4 Ways Retailers Can Leverage AI for Inventory Optimization

Inventory is everything in the retail world. Without it, retailers simply wouldn’t be in business. However, most retailers today struggle with inventory management. Rising consumer expectations have made omnichannel a must. Now, retailers need to make millions of decisions about thousands of SKUs, across every possible channel each day — making it harder than ever to get the right inventory to the right location at the right time to capture sales and, more importantly, margin.

All this complexity creates inventory imbalances that hurt profits. With too little inventory, retailers wind up with out-of-stocks, lost sales, and unhappy shoppers who may turn to a competitor to get the products they need. Holding excess inventory is also a problem. It ties up capital and comes with high carrying costs.

To be successful in the omnichannel world, retailers need to reimagine overly complex inventory management processes. They need a smarter, simpler approach where every decision drives profitability — and artificial intelligence (AI) can make it all possible.

How AI Powers a New Approach

AI-driven, omni-capable inventory optimization tools can empower retailers to reduce inventory costs, improve customer satisfaction, and ultimately boost profits. The solutions are designed to optimize the following:

Demand Forecasting

Smart inventory planning begins with accurate demand forecasts. However, many retailers still generate forecasts using a combination of historical data and guesswork. This approach is not fit for today’s omnichannel world, where demand is ever changing and is influenced by a multitude of internal and external factors. Retailers need a way to get more accurate, reliable and granular demand forecasts, and the best way to do this is with AI tools.

These solutions use explainable AI and advanced analytics to process massive data sets and generate highly accurate forecasts. They take into account hundreds of variables and can detect any shifts in demand, helping retailers quickly adapt to customers’ evolving needs.

Moreover, AI-powered forecasting solutions offer the level of granularity retailers need for success. These solutions can create more accurate short-term forecasts down to the SKU/ZIP Code/day/fulfillment preference level, as well as long-term and promotional forecasts.

With these forecasts, retailers can predict how, when and where omnichannel customers will want their orders to be fulfilled, and determine the right amount of inventory needed to meet customer demand. But a forecast alone isn’t enough. Retailers need to take action with optimal decisions.

Inventory Allocation

Inventory allocation is where tangible decisions begin to come into play. The goal is to position the right amount of the right products close to omnichannel customers. However, inventory allocation models are typically rule-based, where decisions are made based on rules pre-set by a human inventory planner. With the added complexity of omnichannel, this approach is outdated. Retailers run the risks of allocating too much inventory to the store which leaves leftover stock and markdowns or early stock-outs and lost sales.

Instead, AI-based solutions that focus on maximizing profit — not satisfying rules — can optimize inventory across a retailer’s entire demand network, including online and offline. Allocation decisions are generated down to the granular SKU-store or fulfillment center level, resulting in higher sell-through and reduced overall direct costs of goods sold.

Store and Distribution Center Replenishment

When making replenishment decisions, retailers usually aim to hit a specific service level. However, this is a judgment-driven process measured by key performance indicators that have been set by human inventory planners. These KPIs often conflict with inventory or financial KPIs.

AI-based, profit-optimized solutions can enable retailers to provide superior customer service levels and generate the highest possible profit. How? By using AI-powered omnichannel forecasting to replenish DCs, stores, fulfillment centers, hub stores and/or dark stores with the right amount of inventory at the right time in anticipation of omnichannel demand that could be fulfilled from every possible source.

These solutions make daily replenishment decisions, taking into account product profitability, services costs, strategic considerations, changing demand patterns, and supply chain constraints. The AI system automatically determines how much inventory to hold back and pinpoints the ideal time to replenish inventory, down to the SKU-location level, to maximize profitability.

Inventory Transfers

In a fast-paced environment, inventory positioning requires continuous optimization. After all, retailers don’t want inventory to sit unsold in some stores, while they stock out in locations where demand is high.

AI solutions can help retailers rebalance inventory, moving products from underperforming locations to other locations with higher probability of sales. To optimize transfer plans, AI solutions compute the expected increase in probability for each product if a transfer is needed, taking into account the time it's not available for sale.

Implementing AI is Easier Than You May Think

Why are many retailers still hesitant to invest in AI-based inventory optimization solutions? They see introducing AI as an extensive, long-term project where they would need to rip and replace all their existing supply chain technology.

It's true that some AI-based solutions require complicated upgrades or replacements to existing systems, to the point where it takes retailers a year or more to get up and running or see any improvements. But fortunately, that doesn’t have to be the case. Today, innovative AI inventory solutions are available that can be integrated with a retailer’s WMS, ERP, and other IT systems in just 90 days. These solutions are ready to start making inventory decisions immediately for rapid return on investment.

Here’s a great real world example. One $5 billion specialty retailer implemented an AI inventory optimization solution in just three months. A statistically proven A/B test showed that the solution increased revenue by 128 bps, with a reduction in inventory coming out of the holiday season which equated to over $35 million in profit.

Like this innovative specialty retailer, your retail business can optimize inventory management with AI. The right solution will not only make smarter forecasts, but also smarter decisions so you can boost profits in today’s omnichannel retail world.

Tav Tepfer is the chief revenue officer at Invent Analytics, a global retail planning solutions provider.