Solving Mission Impossible: Using AI and IoT to Improve On-Time Delivery
Michael George Jr., co-author of Lean Six Sigma in the Age of Artificial Intelligence, will share how Artificial Intelligence (AI) and the Internet of Things (IoT) were combined with other improvement strategies to address a challenge and improve performance impossible to solve through traditional means and technologies. Specifically, this session will focus on the “mission impossible” challenges that need to be overcome to improve On-Time Delivery and OTIF (on-time in-full). Even with all the advances in ERP and other systems, companies (manufacturers, ecommerce, servicers and others) still struggle to achieve OTIF at levels much better than 50-60%.
Why is it so hard to be on-time consistently? What are the challenges with traditional methods? Current scheduling systems are “fire and forget.” Work, jobs or orders are launched into a system, and it is assumed based on standards, jobs will exit at such and such time.
Unfortunately, when variation and other unexpected issues occur, current scheduling, ERP and other systems can’t accurately predict delivery dates and are late recognizing when jobs will be delayed. System limitations, inability to account for unplanned issues, inaccurate delivery dates and no early warning signs all lead to missed deliveries and unhappy customers.
Unlike guidance systems for ballistic missiles that constantly adjust to hit a target, traditional scheduling systems provide no ability to do a “mid-course” correction to bring late jobs back to on-time status. Michael will briefly describe how AI solves the “Traveling Salesman Problem” and how it relates to on-time delivery and AI. More importantly, he will show how AI, IoT and other technology and approaches were and are used to do what traditional scheduling software and typical improvement methods cannot.
Michael will explore an example that resulted in a patented process that was used to give more accurate promise dates to customers and achieve a 98% on-time delivery rate. IoT and AI made the impossible possible, providing updated delivery times every 15 minutes while accounting for an almost infinite combination of changing factors from variation to absenteeism. Armed with enhanced real-time alerts to potential late deliveries, Michael will share the reprioritization and interventions management can now take to ensure on-time delivery. Even though this example is a manufacturing one, lessons learned are applicable to service organizations as well.