Abstract
The Product Service Systems (PSS) paradigm has been launched in the 1990s, subsequently playing a great impact on industry and academia. The main drivers for its diffusion have been identified in the need for modernizing business models, carrying out internal companies’ reconfiguration, enhancing environmental sustainability by shifting the focus from manufactured physical goods to services. According to prioritized objectives and the kind of business, three main models of PSS implementation are known, namely product-oriented, use-oriented, and result-oriented.
However, despite the large number of contributions and the enthusiasm featuring PSS field, sparks of criticism have recently emerged, as well as the authors have identified lacks in the analysis of PSS-based experiences. The results ensuing from PSS adoption have not been rigorously assessed, especially in terms of economic return and contribution to environmental friendliness. Conversely, a great amount of literature is still concerned with the narrative of PSS experiences, while it fails to provide insights, recommendations about design and managerial issues, contributions to theory. A possible cause of poor quantitative analysis regards the service aspects of PSS, especially hurdles in service modeling and evaluation. The interest on service modeling has emerged just recently and a standard framework has been not agreed up to present. The literature highlights that obstacles to modeling ensue from the intangible and hardly quantifiable aspects concerning services, recipients and several lifecycle issues. These immaterial, not-deterministic and hardly quantifiable aspects complicate the matters from the viewpoint of selecting and optimizing appropriate technical solutions to the design of the PSS.
The objective of the present paper is to overcome these limitations. A tool has been developed to assess and forecast the added value of services related to the introduction of PSS. This tool, named Service Added Value Estimate (SAVE), aims at providing a single reference value that supports decision-making processes connected to PSS development and design. The fundamental parameters that have been introduced in the quantitative estimation of SAVE are the service fees charged on customers and the provider’s cost. A specific analysis model (mixing qualitative and quantitative measures) has been employed for the estimation of the latter.
This tool, and its contribution in PSS design and implementation, was tested in cooperation with a B2B SME designing and manufacturing customized high-end white goods, which are purchased by dealers operating mostly in the European market. The firm has up to now no experience in providing services to dealers or end customers. The experiment demonstrates the applicability of the SAVE formula. Besides, its use for different typologies of product-service integration has given rise to reasonable outcomes, according to the feedback of firm’s leaders.