Sales and Statistical Forecasting Combined: Mixing Approaches for Improved Forecast Accuracy

Shaun, Snapp

ISBN 10: 1939731496 / ISBN 13: 9781939731494

Published by Scm Focus, 2014

About this Item

Seller Inventory # ABLIING23Mar2912160345946

Bibliographic Details

• Title: Sales and Statistical Forecasting Combined: Mixing Approaches for Improved Forecast Accuracy
• Publisher: Scm Focus
• Publication Date: 2014
• Language: English
• ISBN 10: 1939731496
• ISBN 13: 9781939731494
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Companies a number of problems with forecasting, and typically these problems are explained as separate spheres -- so problems with statistical forecasting, and then problems with sales forecasting. This is one of the few books that focuses on how to integrate sales with statistical forecasting and is the only book that focuses on all of its attention on this one topic

From the Back Cover

Instead of confusion regarding how to combine two of the most important types of forecasting, have your forecasting flourish from improved clarity on the topic.

In most companies the statistical and sales forecast are poorly integrated, and in fact most companies do not know how to effectively combine them. Strange questions are often asked such as "does the final forecast match the sales forecast?" without appropriate consideration to the accuracy of each input. Effectively combining statistical and sales forecasting requires determining which input to the forecast have the most "right" to be represented - which comes down to those that best improve forecast accuracy.

Statistical forecasts and sales forecasts come from different parts of the company, parts that have very different incentives. Forecast accuracy is not always on the top of the agenda for all parties involved in forecasting.

By reading this book you will:
· See the common misunderstandings that undermine being able to combine these different forecast types.

• Learn how to effectively measure the accuracy of the various inputs to the forecast.
• Learn how the concept of Forecast Value Add plays into the method of combining the two forecast types.
• Learn how to effectively run competitions between the best-fit statistical forecast, homegrown statistical models, the sales forecast, the consensus forecast, and how to find the winning approach per forecasted item.
• Learn how CRM supports (or does not support) the sales forecasting process.
• Learn the importance of the quality of statistical forecast in improving the creation and use of the sales forecast.
• Gain an understanding from both the business and the software perspective on how to combine statistical and sales forecasting.