Artificial intelligence and cognitive computing are transforming the global logistics landscape. Here’s what you need to know.
That the global supply chain crisis may not be as fleeting as most thought is a truth that is slowly dawning upon the many. The tumult caused by the COVID-19 pandemic has proven to be the primary progenitor of the observed distortions in the cost and availability of cargo containers, shipping rates, truck drivers or warehousing capacity.
The more alarming fact according to research, however, is that most of the issues – rather fundamental in the functioning of the global logistical infrastructure – were pre-existing; and COVID-19 may have had a rather smaller-than-expected impact in exacerbating said strains. Forbes opines:
“[..] adjustments will need to be embraced, in fact heavily invested in and higher prices charged for, if the world economy—consumers, workers and firms—wish to continue to move more toward a system of “just-in-time” market transactions and just-in-time “factory-to-end-user” deliveries and away from the legacy “just-in-case” regime—one that relies more on warehousing and in-company stock management as ways to mitigate risks, and for which lower prices should be charged relative to a “just-in-time” paradigm.”
This ‘adjustment’ will require smartly embedding sustainability deep into the business strategy paradigm, transforming day-to-day operations and key performance indicators that stakeholders hold dear to assess long-term performance. COVID-19 simply hastened a process that required deep structural changes anyway.
Supply chains today are substantially longer and more convoluted than ever before. Increased physical flows and rising complexities, especially in the face of highly volatile markets, have thus increased attention towards developing a more agile, flexible and environmentally sustainable supply-chain-infrastructure paradigm. Artificial intelligence is expected, in this regard, to be the primary driver of said transformation. McKinsey writes:
“An integrated end-to-end approach can address the opportunities and constraints of all business functions, from procurement to sales. AI’s ability to analyze huge volumes of data, understand relationships, provide visibility into operations, and support better decision making makes AI a potential game changer. Getting the most out of these solutions is not simply a matter of technology, however; companies must take organizational steps to capture the full value from AI.”
AI will have to prove to be the holistic bond linking multiple functions of the supply chain, including logistics, procurement, production, marketing and sales. Integrated planning will thereby enable firms to not only increase operational sustainability and resilience, but also help bring together the manufacturing and logistics supply chains, provide premium service levels as well as implement demand-sensing for short-term changes. In fact, a recent IBM report, to this end, even found that over 80% of the supply chain executives surveyed believe cognitive computing would completely transform their demand planning and forecasting capabilities.
Recent research from McKinsey has also found that successfully implementing AI-enabled supply-chain management technologies has enabled early adopters to reduce logistics costs by 15%, inventory by 35% and service costs by up to a whopping 65% when compared to competitors.
The solution features implemented by some of these firms include “demand-forecasting models, end-to-end transparency, integrated business planning, dynamic planning optimization, and automation of the physical flow—all of which build on prediction models and correlation analysis to better understand causes and effects in supply chains.”
An oft-cited study by Absolute Markets Insights found the global Logistics and Supply Chain AI-Market ecosystem to be valued at $1.7 billion in 2018, expected to reach $12 billion in 2027, growing at about 24% annually. While this statistic is rather old and will have undergone several changes in the recent past, what’s rather interesting to note is that, given the lucrative scope for the industry, several start-ups have started entering the foray for a share of the pie.
Marble, a US-based startup, raised about $10 million to create a fleet of intelligent courier robots, while Evertracker, a German technology firm, has been matching IoT applications with AI to enable inaccessible objects to communicate. Start-ups such as these have been instrumental in revolutionising logistics and supply chains.
In fact, leading players in the market such as FedEx, UPS, DHL etc. too have taken major strides in upgrading existing processes and implementing new technologies using AI in several aspects such as risk management, supply chain planning, warehouse management, virtual assistants, freight brokerage etc.
It is as IBM puts it: supply chain is, indeed, a natural fit for AI.