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About Aidan

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So far Aidan has created 20 blog entries.

How do I use Statistical Models to Forecast Sales?

2021-08-20T11:14:33-04:00Categories: Forecasting Education|Tags: , , , , , |

There’s no question that judgment can (and probably should!) play a significant role in arriving at your final, consensus forecast–but statistical forecasting can offer a level of automation and insight that can substantially improve your forecast accuracy.

Understanding Pareto (ABC) Analysis

2021-08-19T13:55:34-04:00Categories: Forecasting Education|Tags: , , , |

In the 19th century Dr. Wilfredo Pareto, an Italian economist, gave birth to the “80/20 rule” when he observed that 80% of the country’s wealth was held by 20% of the population. Today, many organizations find that the 80/20 rule (or a similar ratio) applies to their products—80% of their revenue comes from 20% of [...]

Box-Jenkins Forecasting

2021-08-19T13:54:23-04:00Categories: Forecasting Education|Tags: , , |

Box-Jenkins (ARIMA) is an important forecasting method that can yield highly accurate forecasts for certain types of data. In this installment of Forecasting 101 we’ll examine the pros and cons of Box-Jenkins modeling, provide a conceptual overview of how the technique works and discuss how best to apply it to business data. […]

How to Forecast Data Containing Outliers

2021-08-23T14:16:17-04:00Categories: Forecasting Education|Tags: , |

An outlier is a data point that falls outside of the expected range of the data (i.e., it is an unusually large or small data point). If you ignore outliers in your data, there is a danger that they can have a significant adverse impact on your forecasts. This article surveys three different approaches to [...]

What are Time Series Methods and When Should I Use Them?

2021-08-26T14:03:46-04:00Categories: Forecasting Education|Tags: |

Time series methods are forecasting techniques that base the forecast solely on the demand history of the item you are forecasting. They work by capturing patterns in the historical data and extrapolating those patterns into the future. Time series methods are appropriate when you can assume a reasonable amount of continuity between the past and [...]

Using Seasonal Simplification to Improve Forecasts

2023-08-24T18:05:07-04:00Categories: Forecasting Education|Tags: , |

Forecast Pro includes a forecasting approach called seasonal simplification. Seasonal simplification is an extension of exponential smoothing which “simplifies” the modeling of the seasonal pattern by reducing the number of indices used. In many cases the seasonally simplified model can substantially improve forecast accuracy. […]

Creating Accurate Forecasts When Your Demand History Includes Outliers

2021-08-23T17:34:39-04:00Categories: Forecasting Education|Tags: , , , |

Preparing forecasts using data that contain one or more unusually large or small demand periods can be challenging. Depending on your forecasting approach, these “outliers” can have a significant impact on your forecasts. This article surveys three different approaches to forecasting data containing unusual demand periods, discusses the pros and cons of each and recommends [...]

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