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Community Blog How a Construction Giant Crushed Data Silos with Quick BI & AI

How a Construction Giant Crushed Data Silos with Quick BI & AI

This article explores how Quick BI transformed heavy machinery ops—real-time visibility, 80% faster reporting, and smarter decision-making.

Client Overview:

Firm D, a global leader in construction machinery, has been shaping China's infrastructure landscape since 1990s. Specializing in excavators, forklifts, and machine tools, it now commands a vital position in China's booming heavy machinery market. From 2023, the company embraces digital transformation, leveraging AI and big data to drive industry innovation. As domestic competition grows, Firm D remains committed to intelligent solutions that enhance operational efficiency and customer value across the construction ecosystem.

"Through digital initiatives, we aim to achieve three key goals: data-driven business operations, data resource utilization, and data service transformation. This will enhance IT operational efficiency and deliver multiplied returns in member value and business outcomes."


------Gu Beili
Head of the IT Department

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Problem Statement:

Over two decades, the company invested heavily in SAP and multiple standalone systems---call-center, sales-funnel and dealer portals---gaining an early IT lead. Yet the resulting data landscape is fragmented: customer information sits in silos, analysis relies on manual spreadsheets, marketing campaigns cast a wide net with low returns, and quality teams only learn of defects through warranty calls. Leadership sought a digital upgrade capable of transforming data into actionable, sales-driven intelligence.

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Solution Implemented:

We consolidated customer, sales, service and warranty records from SAP and ancillary platforms into a cloud-based customer data platform. Using CDC pipelines, each transaction now streams into a unified lakehouse where a canonical customer schema and golden IDs were established. Built-in ELT jobs create subject-area marts that power self-service dashboards in Quick BI. Automated reporting replaces spreadsheet collation, delivering daily insights on pipeline health, dealer performance and service KPIs straight to management's mobile app.

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On top of the data fabric we deployed AI-driven modules for advanced analytics. A propensity model segments customers by lifetime value and churn risk, triggering targeted campaigns through a marketing automation engine rather than blanket outreach. Meanwhile, an anomaly-detection model ingests IoT sensor and field-service logs to flag potential failures before they reach the call center, enabling proactive maintenance requests. These predictive signals flow back into the CRM, closing the loop between analysis and action.

Outcomes Achieved:

Within six months, the integrated platform cut manual report preparation time by 80% and provided real-time visibility across 100% of dealers. Sales leaders gained granular, trusted customer profiles, boosting cross-sell conversion rates by 18% and reducing cost-per-lead thanks to sharply targeted campaigns.

Predictive quality analytics reduced warranty incidents discovered via customer complaints by 30%, cutting warranty expenditure by 22% and lifting customer satisfaction scores seven points. Marketing ROI climbed 25% as resources shifted from blanket promotions to data-driven outreach. Collectively, the initiative established a scalable digital backbone that now underpins ongoing product, service and revenue innovations, delivering company-wide efficiency gains.

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