Wholesale Inventories Dropped 0.3% in January, More Than Expected

The U.S. Census Bureau revised its wholesale inventories estimate for January downward Wednesday (March 6).

Total inventories dipped 0.3% in January compared with December 2023, rather than the drop of 0.1% the agency reported earlier in an advanced estimate, the Census Bureau said in a Wednesday press release.

This was a bigger drop than some had expected, Reuters reported Wednesday. Economists polled by the media outlet had expected that inventories would remain unrevised at the previous 0.1% figure.

The decline in wholesale inventories could have a negative impact on economic growth estimates, according to the report.

Inventories are an important component of gross domestic product (GDP), and they reduced the GDP growth by 0.3 percentage points in the fourth quarter, the report said.

When announcing its revised figures, the Census Bureau said wholesale inventories totaled $895.1 billion at the end of January. That figure includes total inventories of merchant wholesalers, except manufacturers’ sales branches and offices, with adjustments for seasonal variations and trading day differences.

Compared to January 2023, wholesale inventories were down 2.5%, according to the press release.

From December to January, durable goods inventories increased 0.2%, the release said. Among the categories contributing to that gain were computer equipment, up 1.7%, and automotive, up 0.7%.

During the same period, nondurable goods inventories decreased 1%, per the release. The month’s biggest drops were seen in farm products, down 4.5%, and apparel, down 3%.

Manufacturers often understand what they sell to a retailer, but they have little visibility into the inventory at each of that retailer’s individual stores — and therefore the conditions that shoppers are experiencing at those stores, David Gottlieb, chief revenue officer at Trax, told PYMNTS in an interview posted Friday (March 1).

Signal-based merchandising addresses this gap, with Trax’s solution doing so with proprietary image recognition and machine learning (ML) algorithms, Gottlieb said. The company’s solution collects and analyzes real-time, in-store data points (or “signals”) from high-traffic shoppers via a mobile app.

“Whether it’s in Walmart or Target, we have more than one shopper in every one of those outlets every single day, so we’re essentially [getting] a sense of what products are available for sale to the shopper on a day-by-day basis,” Gottlieb said.