Mango drives company-wide data culture in global fashion
Up to 20% increased productivity of data teams
Data users through different departments and data teams
Rationalize in-house data catalog and quality tooling
Retail & Apparel
Databricks, Delta Lake, Snowflake, Looker, Business Objects, SAP, Cobol, Informatica, dbt
Advancing Visibility Across the Data Estate
Mango has a data department of more than 70 data engineers, data scientists, and analysts working on sophisticated pricing optimization, generative AI for product design, and KPIs on environmental sustainability. In addition, there are more than 1,000 users throughout different business departments, from product, retail, ecommerce, supply chain, finance, and HR. However, as they continued to grow their teams and use cases, they recognized different areas for further improvement:
Mango saw that their expanding teams and separate systems were making it slower for users to find data for their day-to-day responsibilities and putting more workload on the data platform teams to support these requests.
Data issues could have meaningful impacts on the organization, and Mango wanted to go beyond their existing in-house tooling capabilities. For example, incorrect product pricing being printed onto price tags could lead to the re-tagging of thousands of items across multiple stores and distribution centers.
Valuable information about key data was informally scattered across emails, chat messages, and the memories of individual employees, which affected productivity and processes for the growing teams.
The different data teams wanted to establish a common language for key business terms with standardized glossaries and data definitions, such as what was defined as a sale, invoice, or transport, for more effective communication and collaboration among teams.
Business teams relied on data teams for questions about reports and dashboards, making it essential for the data to be highly reliable and response times to be quick, in order to drive new business opportunities and accelerate the pace of innovation.
Unified Data Discovery, Observability, and Governance with Collate
To address these challenges, Mango implemented Collate’s managed OpenMetadata service to establish a single source of truth for data across the entire organization. The Collate platform goes beyond a traditional data catalog to help teams find, understand, and trust the data they need with more complete context.
Collate unifies data discovery, observability and governance for all the different business departments and data teams to a single source of truth where data users can collaborate together.
Self-service is significantly increased throughout the organization, with users creating no-code quality tests, leveraging data definitions in the glossary, and reviewing data contracts in the knowledge center.
Instead of email agreements between groups on data structure, data contracts are now created and stored in Collate. This has prevented data discrepancies, improved team alignment, and reduced new data integration time by 3x.
The data governance team has a better understanding of the data landscape, with visibility to monitor data flows, quality, stewardship and more, for a more confident and comprehensive management of all their data.
Collate is seamlessly integrated into Mango's internal data portal, providing business users with easy access to data glossaries, articles, and data quality features directly within their existing workflows.
Driving increased business revenue with better-quality data
The fashion industry is intensely competitive and fast-paced, with evolving consumer tastes shifting every season. With Collate’s unified platform for all their data teams, Mango can stay ahead with the insights to keep their customers and their business on trend.
Higher data quality leads to better ML models for pricing and discounting for seasonal sales, as even a 1% change in accuracy can significantly impact revenue.
Each training round for the pricing ML models can cost thousands of euros and take days to complete. Collate’s improvement to data quality leads to fewer rounds of training, directly resulting in cost and time savings.
The centralized data knowledge and improved data discovery capabilities provided by Collate have significantly increased productivity and trust in data across the organization, empowering business teams to make more informed, data-driven decisions.
Collate's robust data governance features have helped Mango mitigate risk, manage customer privacy, and ensure compliance with regulations like GDPR, protecting the company from potential fines and reputational risk.
Overall, the adoption of Collate has transformed the way Mango manages its data assets and how its data users work together, unlocking new opportunities for collaboration, growth, and innovation.
