The differences between qualitative and quantitative forecasting techniques
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Forecasting attempts to predict the future. There are several methods available for forecasting and they all fall into two general categories. These are called “quantitative” and “qualitative.” The choice of technique for a forecast depends on the purpose of the forecast.
Different methods would be used to predict demand for a product, and thus plan production capacity, to those that would be used for setting policies of a political party. Whatever method you use, you will need to base the forecast on source data.
Quantitative forecasting deals with quantities. It is an empirical field that focus on numbers. The quantitative forecast will have a numerical output and will be based on statistical source data.
Qualitative techniques examine opinion. They are harder to formalise into a methodology for forecasting. Businesses use qualitative research to test the perceived value of their products or to ensure that their services are delivered in an efficient manner.
The main differences between quantitative and qualitative techniques lie in how data is gathered. For example, if a hospital administrator wants to measure the performance of a department, the quantitative approach would involve checking admissions records to establish a pattern of throughput. The qualitative method would ask patients leaving the hospital whether they were satisfied with their treatment. Although qualitative methods deal with opinion, that opinion is usually expressed in terms of numbers. For example, the results of the hospital satisfaction survey would be a report showing the number of people who were satisfied and the number of people who were dissatisfied.
- The main differences between quantitative and qualitative techniques lie in how data is gathered.
- The qualitative method would ask patients leaving the hospital whether they were satisfied with their treatment.
Quantitative forecasting looks for patterns in historical data and derives a formula from that. This is called trend analysis. For example, if you sold 2,000 widgets a year for the last three years, the chances are that you will sell 2,000 widgets this year as well. Qualitative forecasting scans the environment for confounding factors. In this method, the word “trend” does not relate to a numeric progression. Instead, experts are asked to give their opinion of where the market is headed. Product testing with groups of consumers is another qualitative method. These ask members of the public to discuss how they feel about a product and whether they would buy it if certain aspects, like price and pack size, changed.
- Quantitative forecasting looks for patterns in historical data and derives a formula from that.
- Instead, experts are asked to give their opinion of where the market is headed.
Quantitative forecasting is easier to carry out and easier to justify. The results make sense because the forecast is supported by evident data. Qualitative methods are harder to plan because their results do not have the support of hard data. Qualitative methods are sometimes the only methods available. For example, when launching a new product a company has no historical data for inputs to the forecast. Organisations that work towards a goal of societal change, such as animal rights activists, are not interested in statistical throughput, but want to predict changes in public opinion and detect methods to influence it.
- Quantitative forecasting is easier to carry out and easier to justify.
- The results make sense because the forecast is supported by evident data.
Stephen Byron Cooper began writing professionally in 2010. He holds a Bachelor of Science in computing from the University of Plymouth and a Master of Science in manufacturing systems from Kingston University. A career as a programmer gives him experience in technology. Cooper also has experience in hospitality management with knowledge in tourism.