BASTIAN DIETZ

In the digital age, technology is a key enabler of business model innovation. Organizations stuck in legacy models risk disruption from agile competitors leveraging AI, IoT, and cloud platforms to create new value. True innovation requires a bold mindset, willing to experiment and reimagine how products and services are delivered. It also demands strategic investments in emerging technologies aligned with customer needs. Business leaders must foster cross-functional collaboration and embrace iterative development cycles to rapidly test and refine new ideas. Leveraging technology not only enhances existing models but opens doors to entirely new markets and revenue streams.

The following, practical framework for business model innovation (BMI) is tailored to mid-sized companies, leveraging technology and adaptable to evolving markets:

1. Assess Current Business Model and Market Context
   Start by mapping the existing business model using tools like the Business Model Canvas to capture key components—value proposition, customer segments, channels, revenue streams, resources, and partnerships. Analyze internal capabilities and external market trends, including emerging technologies impacting production, supply chain, and customer needs.
2. Identify Innovation Opportunities
   Engage cross-functional teams to explore pain points, unmet customer needs, and technological possibilities (e.g., IoT for smart manufacturing, AI for quality control). Use data analytics and customer feedback to pinpoint areas where digitization or automation can create new value or efficiencies.
3. Ideation and Concept Development
   Generate multiple innovative business model concepts by combining new technologies with customer insights. Consider alternative revenue models such as subscription, pay-per-use, or servitization (selling outcomes rather than products). Prioritize ideas with strategic fit, feasibility, and market potential.
4. Prototype and Validate
   Build MVPs (minimum viable products) or pilot projects employing digital tools like CAD/PLM systems or production simulations. Test with select customers or markets to gather feedback on viability, user experience, and operational impact. Use agile iterations to refine concepts based on real-world learnings.
5. Develop Implementation Roadmap
   Define a clear roadmap outlining required technology investments (e.g., ERP upgrades, cloud platforms), organizational change, process redesign, and skill development. Incorporate change management plans addressing cultural shifts and employee enablement to support innovation adoption.
6. Scale and Integrate
   Roll out the validated business model at scale, integrating new technologies with existing production and IT systems. Establish performance metrics focused on innovation outcomes such as reduced time-to-market, improved quality, or new revenue streams. Continuously monitor and adapt based on market feedback and technological advancements.
7. Create a Culture of Continuous Innovation
   Embed processes and incentives to encourage ongoing experimentation and learning. Leverage platforms for collaboration and idea management to surface emerging opportunities and respond rapidly to disruptions.

This framework balances strategic foresight with practical execution, emphasizing technology as an enabler, rigorous validation, and organizational readiness. It is customizable for mid-sized production firms aiming to transform legacy operations and sustainably compete in a digital-first economy.

But what technology or IT platforms would a company use to support such an endeavour?

I would propose these three IT platforms, because they stand out as the best candidates to support various phases of a BMI project:

1. Siemens Opcenter (formerly CAMSTAR and Preactor)
   Siemens Opcenter is a manufacturing execution system (MES) platform that integrates production planning, quality management, and real-time monitoring. It supports digitization and automation, enabling process optimization and rapid prototyping integral to innovation. Its scalability and integration with ERP, PLM, and IoT systems make it ideal for mid-sized manufacturers transforming operations and embedding smart manufacturing technologies.
2. Microsoft Power Platform (Power BI, Power Apps, Power Automate)
   The Microsoft Power Platform offers no-code/low-code tools for rapid application development, workflow automation, and advanced analytics. This platform empowers cross-functional teams to prototype digital solutions quickly, automate business processes, and leverage data-driven insights to validate and refine innovative business models. Seamless integration with Microsoft 365 and Azure ensures extensibility and enterprise-grade security.
3. PTC Windchill and ThingWorx
   PTC Windchill provides robust Product Lifecycle Management (PLM) capabilities essential for managing complex product data, engineering changes, and compliance throughout innovation cycles. ThingWorx complements this by delivering industrial IoT solutions that monitor assets, collect production data, and enable predictive maintenance. Together, they form a powerful ecosystem for mid-sized producers aiming to combine digital twin concepts with data-driven decision-making in business model innovation.

These platforms cover the critical dimensions—from production process digitization and product data management to business process automation and analytics—needed to execute an adaptable, technology-driven business model innovation successfully. The choice depends on existing IT landscapes and strategic priorities, but integrating these solutions offers a holistic digital foundation.