Disclaimer
This scenario breakdown is a fictionalized, illustrative case study created for educational and strategic thinking purposes. While inspired by real-world patterns and organizational challenges, all details—company context, team structure, and suggested approaches—are generalized and do not represent any specific employer, client, or confidential situation.
The content is designed to demonstrate strategic problem-solving, not to prescribe one-size-fits-all solutions. Readers are encouraged to adapt ideas and frameworks to suit their unique organizational needs, capabilities, and compliance contexts.
A 40-year-old manufacturing firm with global operations wants to modernize its R&D and operations through AI and digital transformation. The firm is still heavily on-prem, cloud adoption is minimal, and there's low awareness of modern tooling. Teams are siloed — IT, product, and operations don’t collaborate frequently. Leadership is sceptical about AI and prefers small pilot wins before committing larger budgets. The company is under pressure from competitors who have already deployed predictive maintenance, intelligent supply chains, and data-driven quality control. However, internally, most initiatives either stall or never pass the proof-of-concept stage.
Root Problems
- Cultural Inertia: Fear of change, risk-aversion, and a top-down mindset blocks innovation.
- Legacy Infra: On-prem systems, data stored in silos, lack of APIs for integration.
- Lack of Enablement: Teams lack exposure to AI tools, use cases, and have limited upskilling opportunities.
- Pilot Purgatory: Projects get stuck in prototype phase with no follow-through.
- Disconnected Leadership: Execs want results but don’t invest in structure or cross-functional ownership.
Apply the Modernization Flywheel: Enable ➝ Demonstrate ➝ Institutionalize