Data Mesh and Supply Chain: How Data Mesh has improved HelloFresh's Supply Chain
summary
HelloFresh reorganizes into domain teams with a self‑serve data platform and federated governance, building 100+ data products per year using pipelines like Kafka → S3 → Spark → Snowflake plus Airflow, Kafka Connect, low‑code ETL, monitoring and a PII anonymization tool. Two concrete wins: dashboards that cut unknown food waste by exposing returned/donated/disposed ratios, and demand‑forecast models trained on source‑aligned data whose outputs are pushed via API into procurement, achieving ~98% forecast accuracy and measurable supply‑chain efficiency gains.
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chapters (13)
- 0:00Introduction
- 1:32Speaker background
- 3:18HelloFresh supply chain
- 5:26Data landscape before
- 7:12What is Data Mesh
- 9:44Data Mesh at HelloFresh
- 11:09SCM Analytics team
- 13:59Essence of data product
- 17:33Data product creation
- 21:53Supply chain transparency
- 26:28Demand forecast with Data Mesh
- 29:20Conclusions and impact
- 30:43Q&A
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