The smart and resilient transformation of manufacturing firms has flourished in the last decade. This paper investigates the smart and resilient transformation of manufacturing firms with the application of digital services. It uses a Serbian data set of 136 manufacturing firms from the Digital Servitization Survey from 2022 coordinated by IFIP WG5.7. The authors applied a different method approach through social network analysis, correlation analysis, and interviews with representatives from the manufacturing firms. The main results show that manufacturing firms that apply an adequate combination of services and digital technologies have the highest impact on the network of manufacturing firms. Moreover, the results show that applying digital technologies, such as additive manufacturing/3D printing, big data analytics, and digital twin, increases the gross annual turnover of manufacturing firms in the COVID-19 era. Finally, the results show that for a successful smart and resilient transformation, manufacturing firms need to develop a strategy and motivation oriented to profit to be resilient enough to withstand market change.

The combination of servitization and digitalization is increasingly changing the economy and society at the global level towards sustainability goals. Companies are shifting their business models, typically oriented to selling products, towards providing bundles of products and services and integrating them with technologies enabling data collection and analysis, resulting in the so-called smart Product Service Systems (PSS). Different approaches and techniques have been put forth to design PSS and, more recently, smart PSS, but they continue to primarily concentrate on establishing value propositions and ignore the question of what sort of operational data can be gathered and used to deliver the PSS solution. Therefore, manufacturing companies willing to expand their portfolio with new advanced services nowadays still face multiple challenges. To address this gap, this study proposes the Service Engineering Methodology for the engineering of smart PSS (SEEM-Smart), which takes into account the trade-off between customer satisfaction and internal efficiency with a focus on data gathering and information flow. The methodology is then applied in a real-world setting. The case study shows the application of the SEEM-Smart for engineering a new data-driven service offering enabled by a cloud-based platform supporting the service provision.