A short introduction to the practice and pitfalls of short term forecasting – and how to increase its value to the business
This is a guidebook about short term Operational Forecasting – the sort that is done to determine how much product you need to source or how many people you need to draft in to meet customer demand.
This is a guidebook about short term Operational Forecasting – the sort that is done to determine how much product you need to source or how many people you need to draft in to meet customer demand. 
It is organized under 5 headings:1.The purpose of operational forecasting2.Understanding demand3.Forecasting methods4.Understanding forecast performance5.Managing forecast performance.
The first two sections and part of section three are essential reading for anyone involved in or responsible for operational forecasting. The rest of the book is most helpful for practitioners.
The aim is to produce something that provides a useful introduction to operational forecasting for both practitioners and their bosses by filling in the gap that lies between a naïve common sense understanding of short term forecasting and the complex technicalities of mathematical forecasting techniques. 
The authors background as a self-taught business orientated forecasting nerd with limited mathematical expertise qualifies who tell it the way it is makes him well qualified to fill this gap. 
The book has been designed to be simple but not simplistic, using short and to the point learning points supported by clear graphics. It is technically sound but also highly practical. 
The hope is that it will help create a common language to help people talk intelligently about forecasting and help stop people doing dumb stuff – which is where most of the potential for improvement lies. It will also help people design good forecast processes and informed software purchasing decisions. In doing so it will help people realize that forecasting is important and that investing in people as well as software will generate enormous benefits for many businesses.