At the risk of rolling eyes about another AI something in the freight tech space, hold on.  This is different.  Really.   Our most recent version of LOG-NET is not released as an AI tool set to enhance people’s performance in supply chain and logistics.  We have released a platform to replace 70% of the people managing and processing today’s global supply chains.  It is not as bad as that sounds.  My hope is to break through the myopia of entrenched preconceptions about AI and start talking about the incredible new capabilities and jobs it is creating.

We have birthed a platform (LOG-NET 9) that can replace seventy plus percent of the staffing of a traditional 3PL (third party logistics provider) in global logistics.  It is for real.  We have customers going live.  We’ve done all sorts of POCs (proof of concepts) on tens of thousands of international shipping containers and air freight.

But let me set some boundaries to specify the use cases being solved.  The customer profile ships one thousand or more containers per year.  The customer is operating at the SKU or lower level of detail, including the order.  They may need to track size, color, serial number, UPC.  The customer may require carton or case level detail.  We bookend the process with issuing an order to a supplier somewhere in the world.  Follow the manufacturing work in process (WIP)  to shipment planning, documentation, and the carrier processes.  Track and trace, customs, transloading to the store or door at the other end.  This customer will negotiate carrier contract rates and need their allocations managed and audited.  Any booking or forecasted shortfalls by the carrier need to be audited and alternates arranged.  The machine factors and manages production forecasting, OTIF rating, carrier forecasting and allocation.  The AI manages ETAs, expediting requests and budgets.  The system can handle local and network wide incidents rescheduling items, accelerating alternate stock.  It watches and optimizes demurrage and per diem free time use and delivery.  All while taking care of preparing and distributing all your paperwork, following up on vendors and service providers and auditing product and service costs.

The first mile is as important as the last mile.  Hyper care of planning, manufacturing, transporting and cost management are embedded goals.

What do you look for in a logistics provider?

What makes a good logistics service provider.  When looking at Gartner, Forrester and others some of the key capabilities that they advise clients to look for in a quality logistics provider include a provider that;

• Constantly looks for ways to improve On Time In Full (OTIF) performance
• Constantly drives cost efficiency
• Capable and Competent
• Customer Focused
• Agile and Responsive
• End-to-end capability
• Link constituent performance from factory floor to customer door
• Traceability of product and information
• Information assurance, accuracy and no spreadsheets
• Real Time Visibility
• Data Driven
• ESG Focused
• Understand and effectively manages unique customer requirements
• Technical capability
• Integration and collaboration capable
• Available and responsive customer service
• Security focus
• Knowledge management and partner enablement
• Does the heavy lifting to simplify the global supply chain for the customer
• Manage and organize supply chain KPIs
• Aggregates, cleans and effectively uses customer data to drive future performance
• Rapidly address, communicate, remediate and escalate, when necessary, supply chain disruptions

LOG-NET 9’s AI based forwarding operations checks all the boxes.

Internally we realized during one of our POCs a few years ago that the platform was ready to take the training wheels off and allow it to ride on it’s own.  The platform could perform forecasts and adjustments.  Reject or accept complex booking scenarios and email partners for adjustments or corrections.  The system performs Customs filings, prepares shipping instructions and analyzes and optimizes the flow of equipment and product.   The trading partners that collaborate with the platform are unaware their dialogue is with a machine.

How do you define machine intelligence

The scale of care that it takes on each task is impressive.  Artificial intelligence’s edge is its computational scale.  This is what takes years to develop.  Consider that if you were to analyze the unloading of a particular carton of a SKU you would have hundreds of things to consider.  When is the SKU ETA?  What is the stock level of that SKU?  Did it have a required delivery date?  How heavy is it?  Does it fit my conveyor? Do I need an appointment for that SKU?  Is my customer going to cancel the SKU?  Do I have an alternate order of the same SKU?  How is the OTIF performance of this supplier? When is that SKU scheduled to depart the next hub?

All of these questions can be considered as being on the SKU dimension.  Now add the transport dimension.  How is the truck or container doing?  Has the container arrived?  Did all the items clear customs?  Has a delivery order been issued?  Is the drayman available?  Has there been an accident? Is a special chassis required?

Then add similar exercises on the document dimension.   The warehouse dimension.  The Export and Import Customs dimension.  The destination and route dimensions. Finally model all of this on to a matrix of nodes in the supply chain representing these dimensions and the carriers, origins, destinations that will impact the movement at its present location, future locations and how the dimensions interact.  Then optimize the state of that graph, whenever anything changes along any dimension.  This is a mind-numbing computational exercise for humans but within the capacity of today’s machines.

That is why human cognitive intelligence is so often sited in supply chain in the past as having the best results.  It is probably why the industry has a reputation for stress.  You also have to consider the myriad exceptions of companies and commodities.   The specialized regulations by jurisdiction.  The nuanced rules of loading requirements for the set of products in the warehouse to be load right now.

In LOG-NET 9 this is all handled computationally.

Exciting New Horizons enabled by AI Native platforms like LOG-NET 9

LOG-NET 9’s AI and machine based processes open up new horizons and allow us to leave the limits imposed by our preconceptions that a human is required for many of today’s supply chain jobs.

This horizon is set with a different set of limits.  We are not constrained by

• a limited supply of international supply chain expertise
• poor in transit visibility
• slow response to supply chain disruptions
• supply chains that are slow to respond to market changes
• supply chains that do not dampen the bull whip effect
• lack of transparency in supply chain costs
• lack of transparency in supply chain labor practices
• lack of transparency in supply chain custody and control
• lack of understanding of ESG trade offs

We have opened global supply chains to use AI Native platforms to assist us in transformative levels of performance and standards of living.  We can now look at the impacts of our actions on an end-to-end basis.  With the cost, ESG, efficiency and transparency we have enabled better understanding of the fairness and quality of prices and costing that have been hidden, by sometimes intentional barriers, for centuries.  We are now able to trace accountability for labor practices, greenhouse gases and have better control of cash-based transactions in developing economies.  In developed economies we are reducing the frictions between partners and supply chain nodes that have constrained efficiency for all parties reducing transactional, inventory, time and wasted costs.  This AI capability enables us to lift the quality of lives around the world.

I am so proud of our team for resetting our horizons.   I am honored and excited to work with our forward-thinking customers who are taking on the challenges of our new AI enabled horizon.

Check it out http:www.log-net.com.