The Use Of Qualitative And Quantitative Forecasting Techniques in Short, Medium, And Long Range Forecasting

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The forecasting is an estimate of what will happen in the future. The fact may be product demand, rainfall at a specific location, the country's population or technological development. In enterprises, forecasts can be broken down into technical provisions, economic forecasts and demand forecasts. The combination of hardware and software is called "technical prediction". This means some features, such as technical performance levels and the speed of technological development. Government agencies and other organizations involved in data collection and assessment of the general business environment as "economic forecasts".

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"Demand Forecasting" gives the expected level of demand for goods or services.

Quantitative and qualitative are two general forecasting methods. Quantitative forecasts typically use historical data, such as past sales and revenue data, production and financial reports, and site traffic statistics. See seasonal sales data, for example, to help you plan monthly or quarterly data for next year. Qualitative forecasting techniques come from the experience and instinct of the seasonal business expert.

Case study

The case study is based on the reality of "Sr.

The designer's global designer has encountered problems with forecasting technology. The emphasis is on the footwear division of the company. Both quantitative and qualitative methods are combined by the case study.

Over the past two decades, consumers in the garment industry have become more fashionable and lifestyle-related. In order to meet the ever-changing customer needs, the company has been relieved of mass production. Although they used to produce standard styles due to factory-defined constraints, they are looking for ways to continually offer unique and refreshing products.

Forecasting methods and techniques

Companies in the fashion industry are working hard to handle demand for many years, which has led to the development of specific forecasting methods and techniques. Demand forecasting requires the choice of appropriate mathematical or statistical techniques to create periodic forecasts. Choosing the right technology for a particular situation can be confusing. However, although there are hundreds of mature forecasting techniques and techniques, managers need to understand only some basic techniques.

1.Qualitative forecasting technique

Qualitative techniques are time-consuming and highly dependent on expertise, so they are costly. Qualitative techniques are ideal when only a few historical data are available, so management decisions are required.

2.Time series forecasting technique

Time series technology is a statistical method used when historical sales data contains relatively clear and stable relationships and trends are available. "Time series techniques are quantitative - that is, they use values recorded at fixed time intervals (sales history) to predict future values.

3.Causal technique

Causality, often referred to as regression predictions, is a quantitative method used to study the causal relationship between two or more variables. Often, the purpose of the prognostic is to discover the cause and effect of a variable against another, such as price changes or the impact of advertising on product demand.

Appropriate forecasting using both quantitative and qualitative methods

The forecast attempts to use a quantitative or qualitative approach or a combination of both to predict the future. The time series approach uses historical sales data to track and predict trends and seasonal patterns. Causal techniques take into account external factors but are not able to determine trends or seasonality. Causal techniques require more data than time series methods, so they cannot be acquired quickly. Qualitative methods have a big advantage over time series and causal methods because they can take into account changes in business environments without historical data. In order to achieve a more accurate forecasting of sales, forecasting officers can use time series techniques to determine initial forecasts, causality techniques provide a wider picture of environmental factors, and final quality techniques can be used to adjust quantitative forecasts.

Qualitative forecasting techniques may be considered the best way to predict such demand if they are combined with appropriate and available historical data because the combination of forecasting methods tends to outperform most individual forecasts. However, the problem with quality forecasting techniques is unreliable, which is the error in all crisis forecasts and will only reduce the accuracy of forecasts in the long run.

Because of the obvious problems with other major methods, qualitative crisis forecasting can be considered as a basic forecasting method for the company. Therefore, while it has been recognized that unreliability is unavoidable to some extent, it is important to use a qualitative method in a way that minimizes credibility.