What forecasting books would you recommend?
That’s a question I’ve been asked a few times in recent weeks. Here are two books that will provide you plenty of insight and expertise to help your forecasting endeavours become more useful and accurate…
1️⃣ The first is Forecasting: Principles and Practice (3rd edition) by Rob Hyndman and George Athanasopoulos. It covers an enormous range of forecasting models and guidance on how to implement them in practice. It even has a full chapter dedicated to graphs, and if you’ve met me you’ll know I’m obsessed with visualisations.
There are many code examples in the text using R. If you wish to forecast using Python, there are various websites where you can find the examples in Python. The book is published by Otexts, and it is available online for free at https://otexts.com/fpp3/
2️⃣ The second book is Data Science for Supply Chain Forecasting, by Nicolas Vandeput (the 2nd edition). It covers many of the forecasting models featured in the first book, though not in as much detail, yet it is done in an enormously readable and accessible way. This book has many examples in Python.
The real value of the Vandeput book is the many examples of using different Machine Learning algorithms to forecast. The Python code will give you the knowledge to test the ML methods on your own data. This book, like the first one, has many great tips about forecasting in practice. It is published by de Gruyter.
Despite containing chunks of R and Python code, both books still have much content that is useful for those who use Excel for forecasting. Both books are widely available at online bookstores.
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Philip Stubbs is Partner of Atlantic Insight, and has over 25 years’ experience of improving performance within operational areas within a wide range of industries.
