Introduction
Forecasting is an important concept in any business especially in relation to the weather forecast as it prepares the organization on what to do and what to avoid. Forecasting is the process of predicting the near future on the events of occurrence of any prescribed incident and the impact to the business.
Forecasting assists in the decision making of the company for example, if a rainy season is anticipated and the business is specialized in cloth production, and then the business is in a better position to increase its sales of more woolen clothing (Hanke, 2005). The business also is able to plan for the expansion and increase in the number of employees in the manufacturing industries and service providers for example, the banking sector during summer people tend to increase their expenditure on luxurious items hence provide loans and could raise their banking rates. They keep the management on alert to face any coming challenge that affects the business, whether it is the weather forecasting on the financial situation of the business (Hanke, 2005).
The confidence of the management team gets a boost since the business plan and makes a sound decision that concerns the production process to meet the demand of the customer. Various techniques used in the forecasting analysis which some are concerned with subjective, measurable and qualitative data. Though such tool does not give accurate results, they give a rough estimate on the business forward prospects. Scenario writing, which gives different starting criteria that decision makers makes a probability of the outcome from the detailed scenarios listed and give strategy to curb or boost it (Anbarci, 2008). Time-series forecasting uses the data collected earlier to show the trends, for example cyclical, seasonal events especially concerning the food production retailers and producers. The technique is appropriate to be used by both the manufacturing industry and the service providers (Anbarci, 2008).
The technique is appropriate in the food industry is the time forecasting since it is focused on recording the trends that happen daily, weekly , yearly and even longer . The changing eating habits of the consumers can be noted and the management can predict the level of demand of certain kinds of food products, therefore, they adjust appropriately. The ideal model is to adopt the changes for example, during cold sessions people prefer taking foodstuff as stocks in the house to avoid getting outdoors and catch cold.
Reference
Hanke, J. E., & Reitsch, A. G. (2005). Business forecasting. Boston: Allyn and Bacon.
Anbarci, N., & Deakin University. (2008). Economic bias of weather forecasting: A spatial modeling approach. Melbourne, Vic.: School of Accounting, Economics and Finance, Deakin University.
