As supply chain disruptions continue to challenge global operations, AI is emerging as a powerful ally in restoring predictability and resilience.
Border States, one of the nation’s largest employee-owned electrical distributors, found itself confronting growing inefficiencies stemming from volatile supplier performance, rising costs, and outdated forecasting methods. Managing more than 200,000 SKUs and $650 million in inventory across 130+ branches in 31 states, the company needed a solution that could move beyond static averages and anticipate real-time market complexity.
To address these challenges, Border States partnered with GAINS, a leading supply chain optimization technology provider, to implement the AI-powered Lead Time Predictor Service — a solution designed to improve forecast accuracy, reduce manual intervention, and strengthen operational efficiency.
AI in Action: From Forecasting to Foresight
The GAINS platform harnesses machine learning (ML) to analyze extensive datasets, including supplier performance, order histories, transit times, and external market indicators. Instead of relying on historical averages, it dynamically forecasts lead times at the material and order level, identifying potential disruptions before they occur.
The implementation process included:
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Data cleansing and model training to ensure predictive accuracy.
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AI model deployment integrated across procurement and inventory systems.
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Continuous optimization through real-time feedback and supplier performance analysis.
The impact was immediate and measurable. Border States achieved 97% material availability, a 32% reduction in purchase orders, and a 25% expansion in locations — all while decreasing expedited shipments and lowering its carbon footprint. Internal adoption soared as teams began to trust the system’s predictions, now responsible for more than 90% of all purchase orders.
“Adoption soared when teams saw predictions they could trust,” said Kory Jacobson, Regional Procurement Director at Border States. “This innovation doesn’t just react to disruptions — it predicts them, helping us plan smarter and operate with greater resilience.”
A Paradigm Shift in Supply Chain Planning
According to Amber Salley, VP of Industry Solutions at GAINS, the Lead Time Predictor represents a major leap forward for supply chain professionals. “Traditional ERP and forecasting models struggle with complex, heterogeneous data,” she said. “Our platform reduces lead time errors by 31% and increases accuracy by 65%, enabling proactive, not reactive, management.”
Beyond accuracy, the AI-driven system also supports sustainability and strategic growth. By optimizing procurement and reducing excess inventory, Border States has cut waste, improved supplier collaboration, and minimized environmental impact through fewer emergency shipments.
“The GAINS Lead Time Predictor redefines how supply chains manage uncertainty,” Salley added. “It turns lead time forecasting from a static calculation into a dynamic, data-driven insight — empowering businesses to build resilience and accelerate performance.”
