TITLE: Production Capacity Investment with Data Updates

SPEAKER: Dr. Phil Kaminsky, UC Berkeley

ABSTRACT:

We consider the capacity investment problem faced by pharmaceutical firms and other firms that have long and risky product research/development/approval cycles for products that require expensive and long lead-time manufacturing capacity in order to meet demand.  These firms must balance two conflicting objectives: on one hand, the delay in scaling-up production once the product is approved must be minimized, and on the other hand, the risk of investing in ultimately unused capacity must be minimized.  In many cases (at least in the pharmaceutical industry), firms are hesitant to reconsider capacity investments once initial investment decisions are made.  To explore alternative strategies, we develop a stylized model of a capacity investment problem where the firm re-evaluates its capacity investment strategy as information about the potential success of the product is updated (for example, via clinical trial results in the case of the pharmaceutical industry).  We characterize optimal investment strategies in a variety of settings, and use a computational study to identify settings in which by frequently reviewing the building strategy, the firm can substantially reduce both the delay of the commercial launch of the new product and the risk of lost investment.    We consider settings where the firm can invest in alternative capacity types with different costs and lead times, explore when the availability of more than one capacity type is most valuable, and investigate whether a firm should ever start to invest in one type of capacity and then switch to building an alternative capacity type.

This research was motivated by projects completed as part of our new Biopharmaceutical Operations Center at UC Berkeley, and I will begin the talk with a brief overview of these efforts.

Joint work with Ming Yuen.