"Forecasting is the process of making predictions based on past and present data."
The process of making predictions about future events based on past and present data, using statistical techniques and models.
Time Series Analysis: The study of data over time, including trend, seasonality, and cyclicality.
Regression Analysis: The use of mathematical models to predict future outcomes based on past data.
Econometric Forecasting: The use of economic data and models to predict future trends.
Judgmental Forecasting: The use of expert opinions and subjective assessments to forecast future outcomes.
Artificial Intelligence Forecasting: The use of machine learning algorithms to create predictions based on historical data.
Qualitative Forecasting: The use of non-numerical data to identify patterns and trends.
Marketing Forecasting: The use of market data to identify potential sales and consumer preferences.
Financial Forecasting: The use of financial data to predict future financial performance.
Operations Forecasting: The use of operational data to predict future demand and production levels.
Statistical Modeling: The use of statistical methods to analyze and interpret data to make informed predictions.
Time Series Forecasting: This is a popular technique that predicts future values based on historical data patterns. It helps to analyze trends, seasonality, and cyclic patterns.
Data Mining: It is a process of discovering hidden pattern in the data. This technique uses statistical and machine learning models to generate forecast models.
Neural Network Forecasting: This technique is used to identify nonlinear patterns between variables. It is based on the structure and function of the human brain, where the neural network is composed of interconnected artificial neurons.
Ensemble Forecasting: This technique combines multiple forecast models to generate more accurate predictions. It involves the use of multiple models and averaging their outputs.
Regression Analysis: This technique is used to estimate the relationship between one variable (dependent) and one or more independent variables. It helps to determine the strength and direction of the association between the variables.
Scenario Planning: This technique involves creating multiple scenarios to forecast future outcomes. It is useful for long-term strategic planning and identifying potential risks and opportunities.
Judgmental Forecasting: This technique relies on the subjective opinions of experts and stakeholders to make predictions. It is useful when there is limited historical data available.
Simulation Modeling: This technique involves using computer models to forecast future outcomes. It helps to analyze complex systems and identify potential risks and benefits.
Forecasting by Analogy: This technique is used when there is no historical data available for a particular product or service, so the forecast is based on the demand patterns of similar products or services.
Forecasting with Econometric Models: This technique uses economic variables such as inflation, interest rates, and GDP to forecast future trends. It helps to identify the impact of macroeconomic factors on the business.
Bayesian Forecasting: This technique uses Bayesian statistics to make predictions about future events. It helps to incorporate subjective beliefs and opinions into forecasts.
Trend Extrapolation: This technique is used to forecast future trends based on historical data. It assumes that previous trends will continue into the future.
Dynamic Regression: This technique combines time-series data with external variables to create a forecast model. It is useful when there is a potential relationship between the dependent variable and the external variables.
Seasonal Adjustments: This technique is used to eliminate seasonal variations in time-series data. It helps to create a more accurate forecast model by removing the effects of seasonal patterns.
"...compare it against the actual results creating a variance actual analysis."
"Prediction is a similar but more general term. Forecasting might refer to specific formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgmental methods or the process of prediction and resolution itself."
"...in hydrology, the terms 'forecast' and 'forecasting' are sometimes reserved for estimates of values at certain specific future times, while the term 'prediction' is used for more general estimates."
"Risk and uncertainty are central to forecasting and prediction."
"...it is generally considered a good practice to indicate the degree of uncertainty attaching to forecasts."
"The data must be up to date in order for the forecast to be as accurate as possible."
"In some cases, the data used to predict the variable of interest is itself forecast."
"A forecast is not to be confused with a Budget, budgets are more specific, fixed-term financial plans...while forecasts provide estimates of future financial performance, allowing for flexibility and adaptability to changing circumstances."
"...both tools are valuable in financial planning and decision-making, but they serve different functions."