French lingerie retailer Etam is consolidating around a data platform for group-wide strategy around key data issues such as architecture, tools, governance and value.
According to Sophie Gallay, the company's global data and client IT director, Etam's IT team was previously organized around applications.
There were a lot of opportunities to use data and a lot of projects going on, but everything was in silos, especially when it came to leveraging data. The most important thing is to have a strong data foundation and your own data sources with quality that you can monitor and control.
But data is a “cross-cutting” subject and teams are siled, making it difficult to develop and deploy an enterprise-wide data strategy, she says. Etam's senior executives recognized that data could play a critical role in growing the business.
In the past, data was considered good when it came to monitoring business performance. Data is now considered not only a nice-to-have, a bonus, but also a key value lever that provides opportunities to help us grow. And now, more attention is paid to data than ever before.
Mr. Gallay joined Etam in February 2023 and began implementing the first 18-month phase of the data strategy in June of the same year. This first phase will run until the end of 2024 and is focused on building a new data platform using Snowflake technology.
The choice of Snowflake was part of a data strategy as we sought to build a foundation that would be used for nearly all of our analytical work, including exploring business intelligence, data science, machine learning, and even generative AI.
Building a strong foundation
The first 18 months of your data strategy will focus on building your data foundation and supporting technology stack. Etam chose to implement Snowflake rather than develop a bespoke platform. Etam runs Snowflake on AWS. The company's data stack includes Oracle as its CRM database and SAP as its ERP. Etam also uses Salesforce Commerce Cloud, Marketing Cloud, and Service Cloud. The company's primary business intelligence (BI) tool is Tableau.
The move to Snowflake is happening in parallel with an application rationalization process, Gallay added.
Creating a group data platform is great, but there are a lot of different tools around the platform. Strong efforts are being made to streamline the tools that collect data and the tools used to export data to users.
The first stage of your data strategy also addresses governance issues. Gallay said that while some employees at Etam were dealing with data quality and compliance concerns, there was no organization-wide structure or roadmap for data governance.
We do data lineage, FinOps, and Data Ops. Everything is done on Snowflake. This is a way to accelerate data governance. It was nearly impossible to implement the same data governance strategy in traditional infrastructure. ”
Get the most out of your data
Etam used Snowflake to collect data and begin building the model. Models are important, Galley advises.
Remember, the most important thing is to think about your data model and how your data will be used within your platform, as well as the right technology partner.
Gallay's team is running two projects to prove the technology's value to the business. The first project is her BI project, creating the company's first dashboard that gives her 360-degree view of her customers. The second is a data science project that will help improve store replenishment predictions.
We have an important challenge in optimizing our warehouse management system. Our ERP has tools to provide replenishment orders. This is a very basic tool, but we want to make it smarter. Switch from basic rules to data science rules. All inventory recommendations are calculated in Snowflake and pushed to the replenishment ordering system.
As Gallay completes the first part of his data strategy to 2024, he will continue to look for new ways to help Etam get the most out of its data. These projects include BI improvements, smarter performance optimizations, and new uses of generative AI. As these use cases evolve, so will the enterprise's use of Snowflake.
We currently use Snowflake for analytics rather than transactional data. However, with some testing, you may be able to use Snowflake as a data hub. Becoming a data hub allows you to manage warm and cold data in the same place. This approach simplifies all internal architecture, data flows, and data transformations.