Collaborative Research: Robust Strategies for Cross-Training Call Center Agents - Taxonomy, Models, and Analysis

交叉培训和呼叫/代理分配策略的研究是一个成熟的研究课题，不仅具有科学创新性，而且在呼叫中心管理实践和绩效方面向前迈出了重要的一步。这项研究有可能通过提高职业发展和生活质量来影响呼叫中心工程师，并通过改进实践来帮助组织建立呼叫中心，从而提高盈利能力。此外，它还将提高呼叫中心用户的服务质量，呼叫中心用户几乎包括所有人口。根据Data Monitor的数据，在过去十年里，呼叫中心已经成为一个雇用了大约300-400万美国人的大型服务行业，每年以约10%的速度增长。呼叫中心的运营管理是一项出了名的困难任务，它已经发展到可以根据呼叫者的技能和培训，将呼入动态地路由到最合适的客户服务代表(CSR)或代理的技术。这不仅关系到方便和利润，还关系到更多。911、警察、救护车和消防调度等关键紧急服务依赖于呼叫中心，并已尝试使用交叉培训呼叫中心工程师来处理多种呼叫类型。为了应对这些紧迫的需求，该项目开发了创新的方法，以制定有效的战略，以确定哪些工程师应就多项任务进行交叉培训，以及如何最好地将呼叫分配给他们。主要调查人员与行业呼叫中心经理和软件解决方案提供商进行了互动，以最大限度地发挥这项工作的影响。这项研究将为呼叫中心环境构建详细的概念性分类方案，以确定与交叉培训策略的选择密切相关的关键特征。它将创建和分析一系列数学模型，这些模型利用基于技能的呼叫路由来预测各种交叉培训模式的性能，并从成本/收益的角度洞察决定其有效性的因素以及系统的响应性能。分析将使用包括排队论、马尔可夫决策过程、离散事件系统理论和模拟在内的工具。这项研究的预期结果是：(1)管理洞察力，极大地加深了对哪些系统将从交叉培训中受益以及实施的合适策略的理解；(2)CSR(客户服务代表)交叉培训策略，这些策略在广泛的呼叫中心中非常有效；(3)用于分析和设计敏捷工作系统的有用分析模型；以及(4)排队技术基础的扩展，以包括广泛的系统类别，其中服务器基于其技能集以新的和复杂的方式运行。实施后，结果将通过提高服务质量影响呼叫中心的用户，通过提高职业发展和生活质量影响代理，通过改进管理实践影响公司(小型、中型和大型呼叫中心)。

This research on strategies for cross-training and call/agent assignment is a ripe research topic that promises not only scientific innovation, but also a significant step forward in call center managerial practice and performance. This research has the potential to impact call center agents through increased career development and quality of life and help organizations with call centers through improved practices that lead to improved profitability. Moreover, it will increase the quality of service experienced by the users of call centers, which includes nearly the entire population. Within the last decade, call centers have become a large service industry employing roughly 3-4 million Americans, growing at about 10% annually, according to Data Monitor. The operational management of call centers, which is a notoriously difficult task, has developed to the point where the technology is already available to dynamically route incoming calls to the most suitable customer service representative (CSR), or agent, based upon their skills and training. Much more than convenience and profit are at stake. Critical emergency services such as 911, police, ambulance, and fire dispatching depend upon call centers and have experimented with cross-training call center agents to handle multiple call types. In response to these pressing needs, this project develops innovative approaches to setting effective strategies for determining which agents to cross-train for more than one task as well as how to best assign calls to them. The principal investigators have interacted with industrial call center managers and software solution providers to maximize the impact of this workThis research will construct a detailed, conceptual classification scheme for call center environments that identifies key characteristics germane to the selection of a cross training strategy. It will create and analyze a series of mathematical models that predict the performance of various cross-training patterns utilizing skills-based call routing and provide insight into the factors that determine their efficacy from a cost/benefit perspective as well as the system's response performance. The analysis will use tools that include queuing theory, Markov decision processes, discrete event systems theory, and simulation. The anticipated results of this research are: (1) managerial insights that greatly deepen the understanding of which systems will benefit from cross-training and a suitable strategy for implementation; (2) CSR (Customer Service Representative) cross-training strategies that are robustly effective across a wide range of call centers; (3) useful analytical models for the analysis and design of agile work systems; and (4) extensions of the queuing technology base to include broad classes of systems where servers operate in new and complex ways based on their skill sets. Upon implementation, the results will impact users of call centers with increased quality of service, agents through increased career development and quality of life, and firms (small, medium, and large call centers) through improved management practices.