About Erik Subatis

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So far Erik Subatis has created 27 blog entries.

Understanding Pareto (ABC) Analysis

2020-10-22T10:08:07+00:00June 15th, 2020|Categories: 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

2020-10-22T10:10:11+00:00May 13th, 2020|Categories: 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

2020-10-22T10:11:18+00:00April 2nd, 2020|Categories: 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 [...]

The Anatomy of a Forecast

2020-08-25T12:19:53+00:00March 23rd, 2020|Categories: Forecasting Education|Tags: |

When you use a statistical model to generate a 12-month forecast, you get more than just twelve numbers. You also get a great deal of information about how the forecast was generated, the model’s fit to the historic data and different measures of expected forecast accuracy. In this article, we dissect and catalogue the different [...]

Utilizing Time Fences in Forecast Pro TRAC

2016-11-17T14:48:28+00:00November 17th, 2016|Categories: Forecasting Education, Using Forecast Pro|Tags: , , |

Sometimes making changes to near-term forecasts can be an expensive proposition. Last minute changes often significantly increase production and procurement costs, decrease profitability, and negatively impact other aspects of the business. To protect against these effects, many companies establish “time fences” to prohibit changes to the forecast over a defined short-term horizon. This edition of Tips & [...]

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

2015-08-17T12:27:18+00:00August 17th, 2015|Categories: 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 [...]

Working with Alternative Baseline Forecasts

2015-05-11T12:39:06+00:00May 11th, 2015|Categories: Forecasting Education, Using Forecast Pro|Tags: , , , |

In Forecast Pro TRAC, you have the ability to import externally-generated forecasts into the override grid view. We can choose which of these forecasts we want to use as our “baseline” forecast. This can be done either on an item-by-item basis or for groups of items. If we have specified a baseline forecast that is [...]

Using Seasonal Simplification to Improve Forecasts

2014-11-10T12:16:40+00:00November 10th, 2014|Categories: 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. […]