService portal; hence, citizens and visitors to the country do not have to visit government offices physically to access relevant services, a factor that improves efficiency. Since most services are offered remotely, a SmartPass is required. It is a single digital account that is unique to every individual where one can then access all the available government services.

Accordingly, the public can access essential information using the contact number, 800555. The contact is toll-free, and members of the public can use it at any time of the day. In 2018, the center handled approximately 900,000 calls with a customer satisfaction rate of 88% (Sutton, 2018). Additionally, the public can use the call center to access some services such as registration of births and application of business licenses. As an illustration of its effectiveness, in 2018, almost all cases of payments of traffic offenses fines and the renewal and application of work permits were processed through the center (The United Emirates’ Government Portal, 2020). Further, individuals can request information on essential aspects, like the visa requirements of other countries.

Despite the relatively high customer satisfaction rate, the agency faces significant challenges that continue to affect its ability to offer services to residents of the UAE. In this study, the area of focus would be the AWT. Therefore, the assessment will explore means of reducing the waiting period from the current 90 seconds to 20 seconds for 80% of the traffic coming into the center, which is the average in the industry. The organization of the research paper is in five main parts, namely, the problem description, research questions, analysis, and data availability, results, and the conclusion sections.

Problem Description

The contact center is involved in the business of service delivery. Consequently, it is vital to have objective measures that gauge its success in delivering its mandate. One of these objective measures is the waiting time a customer takes before getting the case resolved. In best practice contact centers, the primary goal of the management is to minimize the waiting time as much as possible. Such an outcome is beneficial because it improves customer satisfaction while increasing the number of clients that such a facility can serve within a given time. Nevertheless, the waiting period at the center is exceptionally long. The average waiting time (AWT) in the sector is approximately 90 seconds for all call traffic. Yet, the average for the industry is 20 seconds for 80% of the traffic within a call center (Call Center Helper, 2019). This outcome reduces the ability of the facility to serve its clients appropriately, a factor that would lead to an increase in the rate of customers not satisfied with the center’s service. Additionally, it also contributes to the center not achieving its mandate, which is to ensure enhanced access to relevant information. Consequently, addressing this problem is a matter of urgency.

Research Question(s)

1. Why is the call center’s average waiting time higher than the global average of 20 seconds?
2. What action should be taken to reduce the average waiting period to 20 seconds?

The research questions are vital in addressing the underlying problems. By figuring out why the call center’s waiting times are high, it would be possible for both scholars and the management to define challenges and barriers to effective service delivery that the center faces. Secondly, such a step would provide the basis for establishing recommendations necessary for addressing the problem, especially considering that this analysis is objective.

Analysis and Data Availability

The review will take place within the conceptual framework of the waiting time theory, also known as the queuing theory. Additionally, the process analysis framework will be used to provide an overview of the activities that happen within the contact center to determine possible causes for the high waiting times. Having an understanding of the undertakings within the facility is crucial. It offers insights on the potential areas of weaknesses within the center’s operations; hence, it allows the management to troubleshoot and improve the process. Overall, the queuing theory serves as a model with which one can predict the waiting time in a queue. To achieve this outcome, the model takes into consideration the various activities that occur within a service area. For instance, in a contact center, numerous representatives are present within a ‘single node.’ However, not all of them are actively engaged in service delivery at any single time because of elements like breaks and the time lapse between serving one customer and the next.

Given the centrality of the queuing theory in this research, it is vital to provide background information on what the model entails. The theory’s primary concern is the organization of queues within an area — lines are a common scenario in daily activities, such as in banking halls, supermarkets, and in this case, a contact center. Nevertheless, it is worth noting that the nature of a queue in a call center is unique when compared to supermarkets or markets facilities — in the latter, the lines are physical while in the former, they are virtual because of the use of remote communication gadgets, like mobile phones. Nonetheless, the concept behind the model remains the same, whether the line is virtual or physical.

The rationale for using queues in the delivery of services is limited resources. It would not be economically feasible to employ a customer service representative for every individual in the UAE. Therefore, lines are an essential part of daily human activities. However, it is vital for the management of an organization that offers services involving queues to strike a balance between providing efficient services to its clients and economic considerations like budgetary allocations from the government. Thus, the use of the waiting time theory offers management with an opportunity to optimize the resources available while providing timely and efficient services.

The theory is based on two central notions; the arrival process and the service requirements phase. The arrival process entails aspects such as the distribution of time and the way individuals arrive within the queue. For instance, at a call center, the distribution of time implies the periods where call traffic and inquiries are likely to be high. The way individuals arrive refers to whether they come in groups or individuals. In the center, the manner of arrival is often in groups because the number of clients attempting to access available services is usually high at any one time.

Service requirements refer to the evaluation of resources needed. It also covers the service time distribution, which is the period required to address the concerns of a single customer. Additionally, the number of services available is an essential consideration for the service mechanism. Currently, the center focuses on four functions, namely, requesting information, applying for services like visas, as well as making suggestions and complaints.

Accordingly, evaluating both the service requirements and the arrival process is vital for this study. It would help both scholars and the management of the center in understanding why the average wait times are considerably high when compared to other facilities across the globe. Having a conceptual understanding of the underlying problem is integral because it would enough future management practices. Therefore, by applying the waiting time theory, it would be possible for the management to optimize the processes to improve the speed of providing services; hence, reducing the average time in queue.

Some data is vital for the study to take place. Such data includes the center’s average wait time, the number of requests for information, the number of clients applying for services, number of complaints, and suggestions. All this data can be sourced from the government agency, especially considering that it is a public service. Some of the information that may be challenging to obtain is service level agreements. However, given that the agency has committed itself to best practices, then an assumption that its service level agreement is like the global standards would be made. From such information, it is possible to estimate other secondary data, such as the approximate number of employees for the organization. Consequently, the availability of relevant data will not be a significant problem.

Results

From an assessment of data from the contact, the average waiting time is 90 seconds. This period is significantly longer when compared to the industry average, which is just 20 seconds. The long waiting time is attributed to various factors, as highlighted in this section. One of the primary findings is that there is minimal segmentation of the services availed by the contact center. For instance, all requests over the phone must go through the 800555-contact number. This occurrence illustrates a parallel queuing system — a single line for all the customer care representatives at the center. The consequence of such a service architecture is that it tends to be slow. The slow pace arises because each customer must wait for the one ahead of the line to complete their inquiries. The parallel service architecture occurs in contract to the series queuing system, where the representatives offer service across several lines. The challenge with the parallel queuing system is that it is less effective in optimizing resources, especially in circumstances where the number of serves is high, as is the case with the call center.

Another finding from the data is that the traffic to the contact center varies. It changes depending on the times of the day. The demand for services is often at the highest in the morning and early afternoon. Yet, the number of customer service representatives at the center remains constant throughout the day. Such a situation highlights inefficiency at the agency. When customer traffic is high, a backlog ensues, making it difficult for the representatives to honor all the requests for information and facilitate applications for services like visa application payments.

Moreover, the ability of the representatives to dispense complaints and address suggestions is also affected. During low peak hours of the day, traffic, and demand for services. However, even then, the backlog from the peak hours makes it difficult for the contact center representatives to serve customers effectively, despite their low numbers. Consequently, if the center’s management wishes to improve its governance, it should adopt measures to spread out the number of employees such that a high volume is available during peak hours while reducing the same during off-peak hours. This step is necessary as it allows the management to optimize its existing set of resources without having to resort to additional support from the UAE government.

From the evaluation, another challenge facing the agency is inadequate staffing. Its service level agreement intimates that the organization seeks to offer services at a 90% rate. However, according to Baraka, Baraka, & El-Gamily (2013), such a high percentage of efficiency in service provision at a contact center requires a high number of employees. An evaluation of the number of employees the agency has compared to its stated service level agreement indicates that it is relatively understaffed. Accordingly, the low number of employees is one of the main contributing factors towards the high waiting times and unresolved cases that its customers experience. The management must strike a balance between the achievement of customer needs and economic considerations. However, it vital not to give excessive focus on financial concerns at the expense of services available to clients, especially considering that services offered by the organization are public.

From the evaluation above, understaffing is another conceptual problem that faces the agency. As a service, members of staff play a vital role in the center. Therefore, it is not only essential to have the appropriate equipment, but also adequate staff numbers. However, it may also point to a lack of productivity among members of the existing staff body. The total number of calls handled by a single employee per day at the center is 23, a number that is below the global average — the global average is 40 calls per employee per day (Call Center Helper, 2019). Without improving on this number, achieving a favorable service time distribution will be a challenge. Therefore, such an outcome may point to a need to retrain the center’s staff on customer service aspects such that they would be able to handle more calls per day while maintaining a high quality of customer service delivery within a short period.

Conclusion

An analysis of the results helps to answer the research questions. The findings indicate that the average waiting period at the center is relatively long, 90 seconds, against the global best practice of 20 seconds. Additionally, the results also indicate that the traffic of calls to the center is not evenly spread throughout the day — network traffic is at its peak during early morning hours and in the afternoon. Similarly, the demand for services varies across the four main categories — applying for services is the category with the highest demand. Another critical finding is that the agency is relatively understaffed, a factor that may contribute to the long average waiting period. Nevertheless, in the analysis of the results, it is also evident that the productivity of the employees is low — on average, each employee handles about 23 calls a day, an outcome that is below the global average. It is these findings to the research questions that form the basis of the recommendations below.

To reduce the average waiting time, the agency needs to segment its services. Currently, all customers, regardless of the service they desire, approach a server using a parallel queuing system. Nevertheless, this system is not the most optimal, especially considering that the demand for various services varies. Evidently, data from the United Arab Emirates’ Government portal (2020) indicates that the demand for applying services, such as visas and payment of traffic fines, is significantly higher when compared to the rest of the services. Therefore, it is not optimal to allocate a single server in the parallel system to offer assistance in all four categories. Instead, the agency’s management should employ a weighted system where the most in-demand services are allocated the most resources.

Accordingly, the most optimal approach entails the use of a series queuing system. In this approach, the agency’s management would segment its servers based on the categories of services offered. Further, the number of servers should reflect the demand for a service. For example, given that applying for services has the highest level of need, more customer care representatives should be allocated to this segment. To achieve this outcome, it is essential to increase the contact numbers to reflect the number of major service categories. Currently, the only contact number in use is 800555, which implies that all service requests must go through a single node, a factor that may contribute to delayed responses; hence, prolonged average waiting times. Therefore, each of the four services should have a unique contact number to reduce network congestion.

The agency should also change its shift system. Currently, the number of customer service representatives is constant throughout the day. However, an analysis of the results indicates that traffic into the center is not continuous throughout the day — network traffic is high during the early morning and afternoon hours. This variation in network traffic implies that during peak hours, the system becomes clogged with calls, a factor that contributes to the increase in average waiting times. Consequently, the high average waiting times lead to lower rates of customer satisfaction. On the contrary, during off-peak operating hours, most of the servers are idle because the volume of traffic is low. Therefore, while the average waiting times during the off-peak hours is low (and in line with the global average), the figure rises significantly during peak hours, this imbalance leads to the overall high waiting for the center.

To address the problem, it is essential for management to spread its human resources in a way that reflects the varying demand for services. Therefore, to address this challenge, it is imperative to adopt a versatile shift system, and in line with work demand. In the peak operating period, the number of serves should be at its highest, while their numbers should be reduced when operations are slow. This approach is practical because it allows the agency to optimize its existing human resources without requiring additional funding from the state.

In the long run, the agency should consider increasing the number of customer service representatives. In 2018, the center handled 900,000 calls, a testament to the high demand for services offered by the agency. Consequently, the center’s management needs to ensure that its capacity also grows in tandem with the demand for services. A rising number of employees would ensure that more of them are at the disposal of customers seeking services; hence, it would reduce the average waiting times.

The agency should also apply statistical models to determine the most optimal service distribution times and the average waiting times. Presently, computer simulation models exist to calculate probabilities and service mechanisms; hence, the management of the organization should apply similar tools. They are cost-effective and convenient. Furthermore, they provide the administration with an effective platform on which to establish strategic plans because they incorporate the waiting time theory in their statistical models. The justification for this recommendation is that the agency has access to a vast amount of data points that can be used to determine customer requirements; thus, making it possible to predict customer behavior and service requirements. Fundamentally, such an approach would improve the decision-making capacity of the agency.

Finally, the government contact center has improved access to information for citizens and visitors to the UAE. As an illustration, some government services are now almost exclusively offered on the portal. These services include the payment of traffic violation fines. However, despite the efficiency of the contact center, it still faces significant challenges. Some of the core problems it faces is a high average waiting time when compared to the global average and extended service time distribution. To address these challenges, the agency needs to adopt measures that improve its processes, a task that is made possible by applying the conceptual framework of the queuing theory. Based on the theory, some of the recommendations include changing the queuing characteristics from parallel to series. Additionally, it should also improve its capacity in the long run by increasing the number of staff members available.

References

Baraka, H. A., Baraka, H. A., & EL-Gamily, I. H. (2013). Assessing call centers’ success: A validation of the DeLone and Mclean model for information system. Egyptian Informatics Journal, 14(2), 99–108. doi:10.1016/j.eij.2013.03.001

Sutton, M. (2018). Abu Dhabi Government Contact Centre handles 900,000 calls. Arabian Industry. Retrieved from https://www.arabianindustry.com/technology/united-arab-emirates/news/2018/aug/27/abu-dhabi-government-contact-centre-handles-900000-calls-5967325/

The United Arab Emirates’ Government portal (2020). Information and services. Retrieved from https://www.government.ae/en/information-and-services#/