The concept of a service level balances the clients’ expectation of immediate service fulfillment and the imperative of loading the capacity of service providers to meet the objectives by means of accounting figures. The basic problem is simply illustrated by a stochastic process of upcoming service orders, for example, customers arriving at a supermarket checkout or inbound telephone calls arriving at a call center. The process of service requests is usually a Poisson process, or if different qualities of services are considered, a multivariate Poisson process.
The number of operators who are active in a time unit determines the costs as well as the capacity of the system. If the operators are busy when a new service request arrives, the client has to wait for the service. The service level expresses the percentage of clients who do not have to wait longer than a given threshold: the acceptable waiting time. The arrival rate of service calls in the system is called λ (intensity of the Poisson process), and β is the intensity of handling and providing the service (β = μ-1).
The simplest system is modeled by an Erlang-C system. If there is an average of one call per time unit (i.e., on average, one customer enters the checkout zone of a hypermarket in a minute): λ = 1, the checkout takes about six minutes: β = 1/4, and if, in this example, there are six checkouts serving the customers, one would expect that none of the customers has to queue at the checkout, because the capacity is 90 customers per hour, but only 60 are arriving. However, the arrival process is a random process, and therefore the time intervals between the customers’ arrivals are not fixed. Assume the waiting period of 30 seconds would be acceptable to the customers.
Solving this Erlang system mathematically now yields the interesting result that only a fraction, 78 percent of the clients, will get the service within the 30 seconds. Thus, the service level is 78 percent.
Defining an appropriate service level is relevant in various management tasks. The design of physical service systems is straightforward, for example, checkouts in retail outlets or check-ins at airports. A more prominent application domain is the configuration of information processing systems. For instance, database retrieval might be acceptable within 20 to 30 seconds, in the case of a hotel booking system or a flight reservation system. However, in the control of hospital intensive medical care, a response is needed within fractions of a second. Beyond these technical applications, human resource planning of many companies should be governed by the aim of reaching the appropriate service level. In outsourcing projects, mutual signing of a service level agreement (SLA) is common practice. During the negotiation of these projects, the partners discuss service level requirements (SLR), which address the same contents, but are not noncommittal contractually.
The service level has advanced to one of the most assessed aspects of service quality in technical disciplines, and has recently been receiving increasing attention in general management studies. This can be traced back to three modern management developments:
- The dominance of the service process perspective in the redesign of business process literature at the end of the 1990s: For instance, the balanced scorecard concept of Robert Kaplan and David Norton, which has been widely adopted in business practice, is grounded in the idea of separating business processes and assigning process responsibilities to individual employees.
- The ascendancy of supply chain management systems in business practice and research literature: The service level enables defining quality criteria for the replenishment of all kinds of physical goods at the point of sale. Criteria based on service level are superior to criteria concerning the periods of out of stock in a wide range of scenarios.
- The paradigm shift in marketing science: Starting with the seminal contribution of Stephen L. Vargo and Robert F. Lusch in 2004, marketing scientists, practitioners, and consultants are reconfiguring their marketing strategies and related performance metrics. The core contribution of Vargo and Lusch highlights the relevance of services rather than the products in conventional marketing mix management. Consequently, the service level advances to a key concept for deriving quantitative performance metrics for this innovative marketing gestalt.
The mathematical formalism to calculate the service level is implemented in standard business process software systems, such as SAP.
However, the concept of the service level has a serious drawback: No further information concerning the not-served clients is derived. Here, the critical question is their actual waiting time in addition to the accepted waiting time. More sophisticated performance metrics are derived from the stochastic Erlang model, but their adoption is restricted to technical applications.
Another problem is the determination of an appropriate service level. This task is comparatively easy in the replenishment application, if strategic goals are neglected. In this case, the costs of increasing the service level need to balance the profits from additional sales in an accounting calculus for determining the optimal service level. If additional strategic goals are considered, for example, differentiation from competitors by means of service offers, calculations are more complicated.
Bibliography:
- Brad Cleveland and Julia Mayben, Call Center Management on Fast Forward: Succeeding in Today’s Dynamic Inbound Environment (Call Center Press, 1997);
- Andrew Hiles, E-Business Service Level Agreements: Strategies for Service Providers, E-Commerce and Outsourcing (Rothstein Catalog on Service Level Books, 2002);
- Robert S. Kaplan and David P. Norton, The Balanced Scorecard: Translating Strategy Into Action (Harvard Business School Press, 2008);
- Ger Koole, Redefining the Service Level in Call Centers (Vrije Universiteit, 2003);
- Management Advisory Services & Publications Consulting Group, How to Prepare Service Level Agreements (SLAs) for Application Service Provisioning (ASP): Checklists and Guidelines (Management Advisory Services & Publications, 2001);
- John McConnell and Eric D. Siegel, Practical Service Level Management: Delivering High-Quality Web-Based Services (Cisco, 2004);
- Rick Sturm, Mary Jander, and Wayne Morris, Foundations of Service Level Management (Sams, 2003);
- Stephan L. Vargo and Robert F. Lusch, “Evolving to a New Dominant Logic for Marketing,” Journal of Marketing (v.68/1, 2004).
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