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Forecasting product demand by 10 weeks in advance with Machine Learning

A brief introduction of the Linas Matkasse Success Case:

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Understand how the largest meal kit supplier in the Nordics managed to get accurate estimations about their food demand by 10 weeks in advance with a marginal error rate of 2,5%.

With this powerful forecasting solution they reduced food waste and lowered operational costs.

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linas matkasse case study

Linas Matkasse

Linas Matkasse is the largest meal kit supplier in the Nordics. They work every day on composing menus and inspiring meal kits to serve their weekly +30k customers. They spend around 40 million euros on food every year, so getting the wrong quantities has a huge impact on their business.

The challenge

Create the best analytics architecture and most powerful Machine Learning forecasting model to predict orders with the lowest margin of error (<10%). This way they would also be able to:

Reduce food waste
Lower operational costs

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About Syone

From Portugal to the world, Syone works with leading companies by implementing mission-critical projects and helping organisations to increase agility with Digital Transformation and Open Source technologies.

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