Harvey M. Wagner

New-Product Strategy and Industry Clockspeed

We study how industry clockspeed, internal firm factors, such as product development, production, and inventory costs, and competitive factors determine a firms optimal new-product introduction timing and product-quality decisions. We explicitly model market demand uncertainty, a firms internal cost structure, and competition, using an infinite-horizon Markov decision process. Based on a large-scale numerical analysis, we find that more frequent new-product introductions are optimal under faster clockspeed conditions. In addition, we find that a firms optimal product-quality decision is governed by a firms relative costs of introducing new products with incremental versus more substantial improvements. We show that a time-pacing product introduction strategy results in a production policy with a simple base-stock form and performs well relative to the optimal policy. Our results thus provide analytical support for the managerial belief that industry clockspeed and time to market are closely related.

Algorithms and heuristics for variable-yield lot sizing

Abstract : We consider the multiperiod lot-sizing problem in which the production yield (the proportion of usable goods) is variable according to a known probability distribution. A dynamic programming algorithm for an arbitrary sequence of demand requirements is presented. We review two economic order quantity (EOQ) models for the stationary demand continuous-time problem and derive an EOQ model when the production yield follows a binomial distribution and backlogging of demand is permitted. Heuristics based on the EOQ model are discussed, and a computational evaluation of these heuristics is presented. The heuristics consistently produced near optimal lot-sizing policies for problems with stationary and cyclic demands. (Author)

OR Forum-The Next Decade in Operations Research: Comments on the Condor Report

Under the sponsorship of the Systems Theory and Operations Research STOR Program of the National Science Foundation, a Committee on the Next Decade in Operations Research CONDOR held a 3-day workshop in mid-1987. The report of this committee appeared a year later in Operations Research pp. 619-637. In view of the importance of this subject, and because CONDOR had, a fortiori, to limit its considerations to a number of important ones of primary interest to its members, a number of other OR analysts of widely different experience were asked to comment on this report. Four of the responses are presented below.

Evaluating focused factory benefits with queuing theory

Abstract In this paper, we study the benefits of a focused factory using lead-time as a performance measure. Specifically, we model a production process, using multi-class (multiple product types), general interarrival and processing time distributions with multiple machines ( GI/G/c ) queuing models for deriving each product’s mean lead-time. We also perform simulations for estimating the standard deviation of lead times. There are two product types: a standard and a customized product. The customized product has a more variable demand pattern than the standard product, and also requires additional processing time (setup and run time) in its production process. We assume that management is willing to sacrifice the lead-time performance of the customized product in favor of improved performance for the standard product. The paper shows that focusing the factory is more attractive for plants operating at higher utilization, and manufacturing products that have higher processing time and demand variability differentials between product types.

OR Forum-Operations Research: A Global Language for Business Strategy

Based on the authors observations and experience, this paper argues that the concepts and vocabulary of operations research have become a pervasive part of the thinking of modern American industrial managers, and that the related models are playing important roles in informing the decisions that they make. Since any model is only a partial representation of reality, this fact-and the criticisms that it has evoked-present the operations research and management communities with continuing challenges for improving their work.

The Accuracy of Aggregate LP Production Planning Models

This paper provides valuable evidence concerning the use of small, simple models to represent complex systems. The focus is on linear programming planning models. The starting point is a large, detailed model which serves as a proxy for reality. From the large model, we derive a smaller one through aggregation. Through a process of calibration, we develop estimation models for determining the value of the detailed model objective function value from the aggregate model objective function value and a few additional explanatory variables. This overall procedure proves to be remarkably accurate.