The success of generative Artificial Intelligence (AI), such as ChatGPT, has brought data into the spotlight. Without training data, there would be no ChatGPT. As many of us have experienced hallucinations with ChatGPT, we understand that the quality of ChatGPT results is not solely determined by the quantity of data. Instead, it relies on the training data having the appropriate information content and quality.
Digital twin as data product
Just as ChatGPT relies on the right data, your business applications also require the appropriate data or data product. This entails refining raw data to ensure relevant information content, quality, and formatting (Schlueter Langdon & Sikora 2020, Crosby & Schlueter Langdon 2019). Enter digital twins: these are data products that depict a digital model of an intended or existing real-world physical object, system, process, or person. Digital twins serve as effectively indistinguishable digital counterparts, and therefore, inherently require the right information content and quality.
Figure 1: Use case monetization short-cut with digital twins as refined data products
Short-cut to automation success: Digital twins
Any IT investment necessitates a clear use case to ensure a positive Return on Investment (RoI). As outlined by McKinsey and illustrated in Figure 1, the standard monetization process begins with raw data, followed by its refinement into a tailored data product that aligns with the requirements of a software application designed to automate a specific use case (McKinsey’s Desai et al. 2022a, 2022b). The greater the distance in this journey, the more time it takes to achieve break-even. A shortcut to quicker RoI involves commencing with data products, such as digital twins.
Catena-X data ecosystem advantage: Super-apps with digital twins
Dataspace technology has emerged to make more and better raw data available as it enables data sharing with data sovereignty protection (see “Dataspaces 101”). This capability has been successfully demonstrated in a pioneering pilot of RealLab Hamburg. Lately, first data ecosystems, like Catena-X, have emerged that go beyond merely providing a dataspace network for data exchange. These ecosystems offer readily usable building blocks, including super-apps designed for specific use cases, accompanied by corresponding data products or digital twin template go beyond providing a dataspace network for data exchange to add readily usable building blocks on top of it, such as super-apps for use cases together with corresponding data products or digital twin templates. In contrast to building McKinsey's data monetization chain from the ground up, Catena-X presents a modular, Lego-style approach to use case automation: Chose the Catena-X (C-X) ecosystem, then pick a certified C-X carrier or operating company like Cofinity-X, and finally, within the Operating Company's app store, one can choose a C-X certified application. These certified applications come equipped with digital twin templates, establishing a standardized framework across all tiers of your supply chain. This innovative approach was showcased in a live data chain at CES 2024, demonstrating the sharing of CO2 or product carbon footprint (PCF) tracking data.
Our case studies: CO2-Pilot@CES and RealLabHH@ITS
How to obtain CO2 values from the suppliers of the parts used in your product? This has been successfully demonstrated at CES 2024 in Las Vegas. Flex and Ford have partnered with T-Systems International (TSI) and IBM to launch the automotive industry's first product carbon footprint (PCF) tracking pilot with a live data chain across multiple supply chain tiers. The pilot demonstrates the readiness of commercial solutions based on Catena-X standards with trusted identities provided by our partner Cofinity-X and open-source technology. Participants in the pilot can:
- Execute data exchange across participants in a sandbox environment provided by TSI based on open-source Catena-X technology from Eclipse Tractus-X for free.
- Get connected into an OEM-Tier1-Tier2+ data chain in this sandbox using a fully Catena-X certified TSI connectivity product for free.
- The IBM Supply Chain Intelligence Suite (SCIS) will be used to trace and analyze exchanged PCF values along the supply chain using an intuitive graphical user interface.
Figure 1 illustrates how Catena-X provides a RoI short cut as it provides digital twins as refined data products. This contrasts with an earlier case study, a first dataspace pilot based on gen 1 technology from International Data Spaces Association (IDSA). This pilot demonstrated how dataspace technology can provide the date required to orchestrate and offer the citizens of the city of Hamburg a novel seamless intermodal travel solution across multiple modes of travel, such as micro-mobility integrated with public transport. This solution was launched for use by visitors of the 2021 ITS World Congress in Hamburg, and delivered faster A-to-B travel speeds of up to 30%. Back then, all components from raw data to refined data to super-app had to be created from scratch.
Please check out our products: link
For additional insights from our projects:
- CO2/ PCF-Pilot@CES Las Vegas case study: link
- RealLabHH@ITS case study: Data Move People and RealLab at ITS
- R&D on “Data products: Digital twins”: Link
References
Crosby, L., and C. Schlueter Langdon. 2019. Data as a Product to be Managed. Marketing News, American Marketing Association (October 10th), link
Desai, V., T. Fountaine, and K. Rowshankish. 2022a. How to unlock the full value of data? Manage it like a product. McKinsey Article (2022-06-14), McKinsey & Company, link
Desai, V., T. Fountaine, and K. Rowshankish. 2022b. A Better Way to Put Your Data to Work - Package it the way you would a product. Harvard Business Review (July–August 2022), link
Schlueter Langdon, C., and R. Sikora. 2020. Creating a Data Factory for Data Products. In: Lang, K. R., J. J. Xu et al. (eds). Smart Business: Technology and Data Enabled Innovative Business Models and Practices. Springer Nature, Switzerland: 43-55, link
