Flexible service systems

Service science combines scientific, management, and engineering disciplines to improve the understanding of how service systems cooperate to create business value. Service systems are complex configurations of people, technologies, and resources that coexist in a common environment of service provisioning. While the general concepts of service science are understood and agreed upon, the representation of service systems using models is still in its infancy. In this chapter, we look at business processes and their role in properly representing service systems. We propose flexible process graphs, a high-level process modeling language, and extend it in order to specify service systems and their compositions within shared environments in a flexible way. The discussion in this chapter is the first step towards a formal description of service science environment, including service systems, networks, and whole ecology.

Stochastic optimization for adaptive labor staffing in service systems

Service systems are labor intensive. Further, the workload tends to vary greatly with time. Adapting the staffing levels to the workloads in such systems is nontrivial due to a large number of parameters and operational variations, but crucial for business objectives such as minimal labor inventory. One of the central challenges is to optimize the staffing while maintaining system steady-state and compliance to aggregate SLA constraints. We formulate this problem as a parametrized constrained Markov process and propose a novel stochastic optimization algorithm for solving it. Our algorithm is a multi-timescale stochastic approximation scheme that incorporates a SPSA based algorithm for ‘primal descent' and couples it with a ‘dual ascent' scheme for the Lagrange multipliers. We validate this optimization scheme on five real-life service systems and compare it with a state-of-the-art optimization tool-kit OptQuest. Being two orders of magnitude faster than OptQuest, our scheme is particularly suitable for adaptive labor staffing. Also, we observe that it guarantees convergence and finds better solutions than OptQuest in many cases.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.

Product Service Systems and supply network relationships: An exploratory case study

Purpose - In recent years there has been increasing interest in Product Service Systems (PSSs) as a business model for selling integrated product and service offerings. To date, there has been extensive research into the benefits of PSS to manufacturers and their customers, but there has been limited research into the effect of PSS on the upstream supply chain. This paper seeks to address this gap in the research. Design/methodology/approach - The research uses case-based research which is appropriate for exploratory research of this type. In-depth interviews were conducted with key personnel in a focal firm and two members of its supply chain, and the results were analysed to identify emergent themes.b Findings - The research has identified differences in supplier behaviour dependent on their role in PSS delivery and their relationship with the PSS provider. In particular, it suggests that for a successful partnership it is important to align the objectives between PSS provider and suppliers. Originality/value - This research provides a detailed investigation into a PSS supply chain and highlights the complexity of roles and relationships among the organizations within it. It will be of value to other PSS researchers and organizations transitioning to the delivery of PSS. © Emerald Group Publishing Limited.

Influencing factors of successful transitions towards product-service systems: A simulation approach

Product-Service Systems (PSS) are new business strategies moving and extending the product value towards its functional usage and related required services. From a theoretical point of view the PSS concept is known since a decade and many Authors reported reasonable possible success factors: higher profits over the entire life-cycle, diminished environmental burden, and localization of required services. Nevertheless the PSS promises remain quantitatively unproven relaying on a simple theory that involves a few constructs with some empirical grounding, but that is limited by weak conceptualization, few propositions, and/or rough underlying theoretical logic. A plausible interpretation to analyze the possible evolution of a PSS strategy could be considering it as a new business proposition competing on a traditional Product-Oriented (PO) market, assumed at its own equilibrium state at a given time. The analysis of the dynamics associated to a possible transition from a traditional PO to a PSS strategy allows investigating the main parameters and variables influencing an eventual successful adoption. This research is worthwhile because organizations undergoing fundamental PSS strategy are concerned about change and inertia key processes which, despite equilibrium theory and because of negative feedback loops, could undermine, economically, the return of their PSS proposition. In this paper Authors propose a qualitative System Dynamics (SD) approach by considering the PSS as a perturbation of an existing PO market featured by a set of known parameters. The proposed model incorporates several PSS factors able to influence the success of a PSS proposition under a set of given and justified assumptions, attempting to place this business strategy in a dynamic framework.

A framework for designing product service systems

In this competitive globalizing scenario, manufacturers are adopting a strategy of bundling products and services into an integrated solution to create sustainable competitive advantage. Servitizing manufacturers are increasingly transforming their processes and practices to build product-service systems (PSS). During this transformation they require substantial support to face stringent challenges. Research in the PSS domain is heading towards the development of a design theory and methodology that facilitates the systematic creation of viable PSS conceptual designs. In this paper, various proposed design methods are reviewed and research gaps are summarized. Primarily, it has been observed that the importance of the capabilities of the stakeholders involved in designing PSS has not been noted in the proposed methods. Regarding this capability view point, a framework for designing PSS has been proposed. This framework highlights the important features required in designing PSS such as co-creation, responsibilities and competences. Every step in the framework has been explained with a case study involving laser systems used for manufacturing cutting operation.

A life cycle model for product-service systems design

Western manufacturing companies are developing innovative ways of delivering value that competes with the low cost paradigm. One such strategy is to deliver not only products, but systems that are closely aligned with the customer value proposition. These systems are comprised of integrated products and services, and are referred to as Product-Service Systems (PSS). A key challenge in PSS is supporting the design activity. In one sense, PSS design is a further extension of concurrent engineering that requires front-end input from the additional downstream sources of product service and maintenance. However, simply developing products and service packages is not sufficient: the new design challenge is the integrated system. This paper describes the development of a PSS data structure that can support this integrated design activity. The data structure is implemented in a knowledge base using the Protégé knowledge base editor.