The disruptions of the past few years have brought urgency to the role of technology to optimize the supply chain and deliver a superior customer experience. Buy online, pick-up in-store (BOPIS), curbside delivery, same-day delivery, and related variations established better customer experience as one of the most important advantages that a company could enjoy in serving their customers.
As manufacturers and shippers have operated in stop-and-starts due to disruptions and rushed to adjust to changing consumer demands, the global supply chains have deviated from the course of business-as-usual. Companies have looked to technology as a key enabler to restore business continuity in their operations.
Bringing Routine Back to the Future
Technology –– including artificial intelligence (AI), advanced analytics, workflow automation, digital twins, and control towers –– offer more business resilience. The promise for retailers to optimize procurement schedules, the use of advanced analytics for shipping channels, as well as enhanced tracking for end customers, has lent more control over an uncertain market environment.
Some companies, because of earlier investments, have withstood these significant changes better than their peers. Focus has increasingly turned to investment in supply chain technology to enable more resilient operations and accelerate decisions at the edge –– where frontline workers, computing, and industrial activity intersect. Before the onset of the pandemic, the market research firm IDC figured that, by the end of 2021, half of all manufacturing companies had invested in AI in their supply chain, increasing productivity by 15%*.
One of the lessons of the last few years for supply chain executives has been the importance of AI to continuously improve enterprise decisions, mitigate risk, and empower teams at the edge to do the same. A recent survey from Interos, a supply chain risk software company, estimated that 77% of supply chain executives planned to implement or introduce AI in the next 12 months to enhance visibility in their supply chain.
The Emergence of AI in an Overlooked Segment of the Supply Chain
Whether companies select an off-the-shelf product or build a solution in-house, AI has become a necessary method to accelerate and distribute decisions. Many companies leverage AI for just this reason –– to put more of their employees in a better position to make better decisions.
Because of the sprawling complexity of the global supply chains, the adoption of AI in the sector has pushed the development of the technology to be accessible and secure to the right people at the edge.
Compared to centralized decision-making, the edge enjoys subject matter expertise and physical proximity to the affected area of the supply chain decision. Teams can adjust quickly to market conditions.
Supply chain managers realized the value of this feedback loop. By 2025, Gartner estimates that a quarter of all supply chain decisions will be made at the edge, an evolution from the traditionally centralized supply chain planning. The immediate impact and feedback are compelling reasons for supply chains to venture into new territory for AI: fleet maintenance.
The Role of Predictive Maintenance in Supply Chain Management
Fleet maintenance has historically been a cost center. Budgets often set the pace of work, with maintenance happening on a time - or usage basis or until a vehicle has an issue that can’t be ignored.
As an example, take seafood imports. Once the container is unloaded at the port, the shipment heads to a nearby warehouse and then on the bed of a long-hauler. Before the truck takes off, the refrigerated trailer is checked and checked again. Smart sensor technology monitors trailer temperatures to ensure that the freight doesn’t spoil before it reaches the grocery store.
AI in fleet management, and especially vehicle maintenance, plays a similar role. By leveraging vehicle and maintenance data that fleet management already collects, maintenance teams can identify vehicles with impending issues and the recommended steps to correct potential failures. For maintenance and operations leaders, comparison at the shop and regional levels enables them to monitor maintenance costs and establish enterprise-level benchmarks for vehicle reliability and maintenance productivity.
Similar to AI applications in other areas of the supply chain, predictive maintenance is trending toward no-code solutions. It makes user adoption intuitive, whether it’s a technician looking into an engine cooling issue, a maintenance head ordering spare parts, or a supply chain leader evaluating maintenance expenses. Predictive maintenance software consolidates the hundreds of thousands of vehicle and repair data points and presents it back to fleet and supply chain management in an actionable format.
The Payoff of Predictive Maintenance for the Customer
Supply chains stand to gain more reliability and consistent customer service out of their on-highway fleets. The improved vehicle availability and regularity in day-to-day operations translates into more satisfied employees –– including drivers, technicians, and fleet managers.
As one fleet manager for a large food and beverage manufacturer said, predictive maintenance “lets his employees get home at night.” Supply chains have the data and technology in place to move on predictive maintenance, and to turn commitments to delivery into a guarantee of customer service.
About the Author
Dr. Manish Govil, Global Segment Leader, Supply Chain, AWS
Sources
*MIT Management, Sloan School – 5 Supply chain technologies that deliver competitive advantage
