METRO: Stacking technology and business intelligence to simplify customers' lives

About METRO

Founded in Germany in 1964, METRO is a B2B wholesaler with revenues of €36.5 billion. The company's tech unit METRONOM has more than 2,000 employees in 8 locations.

Industries: Other
Location: Germany

About freiheit.com technologies GmbH

Based in Hamburg and Lisbon, freiheit.com technologies GmbH is one of Germany's Internet Pioneers, building large-scale digital business software platforms since 1999 for the who's who of German and European businesses and industries.

With an ecommerce platform and data lake project, German wholesale giant and food specialist METRO is using Google Cloud Platform to help its customers take more advantage of digital possibilities.

Google Cloud Results

  • Can reduce instability of its ecommerce platform by up to 80%
  • Scales capacity to match 45x increase in daily events in just three 3 during data lake ramp-up phase
  • Reduces infrastructure costs by 30% to 50%

Cuts infrastructure costs by more than 30%

METRO is one of the largest B2B wholesalers and food specialists in the world, supporting small and large businesses from the Atlantic coast of Portugal to the Pacific shores of Japan. But as for any company, of any size, METRO's success rests on the everyday decisions its customers make, not just on what they purchase, but how they want to buy.

"The industries we supply tend to have fixed ways of working," says Dr. Werner Rath, METRONOM's Unit Owner IT Operations. "Until recently, orders were still often made by telephone, or even fax. But when that started to change, we decided to fully embrace digitalization, with a close focus on our customers and their needs."

METRO has achieved that goal by rebuilding its digital applications and making company and customer data analysis much more available inside the business. By migrating its ecommerce platform to the cloud, the company can now deliver more stable, scalable services for customer and internal teams. At the same time, a new data lake provides a base from which to explore innovative analytics and machine learning.

"One of our unique selling points is that we give entrepreneurs as much support as we can to run their companies," says Sven Lipowski, Unit Owner Customer Solutions at METRONOM. "A new data lake built with Google Cloud Platform (GCP) managed services and integrated analytics and machine learning lets us further develop our products based on far more precise observation points and therefore serve our customers better."

"When we looked at the data lake project, I immediately recommended that we use managed services on GCP," says Werner. "Beyond the short-term advantages of saving time and resources, in the long run, Google Cloud AI and machine learning is always going to be ahead of the things we can build in-house."

"Scaling is about more than storage space, it's about having analytical power available on demand. Calculating item recommendations for customers requires a lot of CPU. With Cloud Dataproc we can create a cluster for the calculation, get the results, and then shut the cluster down. It's much more efficient."

Marko Schwob, Domain Owner Analytical Platform Engineering, METRONOM

Stable, simple ecommerce infrastructure that customers can rely on

To help METRO's ecommerce platform scale fast enough to match the pace of progress and improve stability, the company partnered with the software development company freiheit.com technologies to build a new, cloud-based microservices platform. "After trying several other solutions based on Docker, we became early adopters of Kubernetes when it was still in the early beta. We never looked back," says Stefan Richter, Founder and Head of Engineering at freiheit.com. METRO ran a benchmark between leading cloud providers. "We loved the way Compute Engine offered a generic approach to VMs," says Werner. "It's a simpler, more practical setup. Instead of a huge range of VM types that need upgrading every few months, we just match memory and CPU to workloads, and leave the VMs to get on with it. At the same time, the simple costing model means we can configure machines as we need them, without worrying about a major cost impact."

The team migrated its ecommerce platform to Compute Engine instances on Google Cloud Platform, using Virtual Private Cloud to create easy integrations with the company's backend systems. The results were dramatic. "With a lift-and-shift migration, we reduced infrastructure costs by 30 to 50 percent," says Werner. "Instead of 10 VMs rebooting every week, we rarely have to deal with one. Outages or periods of instability are down by up to 80 percent. And there have been no major incidents whatsoever since we made the migration."

With the new ecommerce infrastructure in place, attention turned to making data science accessible throughout the company via the new highly scalable data lake.

Bringing real, up-to-the-minute data into everyday decisions

So far, business intelligence at METRO was mainly based on a well-accepted, heavily used and user-friendly enterprise data warehouse reporting system. Now its BI landscape has a valuable enhancement, with a data lake of big data and advanced analytics solutions, which can store unlimited information for data science and advanced analytics. The cloud approach gives METRO the possibility to run complex models with high computing power. METRO wanted to democratize data analysis, collecting more semi-structured and detailed data from tills, customer databases, and marketing campaigns, and making it available inside the company.

"When we built the new ecommerce platform with METRO, our software engineers integrated the collection of behavioral data from day one. We stream the data into BigQuery and we are using Datalab infrastructure to create customer insights and develop machine learning models with Tensorflow."

Stefan Richter, Founder and Head of Engineering, freiheit.com

To make that happen, METRO built a data lake and analytics solution, mainly based on BigQuery and other Google BI services together with the Data-Science and Machine Learning Experts from freiheit.com technologies. "The main advantage of the managed services is that we can scale up and down," says Marko Schwob, Domain Owner Analytical Platform Engineering at METRONOM. "Scaling is about more than storage space, it's about having analytical power available on demand. Calculating item recommendations for customers requires a lot of CPU. With Cloud Dataproc, we can create a cluster for the calculation, get the results, and then shut the cluster down. It's much more efficient."

"When we built the new ecommerce platform with METRO, our software engineers integrated the collection of behavioral data from day one. We stream the data into BigQuery and we are using Datalab infrastructure to create customer insights and develop machine learning models with TensorFlow. We trained the Product Owners to use BigQuery SQL, so that they can explore the data themselves," adds Stefan Richter.

With one API for data ingestion, and another for integrating with other products, the solution enables real-time reporting on data streamed direct from stores and applications. By combining that data, METRO can develop a deeper understanding of its customers and their needs. It can then turn valuable insights into tangible action points, helping customers make key improvements such as reducing time spent on complex tasks, and enhancing their product offering.

"With the data lake, we can do much more for customers," says Sven. "By connecting data points, we can offer advice like hygiene laws for certain foods, or information on provenance. We can even integrate their local weather forecast so a store doesn't run out of ice cream on a sunny day."

Internally, the data lake supports a huge range of projects, and is currently being built to support sales personnel in 26 countries in the future, so they can access presentations made with Google Data Studio. "We see Data Studio dashboards that pull data from our data lake built on Google Cloud pop up in every part of our organization," says Sven. "They're driving a new emphasis on outcome-driven product management. Instead of relying on opinions, we use KPIs on dashboards as a commonly agreed upon framework to set out our priorities."

To help internal product teams use the data lake, METRO created more than 100 data analytics workbenches. "The workbenches are like playgrounds for data," says Marko. "Each one is tailored to a certain function and gives a team easy access to services on BigQuery, Cloud Dataproc and other tools. People can play with machine learning applications there, too, exploring in the future TensorFlow and other possibilities."

"With the data lake, we can do much more for customers. By connecting data points, we can offer advice like hygiene laws for certain foods, or information on provenance. We can even integrate their local weather forecast so a store doesn't run out of ice cream on a sunny day."

Sven Lipowski, Unit Owner Customer Solutions, METRONOM

For METRO, machine learning is already making an impact. Drawing on customer behavior data from many areas, a new app measures and predicts levels of customer satisfaction, so sales teams know which customers to reach out to, when to do it, and why. For small business owners, this technology is exciting, because it harnesses machine learning to predict the what and when of customer demand. With Google Cloud, businesses are now able to make more accurate buying decisions, saving money and reducing waste.

"We expect to be able to integrate with our customers' point-of-sale and ERP systems in only the next couple of years," says Sven. "That will mean being able to automatically replenish stock, forecast shortages, and match a customer's seasonal needs for produce. It means taking the stress out of planning ahead."

"We ran extensive workshops with people from all around the organization to find where AI could add most value," says Dr. Ehler Lange, METRONOM's Domain Owner. "We picked out key subjects to focus on, from improving customer analytics, to optimizing pricing, reviewing our assortment, and making our supply chain more efficient. This isn't abstract for us. We have a clear roadmap to make gains from machine learning."

Increasing sales, scaling up data, and planning ahead

Meanwhile, more elements of METRO's business are connecting to the data lake. In the ramp-up phase of the data lake at the end of 2018, its daily intake of events increased by 45 times, from 1.2 million events a day in October 2018, to 54 million in January 2019. Now the company is optimizing its analytical tools as it works towards achieving omnichannel analytics: tracing a customer's whole experience of interacting with METRO. "We're committed to that goal," says Marko. "All of our future customer-facing applications will soon be measured by Google Analytics 360, and then that data, too, will be added to the data lake we built on Google Cloud."

The new ecommerce platform is now live in 14 countries. "From 2017 to 2019, we tripled the number of orders executed through the platform," says Sven. "We see a positive effect of the platform, in overall sales as well as ordering customers."

And thanks to the team's success connecting the ecommerce platform to a legacy backend, METRO is now migrating its SAP S/4HANA finance systems to GCP. Timo Salzsieder, CIO/ CSO METRO AG, recently announced the move: "Google Cloud, in addition to technical advantages, offers the possibility to optimize collaboration within the individual teams. Moreover, we can now adapt our system to customer demands in real time."

About METRO

Founded in Germany in 1964, METRO is a B2B wholesaler with revenues of €36.5 billion. The company's tech unit METRONOM has more than 2,000 employees in 8 locations.

Industries: Other
Location: Germany

About freiheit.com technologies GmbH

Based in Hamburg and Lisbon, freiheit.com technologies GmbH is one of Germany's Internet Pioneers, building large-scale digital business software platforms since 1999 for the who's who of German and European businesses and industries.

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