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Databricks delivers on Gousto growth plans with AI and analytics solutions

Databricks delivers on Gousto growth plans with AI and analytics solutions

Case StudiesEuropeRetailSoftwareSuccess StoriesTop Stories

Gousto, a leading UK-based meal kit retailer, has leveraged a Databricks data management and AI solution, enabling the company to become more customer-centric and agile in response to the pandemic; drive operational improvements and deliver on its strategic goal of maiden profitability in 2020.

Gousto has utilised Databricks’ data and AI technology to deliver its ambitious 2022 growth plans as the data-driven recipe box prepares to triple capacity, creating over 1,000 new jobs in the process.

While having seen significant growth over recent years, Gousto accelerated its expansion plans in light of increased demand and the structural shift to online grocery, sparked by the lockdown. The partnership with Databricks is providing the foundation for this future growth.

Gousto has developed proprietary algorithms that optimise the speed of box packing, maximising pick accuracy and minimising food waste. The algorithms run across more than 50 weekly recipes, from Joe Wicks’ Lean in 15 and family classics to an expanding range of meat-free plant-based options. 

Gousto has established a market-leading position in the UK by utilising data and technology to offer choice, convenience and value. As a result, the company expects to report a significant maiden profit in 2020. Through its work with Databricks, Gousto will enhance its industry-leading technology platform as they prepare to roll out next-day delivery and meal customisation. 

Shaun Pearce, Chief Technology Officer, Gousto, said: “We identified Databricks as the standard in building real-time data platforms. The platform brings data engineering, data analytics and data science closer together, with a huge potential to make our journey to data strategy more efficient and collaborative.

“We have reduced the time it takes to develop new ideas from days to minutes and increased the availability and accuracy of our data. This is essential as we continue to grow at pace, expanding our customer fulfilment capacity from one factory to four in the next year.” 

Gousto moved from daily batch updates to near-real-time streaming data, utilising AutoLoader and Delta Lake. The robust and scalable Data Platform provided by Databricks enables Gousto to respond to an ever-growing demand by providing real time insight into performance on the factory picking lines, improving the quality and efficiency of the picking.

David Wyatt, SVP EMEA, Databricks, added: “We are on a mission to help organisations solve the toughest problems. Gousto were already at an advanced stage with their analytics and they had a clear vision of the path ahead.

“Together we have been able to build a cost-efficient data platform that can deliver their goals today and also set them up for the next phase of their growth, all fuelled by data-driven decisions.”

We asked Gousto’s CTO, Shaun Pearce, to tell us more about why the company chose to work with Databricks….

When did you implement the Databricks platform and why did you decide to work with this vendor?

We implemented the Databricks platform earlier this year after having identified them as the standard in building real-time data platforms.

What challenges were you looking to address ahead of selecting this solution?

Prior to working with Databricks, we were very batch focused with our data insights. While the business had been growing rapidly over the last few years, our growth accelerated dramatically this year as a result of changes in consumer behaviour. It became more apparent that we needed a tool to enable real-time data insights to provide the foundations of this growth.

How are you using Databricks technology currently – what phase of the project are you at?

We’re utilising Databricks’ AutoLoader and Delta Lake for near real-time analytics dashboarding on the performance of our pick lines in our fulfilment centre.

The fulfilment centre is built on our own algorithms that optimise the speed of box packing, maximising pick accuracy and minimising food waste. The Databricks platform allows us to identify any bottlenecks in the fulfilment process, which improves the quality and efficiency of the picking. This is crucial as we expand our network of fulfilment centres from one to four sites in the next couple of years.

How do your staff find the technology?

The tech allows the team to work more efficiently, making data-driven decisions much quicker. It takes away the heavy lifting when it comes to the business’s data strategy and the team value and trusts it.

What are the key benefits of this platform?

The ultimate goal of using the platform to improving efficiencies on the picking line and making quicker data-driven decisions comes down to providing the best possible experience for our customers. 

Access to real-time performance data helps us proactively resolve potential customer related issues such as a missing item before it gets to our customer’s door.

Most importantly, enhanced efficiencies on the picking lines mean we can continue to push our market-leading customer proposition of the most choice, quickest delivery lead times at the best value for our customers.

How far would you say this solution has enabled your organisation to scale?

We’re in the process of becoming a multi-site network from having one fulfilment centre to four in the next couple of years. Databricks is already helping us make key decisions on how our future factories look and is an essential in helping us make data-driven decisions for the longer term as we scale.

What advice would you offer other organisations looking to implement similar technology?

A platform like this is an invaluable part of an effective data strategy. We have reduced the time it takes to develop new ideas from days to minutes and increased the availability and accuracy of our data. For any tech business scaling at pace like we are, you will feel the benefits of a platform providing real-time data insights.

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