The manufacturing sector needs to adopt an AI-first approach that enables dynamic, event-driven decision-making.
By Piet Buyck, Logility, an Aptean company
Information has always been the lifeblood of manufacturing and supply chain management, but our process for using it is broken.
The ritual is familiar and, too often, futile. A leader gets an alert: a global pandemic reorients demand, a container ship blocks a vital canal, or a regional conflict disrupts the flow of raw materials.
Emergency meetings are called. Conflicting spreadsheets are aggregated. Frantic calls are made. By the time a new plan is approved in the monthly Sales & Operations Planning (S&OP) meeting, weeks have passed, and the opportunity is lost.
The manufacturing sector can’t afford to move slowly. It can’t react to change. It needs to adopt an AI-first approach that enables dynamic, event-driven decision-making.
Here’s how.
Historically, manufacturing supply chains have been planned and informed by historical data, with the hope that past events will provide a roadmap for the future. Too often, these insights are nonexistent or imprecise, amounting to nothing more than a hypothesis or educated guess about the future.
As I share in my recently published industry analysis, AI enables manufacturers to plan their supply chains in response to real-time signals from the outside world. Factors such as customer orders, social sentiment, and even weather can provide actionable insights that inform supply chain priorities and execution.
Spreadsheets and legacy systems can’t process this amount of information and deliver meaningful insights, but AI can.
Practically, this means manufacturers need to:
This forward-looking, real-time, insight-driven approach to manufacturing and supply chain management presents one path to a more resilient, efficient, and profitable future.
Manufacturing and supply chain decision-makers, like leaders in many other industries, are often siloed within their own departments. Sales teams collaborate with sales teams, operations specialists with procurement agents, and finance managers with finance managers.
The result is an incomplete picture of what’s actually happening throughout the supply chain.
Better manufacturing logistics require data integrity so that every team is working from the same version of the truth. AI and a new language of planning make these assumptions visible, digital, and trackable for everyone.
Specifically, GenAI solves the alignment problem by replacing formal reports with natural language interaction. A leader in any department can ask the system, informed by a unified data set, why a change is happening or what the immediate impact will be on delivery dates and get an explainable answer.
Within this new language of planning, management can now focus on real, informed decision-making, considering changes to the plan and any risks and opportunities that arise.
Even with the best technologies, manufacturing supply chains are always susceptible to risk. That doesn’t mean that volatility can’t be converted into upside. Anti-fragility is the state of a supply chain that not only withstands but also benefits from volatility by assessing and capitalizing on change.
Manufacturers looking to convert volatility into a strength can start by embracing scenario planning. Use a digital twin to model the impact of uncertainties and make adjustments accordingly. For example, manufacturers can use a digital twin to anticipate the implications of various tariff scenarios and their impact on supply, demand, and cost.
This is an ongoing process. Management can (and should!) continuously monitor and map risks and opportunities for their organization, allowing them to take immediate action to provide a sufficient supply and promote their own product’s market share.
For manufacturers, the traditional planning process is no longer good enough. Static spreadsheets, siloed teams, and backward-looking forecasts are no longer fit for purpose. GenAI may still be an “in-progress” technology, but modern manufacturers can start accruing the benefits now. Make GenAI a collaborative partner to empower your people with the insights they need to drive real-time, event-driven action.
About the Author:
Piet Buyck is a global technology executive with over 30 years of experience in managing and positioning high-value IT applications that disrupt current practices and author of the new book AI Compass for SC Leaders. He is well-known as an influential and strategic business thought leader and entrepreneur with significant achievements and expertise in artificial intelligence, demand sensing, and demand planning. As Senior Vice President, Innovation Strategies at Logility, an Aptean company, Piet is on a crusade to make artificial intelligence for planning easy, accessible, and explainable while keeping human decision-makers in control.
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