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Reference context for Factory-X, data ecosystems, ecosystem roles, and the House Building Logic metaphor. This skill is not user-invocable - it is consumed by other skills for domain context and terminology.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Assigns all measures from the Action Plan to 30/60/90-day phases, maps dependencies, defines outcome-based KPIs, identifies resource and decision needs, and establishes tracking governance.
Translates risk heatmap findings into SMART measures organized by workstream with full RACI accountability assignments.
Maps the complete cost structure across value creation steps including fixed/variable, one-time/recurring, partner costs, scalability analysis, and controllability measures.
Synthesizes and evaluates the entire value creation design - monetizable contributions, costs, governance maturity, risks, and Go/Review/Stop recommendation. Use for ecosystem feasibility assessment or when completing value creation analysis.
Consolidates all prior analysis results into a decision-ready one-pager for gate reviews and pitches, with full traceability from business idea through risks to next steps.
Orchestrates the complete House Building Logic process for developing data-driven business models. Navigates between rooms (Entrance -> Blue -> Red -> Green -> Yellow -> Exit), manages transitions, performs consistency checks, and provides Factory-X/data ecosystem context. Use this skill for any request about business models, business model canvas, value propositions, data ecosystems, Factory-X, or when a user wants a structured business model development process.
| name | context-factory-x-data-ecosystems |
| description | Reference context for Factory-X, data ecosystems, ecosystem roles, and the House Building Logic metaphor. This skill is not user-invocable - it is consumed by other skills for domain context and terminology. |
| user-invocable | false |
| metadata | {"internal":true} |
This document provides the industry context and methodological foundations for business model development in data ecosystems.
The factory equipment industry - also known as factory outfitters - comprises companies that equip industrial production facilities with machines, systems, automation technology, software solutions, and complementary services. It forms a central pillar of industrial value creation, particularly in Germany, and is characterized by high engineering competence, innovative strength, and export orientation.
Traditionally, the focus of this industry was on delivering highly productive and reliable machines and components. However, this product-centric approach is no longer sufficient. The industry is undergoing a profound transformation driven by digitalization, data-driven business models, and new customer requirements. A paradigm shift toward benefit-based added value is essential to differentiate from the competition and remain successful in the long term.
Factory equipment manufacturers must increasingly view their products in the context of their application and offer comprehensive solutions. Product-service systems combine physical products with digital and organizational services. Such systems enable new value creation models and strengthen customer loyalty. They also open up perspectives for data-based business models in the "Everything-as-a-Service" economy (XaaS), where machine functions, maintenance, or analysis are offered as a service.
Data ecosystems (often called "data spaces") are technical-organizational frameworks for sovereign, secure, and rule-based data exchange, enabling the exchange and shared use of data across company, industry, and national borders. The central idea is that data does not remain isolated in silos but can be shared and combined in a trustworthy environment at scale.
Factory-X is a lighthouse project initiated by the German Federal Ministry for Economic Affairs and Climate Action (BMWK) to create an open and collaborative data ecosystem for factory equipment manufacturers and operators. The goal is to improve industrial processes along horizontal and vertical supply chains through accelerated digitalization and cross-manufacturer data consistency.
The project is part of the overarching Manufacturing-X initiative and is supported by over 40 companies. It addresses topics such as:
Digital business models in Industry 4.0 focus on connecting machines, products, and people. Data forms the foundation for creating new business models and leads to approaches such as:
A business model defines how a company creates and delivers value for customers and how it converts payments into profits. At the core is the Value Proposition, complemented by the dimensions:
The "House Building Logic" is a metaphor to illustrate the process of business model development:
| Metaphor | Meaning |
|---|---|
| Builder | A company (e.g., machine manufacturer) |
| Building a house | Building a successful service offering and business model |
| Settlement X | Factory-X ecosystem |
| Building regulations | Prerequisites and rules in Factory-X |
| DIY house | Self-designed service offering and business model |
| Model house | Pre-fabricated Factory-X-compatible business model patterns |
| Roof | Core business model idea with value proposition and customer benefit |
| Rooms | The 4 business model dimensions |
| Foundation | Rules, laws, data exchange principles |
| Room | Color | Dimension |
|---|---|---|
| Blue Room | Blue | Customer & Need = Customer View |
| Red Room | Red | Value Promise = Value Proposition |
| Green Room | Green | Value Creation = Value Creation |
| Yellow Room | Yellow | Monetization = Viability |
Entrance Area -> Blue -> Red -> Green -> Yellow -> Exit Area
After the initial pass, rooms can be revisited iteratively for optimization.
| Role | Description |
|---|---|
| Data Provider | Supplies data |
| Data Consumer | Uses provided data |
| Service Provider | Offers data-based services |
| Infrastructure Provider | Provides technical infrastructure |
| Orchestrator | Coordinates the ecosystem |
| Data Broker | Mediates between data providers and consumers |
| Technical Enabler | Enables technical integration |