In 2022, some of the largest and most sophisticated companies in the world overbought or overproduced inventory by many millions of dollars. The reason, at its simplest, is that consumers did not behave as they had predicted.
“Demand planning went out the door for three years. Now they’re picking it back up because they have all this excess inventory everywhere. And they’ve forgotten how to do it, or they didn’t do it well before.” - Rick Jordon (senior managing director with FTI Consulting)
To get better results, companies are turning to new data sets and new technological tools like artificial intelligence to analyze them.
An executive survey by McKinsey from early 2022 found that spreadsheets are still the primary planning tool for supply chain leaders, with 73% of respondents relying on them.
But, 43% said they planned to use artificial intelligence and machine learning for some planning activities. Another 17% said they planned to use AI and machine learning for most activities at some point.
A survey this year from BlueYonder, a supply chain software company, found that demand forecasting and inventory optimization are among the top uses of AI and machine learning technologies by supply chain executives
“We’re moving well beyond Excel, and just moving to a more advanced tool set,”- Ron Scalzo(senior managing director, FTI Consulting).
At the most basic level, AI takes in data and spits out predictions. To get the best predictions, the data fed into them might matter even more than the AI tools themselves.
“There are systems pulling in data which is lying inside the company already, from across their enterprise systems, POS systems, the inventory levels from their stores and all that. There are very few companies that actually go outside of this box and get data from sources that are completely unstructured.” - Meher Dinesh Naroju (director of AI services, Centific)
At Nucleus, we're closely following this space. As seen here, here, here, here, here and here. As we've said before, we can't help but think this technology is going to fundamentally change almost all industries; so it's definitely a space we want to understand.
Source: Supplychaindive
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