Model Management Systems in Business

By Bharadwaj, Anandhi; Lo, Amber et al. | Business Perspectives, Spring 1990 | Go to article overview

Model Management Systems in Business


Bharadwaj, Anandhi, Lo, Amber, Shetty, Bala, Business Perspectives


Model Management Systems in Business

An addition to database technology that would provide managers with a more effective decision-making environment

Rapid progress has been made in the area of data management, and today managers can, within seconds, use their desktop computers to retrieve the data they want. However, the power of currently available database management systems is limited to data retrieval and simple manipulations of raw data. If complex analytical models such as a linear program for an investment decision or a forecasting model for estimating market demand are required, the managers must depend on management science practitioners for assistance.

Such dependency has been avoided by many managers for several reasons. One is that the management science models are often too complex and incomprehensible to nonspecialists. This fact, combined with the inadequate business skills of many management science practitioners, turned managers elsewhere for help. Those who learn to use management science models often feel less powerful due to too much dependence on such models. These managers use the models mechanically without fully understanding them or knowing how they can aid in a better decision-making process.

In order to facilitate a greater acceptance of analytical models by nonspecialists and to make use of the tremendous opportunity afforded by desktop computers, a new generation of computer software called model management systems (MMS) is emerging in several research environments. Database management systems have become very popular in the last decade mainly because they make the storage, retrieval, and manipulation of data very easy. The user can obtain information from a database by simple queries in English-like language. The purpose of a model management system is analogous to that of a database management system. Just as data management systems insulate their users from the physical aspects of database organization and processing, so also do model management systems insulate their users from the physical aspects of modelbase organization and processing.

Model management systems provide a structured environment for storing, manipulating, and retrieving models. These systems also allow managers easy access to a wide variety of analytical models for optimization, forecasting, regression, simulation, and manufacturing and inventory control. Using model management systems, a manager can analyze business problems without getting involved in the technical and/or procedural aspects of model formulation and implementation.

ROLE OF MODELS

A model, defined in very general terms, is a representation of reality. In the context of model management systems, a model is defined as a mathematical representation of a problem that can be solved using certain computer programs called "solvers." Examples of models commonly used in business decision making are those used to calculate economic order quantities (EOQ) for inventory items, financial models for analyzing returns on investments, forecasting models for estimating the demand for different products, and a wide range of optimization models for maximizing (or minimizing) costs in a variety of situations.

There is less risk working with a model when attempting to solve an actual problem. The environment that decision makers face is usually so complicated and dynamic that it often becomes difficult to solve a problem by intuition alone. …

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