Retailers Tackle Excess Inventory with Demand Planning Tools

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Gap, Kohl’s, and Nordstrom are all deploying deep discounts to clear excess inventory from store shelves this fall — and they’re not alone. Across the country, multi-location retailers and brands have seen demand slow, right as supply chains came back online and orders that were placed months ago finally began showing up in-store. 

According to the National Retail Federation, clothing and clothing accessory store sales were down 0.6% month-over-month in July. The “days of inventory outstanding” at general and specialty retailers has increased from 57.4 days last year, to 63.7 days in the second quarter of 2022. Across all industries, products are remaining on store shelves for an average of 46.5 days.

The scramble to move excess summer inventory ahead of the holiday shopping season is forcing retailers to take a second look at new technology designed to help companies determine how much to discount or raise pricing to maximize profitability. At o9 Solutions, an enterprise AI software platform provider, retail clients are increasingly seeking out demand planning tools to help with demand sensing and inventory visibility. 

“Excess inventory is leading to [increased] costs due to the need to store this inventory somewhere, and with the rise of warehousing costs this is leading to pressure on retailer margins,” says Vikram Murthi, vice president of industry strategy at o9. “The inventory glut is forcing retailers to discount items such as seasonal products, electronics and televisions, putting further pressure on profits.”

In regular times, retail pricing is typically set by merchandising and operational teams. Those teams use financial parameters, like profit-margin targets and promotional budgets, set by a company’s chief financial officer. However, with the retail market in a state of flux and inflation pressures growing, more retailers are sacrificing profit margins and leaning into discounts to clear inventory.

Tools for demand sensing and inventory visibility help retail brands think more strategically about how they push out or cancel purchase orders depending on any number of market factors. As a best practice, Murthi says retailers should be comfortable allocating supply to channels and regions with the most potential sales, or surgically leveraging discounts and promotions to increase sales. 

Software platform providers like o9 use artificial intelligence, or AI, to facilitate demand sensing at scale, which is especially important for multi-location retailers with local storefronts in different parts of the country.

“Apart from traditional time-series statistical methods, newer machine learning techniques enable demand sensing with pattern recognition and improve the accuracy of forecasts across all channels in a number of ways,” Murthi says.

Newer algorithms, like gradient boosting, support vector machines, and ensemble methods, are used concurrently to leverage internal drivers, like everyday shelf price, sale price, product placement, offers, and digital coupons. Murthi says software can also be setup to incorporate a host of external causals, like weather, GDP, new housing starts, mobility indices, local school and sporting events, interest rates, inflation, debt to income ratios, and more.

While retail profit margins are currently dipping, due to a combination of high inflation and inventory discounting, retail analysts say they expect to see some improvement as brands get smarter about their pricing and promotional strategies. Bath & Body Works, for example, has already said it plans to reconfigure its promotions in an effort to retain more profits and generate margin dollars heading into the end of the year.

“Many retailers have fallen behind with leveraging external drivers such as disposable incomes, inflation rates, mobility indexes and many other factors to forecast demand,” Murthi says. “Broken systems and processes and the difficulty in hiring and maintaining experienced planners and data scientists is seriously affecting robust demand planning at retailers.”

Stephanie Miles is a journalist who covers personal finance, technology, and real estate. As Street Fight’s senior editor, she is particularly interested in how local merchants and national brands are utilizing hyperlocal technology to reach consumers. She has written for FHM, the Daily News, Working World, Gawker, Cityfile, and Recessionwire.
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