For demand planners, S&OP managers, supply chain leaders, and data scientists. Demand Forecasting Best Practices is a unique step-by-step guide, demonstrating forecasting tools, metrics, and models alongside stakeholder management techniques that work in a live business environment.

You will learn how to:

Lead a demand planning team to improve forecasting quality while reducing workload
Properly define the objectives, granularity, and horizon of your demand planning process
Use smart, value-weighted KPIs to track accuracy and bias
Spot areas of your process where there is room for improvement
Help planners and stakeholders (sales, marketing, finances) add value to your process
Identify what kind of data you should be collecting, and how
Utilise different types of statistical and machine learning models

Follow author Nicolas Vandeput's original five-step framework for demand planning excellence and learn how to tailor it to your own company's needs. You will learn how to optimise demand planning for a more effective supply chain and will soon be delivering accurate predictions that drive major business value.

About the technology

Demand forecasting is vital for the success of any product supply chain. It allows companies to make better decisions about what resources to acquire, what products to produce, and where and how to distribute them. As an effective demand forecaster, you can help your organisation avoid overproduction, reduce waste, and optimise inventory levels for a real competitive advantage.

�ber die Autorin bzw. den Autor

Nicolas Vandeput is a supply chain data scientist specialising in demand forecasting and inventory optimisation. He founded his consultancy company SupChains in 2016, delivering models and training courses worldwide. He co-founded SKU Science ― a demand forecasting platform ― in 2018. Passionate about education, Nicolas is an avid learner enjoying teaching at universities. He currently teaches forecasting and inventory optimisation to Master's students in Centralesup�lec, Paris, France.

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