Success StoriesSupply Chain Analytics & Data Quality for Leader in Home & Security Solutions
#1 global distributor of security products with 130+ years in business
Business Need
Objectives Driving Transformation
A global manufacturer operating 28 plants across 11 countries required greater transparency into supply chain data quality issues impacting financial performance and customer satisfaction. Regional process variation and sales team differences introduced inconsistencies across materials, customer, and plant data. Leadership needed to quantify the scope of data quality gaps, prioritize remediation efforts based on ROI, reduce financial exposure from inaccurate customer and shipping data, and eliminate manual intervention tied to global export and import processes.
- Assess and quantify enterprise-wide data quality issues
- Prioritize materials, customers, and plants for remediation based on financial impact
- Reduce carrier fines and customer dissatisfaction caused by inaccurate address data
- Eliminate manual intervention in export/import processes
- Improve global supply chain efficiency and cost control
- Establish scalable data governance and quality oversight
Improve enterprise data quality across a complex global supply chain to reduce financial risk, operational disruption, and compliance exposure.
Challenge
Barriers to Progress
The organization lacked standardized KPIs and consistent measurement across regions, limiting visibility into the operational and financial impact of data defects. Manual updates to customer addresses and postal codes triggered carrier penalties, while incorrect weights, measures, and sourcing codes drove unquantified cost leakage. Missing commodity codes delayed shipments, resulting in missed revenue and customer dissatisfaction. The absence of structured monitoring made it difficult to link data quality issues directly to supply chain performance and financial outcomes.
- No standardized global KPIs for supply chain data quality
- Heavy reliance on manual data updates across regions
- Carrier fines due to inaccurate customer address and ZIP code data
- Incorrect weights, measures, and sourcing codes driving hidden costs
- Procurement of unnecessary raw materials due to inaccurate master data
- Missed revenue from shipment delays tied to incomplete export/import data
Solution & Results
What Paradigm Enabled
Paradigm conducted a comprehensive data quality assessment and implemented a standardized analytics framework to monitor and remediate supply chain data issues. Six enterprise KPIs were established to provide actionable visibility across plants, materials, and customer records. Real-time dashboards and automated alerts enabled proactive oversight, while governance best practices were introduced to sustain improvements. The initiative shifted the organization from reactive data correction to measurable, performance-driven data management.
- 55% reduction in supply chain data errors
- $5M in cost savings through error remediation
- Identification of data accuracy issues across 14% of customers and 20% of materials
- Six standardized KPIs enabling drill-down analysis and prioritization
- Real-time monitoring and alerts for ongoing data quality control
- Enterprise data management best practices institutionalized across regions
The organization now operates with a transparent, KPI-driven supply chain data framework that reduces financial exposure, improves global shipping performance, and supports scalable operational excellence.
55%
Reduction in data errors
$5M
In cost savings