Need to predict the future?
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In about one hour you can learn to:
Most managers involved in forecasting are missing one or more skills in basic forecasting. We boil it down to five steps, and show you how to master each one.
This course is all about doing. You look over our shoulders and view the computer screen as we forecast sales for multiple products and industries.
Every forecaster should be able to do exponential smoothing. It is by far the most popular forecasting approach among experienced forecasters.
One of the biggest leaps you can make as a forecaster is in accuracy measurement. We show you the best way, and we demonstrate it throughout the course.
Forecasting software works, so you don't need to understand detailed forecasting formulas. Instead, we focus on how to use forecasting software wisely.
We are confident that mastery of the basic concepts provided in this course will significantly increase your forecast accuracy. The result: fewer stock-outs, higher sales, and lower inventory costs.
Included in this course:
We tap into the very latest thinking on forecasting. But rather than bore you with our technical mastery of the subject, we focus on simplicity and practicality. Only the essential ingredients of forecasting excellence are presented. And we do so with passion.
We hope you enjoy the course. Good luck and good forecasting!
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|Section 1: Lectures|
In the Introduction I briefly describe myself and the course. I am the author of numerous books and articles. My most recent book is Sales Forecasting: A Practical Guide (available at Amazon). This course is designed for busy managers who need to learn the fundamentals of sales forecasting.
In the Background chapter I talk about how sales forecasting differs from other types of forecasting. Then I show how the learning curve applies to sales forecasting and talk about how this course was designed to avoid complex formulas. I close the chapter by discussing the forecasting attitude and give you an exercise to stretch your thinking.
In this chapter I discuss the first and second most common mistakes made by rookie forecasters. Then I describe how to set up a test using historical sales data, and demonstrate the process with an example.
The third step on the forecasting learning curve is to avoid linear extensions. In this chapter I review the linear extension, with the intention of dissuading you from using it. I describe MASE, or the best way to measure forecast error. These concepts are demonstrated using the online banking example. Then I conclude with a discussion of why the linear extension is such a poor choice for sales forecasting.
This chapter describes the factors that make exponential smoothing accurate. Then we demonstrate its use with the online banking company.
In this chapter I describe how to detect potential data distortions, the data cleaning process, and how to check whether the effort was useful from a forecasting perspective.
In this chapter, I describe why multiple sales forecasts are common, and provide some simple techniques for managing them. Once this groundwork is laid, I describe the process and guidelines for creating a future forecast and assessing its accuracy.
The last chapter summarizes the major points in a process I call Five-Step Forecasting: Plot, Divide, Test, Assess, and Apply.It is possible to make the process more complex, but I can’t recommend a simpler one. These steps form the minimum requirements of a sound sales forecasting process.
Mark Blessington is a highly respected sales and marketing consultant. He has worked for many of the world's largest corporations (e.g., Pfizer, Wells Fargo, GE, AT&T). He has published two books (Sales Quotas: An Analytical Approach to Quota Setting; Sales and Marketing Reengineering) and over 20 articles on sales and marketing topics. He has been widely quoted in the Wall Street Journal and the New York Times. Mark's particular areas of expertise include: sales compensation, sales forecasting, and skills training in sales and marketing.
Karl is a new breed of consultant, speaker, and writer, combining fascinating “real life” sales and marketing stories with powerful principles and best practices. Karl’s work is well published and includes The Customer Learning Curve, a book he co-authored. Karl’s astuteness and humor quickly engage students in his eLearning courses. He earned his Doctorate in Business Administration at Georgia State University, where his dissertation topic was “Optimizing Investment in Different Levels of Key Account Relationships.”
Kevin O'Connell is a sales and marketing consultant with 25 years experience. His client work involves developing and implementing sales effectiveness strategies to improve revenue growth, profitability, and alignment. Clients cross multiple industries (pharmaceutical/bio-tech, digital media, insurance and financial services, etc.) enabling Kevin to bring a broad perspective to address sales and marketing challenges. Kevin's expertise includes sales compensation; sales forecasting and quota setting; and sales, marketing, business strategy alignment.