Author(s): King, John Leslie | Abstract: The long-standing debate over whether to centralize or decentralize computing is examined in terms of the fundamental organizational and economic factors at stake. The traditional debate is examined and found to focus predominantly on issues of efficiency vs. effectiveness, with solutions based on a rationalistic strategy of optimizing in this tradeoff. A more behavioralistic assessment suggests that the driving issues in the debate are the politics of organization and resources, centering on the issue of control. The economics of computing deployment decisions is presented as an important issue, but one that often serves as a field of argument that is based on more political concerns. The current situation facing managers of computing, given the advent of small and comparatively inexpensive computers, is examined in detail, and a set of management options for dealing with this persistent issue is presented.

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Centralized versus decentralized computing: organizational considerations and management options

This paper develops a model of the growth of information systems expenditures in the United States. The model incorporates two major factors that influence the rate and pattern of spending growth—the diffusion of technological innovation and the effect of price on the demand for computing. Traditional studies have focused on the role of innovation while ignoring the effects of price on the growth process. We show that while information systems expenses initially grew following an S-curve, more recent growth has converged to an exponential pattern. These patterns are consistent with our integrative price-adjusted S-curve growth model.

An Integrative Model of Information Systems Spending Growth

Using readily available data on CPU characteristics—main memory size, cache memory size, number of channels, and machine cycle time—it is possible to predict relative CPU performance for a wide range of machines. Statistical analyses indicate that these characteristics explain virtually all the variance in relative performance.

Attributes of the performance of central processing units: a relative performance prediction model

Does Grosch's law, which postulated that the costs of computer systems increase at a rate equivalent to the square root of their power, still hold? The age of mini-, micro-, and supercomputers seems to have complicated the situation. When computers are grouped according to their size and power, Grosch's law seems to hold within each group, but not between different groups.

Grosch's law re-revisited: CPU power and the cost of computation

The Intelligent Database Machine (IDM), manufactured by Britton-Lee Inc., is a back-end processor and storage system that contains a complete data management system. It includes specialized hardware to perform data management functions. It is our contention that the designers of a database machine must choose a focus for their machine which strongly influences other design decisions. The IDM is low cost, high performance machine designed to support "midrange" users. This paper presents the reasons for this choice, and the resultant design issues.

Design decisions for the intelligent database machine

Econometric models of the U.S. computer market have been developed to study the relationships between system price and hardware performance. Single measures of price/performance such as “Grosch's Law” are shown to be so oversimplified as to be meaningless. Multiple-regression models predicting system cost as a function of several hardware characteristics do, however, reveal a market dichotomy. On one hand there exists a stable, price predictable market for larger, general purpose computer systems. The other market is the developing one for small business computer systems, a market which is relatively unstable with low price predictability.

L. L. Gremillion

Papers

Price/performance patterns of U. S. computer systems