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Inventory Management

Why Spreadsheet-Based Inventory Planning Fails

Most small and mid-size businesses manage inventory with a combination of ERP reorder points, Excel models, and experienced buyers who know the business. This approach works until it doesn't, and it tends to break at the worst possible moments: during seasonal demand spikes, supply chain disruptions, product launches, or rapid growth.

The fundamental problem is that static reorder points can't adapt to changing conditions. A reorder point set based on last year's average demand doesn't account for the promotional campaign marketing just launched, the competitor who just went out of stock, or the supply chain delay that's adding two weeks to your lead time from a key vendor. By the time someone notices the mismatch and adjusts the numbers, you've already lost sales or committed to excess inventory.

Sentie's inventory agents replace static rules with dynamic, data-driven forecasting that adapts in real time. They pull signals from your sales data, marketing calendar, supplier lead times, seasonal patterns, and even external factors like weather and economic indicators to predict demand at the SKU level. The forecast updates daily, and purchase recommendations adjust automatically. Your buyers stop guessing and start executing against data they can trust.

Demand Forecasting That Accounts for Reality

Traditional demand forecasting relies on historical sales averages, maybe with a seasonal adjustment layer. That's fine for stable, predictable products. But most businesses have a long tail of SKUs with irregular demand patterns, new products with no sales history, promotional spikes that distort baselines, and external factors that create sudden shifts.

Sentie's forecasting agents use multiple signal sources to build forecasts that account for the messiness of real-world demand. For established products, the agents analyze sales velocity, trend direction, seasonal decomposition, and demand variance to produce probabilistic forecasts with confidence intervals. For new products, they use analogous product performance, category trends, and early sales signals to bootstrap forecasts until enough data accumulates.

Promotional demand gets its own model layer. When your marketing team schedules a campaign, the forecasting agent estimates the demand lift based on historical promotional performance for similar products and channels. It pre-positions inventory to meet the expected spike and scales back orders after the promotion ends to avoid post-promotional overhang.

Supply-side variables are factored in as well. The agent tracks supplier lead times, monitors for disruptions, and adjusts reorder timing when lead times stretch. If a key supplier is running two weeks behind schedule, the agent moves up purchase orders across affected SKUs automatically rather than waiting for someone to notice the delay.

Automated Purchasing and Reorder Optimization

Converting a demand forecast into purchase orders sounds simple, but the optimization problem is surprisingly complex. You need to balance order quantities against minimum order requirements, volume discounts, container utilization, warehouse capacity, cash flow constraints, and supplier payment terms. Doing this manually across hundreds or thousands of SKUs means most businesses default to simplistic rules and leave money on the table.

Sentie's purchasing agents optimize orders across all these constraints simultaneously. For each reorder cycle, the agent evaluates the demand forecast, current inventory position, incoming shipments, safety stock targets, and supplier terms to generate optimal purchase orders. It might consolidate orders from the same supplier to hit a volume discount threshold, delay a low-priority order to stay within a cash flow limit, or split an order across suppliers to reduce concentration risk.

The agents also manage safety stock dynamically. Instead of a fixed safety stock level, the buffer adjusts based on current demand variability and supply reliability. During stable periods, safety stock drops to free up working capital. During volatile periods or when a supplier is showing signs of unreliability, safety stock increases to protect service levels.

Purchase orders route through your existing approval workflows. Your buyers review AI-generated orders, make adjustments if needed, and submit to suppliers. Over time, as confidence builds, many clients configure auto-submission for routine replenishment orders, with human review reserved for large, unusual, or strategic purchases.

Multi-Location Inventory Optimization

Businesses with multiple warehouses, stores, or fulfillment centers face an additional complexity layer. Inventory needs to be in the right place, not just at the right quantity. A product sitting in your East Coast warehouse doesn't help a customer on the West Coast who needs next-day delivery.

Sentie's allocation agents optimize inventory distribution across locations based on regional demand patterns, fulfillment cost structures, and service level requirements. They analyze which products sell where, at what velocity, and through which channels to determine optimal stocking levels at each location.

Transfer recommendations happen automatically. When one location is overstocked on a product that another location is running low on, the agent recommends an inter-location transfer, factoring in transfer costs and time against the cost of a potential stockout. These aren't reactive fire drills; they're proactive rebalancing based on projected demand at each location.

For businesses with both online and retail channels, the agents manage channel-specific allocation. They reserve inventory for high-value channels, manage ship-from-store logic, and optimize which fulfillment center handles each online order based on proximity, inventory availability, and shipping cost. Your Success Manager configures allocation priorities based on your business rules and margin structure.

Inventory Intelligence and Dead Stock Prevention

Every business has slow-moving inventory that's quietly eating cash. Dead stock typically accounts for 20-30% of total inventory value, and it accumulates gradually as demand shifts, product lines evolve, and purchasing decisions compound over time. By the time someone runs a report and identifies the problem, the markdown required to move the product has already eroded any margin.

Sentie's intelligence agents monitor inventory health continuously. They flag products with declining velocity before they become dead stock, recommend markdown timing and pricing to maximize recovery, and identify purchasing patterns that create slow-moving inventory so you can break the cycle at the source.

The agents also surface product lifecycle insights. When a SKU's demand curve starts following the characteristic decline pattern of an end-of-life product, the agent alerts your team and recommends an inventory wind-down plan: reduce reorder quantities, increase marketing to clear remaining stock, and transition to replacement products.

Your Success Manager reviews inventory health metrics monthly, including carrying cost analysis, turnover rates by category, and dead stock trends. These reviews often reveal systemic issues: a category that's consistently over-ordered, a supplier whose products have higher-than-average obsolescence rates, or a seasonal pattern that your purchasing team hasn't adapted to. Fixing these patterns at the root drives more value than optimizing individual SKU reorders.

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