Ahead of the Curve:
2025 Innovation Priorities for Manufacturing

For manufacturers, technology-driven innovation is no longer limited to operational KPIs like throughput, quality, or equipment uptime. It’s also about pursuing evolved business models and more sophisticated approaches to client-centricity. The innovation priorities in manufacturing are aligned to three different factors: first, optimization of COGS through yield, throughput, quality, efficiency, etc.; second, effective selling and delivery through better customer and supply chain experience; and finally, expansion of the revenue potential through the creation of new revenue streams using As-a-Service or Servitized business models.

The pursuit of excellence through those factors is leading to three primary shifts that are not just changes but transformative forces that are reshaping the manufacturing industry:

• From Products to Services: Manufacturers are at the forefront of this shift. One in three seeks to deploy product-as-a-service models in discrete manufacturing, process manufacturing, and chemical value streams. While servitization isn’t new—pioneers like Xerox, GE Aerospace, and Philips have long relied on the revenue from service-based business models—it’s on a path to becoming more common and taking on new forms. Several models of Servitized offerings are evolving in industries such as commercial elevators and heavy industrial equipment.
• From Transactions to Experiences: Due to servitization, point interactions become end-to-end experiences. Manufacturers must focus on delivering lifetime value rather than selling and shipping units. Digital services can bridge the gap between equipment life (sometimes 30+ years) and component life (typically less than 5 years), providing durable customer support while creating more post-sales touchpoints.
• From Value Streams to Ecosystems: As manufacturers expand their service bundles beyond physical products, they increasingly rely on a complex partner ecosystem. Forward-thinking manufacturers like Tesla do more than manufacture batteries and automobile hardware: They architect partnerships (think of Tesla’s close collaboration with NVIDIA on advanced GPUs) that add value. In Tesla’s case, the ecosystem partnerships (not core manufacturing capabilities) are the engine behind rich media experiences, advanced driver assistance, and new energy storage and generation opportunities.

Manufacturers actively implement digital interventions, such as IoT devices for real-time monitoring or AI for predictive maintenance, to facilitate these transformative shifts in their business operations.

1. Data Monetization: Digital and data-driven enterprises are driven by approaches that lead to (direct or indirect) data monetization. This creates a set of digital services that are either consumed by customers at a price or ecosystem stakeholders, leading to significant efficiency or effectiveness gains. Data-driven approaches can lead to more than 25% productivity and efficiency improvement.
2. Efficiency and resiliency focus build inherent resiliency in operations while focusing on efficiency across operations comprising product design, manufacturing, supply chain, and logistics. Building an ability to mitigate supply chain and manufacturing capacity disruptions is the utmost priority for most industrial manufacturing organizations going forward.
3. Autonomous operations are characterized by an ability to go beyond automation of all types, leading to an ability to (eventually) learn new tasks. This class of technologies encompasses everything from soft and hard robotic automation to autonomy. These are essential given that over a fourth of the US and European workforce is older than 55.
4. Sustainable operations continuously focus on energy consumption, waste elimination, circularity, and transparency, and they focus on the three scopes of organizations and ecosystems: (1) Direct operations, (2) Supply chain operations, and (3) Product use and end-of-life.
5. Immersive commerce and services are interactive and engaging technologies that enrich industrial ecosystem stakeholders' experiences. This aligns with the industrial shift from “interactions to experiences.”
6. Finally, AI/Generative AI rapidly evolves into an omnipresent technology across all the other trends and many applications in industrial manufacturing ecosystems. AI is playing across three significant possibilities: (i) Create (generation of alternatives and options), (ii) Reason (diagnose or predict), and (iii) Interact (communicate or converse).

Gautam Sardar, PhD
Consulting Practice Head – Automotive and Manufacturing