Q. Problems and difficulties associated with forecasting?

We have relied to a great degree on the forecasting of data in order to provide an evaluation of the proposal. Not the entire the components are forecast for example we will know that we are able to recover agreed costs. But to the extent that components are forecast there exists the potential for fault in our evaluation which of course leads to uncertainty in our conclusions.

In particular the following problems are evident at this stage

- Uncertainty rise with the length of time forecast. That is the further into the future the less capable we are to predict with accuracy because our initial assumptions may be wrong and small error at the beginning magnify subsequently as the forecast becomes increasingly irrelevant to what is actually happening to the key variable in question. For instance we may have not predicted general inflation rates correctly which could have a large impact on our labour costs.

- Project difficulty the more variables we have to forecast the less probable we are to be accurate. This problem has an inexplicable outcome if there are a large number of variables to forecast the uncertainty concerning the two components are able to have two effects

- The larger the number of components to predict the greater the difficulty in determining project outcome. Forecasting so lots of components can lead to errors for the reason that the scale of the problem is large.

- By forecasting lots of components we assume a relationship between the components which is as well a forecast. This relationship may perhaps change. For illustration the relationship of production variable overheads to units produced may change. Currently they are related to the amount of materials used. If we use predicts based on these assumptions then we as well assume that the relationship between materials used and overheads absorbed is constant. This may possibly not be the situation if the type of materials changes.

- The background information may modify. What happens for illustration if a new competitor enters the market? This effect will be eased to the extent that we have an agreed contract. There are other things which could have a significant effect given enough time to materialise. For instance technological change could have an impact on our industry. In particular social change may be related if consumers begin to demand even higher quality water supplies which would inevitably affect our costs.

- There is forever the random component that could distort our forecasts. But an alternative view would suggest that such random components are really an admission of lack of skill in forecasting. The finest forecasters attempt to anticipate all eventualities.