Classes start next week. Should we be teaching Linear Programming to SCM students? Great read: Supply Chains Can’t Find Talent With The Right Skill Sets… Notice the reference to “optimization”…

“When it came time to identify what the issues to hiring are, 64% said finding the right skill set as the top challenge, followed by 58% citing a talent shortage in data analytics, optimization, automation, etc.”

The context mentions challenges in “optimization.” Linear programming is a fundamental tool for optimization. In various industries, including supply chain, LP can be employed to make the most efficient use of resources. For instance, how to allocate limited resources to meet demand or how to schedule production to minimize costs.

It is making me rethink how much time I dedicate to mathematical optimization techniques as it has done nothing but fade in my teaching content. Note, my students major in SCM and tend to go into very different cross functional career paths (largely procurement of late) that typically do not require these types of skill sets. I do have some former students on the planning side that find value in this.

From chatGPT (note, chat did not make my slide deck below, it is from the 1990s):

My slide deck:Sime Curkovic on LinkedIn: …talent shortage in analytics, optimization, automation.Classes start next week. Should we be teaching Linear Programming to SCM students? Great read: Supply Chains Can’t Find…

From chatGPT…Here are reasons why LP should be taught to supply chain students:

Optimization Skills: LP helps students develop optimization skills, enabling them to make better decisions in complex supply chain scenarios. They learn how to formulate mathematical models, identify objectives, & incorporate constraints to find optimal solutions. These skills are crucial for effective supply chain planning, resource allocation, and decision-making.

Cost and Resource Mgmt: LP techniques allow students to optimize costs and resource allocation within the supply chain. They learn how to minimize costs, maximize profits, or achieve other objectives by considering constraints such as capacity limitations, demand variations, and inventory levels. This knowledge helps them make efficient use of resources, reduce wastage, and improve overall supply chain performance.

Demand and Supply Matching: LP can assist in matching demand w/ supply efficiently. By understanding how to balance production capacity, inventory levels, transportation constraints, and customer demand, students can optimize production schedules, inventory mgmt, and transportation planning.

Decision Support: LP provides students with a powerful decision support tool. By incorporating real-world constraints and objectives into mathematical models, they can analyze different scenarios, conduct sensitivity analysis, and evaluate trade-offs.

Overall, teaching LP to students majoring in SCM enhances their analytical capabilities, decision-making skills, & ability to optimize supply chain operations. It equips them with a valuable toolset to tackle real-world challenges and contribute effectively to the field of SCM.

#supplychain #planning #logistics #optimización

Related Posts

Leave a Reply

Your email address will not be published. Required fields are marked *