Browsing by Author "Michalakis, George"
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- ItemOpen AccessThe development of a forecasting method for mining house capital projects(1982) Michalakis, George; Jervis, W; Ryan, Tom BA broad description of a project is a single, non-repetitive enterprise which is undertaken to achieve planned results within a time limit and a cost budget. This description could equally well apply to fixing a punctured tyre, expanding an existing mine, the design of a computer system or the building of the pyramids. Modern civilisation is largely based on the successful completion of projects. It is surprising therefore, that it is only in the very recent future, since the 1950's say, that the effective management of projects has been considered worthy of academic attention. Today project management in in the process of becoming a management science in its own right. This need for the effective management of projects is further evidenced by the emergence in large organisations of departments whose function it is to control projects. Typically, a project control department would, in addition to other functions, be required to report to management regularly on the health of a project - is the project on schedule and on budget? If it is not, management clearly needs to be given an indication of where the project is heading. A number of techniques are in common use which claim to 'forecast' the final cost and completion date of a project. These techniques include the S-curve in its many forms and Critical Path Networking, amongst others. On close analysis however, it soon becomes apparent that although these techniques offer a wealth of useful information regarding the present state of the project, and give a qualitative idea of the direction the project is heading in, they do not give any quantitative indication of the final cost and completion date of a project. In other words these techniques are control methods rather than forecasting methods. Most forecasting tends, in fact, to be done by an expert judgemental process which is highly subjective. iii It was felt therefore that there was a need for the development of an objective forecasting method. An informal Industrial Opinion Survey was conducted which confirmed this belief. On the basis of this it was decided to attempt to develop an objective forecasting method and to determine whether it was more useful, reliable and accurate than existing subjective forecasts. An exhaustive Literature Survey was then carried out in an attempt to find past work in the field. It was found that most techniques in use were control techniques as described above, with the exception of the Resource Appraisement Model developed by Dr P.P. Pekar. This model (with three variations), provides a means of recalculating the complete project plan in terms of cost at each report period in the light of reported expenditures. However, the model assumes the same time phasing as the original project plan. In other words, it assumes that the project will end on schedule. This assumption limits considerably the practical use of the model. As a result, the Resource Appraisement Model was refined and modified somewhat to include the forecasting of time as well as cost. This was done by relating the two parameters independently to percent physical completion. The resulting model, known as the Generalised Resource Appraisement Model (GRAM), was then tested using a computer program and a case study project. The results of this evaluation were then compared to the forecasts which had been produced by the existing subjective method for the case study project. On the basis of this evaluation it was concluded that the GRAM was more accurate but as reliable as the existing method in forecasting final project cost. It was also found that the model was much quicker in informing management of general project trends (i.e. over or under budgeting). iv It was found however, that the model was too sensitive to large periodical fluctuations in expenditure which were not necessarily true reflections of changes in trend. There is reason to believe that this characteristic may be overcome with relatively minor refinements to the model. The objectives of the thesis were therefore attained adequately. Inevitably however there remains a great deal of work to be done before the technique could be used with confidence. Future work is indicated in taking the model less sensitive to large random fluctuations, and making the model a more flexible management tool by allowing the 'what if' type of investigation.