Data Determines Adaptive Manufacturing Destiny

Last week’s announcement by automotive parts supplier Schaeffler of plans to cut 4,700 European manufacturing jobs was just the latest in a string of similar news pointing to a growing crisis within the European manufacturing sector. Rising costs, falling sales, and increasing global competition mean that Europe’s manufacturers must adapt to technology budgets that are, in real terms, hardly growing. My colleagues Bernhard Schaffrik, Paul Miller, and I have been wondering: Where are the opportunities to put limited funds to best use?

Forrester’s automation predictions for 2025 discuss how citizen developers capitalizing on domain expertise will deliver 30% of generative AI-infused automation apps and a major pivot to governance of data and AI together. Forrester readers are curious about the implications for their traditional enterprise applications like CRM (customer relationship management), ERP (enterprise resource planning), or PLM (product lifecycle management).

To be sure, enterprise software vendors now recognize the immense value of their data assets, but manufacturers are anxious that a volatile outlook threatens their ambitions to reclaim data value using the right mix of enterprise proprietary and pooled partnership language models. But they can still boost their adaptive posture even with limited budgets if they wrap their applications in an “adaptivity” layer and if they pursue new routes to innovation.

Cocoon your applications in a data “adaptivity” framework.

Now is not the time to rip out core enterprise systems that are still (mostly) fit for purpose. But focused investment around the periphery will deliver disproportionate adaptive benefit. You cannot make your ERP or PLM systems more adaptive while they run in production. But you can become more adaptive if you:

  • Encapsulate your legacy apps. In earlier research, we described how technology architecture and delivery leaders can leverage enterprise application governance to improve their agility. But you can also make application sources, sinks, and surroundings more adaptive — for example, by adopting open API architectures and by preparing your autonomous enterprise roadmap.
  • Wrap legacy in automation fabric. You can start by working out how to provide to developers, process admins, and managers access to the full process orchestration lifecycle to use, monitor, and improve it.
  • Accommodate real-time operational process insights. The beauty of real-time process intelligence is that it enables root-cause detection and “decisioning” while processes run so you can act much more quickly than with classic process intelligence.

Pursue new routes to innovation by leveraging partners.

Tech organizations can become more adaptive by selecting a suitable pace for technology renovation and by focusing on new skills and data management. But you can’t do this alone. You will need a co-innovation partner.

Start by complementing familiar cost-cutting exercises with a program of rapid collaborative co-innovation with your own suppliers. A co-innovation partner brings assets, alliances, and solutions and can help you transform by orchestrating the value of your internal and external ecosystems.

We will work on these topics further but would also love to hear your thoughts on how best to invest limited funds to adapt to new challenges. If you are a Forrester client, feel free to schedule a guidance session through inquiry@forrester.com.