Forecasting models working through SPSS help, are useful for researchers and business owners to predict the outcomes regarding sales, supply and demand, market trends, customer behaviour and more. The model is widely utilised by researchers and market investigators mainly in sales and marketing. Apart from that, in education, health care and other service industries, the foresting model is being utilised across the international markets for specific research purposes. There are numerous ways of forecasting the business outcome, and the basic four ways of forecasting analysis techniques are such as,
Ø Time series model
Ø Econometric model
Ø Judgemental forecasting model
Ø The Delphi method
The forecasting time series analysis model uses historical data as the key to reliable forecasting, where the researchers can visualise the patterns of the data for better evaluation. The variables are represented over different periods of time and over time, the researchers try to review the trend and forecast the future activities. Improving the data against time in the plot is effective for data sorting and management, which further helps the researchers to insert relevant values against each period of time and choose a forecast sheet for further representation. Mainly, the graphical representation through line diagrams, pie charts and bar diagrams are utilised to represent the time series data and analyse the gathered data critical to forecasting the future.
An econometric model is also effective to forecast the changes in supply and demand as well as prices. This model incorporates complex SPSS data analysis and knowledge throughout the process of creation. The econometric model is proved to be valuable when predicting the future developments in the economy. Deciding on dependent and independent variables is necessary in order to form the econometric model, where the researchers put the data into X and Y dimensions of the graph. Formulating the hypothesis and putting the data is effective for the researchers to sort the large volume of gathered data and information in a systematic way. Through correlation regression analysis, the researchers can input increasing numbers of variables in the data set to analyse their impacts in long run as well as predict future activities.
The judgemental forecasting model is useful to analyse subjective and intuitive information for making predictions. The characteristics of this model are taking a subjective, opinionated approach, coming with limitations; accuracy improves with the addition of new information as well as assuming specific variables. The researchers try to arrange surveys by empowering a specific group of people for gathering their feedback ad make judgements on the collected data and information, to predict the future.
Delphi model is another way to forecast trends based on the information given by a panel of experts. It assumes that group answer is more effective and unbiased as compared to individual answer, where the researchers try to gather a vast range of data to analyse the trend and predict the future.
Hereby, the forecasting models are beneficial for the researchers to gather a vast range of data and information and analyse it critically. The researchers can gain valuable insights where forecasting gets them into the habit of looking at the past and real-time data to predict the future. Hence, the market data and information are being gathered where authenticity and validity are ensured. The researchers are able to collect real-time data and evaluate it for predicting the future. It is also possible to mitigate past mistakes to progress in future by expecting better activities. It can also decrease the cost of the researchers and investigators as they predict the future activities and accordingly plan for achieving a sustainable outcome. The main benefit of forecasting data analysis is that it provides the business with variable information that the organisations can use to make decisions about the future of the brand. In the recent era of globalisation, businesses in diverse fields are utilising these forecasting models to gather vast market data and conduct market research o understand the recent trend and predict the future trend efficiently. This further provides a scope for the organisational leaders to make effective decisions and reallocate the resources to maximise the organisational goal.
Forecasting analysis is also advantageous to reduce the risks and make better financial planning. In the banking and insurance industry, the forecasting models are widely utilised to predict future activities in the financial industries. This will help the investigators to invest in risk-free resources and increase the asset value in near future. Hence, for managing successful financial decisions, the forecasting method is crucial which helps in increasing the profit margin, and cash flow, improving the resource allocation and creating more opportunities for further sustainable growth. Hence, it can be ensured that, through forecasting, it is possible to enhance economic growth and social; development in long run by making a rational choice decision.
