OPERATIONS
AI-driven improvements help surface the next constraint to address, turning a local productivity gain into a continuous, end-to-end optimisation journey.
Q. CAN YOU SHARE AN EXAMPLE OF WHERE AI HAS HELPED TO AVOID A SUPPLY CHAIN DISRUPTION?
» A recent example is the ongoing Middle East crisis. Through our Logistics Control Tower, we were able to react very quickly when port closures were announced.
Within a short time, we had full visibility of how many shipments and containers were affected, where they were and which routes were still available for shipping. This allowed us to proactively redirect shipments to accessible ports and adjust transport plans early on.
“ SUCCESS IN AI COMES FROM AN ORGANISATION’ S ABILITY TO DEPLOY, NOT RUNNING ISOLATED PILOTS”
Jim Tobojka Senior Vice President of Global Operations TE Connectivity
Instead of reacting once delays had already occurred, the insights helped us stay ahead of the situation and significantly reduce the risk of disruption.
Q. WHAT IS THE BIGGEST CHALLENGE IN SCALING THESE TECHNOLOGIES?
» Scaling strategically remains the most difficult challenge, especially in large, decentralised companies. It’ s extremely complex to deploy new solutions consistently across a global manufacturing footprint.
This requires:
• Standardising solutions for common problems
• Avoiding duplication of effort across plants
• Building governance frameworks and IT integration
• Enabling reuse rather than reinvention.
Closing that gap between pilot and enterprise-wide deployment is where most companies struggle.
Q. HOW DO THESE TRANSFORMATIONS CHANGE THINGS FOR WORKERS?
» The initial reaction to AI tools can include some hesitation or distrust, which is a natural response to change that I’ m sure a lot of companies are managing.