From Uncertainty to Value: The Scoreboard and Feasibility Gate for Early-Stage Financial Planning in Industrial Data Ecosystems

Manufacturing is shifting from products to service-led offerings. Extending this trajectory, firms create value across organizational boundaries via industrial data ecosystems (e.g. Factory-X). These ecosystems promise efficiency, revenue, and sustainability, yet managers lack firm-level guidance on the economic feasibility of participation under federated collaboration. Due to the lack of decision-support artefacts for assessing a company’s financial benefit from participating in industrial data ecosystems, this paper develops an early-stage financial planning artefact. It reuses business-model decomposition from prior evaluation approaches but extends it with multi-role scoring and TCE-based feasibility reasoning for federated industrial data ecosystems. Following a Design Science Research approach, including expert input, the artefact consists of a qualitative Scoreboard and a TCE-based Feasibility Gate, complemented by a prototype semi-quantitative bridge. The Scoreboard captures role-agnostic drivers across value proposition, value creation, value capture, ecosystem network, and governance, including collaboration frictions and transaction-cost factors. A prototype semi-quantitative bridge maps weighted driver scores to scenario parameters and cash-flow templates, yielding indicative metrics such as ROI, NPV, and payback. The artifact is demonstrated in the Factory-X context, where one use case and expert workshops provide evidence of usability and decision relevance. The model supports go/no-go and prioritization decisions and clarifies added value and data-sharing requirements. Within the broader TriProGenix research framework aimed at enabling service-oriented and data-driven business models in mechanical and plant engineering, the proposed model is positioned at the ecosystem layer and complements established approaches for business model innovation at the product and service levels. For research, the work shows how qualitative business-model drivers can be structured as early-stage feasibility signals for subsequent financial planning in federated ecosystems, while respecting transaction costs (TC). For practice, it offers a tool that helps companies assess ecosystem feasibility, weigh role-specific trade-offs, and attribute added value to ecosystem participation.