Next Generation Cold Chains – How Artificial Intelligence & Machine Learning is leap frogging the Cold chains of India
Intelligence in logistics and shipping has become a center-stage kind of focus within supply chain management in the recent years. Faster and more accurate shipping reduces lead times and transportation expenses, adds elements of environmental friendly operations, reduces labor costs, and — most important of all — widens the gap between competitors- Vivek Tiwari, CTO & Co-founder, Godamwale.com
Once thought to be a concept only science-fiction movies could produce, Artificial Intelligence (AI) has become a topic of our mainstreams and Social media chats.
The potential of AI enhancing day-to-day business activities and strategies hasn’t just sparked the interest of common folk and organizations globally, but has initiated rapid conversion at least in the tech tribes.
Understanding categories of AI capacities is important for future implementation of AI into business work tools. In particular, the application of AI into Supply Chain related-tasks holds high potential for boosting top-line and bottom-line value.
Previous studies, by the Tungsten Network, have suggested that valuable time and money is wasted on trivial supply chain related-tasks that are conducted operationally by humans.
Major logistics providers have long relied on analytics and research teams to make sense of the data they generate from their operations.
But with volumes of data growing, and the insights that can be gleaned becoming increasingly varied and granular, these companies are starting to turn to artificial intelligence (AI) computing techniques, like machine learning, deep learning, and natural language processing, to streamline and automate various processes.
These techniques teach computers to parse data in a contextual manner to provide requested information, supply analysis, or trigger an event based on their findings.
They are also uniquely well suited to rapidly analyzing huge data sets, and have a wide array of applications in different aspects of supply chain and logistics operations.
“McKinsey estimated that tech giants such as Google and Baidu spent some $20 billion to $30 billion on AI last year, of which 90% was on research and development and the rest on acquisitions of intellectual properties or companies” (asq.org 2017).
Streamlining procurement related tasks through the automation and augmentation of Chabot capability requires access to robust and intelligent data sets, in which, the ‘procuebot’ would be able to access as a frame of reference; or it’s ‘brains’As for daily tasks, Chatbots could be utilized to:-
· Speak to suppliers during trivial conversations.
· Set and send actions to suppliers regarding governance and compliance materials.
· Place purchasing requests.
· Research and answer internal questions regarding procurement functionalities or a supplier/supplier set.
· Receiving/filing/documentation of invoices and payments/order requests.
By utilizing ML technology, SCM professionals — responsible for SCP — would be giving best possible scenarios based upon intelligent algorithms and machine-to-machine analysis of big data sets.
This kind of capability could optimize the delivery of goods while balancing supply and demand, and wouldn’t require human analysis, but rather action setting for parameters of success.
Intelligence in logistics and shipping has become a center-stage kind of focus within supply chain management in the recent years. Faster and more accurate shipping reduces lead times and transportation expenses, adds elements of environmental friendly operations, reduces labor costs, and — most important of all — widens the gap between competitors.
“Where drivers are restricted by law of the land from driving more than 11 hours per day without taking an 8-hour break, a driverless truck can drive all day long without overtime.
That means the technology would effectively double the output of the U.S. transportation network at a fraction of the cost” (source: techcrunch.com 2016).
The flip side of AI implementations are unlikely to result in large-scale workforce reductions in the near term, companies still need to develop strategies to address how workers’ roles will change as AI systems automate specific functions.
The time is not fare away when Ice creams & ‘Shrikhand’ / Dahi will be dropped with the help of Drones into the hinterland of India .Till then enjoy the Summer !!
The author is Vivek Tiwari , a 2003 UDCT ,Mumbai pass out .He has served the Oil industry in various cutting edge roles in Honeywell ,CMC .His last role was with a major National Oil company in the Middle East before he decided to give his all to start Godamwale.com , a Warehouse aggregating platform in 2015.