Service Chain Management

The growth of the services sector in recent times has been phenomenal with services displacing manufacturing as the main driver of western industrialised economies. However, a disproportionate part of the yearly productivity growth in OECD countries is still due to improvements in manufacturing (Wölfl 2005). In this context, Service OperationsManagement (Johnston and Clark 2001; Schmenner 1995) is becoming increasingly important for companies and government alike to achieve productivity growth and a cost advantage over their domestic and international competitors. This includes technologies and systems for automating and optimising service operations within and across companies which we will refer to them collectively as Service Chain Management.

One of the cornerstones of successful organisations has been the optimal use of their workforce. Two types of resources characterise service organisations: front and back office resources. These resources are defined by their capability (i. e., skills), location and availability. Front office resources handle incoming demand whilst the back office resources execute the services related to the demand. Planning of such resources can be carried out at one of three levels: strategic, tactical and operational; referring to long-, medium-, and short-, term planning respectively. The three levels for planning may overlap or may be distinct. Either way there is a flow of information from strategic to tactical and from tactical to operational. The loop is then closed by flow of information from operational back to strategic (see Fig. 3.1). In this context, strategic planning provides information on the overall balance of customer demand with available resource capacity. Tactical planning suggests a coarsegrain allocation of resources to tasks with no consideration given to when those tasks must be executed. And operational planning represents the allocation of specific resources to specific tasks; detailing the specific times of execution. The level of detail required for planning increases as one moves in time from strategic to operational. For strategic planning it is sufficient to analyse resource requirements based on the number of resources and their levels of productivity. On the other hand, for operational planning it is imperative that details such as starting location, preferred working location, scheduled hours, and availability for overtime are identified for accurate deployment to be realised.

Compared to traditional manufacturing and supply chain, forecasting in the service industry is in a nascent stage. Forecasting in the service chain is not limited to forecasting of sales, raw material or components but it could be as varied as forecasting internet bandwidth requirement, call volumes at a call centre or the customers walking into restaurant between 8 pm to 9 pm on Saturday evening. The variety and complexity of forecasting requirements changes from business to business.

One of the key goals for service businesses is to find the right balance between the quality of service delivered to its customers and the incurred cost. The quality of service should be as high as possible in order to achieve high customer satisfaction and retention, and this often increases costs. Authorising overtime, for example, to guarantee timely service delivery has financial consequences. However, costs generally should be as small as possible to achieve high profitability. Clearly both objectives are contradictory and often cannot be fully satisfied at the same time due to the constraints on resource utilisation

For network centric businesses such as telecommunication providers and utilities, networks form the core of their business and comprise a very expensive asset that needs careful management to fulfil both present and future requirements of customers. Correctly planning and designing the network is essential to the success of such businesses. The network planning and design process can involve planning and design at different levels of detail from high level strategic or business planning through to low level detailed planning and design. Network planning and design forms part of a wider provisioning process encompassing order handling, job tracking, network design and configuration through to order fulfilment and billing. This chapter focuses on the network planning and design process together with a brief examination of the opportunities provided through use of network optimisation techniques therein improving upon results obtained through use of manual techniques alone.

The increasing sophistication of today’s customers poses certain challenges such as responsiveness, accuracy, predictability and the reliability of service appointing to service providers in both private and public sectors. Reservation management technology is rapidly evolving to address these challenges.

What does Revenue Management (RM) mean and how does it work? In which industries is it being practised already? What is the theory underlying RM1? One might have heard the term applied in the context of the airline industry, but how could it be used in other service industries such as telecommunications? Can it be used in organisations of any size? How much effort would be needed to implement it and how complex is the required technology?

Personnel Shift Scheduling and Rostering problems are found in many different types of organisations and industries including manufacturing, call centres, the airline industry, health services, utilities and the transportation industry. More generally, the importance of an efficient shift scheduling system is critical to any large organisation especially in the service economy where production and consumption normally coincide. The generation of optimised shift and roster patterns is, undeniably, a key instrument for making best use of the resources of a service enterprise. The efficiency of such a system leads to maximisation of the customer experience by matching the demand with the appropriate staffing level and minimisation of the cost by reducing idle time of the resources.

In the last chapter, we discussed the problem of automating and optimising shift allocations to people in order to meet certain service levels. Now that the number and type of people that need to be rostering in on the day have been determined, there is a need for scheduling work to them. The focus of this chapter is on the challenges in implementing an effective work allocation and scheduling system.

The employees within an enterprise performing tasks in the service chain represent the ‘capacity’ available and, therefore, directly influence the ability of the chain to process work. This capacity has a number of component parts: the people themselves, their planned attendance and variations – positive through overtime or negative through absence. This ‘net availability’ must be maintained accurately, and in real time, to enable effective planning, scheduling and reservation of the capacity further along the chain. As well as making this information available to components and functions within the service chain, employees themselves need to view and manipulate it. Enterprises generally do not have a joined up approach to managing this capacity as an entity, rather managing parts of it separately combining manual human resources (HR) processes with limited system support.

The concept of effectiveworkflows is deeply ingrained in virtually every industry today. As businesses become more distributed, there is a need formassively networked workflow tools which is reflected in the emergence of the Service-Oriented Architecture paradigm. This large collection of standards brings into workflow the concept of linking together disparateWeb Services to form composite applications with some integration of human processes. Most implementations of workflow tools, however, require complete adoption at multiple levels of an organisation as well as agreement in standards to enable inter-service communication in heterogeneous environments. This necessitates significant investment in software management solutions, development time and hardware requirements, all of which can lead to inflexible workflow solutions.

For decades, circuit-switched telephony has been the dominant form of telecommunications at home and in the office. More recently, services such as voice over IP, instant messaging and short message services have taken centre stage with the widespread adoption of Internet, mobile and broadband technologies. To a large extent, however, these services have evolved in isolation due to the heterogeneity of legacy networks and computing infrastructures. The industry is now embracing next-generation networks (NGNs) and service delivery platforms (SDPs) as a means to unify and integrate communications with IT applications, web services and business processes.

Customers should be at the heart of any business. In order to improve processes with customer interaction, businesses have introduced customer relationship management systems. These systems collect large volumes of data about customers which contain valuable information that can allow a business to improve its customer relationships and services. Typically, customer analytics focus on reporting what has happened. However, in order to become pro-active and truly shape the future of a business, it is important to predict what customers want and how they will react. In addition to understanding customers, it is paramount for any enterprise to understand how its business has performed at any given time in the past, now, and in the future. Business Intelligence applications available today focus very much on past performance. However, it is becoming essential that not only is the analysis of business performance done on real-time data, but also actions in response to analysis results can be performed in real time and instantaneously change business process parameters.

For IT leaders, the increasing speed of innovation supported by a strong and flexible enterprise-wide software infrastructure, as well as delivering functionally rich and technically robust services is of primary concern. Increasing responsiveness to business changes and growing requirements ultimately require flexible software systems that can embrace such changes. To realise this, business stakeholders and IT executives are focusing on enhancing their older software delivery models. The goal here is to ensure that the enterprises remain competitive and leading. Agile practices in delivery promises to fulfil such a goal. It addresses the need of building business functionality quickly in circumstances of evolving requirements.

In Chap. 4, we have discussed in detail the concepts of Forecasting and Demand Planning where the focus was primarily forecasting within the enterprise. With interdependencies of businesses it is imperative for organizations to engage in collaborative demand forecasting across their service chains. This chapter defines collaborative forecasting and highlights the challenges faced in carrying out this process across multiple organizations. It establishes the objective of such collaborative effort and details a framework which can be used by all organizations. It also briefly discusses the popular CPFR framework and its potential application in the service industry.

With the emergence of the Internet, electronic commerce (e-commerce), revenue management and especially applications that combine both are becoming increasingly an area of innovation for service industries. E-commerce has introduced efficiencies across the service chain and it has allowed improvements to take place within and across organizations. Revenue management when combined with ecommerce and done online not only improves resource management but it can be used as a strategic tool to gain competitive advantage. This chapter examines the current approaches and future trends in these very exciting and promising areas.

In the previous chapter, we examined e-commerce, its impact on service chains and the different strategies that can be adopted in online revenue management. An enabler underlying these emerging areas are several new technologies with the most fundamental one being that of electronic marketplaces. This chapter reviews the state-of-the-art of electronic marketplaces with a focus on the future e-supply chain for both products and services and emerging agentbasedmarketplaces. It also presents frameworks for new concepts such as service resource exchanges which can underpin intra-organisational and inter-organisational service chain management.Agent technologies seem to be well suited to this domain by providing a distributed environment, are network centric, semi-autonomous and collaborative and can communicate with each other to achieve better optimisation with little human intervention.

In the previous chapter, we examined the concept of resource exchanges based on intelligent agents and marketplaces. In this chapter, we are focusing on how the same distributed decision making models can be used for empowering staff. Human resources are the main resources in a service industry. Success or failure of a service operation is often determined by its personnel management policy. A successful management policy would provide job satisfaction to employees, which will lead to higher morale, productivity and service quality.

This chapter is a practical guide to help an organisation ensure that it achieves a realistic benefit from introducing new service chain management technologies into its operations. The focus is on Field Force Automation (FFA) and mobile service workers. The viewpoints expressed are based on the work and experience of Paul Cleaver who served in a number of senior management positions at BT over the last 14 years. The examples are mainly drawn from BT’s major transformation of the engineering workforce between the years 1993 to 2002 that Paul headed but also from his experience in subsequent roles including his latest highly successful endeavour in delivering ICT solutions for BT’s corporate customers.