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Community Blog From Guesswork to AI: How DUSTO Reinvented Fast-Fashion Forecasting

From Guesswork to AI: How DUSTO Reinvented Fast-Fashion Forecasting

This article shows how Quick BI unify retail data, visualize real-time insights, and drive agile merchandising with advanced business intelligence.

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Client Overview:

Founded in 1995, DUSTO is a fast-fashion women’s footwear leader that now operates more than 8,000 brick-and-mortar stores across China. The brand targets style-conscious shoppers with weekly collections and sells over 150 million pairs of shoes annually. Its success depends on lightning-fast product launches and a supply chain that can sense and respond to micro-trends at city-block scale. Facing soaring SKU counts, fragmented systems (ERP, CRM, POS) and a consumer base that buys both online and offline, DUSTO launched a digital-first initiative to turn every store manager into a data-savvy merchandiser and every headquarters decision into a real-time, data-backed action. Quick BI became the cornerstone of this transformation.

“Our digital journey began eighteen months ago. At first we only visualised historical sales, but with AI-powered Quick BI we can now enable every store to act on real-time insights and truly let data speak for itself.”

— Digital Technology Team, DUSTO

1

Problem Statement:

Before adopting Quick BI, DUSTO’s explosive growth outpaced its data infrastructure. Isolated databases, manual spreadsheet reporting, and delayed nightly ETL jobs meant buyers forecasted demand with guesswork, regional managers lacked a single inventory view, and store staff reordered stock by intuition. High fashion turnover pushed obsolete shoes into warehouses, marketing spent blindly, and headquarters could not compare like-for-like store performance. Without timely, trusted data, the company risked margin erosion and lost the agility that fuels its brand appeal.

2

Solution Implemented:

Quick BI was deployed as a real-time data backbone, streaming updates from ERP, CRM, POS and e-commerce platforms every 3-8 seconds via hybrid CDC and API connectors. A cloud data lake normalised dimensions—SKU, region, season, price band—while Role-Based Access Controls ensured the right granularity for headquarters, 112 branch offices, and 8,000 stores.

On top of the model, Quick BI’s AI toolkit delivered demand-forecast widgets, dynamic pricing recommendations, and mobile dashboards. NLP search let non-technical staff ask “Which SKUs run low in Chengdu?” and receive instant charts; Auto-Insight mined anomalies in sell-through; and an intelligent replenishment app alerted store managers when to transfer stock or trigger orders. Implementation followed agile sprints: data plumbing (4 weeks), pilot dashboards (2 weeks), and company-wide rollout with 1,146 dashboards, 32 e-Kanbans, and 47 data portals—all maintained by a three-person BI Center of Excellence.

3

Outcomes Achieved:

Within three months, DUSTO cut report latency from hours to seconds and achieved SKU-level visibility across every shelf. AI-driven forecasts lifted on-time replenishment by 28% while intelligent markdown guidance shaved 15% off season-end inventory. Mobile analytics boosted store-manager engagement—daily active users climbed to 92%, and order accuracy doubled in pilot regions. Marketing teams now segment promotions by real sales velocity, reducing wasted spend and raising conversion by 11%. Most importantly, executives steer growth with a single source of truth, confident that the data foundation scales with every new store opening.

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Alibaba Cloud Community

1,292 posts | 455 followers

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