3. Augmenting demand planning and forecasting: Demand and supply plans are notoriously error prone. That’s because consumer goods supply chains rely on too many manual processes and lack a single source of truth for timely, accurate decision-making. When companies use AI to bring together all their forecasting inputs — machine and human — across the company, it’s a transformative process. It enables a demand signal that’s driven by data and backed by a consensus. That, in turn, reduces bias in the network and turns exceptions into rarities.
4. Identifying and unlocking VAR: Value-at-risk (VAR) is a powerful metric. It provides a well-defined picture of the total financial risk facing a brand, region or business unit, and it supports more effective supply chain planning. With AI, companies can unlock the risks previously buried in their supply chain data — dynamic, granular risks they’ve never been able to see before — and collaborate on how to mitigate them before they create disruption.
5. Improving product quality: With help from AI, supply chain operators can unearth previously hidden patterns in specifications variability and defects in product dimensions, composition and more, so they can predict their occurrence. AI can also recommend actions for preventing issues and help teams prioritize those actions based on the cost to the business. That means more quality products entering the market, and subsequently more reliable supply for the front-line professionals responsible for manufacturing and distributing products
Build or Buy: A Word of Caution
The examples above show that AI isn’t just another technology Band-Aid. It’s a solution that makes supply chains more resilient and less wasteful.
That said, I wouldn’t recommend CG companies build these use cases in-house, for the same reasons that you would not build an ERP or CRM from scratch. The level of effort is beyond what nearly any company would consider.
Should you get dedicated teams of data scientists that begin to work across your company with new tool sets and capabilities — definitely. Just make decisions about what you build and what you buy with realistic expectations.
There will always be complexity and volatility in the supply chain. That is inevitable. But by bringing AI into the CG supply chain now, companies will be better prepared to respond to future disruptions, big and small, and keep goods flowing.
Mike Hulbert is vice president of consumer business at Noodle.ai.