International Symposium on Forecasting (ISF)
Boulder, Colorado, USA
June 17 – 20, 2018
Early bird deadline: March 31, 2018
The International Symposium on Forecasting (ISF) draws the world’s top forecasters and researchers to learn about and discuss cutting-edge developments in forecasting. Sponsored annually by the International Institute of Forecasters (IIF), the 38th conference in Boulder, CO features a “Forecasting in Practice” track offering professional development to business forecasting practitioners.
In addition, Eric Stellwagen will present the workshop Business Forecasting: Techniques, Applications and Best Practices offering practitioners a deep dive into proven forecasting methods and demonstrating practical solutions that can be applied in their own organizations.
Visit the ISF Website for details on the full conference agenda and to take advantage of the early bird discount for registering by March 31, 2018.
Sales and demand forecasters have a variety of techniques at their disposal to predict the future. While most analysts will examine historical sales or other kinds of data as a guide, many forecasters rely heavily on judgment. 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, particularly when you are producing large quantities of forecasts on a rolling basis.
This article covers two common approaches for forecasting sales using statistical methods: time series models and regression models. The advantage of these approaches is that they offer a lot of “bang for your buck”. On one hand, they are robust methods that can detect and extrapolate on patterns in your data like seasonality, sales cycles, trends, responses to promotions, and so on. On the other hand, they are easily accessible approaches, especially with the right tools.
Join us in Orlando, Florida for a comprehensive three-day educational seminar Business Forecasting: Techniques, Applications and Best Practices on March 7-9, 2018.
If your organization is introducing new products in 2018, you’ll want to join our free educational Webinar Effective Methods for Forecasting New Products on January 25, 2018 at 1:30 pm EST (UTC -5:00). We know that forecasting new product sales is a challenge, but you can hit the ground running after learning about the pragmatic approaches reviewed in this live one-hour Webinar.
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 & Tricks details how to set time fences in Forecast Pro TRAC to prevent new statistical forecasts from being generated and/or new forecast overrides from being applied within the fenced horizon.
Users can take advantage of the enhancements available in Forecast Pro TRAC Version 4.1. This new release includes further improvements to the grid view, and substantial improvements to the “hierarchy shuffling” functionality.
Forecast Pro TRAC allows you to view and work with your forecasts in different units of measure. When you set up your data for Forecast Pro TRAC, the units of measure for the input data are referred to as the default units. Unlike Forecast Pro Unlimited, which limits you to a single unit of measure, Forecast Pro TRAC lets you change the units you are working in.
Changing units isn’t just designed for reporting purposes. In Forecast Pro TRAC, as you change the working units you can continue to make adjustments and overrides to the forecast. As a result, the members of your team can view and work with the forecast in the units of measure that matches the way that they think about the business.
ABC classification, also known as Pareto analysis, is a useful method for classifying forecast items based on their relative importance to the organization. Many companies adopt different procedures for creating, reviewing and monitoring forecasts based upon an item’s classification. This enables the forecasting team to focus its efforts on those items which have the greatest impact to the organization.
Items are typically categorized as follows:
- A: important high volume items
- B: medium volume items
- C: slow moving items
In the field of business forecasting, is there a disconnect between practitioners and academia? You are invited to share your opinion in a study being conducted at Central Michigan University
Users can now enjoy the variety of improvements available in Forecast Pro Version 9. The features found in the new release–including an enhanced user interface, methodology improvements and the new Custom Component Model–make the software more powerful and easier to use.
Here’s an overview of what’s new in Forecast Pro Unlimited v9: