Method to Identify Data Related Characteristics for Detailing a Capability Maturity Model for the Smartification of Products
Abstract
Digital transformation has many facets, one of them being the process of smartifying a traditional, non-smart product into a smart product as well as developing smart services. Smart products collect data via sensors, store, process and communicate data via a network, and react to data via actuators. As an added value, a company uses the processed data to offer smart services. The decisions a SME’s CEO needs to make when visioning to smartify or improve the smartification of own products also depend on the knowledge which capabilities need to be build up. Capability and maturity model (CMM) based approaches are common methods to identify the gap between the current situation and the target situation a SME needs to achieve in order to fulfill the business goals which have been set up. We research a methodological and tool-based approach to identify the maturity of SMEs on their way to smartify their products, which is made up of a three-dimensional CMM to determine the maturity levels regarding eleven areas of action as well as their cross-sectoral base capabilities, and a process model to apply the CMM. In this paper we describe a method to detail the subareas of action for each capability/maturity level within the CMM. We define the method requirements to be able to identify and integrate relevant characteristics in our CMM following the sole purpose of smartification but also looking into related subjects like digital transformation as well as retrofitting for Industry 4.0.
Keywords: Smartification, Capability and maturity model based approaches, Data related characteristics, Decision, making
DOI: 10.54941/ahfe1003101
Cite this paper
More from this volume
- The role of Data and AI during development of Smart Services
- COOPE – a framework for managing coopetition in the platform economy
- Preparing Data Science Projects – Between Economic Aspects and Requirements Analysis
- Bringing Data Science to Practice: From Protype to Utilisation
- Towards A Reference Process for Developing Cognitive Service Systems
- AI-based Services - Design Principles to Meet the Requirements of a Trustworthy AI
- New human engagement-first governance approach in craft startups
- Roadmap to Close the Gap Between Undergraduate Education and STEM Employment Across Industry Sectors, Further Studied
- T-Shaped Professional (T-SP) Model to support Human-Machine Interaction
- Digital Transformation, Servitization and Governmentality
- Ethical AI for a Better Society: The Challenging Task of Driving the Digital and Ecological Transformation in Italy
- The process of generating rhetoric to encourage participation in Delayed Benefit Services: A case study of electronic community currency in Japan


AHFE Open Access