Applying operations research to service system design and management

Flexibility and optimization at all levels are the ultimate goals in service systems design and management.  In designing a supply chain, firms are often faced with the competing demands of improved customer service and reduced cost. CITRIS researcher Max Shen has developed a model that incorporates supply chain-related costs while ensuring that certain service requirements are satisfied. His results suggest that significant service improvements can be achieved relative to the minimum cost solution at a relatively incremental cost.

Businesses also need to take steps to deal with disruptions, which can happen to any supply chain, logistics system, or infrastructure network. Today’s firms tend to assemble final products from increasingly complex components procured from suppliers rather than produced in-house. Shen and colleagues are developing models to understand the interdependence of risks faced by a supply chain or a service system, and are working to design service systems that are robust and resilient.

Another area of research is that of service resource allocation. Decisions on resource allocation are made based on assumptions and estimates of demand levels. But those same decisions also affect demand levels, so a complete service system design model should recognize the impact of customer satisfaction on current and future demand. Shen, a Berkeley professor of Industrial Engineering and Operations Research, and colleagues have studied queuing and resource allocation models that respond to satisfaction of previous demand.

In most practical situations, the decision maker does not know the exact demand for each product. Shen has been developing models that can help the decision maker learn the demand distribution. By offering different product assortments, observing resulting purchases, and inferring the demand distribution from past sales and assortment decisions, businesses can quickly learn customer preferences and generate close to optimal profit.