How artificial intelligence is transforming the global supply chain
It’s no secret that the siloed nature of supply chain data has created large scale macroeconomic inefficiencies, resulting in inaccurate forecasting of supply and demand, failed logistics planning and execution, and missed opportunities due to poorly understood risk. This amounts to billions of dollars in lost revenue for supply chain stakeholders, and trillions in reduced growth for the global economy.
In 2020, however, artificial intelligence (AI) will significantly enhance existing supply chain operating models. It will optimise and automate many pivotal supply chain processes, from inventory selection and warehousing to shipping and delivery routing, driving sales uplift and unlocking significant sums in dormant value.
Indeed, AI was identified by Gartner as one of the top eight supply chain technology trends in 2019 — an acknowledgement of its significant potential to disrupt the way retailers and manufacturers operate. Further, McKinsey estimates AI could unlock between $1.3 — $2 trillion of economic value in the supply chain and manufacturing industries.
Its potential is clear, but how precisely is AI transforming the global supply chain?
Automation
At the core of AI’s value proposition is the ability to automate the analysis of trade data, unearthing patterns that will allow businesses to achieve greater efficiency, minimise waste and drive growth. It is capable of levelling the playing field in an industry dominated by a small group of monolithic corporations — chiefly, Amazon — by allowing businesses to use their data to better understand customer buying behaviours.
AI-powered supply chains can reduce operating expenses and deliver enhanced planning capabilities that allow businesses to more effectively respond to current and anticipated customer demand in real time. Using AI, businesses are able to identify which products should populate retail shelves, and which stock-keeping units (SKUs) may no longer be needed, or needed in the same volume. This helps businesses get the right goods, to the right place, at the right time, for the right price — leading to higher gross turnover at an improved margin.
Predictive analytics in demand planning, driven by AI and machine learning, is already being used to analyse hundreds of demand-influencing variables (such as publicly available commercial, weather and sensor data). With these tools in place, forecasting errors have already been shown to fall by 30–50%.
At a practical level, AI tools can also be used to execute time-consuming manual tasks that have traditionally occupied human workers. In addition to streamlining processes, this frees people up to concentrate on strategic tasks that can add further value to their organisations and the supply chain as a whole.
Optimisation
In addition to automating analysis and decision-making processes, AI is also capable of creating new efficiencies by optimising delivery, transport and shipping routing. Small-scale performance optimisations of this variety can generate considerable value for supply chain businesses.
The unnecessary transport of goods and poorly optimised routing are significant barriers to building both a profitable and sustainable supply chain. Any logistics activity that results in the needless transport of inventory increases the cost and carbon footprint of the supply chain without cause.
According to a report from the Environmental Defense Fund, a typical long-haul truck drives empty for more than 14,000 miles each year, consuming 2,400 gallons of diesel and emitting more than 26.4 tons of carbon dioxide. Beyond the obvious environmental impact, the movement of a cargo-less truck also represents an underutilised asset, which could be deployed in a capacity that provides value. Today, AI’s role in the ‘uberisation’ of trucks and digitalisation of freight bookers such as Convoy (backed to the tune of $400million by Bill Gates, Jeff Bezos and Al Gore’s Generation Investment Management), is reducing wasted time, empty trailers and even tailpipe pollution for truckers.
Like a ship that has sprung a leak, the global supply chain haemorrhages value with every unnecessary mile travelled. Artificial intelligence, however, can plug the gaps, increasing efficiency and saving costs by optimising routing and transport processes.
By drawing information from disparate points in the global supply chain and making a high volume of small-scale optimisations, supply chain businesses will see large scale improvements in profit margins.
It’s clear that AI is a monumentally powerful tool, capable of unlocking significant value for supply chain businesses across manifold use cases. However, though progress is quickly being made as more organisations recognise the value of AI, the full extent of the technology’s power to transform the supply chain has not yet been realised.
In the coming years, artificial intelligence will become an indispensable tool — a mainstay of all supply chain businesses that hope to remain competitive in an increasingly ferocious market. By optimising and automating critical supply chain processes and providing an unprecedented level of insight, AI will underpin the most efficient and profitable global supply chain to date.
