The Collaboration Advantage: How Modern Retailers and CPG Brands Win Together

· Source: Databricks · Field: Retail & Consumer Goods — Retail Technology & Operations, Consumer Products & Manufacturing, Supply Chain & Distribution · Depth: Intermediate, medium

Summary

Retail and CPG sectors frequently experience growth impediments due to delayed and siloed data, leading to stockouts, lost revenue, and customer churn. Traditional data-sharing methods, relying on brittle integrations and slow ETL pipelines, cannot meet the demands of modern retail scale and speed. A major CPG brand, for instance, lost $4.2M in sales and 28% of customers due to a 34% out-of-stock rate, caused by production decisions based on data lagging actual demand by weeks. This issue contributes to an estimated $1.75 trillion in annual lost sales from stockouts. Delta Sharing, an open protocol, offers real-time data collaboration, enabling secure access to live data across platforms and clouds, thereby facilitating faster decisions, reducing stockouts, and improving promotional and sales performance.

Key takeaway

For CTOs and VPs of Engineering in retail and CPG grappling with supply chain inefficiencies and lost revenue, adopting an open data-sharing protocol like Delta Sharing is critical. This shift from traditional, brittle ETL pipelines to real-time, governed data access can dramatically reduce stockouts, boost promotion ROI by over 45%, and increase sales by more than 10%, directly impacting your bottom line and competitive standing.

Key insights

Real-time, secure data collaboration is crucial for mitigating significant financial losses in retail and CPG supply chains.

Principles

Method

Delta Sharing provides secure, live data access without moving data, eliminating complex ETL pipelines and enabling real-time updates and granular insights across diverse partner systems.

In practice

Topics

Best for: Executive, CTO, VP of Engineering/Data, Director of AI/ML, Data Engineer, Operations Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by Databricks.