Knowledge that Transforms

Recent evidence suggests the connection between quality improvement and financial results may be weak. Consider the case of Analog Devices, Inc., a leading manufacturer of integrated circuits. Analog's TQM program was a dramatic success. Yield doubled, cycle time was cut in half, and product defects fell by a factor of ten. However, financial performance worsened. To explore the apparent paradox we develop a detailed simulation model of Analog, including operations, financial and cost accounting, product development, human resources, the competitive environment, and the financial markets. We used econometric estimation, interviews, observation, and archival data to specify and estimate the model. We find that improvement programs like TQM can present firms with a tradeoff between short and long run effects. In the long run TQM can increase productivity, raise quality, and lower costs. In the short run, these improvements can interact with prevailing accounting systems and organizational routines to create excess capacity, financial stress, and pressure for layoffs that undercut commitment to continuous improvement. We explore policies to promote sustained improvement in financial as well as nonfinancial measures of performance.

This paper reports the results of a controlled laboratory experiment in which the work of Elam and Mead (Elam, J. J., M. Mead. 1990. Can software influence creativity? Inform. Systems Res. 1(1) 1–23.) was both replicated and extended to explore how knowledge and use of a creativity-enhancing process employed both manually and delivered via computer software affect the level of creativity in response to a problem-solving task. The results suggest the enhancement of creativity in response to open-ended problems is significantly affected by the process employed by the decision maker rather than the vehicle by which the process is delivered. Further, the results indicate that the capability of a decision support system (DSS) to provide directed guidance in the application of a process combined with user knowledge of the underlying process model improves creativity enhancement over use of either the DSS or the process alone.

Low earth orbit satellite (LEOS) systems promise to provide global communication. A LEOS system consists of a large number of satellites in low orbits. A satellite has a limited life of approximately five to eight years. Therefore, frequent satellite replenishments are required, and the LEOS systems will be facing annual replenishment costs in the range of several hundred million dollars. This paper considers static satellite launch policies for LEOS systems. The satellite launch problem is formulated and a solution method based on dynamic programming is proposed. Lexicographic ordering is used to reduce the search space of the dynamic program to a moderate size. An algorithm for calculating optimal static policies is used to demonstrate the potentially significant economic impact of satellite launch policies on system maintenance costs.

Nearly all Fortune 1000 firms claim to have downsized since the early eighties, and it is argued that information technology (IT) is responsible for this massive downsizing. However, earlier research has indicated that IT increases middle management. Even though the impact of IT on the middle management workforce has been studied for the last thirty years, research has failed to clearly explain this phenomenon. Quite the opposite, research has fueled controversy and has provided inconsistent findings. This article addresses the state of inconsistent findings across multiple studies by examining the impact of information technology on the number of middle managers using two additional variables: the degree of centralization of organizational decision authority and the degree of centralization of computing decision authority. One hundred and fifty-five city governments were surveyed. Information technology was found to be both positively and negatively associated with the size of the middle management workforce. The impact of information technology was fundamentally determined by who controlled computing decisions and what interests were being served, and by the roles of middle managers. Information technology was associated with a decrease in the size of the middle management workforce in organizations with centralized decision authority and with an increase in the number of middle managers in organizations where decision authority was decentralized.

Multiissue negotiations present opportunities for tradeoffs that create gains for one or more parties without causing any party to be worse off. The literature suggests that parties are often unable to identify and capitalize on such trades. We present a Negotiation Support System, called NEGOTIATION ASSISTANT, that enables negotiators to analyze their own preferences and provides a structured negotiation process to help parties move toward optimal trades. The underlying model is based on a multiattribute representation of preferences and communications over a computer network where offers and counteroffers are evaluated according to one's own preferences. The parties can send and receive both formal offers and informal messages. If and when agreement is reached, the computer evaluates the agreement and suggests improvements based on the criteria of Pareto-superiority. In this paper, we motivate the system, present its analytical foundations, discuss its design and development, and provide an experimental assessment of its “value-in-use.” Our results strongly suggest that parties using the system in structured negotiation settings would achieve better outcomes than parties negotiating face to face or over an e-mail messaging facility, other things being equal. For example, only 4 of the 34 dyads (11.1%) negotiating a simulated sales transaction face to face or over e-mail reached an “integrative” settlement, as compared with 29 of the 68 dyads (42.6%) using NEGOTIATION ASSISTANT. Systems such as NEGOTIATION ASSISTANT have the potential to be used in emerging “electronic markets.”

“Auction” or “call” trading systems are used in many stock exchanges. An essential problem in the application of these systems is that orders in one security cannot be conditioned on prices of other securities. This paper proposes and analyzes the feasibility of an index-contingent trading system. In this system, limit orders may be conditioned on an index (any weighted average of the security prices that is determined simultaneously with the prices) in addition to the asset price. Without any assumptions about traders' behavior it is shown that under a reasonable restriction on the structure of the limit orders, there is a unique solution (vector of prices) to any set of orders in all securities. Moreover, the paper presents a quick and simple algorithm that converges to the solution. This algorithm is based on an extension of the current mechanisms; therefore it can be implemented easily in any computerized auction system.

This note deals with the joint replenishment problem with stochastic demands. A new class of policies called P(s, S) policy is proposed for this problem. The proposed policy uses independent, periodic review (s, S) policies for each item. Results on test problems show that the proposed policy is superior to other classes of policies for the problem.

In this paper we consider the daily aircraft routing and scheduling problem (DARSP). It consists of determining daily schedules which maximize the anticipated profits derived from the aircraft of a heterogeneous fleet. This fleet must cover a set of operational flight legs with known departure time windows, durations and profits according to the aircraft type. We present two models for this problem: a Set Partitioning type formulation and a time constrained multicommodity network flow formulation. We describe the network structure of the subproblem when a column generation technique is applied to solve the linear relaxation of the first model and when a Dantzig-Wolfe decomposition approach is used to solve the linear relaxation of the second model. The linear relaxation of the first model provides upper bounds. Integer solutions to the overall problem are derived through branch-and-bound. By exploiting the equivalence between the two formulations, we propose various optimal branching strategies compatible with the column generation technique. Finally we report computational results obtained on data provided by two different airlines. These results show that significant profit improvement can be generated by solving the DARSP using our approach and that this can be obtained in a reasonable amount of CPU time.

Our Bayesian dynamic programming model builds on existing models to account for inspection delay, choice of keeping production going during inspection and/or restoration, and lot sizing. We focus on describing how dynamic statistical process control (DSPC) rules can improve on traditional, static ones. We explore numerical examples and identify nine opportunities for improvement. Some of these ideas are well known and strongly supported in the literature. Other ideas may be less well understood. Our list includes the following: Cancel some of the inspections called for by an (economically) optimal static rule when starting in control (such as at the beginning of a production run and following a restoration). Inspect more frequently than called for by an optimal static rule once inspections begin, and inspect even more frequently than that when negative evidence is accumulated. Utilize evidence from previous inspections to justify either restoration or another inspection. Cancel inspections and hesitate to restore the process at the end of a production run. Consider using scheduled restoration, in which restoration is carried out regardless of the results of any inspections. Implementation, limitations, and extensions are addressed.

This paper examines the relationship between one form of manufacturing flexibility—process range—and structure, infrastructure, and managerial policy at the plant level. The paper provides evidence of the strength of the links between manufacturing flexibility and such factors as scale, technology vintage, computer integration, and workforce management. Data from 54 plants in the fine-paper industry are presented, and a model of the determinants of short-term flexibility is developed. The plants examined differed by a factor of 20 in their ability to accommodate large process variation. The evidence suggests that flexibility is strongly negatively related to scale and degree of computer integration, yet positively related to newer vintages of mechanical technology and workforce experience. Some results differ significantly from the prevailing view of the industry, in particular, that newer plants are less flexible. The paper shows that newer machine technology is more flexible once other factors are controlled for. In the longer term, the results show that management has a significant impact on the improvement of flexibility in operations, regardless of the technology and infrastructure in place. Plant network managers' views of flexibility are important. The data suggest that inflexible plants may be inflexible partly as a result of their being considered inflexible by network managers, and never being assigned the product range needed to improve the capability.