State Electric Supply, an electrical distributor headquartered in Huntington, West Virginia, has been an Infor customer for nearly 25 years and moved to Infor CloudSuite Distribution about three years ago. The company operates 42 locations across eight states, has since added AI and automation from Infor Velocity Suite to that ERP to address problems in inventory, sales, pricing and accounts payable.
The work started with inventory and moved through product recommendations and pricing to accounts payable, where the team has gone from five clerks to one exception manager. Each stage drew on data and workflows already in the ERP. Infor’s Velocity Suite’s native integration with CloudSuite Distribution allowed new use cases to be deployed in months without a separate integration project, and Infor Process Mining was used throughout to find process gaps and check whether changes worked.
From Annual Rebalancing to Monthly Recommendations
Inventory rebalancing, a long-standing problem for the operations team, came first. Two full-time employees spent roughly three hours a day on manual analysis that covered only a fraction of the branches, and rebalancing happened once a year at selected locations. In the meantime, dead and slow-moving stock accumulated across the network and tied up working capital.
Infor AI Inventory Rebalancing now examines purchase history and inventory levels across all 42 locations, recommending monthly transfers between branches and identifying products eligible for vendor returns. Infor puts the labor saving at about 2,200 hours a year, although it does not explain how that figure was calculated.
Bringing Product Knowledge and Pricing Into Order Entry
The next two deployments brought AI into order entry. Counter staff had relied on accumulated knowledge of which products belong together, and that knowledge was leaving the business as veteran employees retired. Infor AI Product Recommender now uses basket history to suggest the top 10 complementary products while an order is being entered, and employees add an item with one click instead of looking up and typing its product code. Infor credits the tool with about $25,000 in additional monthly revenue, roughly $300,000 a year, without explaining how that revenue was attributed.
Pricing moved into the same workflow. The team had worked from a static monthly matrix that went stale within days and produced inconsistent prices across branches, while a high rate of sales overrides eroded margin. Weekly AI-generated recommendations now replace the matrix, drawing on market conditions, customer history and competitive signals, segmented by customer and product, and displayed during order entry. The model also learns from accepted and overridden prices. Infor reports 40% fewer pricing overrides and a 1% increase in average profit margin, though it does not say whether the margin gain is relative or one percentage point.
Invoice Processing Moves to Exception Handling
Accounts payable is the most recent deployment. Five clerks had been keying about 330 vendor invoices a week by hand, spending more than five minutes on each.
Infor Invoice Processing Automation, powered by Infor Intelligent Document Processing, now extracts and validates that invoice data, leaving one exception manager in place of the five clerks. Infor reports about 1,500 labor hours saved a year and improved payment accuracy, but it does not say whether the other employees were reassigned or how the staffing change relates to the hours saved.
Process Mining Exposes an Approval Gap
Process mining ran alongside each of these projects, and one of its earliest findings concerned purchasing controls. Within days of deployment, it showed that 40% of purchase order lines were not following the required sequence: invoices were being generated before purchase orders were created, bypassing approval controls and creating compliance and audit risk. Infor reports that the company now identifies process issues 86% faster and spends 50% fewer resources investigating them.
What This Means for ERP Insiders
Check approval sequences before expanding automation. The purchase-order finding shows why teams need to compare actual transactions with required controls. For procure-to-pay projects, identify who owns each approval, review transactions that bypass it and assign responsibility for resolving exceptions.
Evaluate pricing recommendations against margin and override reasons. A lower override rate alone does not establish that prices are appropriate. Track why employees reject recommendations and compare override rates with margins by branch and product. This gives pricing teams evidence for reviewing both recommendations and sales decisions.
Size invoice-processing teams around the remaining workload. Track the proportion of invoices requiring intervention, average handling time and unresolved backlog as volumes change. That provides a clearer basis for evaluating labor savings and staffing needs.
