I work with clients that utilize our supply chain optimization software to maximize their resources. In my upcoming webinar “Should I Optimize My Supply Chain Planning?” I’ll dive deeper into the concepts of supply chain optimization and show examples of when it’s ideal to optimize and when it’s less ideal. In today’s blog post, I’d like to simplify this concept by looking at some basic equations and scenarios to explain how “solvers” or supply chain optimization algorithms work.
In my role as the Director of Analytics, I enjoy working with the Arkieva team and our clients, in building optimization models which help organizations make intelligent decisions with regards to meeting demand, capacity allocation, inventory levels, factory schedules, forecasting, and cancer research. These models are built using a variety of mathematical methods including Boolean
The director of Supply Chain (or inventory, manufacturing, analytics, customer order fulfillment, etc.) has pulled together a cross-discipline team to identify potential enhancements in managing the demand-supply network (DSN) that will result in improved business performance. Typically, these enhancements focus on better coordination and more intelligent decision with respect to matching assets with demand across