Dive Brief:

• Wholesalers are struggling to adapt to new consumer demand patterns, as traditional forecasting processes consistently lead to overstocks and higher costs, according to a new survey by Blue Ridge Global.
• Only 5.2% of the 100 respondents said they used advanced tools such as machine learning or AI for inventory management, while more than 70% use historical sales data or moving averages to forecast. About 65% of respondents later said their processes did not fully provide the "insights" needed to succeed.
• Most respondents said complex demand patterns (37.4%) and volatility (30.6%) would be the biggest challenges facing wholesalers in the next three years. To address this, the survey found, wholesalers were often holding more goods (64.6% hold more than 30 days of inventory) and suffering the higher costs.

Dive Insight:

There's nothing wrong with traditional forecasting processes — until it leads to higher costs and lost sales.

It should be noted the survey was sponsored by Blue Ridge, an inventory management solutions provider, but the results still reveal wholesalers (including their clients) are struggling to adapt to a new consumer-purchasing paradigm. The Amazon Effect demands a greater flow of products, which in turn requires improved precision in forecasting.

Good forecasting is not just about understanding how much a product sells, but how much any given person buys in a mix of channels and stores. The future of inventory management is taking data including weather, social media interactions and competitor pricing into account for planning purposes, and that future is arriving quickly for wholesalers. 

"We have the data now to make the forecasting much more predictable," Rajesh Veliyanallore, Blue Ridge’s chief data & analytics officer told Supply Chain Dive.

But, as the report shows, that new technology is still far from implementation among wholesalers. But Veliyanallore says that's OK as long as supply chain managers begin looking to future indicators as opposed to simply historical data.

"Leverage the information that you already have," he said. If managers begin layering the price changes that happened in the past, collecting the price items sold for, and moving beyond data points to time series, are a step in the right direction.

It may also be you are not equipped to handle complex demand patterns. Recognizing that is far better than looking at changing sales patterns, and overstocking to try and have as much available for when demand comes. 

"It happens all the time," said Rod Daugherty, Blue Ridge’s vice president of product strategy, noting there's a lot of emotion that goes into that. "Even despite good input and good analysis from their solution, people will react. Instead of doing good planning and acting proactively, they will react and throw money at a problem."

Instead of boosting inventory, Veliyanallore recommends striving, unrelentingly, to "understand" the root cause of demand. "Having an inventory of items that you don't need (is) really not going to translate into higher sales," he notes. If wholesalers continue to "chase" demand, it will be tough to catch up.