Global fashion retailer with 4,700+ stores across 76 markets
H&M Group operates a multi-brand retail empire spanning ~4,702 physical stores and 56 online markets across 76 countries. The tech stack reveals a supply-chain and analytics-heavy operation: SAP for core ERP, Databricks + BigQuery + Python for data pipelines, and Looker + Tableau + Power BI for reporting—a mature BI infrastructure typical of large CPG/retail orgs managing inventory at scale. Current hiring focuses heavily on sales and operations roles, with active projects concentrated on logistics (new distribution and omni-logistics centers) and customer engagement (loyalty app, merchandise execution), suggesting a push to modernize fulfillment and direct-to-consumer channels.
H&M Group is a publicly traded fashion company headquartered in Stockholm, Sweden, with a portfolio of brands selling apparel, accessories, beauty, and homeware globally. The organization spans roughly 4,702 stores across 76 markets and operates in 56 online regions, serving millions of customers. The business operates a vertically integrated supply chain: design and product teams use Adobe, Blender, and Rhino; warehousing and inventory are managed through WMS and SAP; and analytics teams work with BigQuery, Databricks, and BI tools to optimize sales and margin. Beyond retail, H&M Group positions sustainability and inclusive design as operational cornerstones.
H&M's core systems include SAP for ERP and SuccessFactors for HR; Databricks, BigQuery, and Python for data engineering; Looker, Tableau, and Power BI for analytics; ServiceNow for IT service management; and design tools like Adobe Illustrator, Blender, and Rhino.
Active initiatives include launching new distribution centers and an omni-logistics hub, promoting a customer loyalty app, enhancing in-store sustainability programs, automating HR/benefits operations, and expanding recruitment through social media and online networking campaigns.
H&M Group's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.