"Forecasting is the process of making predictions based on past and present data."
The process of predicting future demand for products or services based on historical data and other relevant factors, such as market trends and seasonality.
Time series analysis: A method of analyzing past data to identify patterns and trends over time.
Statistical forecasting methods: Techniques used to analyze past data and make predictions about future events.
Judgmental forecasting: A subjective approach to forecasting that relies on the intuition and experience of experts in the field.
Forecast accuracy: The measure of how well a forecast predicts the actual outcome.
Trend analysis: A method of analyzing patterns in data to determine if there is a linear or non-linear trend over time.
Seasonality: A pattern in data that occurs regularly at a specific time of year or season.
Demand forecasting: The process of predicting future demand for a product or service.
Judgmental adjustments: The process of modifying a statistical forecast based on expert judgment or additional information.
Bias: A systematic error in a forecast that leads to consistently overestimating or underestimating future events.
Forecasting intervals: A range of values that determines the uncertainty of a forecast.
Regression analysis: A statistical method for analyzing the relationship between two or more variables.
ARIMA models: A type of time series model that takes into account not only trend and seasonality, but also autoregressive and moving average components.
Exponential smoothing: A method for smoothing out the noise in time series data by assigning exponentially decreasing weights to historical observations.
Forecasting software: Tools that automate various forecast techniques and help with data visualization and analysis.
Big data forecasting: Methods for predicting future events based on large volumes of diverse data sources.
Quantitative forecasting: This type of forecasting involves the use of statistical methods and historical data to predict future trends.
Qualitative forecasting: This type of forecasting involves the use of expert opinions and subjective judgment to forecast future events.
Time series forecasting: This type of forecasting involves analyzing past data and determining patterns that can be extrapolated into the future to make predictions.
Causal forecasting: This type of forecasting involves identifying the causal relationships between different variables and predicting future trends based on those relationships.
Judgmental forecasting: This type of forecasting involves the use of expert opinions and assumptions to predict future events.
Scenario forecasting: This type of forecasting involves the creation of various scenarios, each representing a possible future, and analyzing the potential outcomes of each scenario.
Econometric forecasting: This type of forecasting involves the use of economic models and theories to predict future events.
Leading indicators forecasting: This type of forecasting involves the use of economic indicators that are believed to predict future economic activity.
Technological forecasting: This type of forecasting involves the prediction of future technological developments and their impact on business operations.
Environmental forecasting: This type of forecasting involves the prediction of future environmental conditions that may impact business operations.
"...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."