Real‐time, short‐term rainfall forecasting is gaining recognition as a valuable input to more effective performance of a variety of urban water management activities, including controlling the incidence of untreated combined sewer overflows. An important question is, What levels of forecast error can be tolerated before it is better to abandon adaptive control policies utilizing forecast information in favor of simple reactive control methods? Experiments with an autoregressive‐transfer function model for shortterm forecasting are presented, utilizing the San Francisco North Shore Outfalls Consolidation Project as a case study. A split data technique is used to gain insight into expected forecast errors for selected overflow‐producing storms varying from high intensity‐low duration to low intensity‐high duration. These results are then compared with the performance of the planned system, utilizing automatically controlled gates in a large shoreline tunnel, for various levels of forecast error. The results of a limited number of simulation runs indicate that expected forecast model errors are generally lower than the error threshold above which reactive policies become more attractive.
Management by Objectives (MBO) is a management approach that is frequently discussed and extensively employed, but seldom sufficiently evaluated. In this study, companies were contacted randomly from lists in Business Week's Annual Corporate Scoreboard to ascertain their use of MBO. The resulting 45 companies using MBO were compared with the 34 not using MBO on 5 quantitative organization results. Although MBO users exceeded nonusers on all five criteria, only one difference was statistically significant. Similar results were found when comparisons were made within industrial groupings. Results were related to possible limitations of the study design and of MBO itself.
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