As the bottlenecked supply chains and empty store shelves of the past two years have shown, transportation plays a key role in supply and demand. The increasing chaos of today’s world is causing supply chain disruptions more than ever. In this new normal, smart businesses are breaking down silos and employing AI to create a supply chain that constantly delivers better value.
When a business uses AI to consider historical sales data and related factors, such as order volume, purchase trends, product mix, and revenue, it gleans a clear pattern of customer and market demand. That means transportation leaders can easily identify which routes are healthy, which ones need attention, and which ones are losing money to achieve higher on-time and in-full rates.
On the other hand, businesses that fail to utilize the advantages of end-to-end visibility and actionability of the supply chain dynamics will lack the resiliency of their competitors and have little hope of success in times of struggle. Overburdened machines, deadlocked ports, and constrained cash flow might cause age-old problems. Knowing what to move, what to expedite, what to reduce, and what to eliminate from inventory could easily be determined with AI integration.
Companies that fail to take advantage of AI lack visibility into available inventory and thus have less information about profit margins. Lack of instant inventory information affects shipping quantities, which results in supply chain pressures and, ultimately, poor vendor relationships. Businesses that forego AI sacrifice the ability to see geographical areas with the greatest customer demand and make needed shifts, wasting resources and time.
AI-Driven Businesses Will Lead the Transportation Industry
AI-driven systems keep up with logistics and can offer port operations and fleet managers demand-driven insights to rapidly spot problem areas and proactively mitigate risks. With ports busier than ever, AI logistics not only allows real-time tracking, but can also spot tactical opportunities for improvement.
Smart transportation companies will utilize AI to better understand demand in the following ways:
- To pinpoint areas where material flow is stalling.
- To rapidly audit and use collected information on both macro and micro levels.
- To review and analyze the impact of logistics performance on order fulfillment from the stores, sales, and contribution to indirect logistics cost.
- To know exactly what orders and delivery commitments will lead to customer satisfaction.
- To coordinate processes across the entire length of the value chain to prevent bottlenecks, overspending, and waste.
- To eliminate the need for disparate software solutions and instead gain the ability to respond to rapidly changing conditions in real time.
Using Data and AI to Predict Demand Proactively
Using existing data with AI systems can help with predicting demand more efficiently. Here are a few key ways this can help your business:
- Data and AI will help you know exactly what orders and delivery commitments to take on. That way, you not only accelerate customer satisfaction, but also do it in a manner that has the most significant impact on your bottom line.
- It will rapidly empower you to make intelligent, demand-driven decisions based on demand data modeled against a backdrop of operational constraints.
- It can run multiple order fulfillment scenarios in seconds and identify the ones with the most positive business impacts in real time.
- It can determine what can be sold down based on best- and worst-case lead time predictions.
With the world changing more rapidly than ever before, technology is changing along with it. Transportation companies that want to survive and thrive should embrace AI and follow the touchpoints into the future.
Anita Raj is a seasoned technology thought leader and product marketing expert for building impactful go-to-market strategies for targeted markets such as Europe, the U.K., and the U.S. She is the vice president of product marketing at ThroughPut Inc., responsible for the vision, strategy, and execution of go-to-market and product marketing initiatives, including value proposition, product launches, customer marketing, and product life cycle marketing.
