In the first blog in the AI transportation and logistics series, I featured AI transformation innovations at Purolator; the second blog focused on the acceleration of smarter AI telematics in fleet management. The third blog explored AI emotion sensors and the impact that the affective computing market is having on the transportation and logistics industry. This fourth blog discusses AI revenue growth and operational optimization use cases to ensure your T&L company is positioned for accelerated growth.
AI : Revenue Growth and Operations Optimization Use Cases
Why is this important?
First, the digital transformation of a supply chain is one of the most important investments a T&L company can make to ensure it understands upstream to downstream, and the interdependencies to be able to optimize decisions in real-time. T&L supply chains have tremendous overhead in moving to cloud enablements to easily access to all data sets from diverse vendors to create a more connected enterprise.
Companies like FedEx have recently joined forces with Microsoft to improve its analytics to evolve its offerings to commercial customers. The shipping giant is combining its in-house IoT technology with Microsoft 365 and Azure cloud services. This will further allow Fedex to integrate machine learning and artificial intelligence in its systems to strive to achieve more real-time logistics and inventory management, and provide a more efficient customer supply chain.
In addition to near real-time item tracking, FedEx customers will receive intelligence on global shipping conditions and potential disruptions, such as natural disasters. This new service is designed for customers whose shipping requirements are time-sensitive: like medical supplies, products for research, plants or other perishable goods. Information on geographic availability real time customer visibility is also advancing. FedEx is also pioneering in robotics and AI to further shake up the logistics landscape – with estimates of the global market value varying between $8 trillion and $12 trillion – as they squarely monitor their growth vs market leaders like: Stamps.com, Owens & Minor, DACHSER, ÖBB, CEVA Logistics, Royal Mail, DHL, C.H. Robinson, Deutsche Post DHL Group, UPS and Purolator.
FedEx also recently took part in a drone delivery pilot alongside Google’s sister company Wing Aviation LLC. Last year, FedEx announced a prototype of the SameDay bot, a battery-powered autonomous vehicle that relies on artificial intelligence to navigate safely through the streets of Memphis (FedEx headquarters location).
UPS also recently announced this year, their pioneering drone deliveries, optimized routes and expansion of their GreenFleet of more than 12,000 vehicles.
Other North America leading brands, like Purolator have announced their commitment to innovation, by announcing plans to invest in more than $1 billion with a five-year future growth and innovation strategy. As stated “In recent years, dynamic market shifts driven by e-commerce and technology have changed the way businesses and consumers buy, sell and exchange goods. E-commerce sales are expected to reach $4.88 trillion worldwide by 2021. In the age of convenience, consumers want their packages faster with more visibility, control and flexibility throughout the supply chain…Trading relationships are shifting around the globe, creating new opportunities for businesses of all sizes to expand to, from and within Canada. “ What I like about Purolator’s announcement is the clarity of their commitment to innovation and sharing their action plan. See More Here.
The mix of skills and talents to evolve a T&L digital SCM transformation program is one of the most challenging and exciting opportunities for disruption.
However, integrated a robust enterprise-wide AI strategy across all a T&L industry’s data assets across its value chain will require tremendous investments, and focus to ensure that an enterprise analytics architecture is designed and is easily made accessible to decision makers.
AI is all about asking the right questions that you want to solve, and ensuring that you have unified access to the right data, effectively labelled, to advance optimizing insights and decision making.
Below are AI SCM use cases relevant to the transportation and logistic industry.
As a board director or a CEO, ask yourself are you able to perform these network operations, identify your bottlenecks, and identify opportunities for optimization across the supply chain value-chain?
1.) Supply Chain Resiliency
a. Can you simulate or traverse your operating costs (or bill of materials) to proactively surface supply chain disruptions?
b. Can you easily evaluate in what if scenarios and assess the downstream impact, and simulate to support risk mitigation?
2.) Supply Allocation
a. Can you easily source and allocate limited resources and apply them to the most valuable resourcing areas to drive the maximum allocations?
b. Can you easily shift your mix of products (whether that be a highest margin product, most important customer, or most fragile part of the supply chain) and see the ripple implications?
3.) Working Capital
a. Can you easily identify the total value of working capital across business units?
b. Can you identify surplus inventory, and easily access scenario-based planning, and secure smart modelling (market simulation dynamics) to improve decision making to maximize your working capital.?
4.) Demand Planning
a. Can you easily integrate your sales forecasting data with additional sources such as actual demand, inventory levels, and marketing /pricing promotions?
b. Can you easily analyze your demand planning forecast, have smart alerts on deviations, and allow your planners to proactively adjust or override in real time – other forecasts?
5.) Portfolio Optimization and Pricing?
a. Can you calculate end-to-end SKU-level profitability and reconcile portfolio dynamics?
b. Can you enable profitability portfolio management, scenario planning, and have real-time proactive alerts to alter operational decision making to maximize profits?
6.) Carbon Planning
a. Can you easily quantify and reduce environmental impact while building a resilient supply chain operation?
b. Can you set and monitor collaborative carbon plans across all of your operational divisions?
There are many more T&L supply chain questions relevant to advance an AI Enterprise Journey – the race is on and it is an exciting one. Love to hear from you on what other AI questions that you are working on.
If you are a CEO or a Board Director of a transportation and logistics company, where do you stand in these key self-reflection innovation and leadership questions. In summary, the transportation and logistics industry is undergoing tremendous change.
Are you ready for this digital end-to-end connected enterprise – supply chain management – reality in your logistics and supply company?