How AI Wins the Fight Against Phantom Inventory

In the omnichannel retail world, inventory optimization is more important than ever before. Retailers need to get the right products to the right places at the right time to satisfy demand in an efficient and profitable way — no matter how, when or where their customers choose to shop.

With this in mind, many retailers are now using artificial intelligence-driven technology to optimize their allocation, replenishment, transfer, and even returns processes. It’s all part of an effort to position each piece of inventory where it will have the highest possibility of selling for the highest possible profit.

However, getting inventory to the right location is only half the battle. Once products arrive at the store level, the next step is ensuring that each item is properly placed on the sales floor and readily available for purchase. This is another area where AI can make a big impact. AI-driven solutions are helping retailers tackle in-store inventory management challenges, particularly the big problem of phantom inventory.

What Causes Phantom Inventory?

Inventory inaccuracies are a common issue across retail. When a retailer’s inventory records list a product as “in stock” but it isn’t actually available for purchase, this is known as phantom inventory.

Countless different issues can occur after inventory reaches the store level, leading to cases of phantom inventory. This can range from manual data entry mistakes to shelf stocking errors to theft. Phantom inventory can even be caused by something as simple as a lack of visibility, where a product has been pushed to the back of a top shelf or fallen from its peg where shoppers can’t see it.

With so many unpredictable causes, the phantom inventory problem remains persistent and widespread, especially for retailers with millions of SKUs and hundreds of store locations. Cases easily snowball into even bigger problems for the entire business, like ongoing lost sales, lower profits, unhappy customers, disrupted allocation and replenishment processes, and incomplete data that hurts future forecasting accuracy.

How Can AI Help?

In a busy retail environment, store managers simply don’t have enough time in the day to constantly inspect every SKU on every shelf for inaccuracies. Therefore, most stores have to rely on time-consuming physical inventory counts done just once or twice a year. These manual counts are far too infrequent to catch phantom inventory in a timely manner.

Fortunately, AI is powering a new approach. AI-driven solutions are now available that can accurately identify phantom inventory at the individual SKU-store level — without the need for complicated software integrations or expensive scanning hardware.

This type of solution easily and rapidly integrates with a retailer’s existing IT infrastructure to analyze demand forecasts, sales data, and inventory data. AI then predicts the probability of sales for every single product at every store. When a product listed as “in-stock” should be selling but has no sales recorded, that SKU-store combination gets flagged as a potential case of phantom inventory.

After cases are flagged, the next step is making that information actionable. AI solutions can generate phantom inventory alerts, customized for each individual store location to automate actions or send alerts. The alerts get sent directly to store managers via smartphone app so they can immediately zero in on potential problems. Once the manager checks the item, they simply click “yes” or “no” on the app. All systems get updated and product gets shipped as necessary.

Thanks to this efficient AI-powered process, retailers can finally tackle phantom inventory across all their store locations efficiently. With the right SKUs readily available in the right places at the right time, retailers can capture every sale, satisfy omnichannel customers, and maximize profitability across their business.

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