
This paper describes the design, implementation and evaluation of a system for the management of pension funds by a large institutional investor. As a direct result of this management science based system, which had been in operation for over three years prior to this study, the jobs of security analysts, portfolio managers and the management of the investment function were significantly changed. The institution publicly acknowledged the success of this system in its annual reports and internally acknowledged the additional business revenues generated by this new approach to money management. Three major aspects of this research which spanned a period of over six years are discussed. Initially the behavioral science analysis which helped to determine why classic portfolio selection or equity valuation models had not been accepted by the organization is reviewed. This phase also contains an analysis of the necessary changes to information flows and job responsibilities before the organization could reasonably be expected to accept any normative portfolio management tools. The focus is then directed toward the key management science concepts incorporated in the Management Information System which was designed to remove the behavioral barriers to change. The major tools and concepts employed and presented in this phase are the use of the triangular distributions to collect conditional, subjective forecasts and to provide subjective distribution feedback, loss functions which are based on the impact of outcomes to the institution and not on squared error variability and the construction of feedback measures which are consistent with the organizational responsibilities of the individual. The third phase of this study is an evaluation of whether investment performance was actually improved by the new system. Testing this and related hypotheses is complicated by the fact that it was difficult enough to convince management to install one new money management system, let alone several systems simultaneously to permit controlled tests. Some aspects of this are discussed in the final section.
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