AI and the three levels of Supply Chain visibility technology: A LSP perspective

What exactly is Supply Chain visibility ?

In the world of Supply Chain,  more the information available on what is going on in the Supply Chain, more confident the players in the chain can be. This visibility leads to increased certainity, and with that, the  need for for “overdone” just in case measures like time buffers, labor buffers, inventory buffers etc. can be reduced and significant efficiencies can be derived.

However, what should be considered true Supply Chain visibility ? In my career, I have seen many interpretations of it- from something as basic as “track and trace” to being able to see the characterisics of the product while it is in transit. So what is true Supply Chain visibility ? In my interpretatio, true Supply Chain visibility is a journey (I know- I define all technology transformations as journies but that is how I think). I will define that journey in this article.

Screenshot_20200419-234000_Autodesk SketchBook

Logistics Service Providers (LSPs) and Supply Chain visibility

Do you know that over the last two decades or so, one of the key differentiating issues in cargo movement management has been the ability to strengthen the customer relationship between logistics providers and their shipper customers through enhanced product visibility.

Enhanced visibility management has become a key differentiating factor in logistics.

Providers of the information on what is going on in the Supply Chains have become integral to the successful operation of their customer’s Supply Chains and have the golden opportunity to play an increasingly strategic role.

In this age of Big Data, considering the volume that some of the large LSPs move, if they can leverage this data prudently, can create very lucrative ($$$) opportunities for themselves.

The three levels of Supply Chain visibility technology

The three levels of Supply Chain visibility technology are shown in the illustration below. While some level of fundamental AI can be leveraged in level 2 (which we will discuss in the subsequent section), the true power of AI can be harnessed in level 3 of Supply Chain visibility technology.

Capture

Level 1- Information level

This level provides information on what is happening. Companies that are at this level of expertise have a system to record movement for all consignments and each customer can see where their inventory is throughout the Supply Chain. This capability is obviously helpful but when a shipper has potentially thousands of items being transferred in myriad Supply Chains around the world at any one time, is this information nice to know or necessary to have ? Will shippers be able to incessantly review all the information ? They may end up with significant amount of data that may not be humanly possible to analyze.

This is where the stage gets set for true Business Intelligence (BI) tools

Level 2 – Insights visibility

This level is what I like to call the Insights or the “Actual vs plan” level. This level focusses on planned versus actual Supply Chain logistics performance and is the level where useful information begins to be derived from the vast pool of data associated with the foundational level of “track and trace”. Customers begin to use this information to control Supply Chains with exceptions and solutions reports being produced and communicated by LSPs to their shipper customers: what deliveries are running late, what are the implications, what has been/is being done  about this etc.

Organizations primarily leverage rule based Business intelligence at this level of visibility. Descriptive and prescriptive tools can be leveraged as well in this level of visibility capability.

Level 3- Learning level

This third level is the learning level. At this most advanced level is where you get to leverage true AI. At this level, customers begin to use the experience captured in the data to analyze and redesign their end to end Supply Chain.

This is using the data from Supply Chain visibility at the strategy level as well tactical planning. Repeated problems might indicate an issue of reliability of a certain trade lane or route. Rather than remedying the issue each time, a re-routing of trade flow may avoid the problem occuring in the first place.

This is the level where you can incorporate AI algorithms to create “game changing” products for your customers. Creating such products for multiple customers will allow you to develop a platform as well, that can then become your cash cow. Everyone is providing the offering of moving products and providinh information visibility.

By providing your customer strategic suggestions leveraging AI based platforms that can allow them to reorient their operations and processes is a differentiator very few will be able to match.

I can think of options to leverage Machine learning methodologies, both supervised and unsupervised to draw valuable insights that can allow customers to transform their Supply Chain function. The key is to capture the data in the first level effectively, create a data strategy at that level only, keeping in my mind how that data will be leveraged by Machine learning tools in level 3.

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Views my own.

 

 

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