Forecasting orders with Azure Databricks

Building the Future 2020 Teaser


Get the full Case Study:
PDF & Video


Watch and read this Predictive Analytics Case

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%, using Machine Learning, Azure Databricks and a new Analytics Model.

With this powerful forecasting solution they reduced food waste, lowered operational costs and gained more negotiation power. 😃

machine learning talk linas matkasse syone
mockup case study

The Linas Matkasse Group

Linas Matkasse Group 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
  • Gain more negotiation power
Video Testimonial Alex Edited New Song_COMPRESS

"We now serve 30.000 customers a week. Handling that operational scale without investment into IT and technology is not possible. Syone has been a huge part of our success in being able to digitalize our value chain."

Alexander Aagreen, CTO @ Linas Matkasse Group


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.