Smart Demand & Inventory Analytics

AI-driven forecasting that optimizes inventory levels and eliminates stockouts.

CLIENT

Global Supply Chain Group

LOCATION

Seattle, WA

DURATION

6 Weeks

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Industry Standard

Certified Implementation

45%

Forecast Accuracy Gain

Improved SKU-level demand prediction precision from 62% to 95%.

30%

Inventory Holding Cut

Freed up $3.8M in working capital by eliminating buffer inventory.

99.1%

Fulfillment Rate

Virtually eliminated stockout incidents during regional demand surges.

50,000+

SKUs Automated

Full automated reordering across all regional distribution hubs.

EXECUTIVE SUMMARY

Project Overview

Global Supply Chain Group manages logistics across 85 regional distribution centers. Encelion built a custom predictive analytics engine that analyzes macroeconomic trends, weather patterns, historical sales data, and promotional campaigns to predict demand with 95% accuracy.

THE CHALLENGE

What the Client Faced

Over-stocking led to $4M in annual warehousing holding costs and inventory write-offs, while under-stocking caused lost revenue during sudden demand spikes. Excel-based forecasting methods failed to capture multi-variable market shifts.

THE ENCELION SOLUTION

How We Solved It

Encelion deployed an automated machine learning forecasting pipeline using Prophet, LightGBM, and transformer-based time series models. The platform automatically adjusts inventory reorder points for over 50,000 SKUs.

PHASE 01