The next phase of manufacturing digitization will be to improve information flow across boundaries, because ultimately, every factory still depends on the data that tells it what to do.

Supply chain leaders aren’t waiting to see whether agentic artificial intelligence works before putting it to work.

How is artificial intelligence making its mark on supply chain planning?

PING, a leading manufacturer of innovative golf equipment and accessories for everyone from tour pros to weekend players, partnered with John Galt Solutions to strengthen its supply chain planning capabilities. Through implementation of Galt’s Atlas Planning platform, PING was able to create a fully integrated demand and supply planning environment. 

Supply chains by their nature are complex, interconnected systems where the source of a disruption is rarely obvious at first glance. What might take a team of analysts days to unravel can be surfaced and contextualized far more efficiently through GenAI, freeing up planners to focus on response efforts rather than diagnosing the core issue.

For today’s Chief Supply Chain Officer, the challenge is no longer simply creating a better plan. It is building an operating model that can continuously sense, reason, adapt, and act as conditions change

Organizations that once relied on spreadsheets and gut instinct are finding that legacy tools simply can’t keep up with the speed and complexity of modern supply chains. 

Glowing, optimistic predictions about an explosion in holiday sales mask an important distinction between the money a retailer is taking in and the amount of product it's actually moving.

AI can draw on a raft of data and signals that humans either can’t see, or are unable to process at scale.

In today's complex retail and CPG landscape, aligning inventory with volatile, omnichannel demand is a critical challenge. Traditional forecasting and planning methods often fall short, leading to out-of-stocks, excess inventory, and missed revenue opportunities. This white paper, "Demand Intelligence Impacts," explores how leading companies are overcoming these obstacles by leveraging AI-powered demand intelligence to drive significant organizational outcomes.