#forecastingmethods #forecasting #qualitative #quantitative #timeseriesanalysis
In this video, I discuss forecasting methods – both qualitative and quantitative. We're going to be looking at how to use qualitative methods such as the build-up method, survey method, test market, and simple and weighted moving averages to make predictions. We'll also be discussing the pros and cons of each method, and which one is best for the specific task at hand.
Qualitative and quantitative forecasting methods are two broad categories of techniques used to predict future demand or other variables in different contexts.
Qualitative forecasting methods rely on expert opinions and subjective judgments to make forecasts. These methods are used when there is limited historical data available or when there are qualitative factors that need to be considered. Some examples of qualitative forecasting methods include:
Market Research: This involves gathering information about consumer preferences, attitudes, and behaviors to make forecasts.
Delphi Method: This involves soliciting the opinions of a group of experts, who provide anonymous forecasts that are then compiled and analyzed.
Panel Consensus: This involves soliciting the opinions of a group of experts, who then meet to discuss and refine their forecasts.
Scenario Planning: This involves developing alternative scenarios that reflect different possible futures, and then using these scenarios to make forecasts.
Quantitative forecasting methods, on the other hand, rely on historical data and mathematical models to make forecasts. These methods are used when there is a strong relationship between past and future values. Some examples of quantitative forecasting methods include:
Time Series Analysis: This involves analyzing historical data to identify patterns and trends in the data, and then using these patterns to make forecasts.
Moving Averages: This involves calculating the average value of a time series over a specific period of time and using this average to make a forecast.
Exponential Smoothing: This is a time series forecasting method that assigns more weight to recent data points than to older data points.
Regression Analysis: This involves using a mathematical model to identify the relationship between one or more independent variables and a dependent variable.
The choice of forecasting method will depend on the specific context and the available data. Often, a combination of qualitative and quantitative forecasting methods is used to make more accurate forecasts.
This video is a great introduction to forecasting methods and is especially useful if you're new to the field. Whether you're a business owner, investor, or student, this video is a must-watch!
00:00 Intro
01:26 – Qualitative Forecasting Methods
05:38 – Quantitative Forecasting Methods
09:20 – Simple Moving Average Example in Excel
11:40 – Weighted Moving Average Example in Excel
18:00 – Key Takeaways
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