H. V. Ravinder

The Reliability of Subjective Probabilities Obtained Through Decomposition

The use of decomposition as a procedure for improving the consistency of subjective probability encoding is discussed. Using a psychometric measurement model, an expression is developed that describes the random error associated with decomposition estimates as a function of characteristics of the component assessments. Decomposition is compared to direct assessment in terms of the percent change in measurement error that can be attributed to the use of decomposition. Potential benefits of decomposition are specified and recommendations made on how to utilize decomposition as an approach for error control.

Decision Making in a Standby Service System

A standby service option allows a firm to lower its risk of not having sufficient capacity to satisfy demand without investing in additional capacity. Standby service options currently exist in the natural gas, electric, and water utility industries. Firms seeking standby service are typically large industrial or institutional organizations that, due to unexpectedly high demand or interruptions in their own supply system, look to a public utility to supplement their requirements. Typically, the firm pays the utility a reservation fee based on a nominated volume and a consumption charge based on the volume actually taken. In this paper, a single-period model is developed and optimized with respect to the amount of standby capacity a firm should reserve. Expressions for the mean and variance of the suppliers aggregate standby demand distribution are developed. A procedure for computing the level of capacity needed to safely meet its standby obligations is presented. Numerical results suggest that the standby supplier can safely meet its standby demand with a capacity that is generally between 20 to 50% of the aggregate nominated volume.

An integrated approach to the teaching of operations management in a business school

ABSTRACT The authors discuss a curriculum integration effort that a school of business piloted recently. This effort was aimed at integrating the core functions (finance, marketing, management, and operations) so that undergraduate students would better appreciate the full impact of functional decisions on each other and in achieving the corporations business objectives. The authors deployed a webbed integration model in which a business case was used to highlight the impact of a functional decision on the other three functions. The focus of the article is on how this model was implemented in the context of a required introductory course in operations management. The authors also discuss the results of this effort, lessons learned, and the path forward.

Quantifying the Risk of Intellectual Property Loss in Analytics Outsourcing

The safety of a companys secrets and proprietary competitive practices becomes an important concern when the company is involved in outsourcing. This concern becomes even more critical when the company is engaged in analytics outsourcing where the company shares proprietary data about the internal processes. While there is a growing concern about the larger costs and risks of the wholesale outsourcing of analytics functions in the business press, there are no statistics on the risks or a sense of how big they might be. This paper attempts to fill this gap by building a mathematical model of the vendor-client interaction that will allow some baseline quantification of the risks that are inherent in analytics outsourcing. The paper also discusses the implications of these ideas for companies that work with outsourcing vendors and closes with some ideas for further research.

A Rationale for Additive Decomposition in Multiattribute Utility Assessment

The purpose of this paper is to develop a rationale for the decomposition of a hierarchy of objectives used as the basis for the assessment of a multiattribute utility function. This rationale is based on a comparison of two approaches to the assessment of multiattribute utility functions. One is simply to interrogate the individual whose preferences regarding a given outcome are to be elicited, and obtain an intuitive estimate of the desired utility. This is termed the wholistic estimate, because the different attributes are considered all at once, and no decomposition is attempted. The second alternative is to decompose the problem into several single attribute assessment problems, and then obtain the multiattribute utility function using an appropriate aggregation rule. The advantages cited for this approach are the usual ones associated with any decomposition strategy. A greater degree of systematization is introduced into the assessment problem. Individual problems are smaller and easier to solve, and their solutions can be combined mechanistically using a suitable aggregation rule. However, with each of these assessments one can associate some error, and when the assessments are combined to obtain the decomposition estimate, the combined error might be significant. An analysis of the errors associated with the wholistic and the decomposition strategies will be used to identify when decomposition into a hierarchy of objectives is an appropriate strategy.