Industry 4.0 provides new paradigms for the industrial management of SMEs. Supported by a growing number of new technologies, this concept appears more flexible and less expensive than traditional enterprise information systems such as ERP and MES. However, SMEs find themselves ill-equipped to face these new possibilities regarding their production planning and control functions. This paper presents a literature review of existing applied research covering different Industry 4.0 issues with regard to SMEs. Papers are classified according to a new framework which allows identification of the targeted performance objectives, the required managerial capacities and the selected group of technologies for each selected case. Our results show that SMEs do not exploit all the resources for implementing Industry 4.0 and often limit themselves to the adoption of Cloud Computing and the Internet of Things. Likewise, SMEs seem to have adopted Industry 4.0 concepts only for monitoring industrial processes and there is still absence of real applications in the field of production planning. Finally, our literature review shows that reported Industry 4.0 projects in SMEs remained cost-driven initiatives and there in still no evidence of real business model transformation at this time.

SMEs, as prominent actors in industry, must meet more and more complex customer expectations. Recently, the concept of Industry 4.0 has emerged. This new approach enables the control of production processes by providing real-time synchronisation of flows and by enabling the production of unitary and customised products. Our research goal is to identify Industry 4.0 risks, opportunities and critical success factors with regards to the industrial performance of SMEs. The recent emergence of Industry 4.0 and the inherent difficulty of identifying detailed examples has not yet enabled a satisfactory statistical study to be conducted on Industry 4.0 cases in SMEs. To reach our research goal, we selected 12 experts to conduct a Delphi study supplemented by Régnier’s abacuses. Our study demonstrates that the major risks facing the adoption of Industry 4.0 in SMEs include a lack of expertise and a short-term strategy mindset. Our research also indicates that training is the most important factor for success, that managers have a prominent role in the success and/or failure of an Industry 4.0 project, and that SMEs should be supported by external experts. Lastly, Industry 4.0 offers a unique opportunity to redesign SME production processes and to adopt new business models.

Industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies. On the other hand, many companies have already partially or fully implemented principles and tools from the Lean management approach, which is also aimed at improving productivity. While the two approaches use very different strategies, they share some common principles. The objective of this article is to highlight the links between the principles and tools proposed by Industry 4.0 and those proposed by the Lean management approach, with a particular focus on how some of Industry 4.0's technologies are improving the implementation of Lean principles, depending on the technologies’ capability levels. As such, this study aims to provide a characterisation of the impacts of Industry 4.0 technologies on Lean principles according to targeted capability levels. The results obtained show strong support for Industry 4.0 technologies for Just-in-time and Jidoka, but little or no support for waste reduction and People and Team work. There is, therefore, a clear need to pursue the deployment of Lean management while improving certain Lean principles using Industry 4.0 technologies.

In recent years, data analytics in pharmaceutical supply chains has aroused much interest as it has the potential of enabling better supply and management of healthcare products by leveraging data generated by modern systems. This article presents the current state, opportunities, and challenges of data analytics in pharmaceutical supply chains through a systematic literature review surveying the Scopus, ScienceDirect, and Springerlink databases. 85 publications from 2012 to 2021 were reviewed and classified based on the research approach, objective addressed, and data used. The contributions of this paper are threefold: (i) it proposes a framework focused on challenges and data resources to assess the current state of data analytics in pharmaceutical supply chains; (ii) it provides examples of techniques exemplified that will serve as inspiring references; and (iii) it gathers and maps existing literature to identify gaps and research perspectives. Findings outlined that despite promising results from machine learning algorithms to address drug shortages and inventories optimisation, the various data resources have not yet been fully harnessed. Unstructured data have barely been used and combined with other types of information. New challenges related to green practices adoption and medicines supply during crises call for further applications of advanced analytics techniques.