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As planning problems become more complex and the pace of change quickens in the society, managers are increasingly turning to the computer for assistance in their planning problems. But considering the rather disastrous track record of many computer aided planning systems, there appears to be cause for alarm. The executive needs a good briefing on the managerial aspects of computer based planning systems. [ABSTRACT FROM AUTHOR]

The article evaluates the Uniproduct, a computer simulation for educational purposes which combines a functional business game and a Monte Carlo simulation.

The article discusses research pertaining to U.S. managers' thoughts on electronic data processing (EDP). The study showed wide differences among the firms with regard to management's computer objectives, acquisition practices, employment impact, system design, programming methods, and other factors associated with data processing. Analysts say management misconceptions about EDP may be due to the use of factory automation as the basis for comparison and predictions about computerized office automation. They say management must abandon their oversimplified view of EDP and meticulously analyze the data processing needs of their firm.

The article presents the author's assessment of electronic data processing (EDP) strategies in 1959. He contends that the failures of EDP systems stem from poor planning and poor adaptation by their users. He believes that the standards of EDP users are set too high. The author speculates that the future is favorable for the role of the computer.

The article reports on electronic data processing. The author focuses on future commercial applications of electronic systems in the business field. It is suggested, by 1968, the computer hardware industry will have evolved to the point where computers are being produced on a massive scale. According to the author, the accessibility of computers will lead to the automation of industrial paperwork. Industrial managers will begin to utilize electronic data processing on a grand scale, in order to predict the success of business plans, make policy decisions, and conduct operations research. Additional implications for industrial organizations are also discussed.