Objective and subjective forecasting
Forecasting is act of predicting the future by use of (time series related) data that are available in order to make objective decisions. According to Fides and Bernard there are two basic types of forecasting models- subjective model and objective model. This paper aims to make comparisons between the subjective forecasting method and the objective forecasting method.
Objective models refer to those methods in which there are a specific and well defined procedures of obtaining the forecast. This forecasting method is usually quantitative with alo0t of data involved in completion of the process. At other times the specifications in the objective forecasting is so much well defined such that the method can be replicated by other researchers and obtain the same forecast. Mostly objective forecasting employs computer processing. The various types of objective forecasting include time series, causal/econometrics and artificial intelligence (Stevens, 2003). In time series, the method relies on estimation provided for outcomes expected in the future with regards to data in the past. For instance, historical sales recorded for a commodity is utilized as a predictor of the future sales because of the factors such as brand awareness which affect the trend. For causal forecasting method, the procedure followed involves outcome prediction on the basis of known changes closely associated with outcomes. For instance, temperature acts as a determinant of the quality of sales of ice cream.
Subjective forecasting models also known as judgmental, intuitive or implicit methods refers to the forecasting models in which the process used in obtaining the forecast is not well defined. Here the forecasting process is done ‘in the head’ of the person carrying out forecasting. This method is usually applied by sociologists, medical doctors, managers, political scientists among others. Subjective forecasting tends to be more qualitative whereas there is heavy reliance on educated guesses and rational judgements. The guesses made in subjective forecasting are usually reliant on experience, professionalism and knowledge that the forecaster has. It is well applied in long range forecasting since there is foreknowledge or experience that the forecaster already has. The most suitable instance for this case is in long-range forecasting whereby quantitative data may not be of effective use. The case of long-range data calls for the immediate opinion of an individual to help in establishing a judgement forecast.
There are many ways of testing the outcomes of given method that has been used to carry out activities. However the two most common and effective ways to evaluate the outcome of a project are outcome evaluation and process evaluation. These two methods are the most used to shows the effectiveness of projects outcome activities.
The outcome evaluation is the very common one to both the profiting projects and the non-profiting projects. There should be analysis of the quality and quantity of the programs achievements. The quality and quantity should go hand in hand for the method to be considered very effective. Quantity is the number of the achievement that has been attained by the method. Quality on the other hand is the degree of effectiveness of the project. For the outcome to be considered very effective it must be of high quality and quantity. If the program is capable of serving many people effectively then the outcome is of greater good and therefore the program is encouraged.
The process evaluation technique is allows for the concentration on the developing part. It focuses on the development of the methods. It also allows for the evaluation on the cost of the different methods and their effective. If two methods are to yield the same output but the prices of putting them into practice are different, the cheaper method is thus considered effective and of high quality and quantity output. The cheaper method is thus encouraged. The process evaluation also focuses on the technology that is used in carrying out the different methods. The program that is not technology intensive but still effective is considered have the best output.
There is need to highlight the similarity and difference existing between the two in order to come up with a distinct picture. The first difference between the two are that subjective forecast is mainly based on the expert opinion such as the personal insight, the panel consensus, the Delphi, method and the historic analogy while the objective forecasts are mainly based on the casual methods such as the analysis of the causes of the demand. Another difference is that the subjective forecast is based on an opinion of the consumer, for example, it is determined indirectly by the composites of the sales force or directly by the market surveys. On the other hand, the objective forecast is based on time series or the projective methods i.e. it involves the analysis of the demand for the previous events, determination of the demand patterns as well as the forecasting of the demand by considering the data from the previous periods that happened in prior.
The similarities between the methods are that they measure all forms of data, they are all given writings and calculations, all the methods tends to be timely in prediction of the events, they all strive to be as more accurate as possible thus avoiding the wrong predictions, they are all given in the meaningful units of measurements that correlate to the measured or predicted events. Another important similarity is that all the methods are presented in the forms that are easy to use or understand in many cases so that the main point or a digit is not missed. When the information is missed, the result might mean something else altogether thus rendering the outcome as bias and wrong.
The two methods are both utilized in the production process, by business, to help in establishing profitable operations. In the case of objective forecasting it is mostly used in short range forecasting. This involves determining how much the customer will want. It is used to predict trend in the sales and thereby allow the business to come up with appropriate marketing strategies that would cover for the future changes. For instance, by predicting better sales in the next coming 1 year the company in subject will establish strategies that would help them to improve production. This is because better sales is related to demand in the market and by predicting increase demand the firm will need to increase production in order to satisfy their customers. The forecasted demand allows the business to put up strong measures in aligning its production process with the change in demand. For subjective forecasting, its used in the production process is mainly reliant on qualitative study. This is whereby a company may need to predict what qualities the clients may want in 10 years from now.
References
Stevens, D. (2003). Inefficiency in Earnings Forecasts: Experimental Evidence of Reactions toPositive vs. Negative Information. Department of Economics, Indiana University, Wylie Hall 105.
