The 4-Pillar Value Framework

PRIO powered by RSI is built around four differentiators that help planners and leaders focus on what matters most:

 1.     Simulation-Driven Buffer Precision

Inventory buffers are set by simulation, not averages, ensuring accuracy for every SKU-location.  These inventory policy settings are the foundation of daily prioritized replenishment actions, active inventory health monitoring, and reliable and repeatable planning for every SKU in every location.

 2.     Daily Prioritized Action Plans

Clear, prioritized task lists replace noise with focus for planners and buyers to execute with confidence.  These priorities also serve to enable replenishment decisions that are not based on demand fulfillment. For example, a planner may be faced with a choice of items required to fill up a full container. PRIO powered by RSI helps solve this dilemma by prioritizing items based on sound policies and real-time inventory health trends instead of simple volume metrics.

 3.     Inventory Health Dashboards

RYGB (Red, Yellow, Green, Blue) inventory health monitoring provides visibility into risks and trends.

RED = at risk of stockout – needs immediate attention and investigation

YELLOW = at risk of future shortfall – normal replenishment order needed

GREEN: = on target – no current action required

BLUE: = overstocked to expected simulation result – requires investigation

 4.     Proactive Spike Alerts

Detect future demand shocks before they disrupt operations. PRIO powered by RSI accesses the normal demand pattern for every item in every location and proactively identifies when there is a future order that is outside of that pattern.  This forward-looking insight helps teams respond with confidence — not react in panic.  Most ERP systems still rely on rigid, rule-based formulas that, at best, produce “roughly right” replenishment guidance. Why do these methods often break down in the face of intermittent demand, lumpy patterns, and shifting service trade-offs? Because they use overly simplistic assumptions about the variability that exists in the real world.