The outcome economy is a relatively new economic and business paradigm that promotes focusing on the effects that the use of provided products and services create for customers in their markets, rather than focusing on these products or services themselves from the providers’ perspective. This paradigm has been embraced in various fields of business but has not yet been fully integrated with the concept of smart industry. To fill this gap, in this vision paper we provide a framework that does make this integration, showing the full structure of customer outcome management in smart manufacturing, from both business and digital technology perspectives. In applying this structure, a feedback loop is created that spans the markets of provider and customer and supports data-driven product evolution, manufacturing, and delivery. We propose a business reference framework that can be used as a blueprint for designing practical scenarios. We show how integrated digital support for such a scenario can be realized using a well-structured combination of technologies from the fields of the internet of things, business intelligence and federated learning, blockchain, and business process management. We illustrate all of this with a visionary case study inspired by industrial practice in the automotive domain. In doing so, we provide both an academic basis for the integration of several currently dispersed research fields that need to be integrated to further smart manufacturing towards outcome management and a practical basis for the well-structured design and implementation of customer outcome management business cases in smart manufacturing.

In the current economy, we see a shift of focus from delivering products or services to delivering value or outcomes to customers, reflected in the concept of the outcome economy. The concept has been embraced by research and practice but lacks proper operationalization to make it fit for the digital transformation of supply chains. In this paper, we translate the concept into a cybernetic model and accompanying technique and tool that can be used for outcome-based business engineering, leading to structures for Internet-of-Thingsenabled, data-driven value delivery in supply chains. Based on a design science research approach, we discuss the development of the Alpha version of this model and tool, the application in business practice, and the use of this experience to develop a Beta version. We provide a bridge from a leading contemporary business concept to structured application in practice, positioning Internet-of-Things and Business Intelligence technologies for data-driven business execution.