Revitalizing industrial manufacturing: A path to prosperity

Over the past five years, industrial manufacturing in Germany, Austria, and Switzerland has faced tough conditions with declining profits, rising costs, and slower productivity growth across sectors like automotive and machinery. Historically, innovations such as lean manufacturing and automation boosted productivity by over 30% from 1990 to 2002, with similar gains in the following decade. However, transitioning to Smart Manufacturing and Industry 4.0 has proven challenging. Companies struggle to balance investments with returns, leading to minimal productivity growth of just 5% since 2010. Advanced technologies like generative artificial intelligence may offer new opportunities for growth.

Crafting a GenAI strategy for industrial success

Reflecting on the past, various technological innovations have been tested, offering valuable insights into their potential. Now it is time to consolidate these lessons and devise a focused, top-down strategy for implementing GenAI. Like previous technological trends, GenAI faces its own set of challenges and investment barriers. Our survey identifies the following key obstacles: insufficient data and poor data quality, lack of specialized skills, and inadequate IT infrastructure. To navigate these challenges, the strategy should outline a vision for how GenAI will transform the future operating model, from incremental improvements to disruptive changes. Establishing a governance framework will help ensure compliance with regulations and ethical standards in GenAI. Additionally, creating an incubator can provide the necessary guidance and power for effective and efficient implementation of use cases. Building strong partnerships will expedite the development of essential workforce capabilities.

A strategic blueprint for GenAI success

To infuse structure and value-driven thinking into companies' GenAI implementation programs, we employ a strategic approach that unfolds in three distinct stages, fostering a comprehensive understanding of GenAI's role in business:

• Craft a top-down vision Develop a clear strategy that outlines your goals, defines your ambition level, and sets targets for both top-line and bottom-line enhancements. Engage and align with stakeholders to ensure a cohesive vision.
• Establish an AI incubator framework Determine the purpose, scope, and methodology for how the incubator will assess and select GenAI use cases. This framework should guide the launch of impactful initiatives.
• Monitor and manage implementation for optimal impact Initiate projects, regularly assess progress, discontinue underperforming initiatives, and expand successful strategies on a larger scale.

While achieving financial targets and delivering a return on investment is undoubtedly crucial, evolving, testing, and selecting GenAI use cases require a period of open-ended experimentation. Only through this exploratory phase substantial returns on investment can be realized:

• Evolution The journey begins by accelerating initial adoption, fostering innovation by reducing management constraints, and providing resources for experimentation without immediate financial targets
• Implementation Successful ideas are then organized for large-scale delivery, where prototypes are expanded, employees receive upskilling, and pilot projects are executed
• Optimization This phase ensures sustained return on investment by rigorously monitoring key performance indicators (KPIs), refining and standardizing processes, and scaling impactful use cases while eliminating underperformers.