The global logistics industry today is worth US$4.7 billion, and set to grow to $12.2 billion by 2022. The digital revolution has significantly spurred progress in the sector, and AI has played a key role. The networked structure of logistics lends itself well to the implementation of AI systems, boosting efficiencies from end to end.
Companies that don’t adapt run the risk of being outpaced by competitors, and rendered obsolete. So what are three key benefits of AI implementation in logistics?
Predictive demand and capacity planning:
Businesses across every sector appreciate the value of harnessing data-driven insights, and logistics is no different. Regardless of the issue being considered - whether the optimal shipping route, or forecasted sales volumes - it is data that drives success. Sophisticated new algorithms are capable of handling vast quantities of complex and varied data, and detecting patterns and correlations not obvious to humans.
Permutational analysis via AI equips businesses with the insights to improve planning and investment decisions. Within the specific context of supply chains, for example, AI allows companies to forecast predicted sales, and preemptively distribute stock closer to the customer before they’ve even ordered. This lowers the overall time and cost of shipping when the customer does then submit the order. Walmart is one retailer which has been highly successful with this approach, using AI and other emerging technologies to drive down costs and pass those savings onto the customer.
Perhaps a business is considering the optimal shipping route for a certain package. Previously, a human would have developed a set of rules and guidelines based on the respective storage, handling, and transportation costs. AI, however, has the ability to make swift calculations based on a much broader range of particular variables, all within the context of hundreds of thousands of concurrent orders, and in real-time. AI platforms can speedily consider specifics such as fulfilment locations, real-time changes in service levels and surcharges, and the effect of adverse weather on different modes of transport. This ability to make constant micro evaluations and adjustments provides enormous benefits to businesses - in terms of time, cost, and resilience.
We know that logistics companies are operating in an increasingly competitive world, under pressure to reduce costs, and provide higher service levels for reduced prices. There are plenty of back-office and internal functions (accounting, HR, finance etc.), which are renowned for involving plenty of detail-oriented, tiresomely repetitive tasks. It’s here that AI - via cognitive automation - offers the chance to save time and money, and significantly boost productivity and accuracy.
Cognitive automation is essentially about software bringing intelligence to information-intensive processes. It is the merging of AI and robotic process automation (RPA). RPA is distinct from AI in that it cannot learn beyond its initial programming, but it is very effective in using well-structured inputs from humans to execute repetitive, data-related tasks, such as filling in web-forms. When RPA is combined with AI’s ability to learn and improve processes, tiresome back-office processes can be processed with a significant increase in efficiency.
Let’s consider the role of cognitive automation in customs brokerage processes, for instance. This is a complex area of logistics, relying on in-depth knowledge of specific regulations, industries, and customers. There is constant cross-checking of information for shipping documents and invoices, which need to be accurate and completely harmonized before sharing with customs officers. The processes involved are time-intensive, and mistakes can be costly.
This is where an AI platform comes in. If effectively trained in industry regulations and brokerage data, it can use language processing to swiftly extract relevant information from a broad range of customs documents, and ultimately produce a customs declaration ready for human review. This significantly reduces the amount of man-power needed, and minimizes the opportunities for human error and oversight.
Resilience to market shocks:
COVID-19 and Brexit are examples of two market ‘shocks’, with long-term and far-reaching consequences, even beyond those we currently understand. In the case of the pandemic, it was difficult to predict the speed with which it spread globally, and the impact of disruptions across all parts of logistics operations.
Air freight, for example, represents just 1 percent of global trade in terms of tonnage, but 35 percent in terms of value. However air freight capacity has suffered severely due to the reduction of passenger flights during COVID-19. This has led to an overall surge in air freight costs, although the (often opaque) charges imposed by specific logistics providers still vary wildly. This makes logistics buyers’ jobs all the more difficult when it comes to picking optimally cost and time-effective routes.
Increasingly, companies of all sizes are investing in producing resilience-predicting data (such as DHL’s ‘Resilience360’ platform), which allows businesses to predict and mitigate risk quickly in almost real-time. Software like this minimizes disruptions from incidents, but also gives users a competitive advantage over those who aren’t utilizing it.
For logistics businesses, integrating AI allows for earlier and more intelligent responses to market shocks like COVID-19, and enables the management of otherwise critical disruptions within the supply chain. AI can help with intelligent route optimization, allowing businesses to assess - in real-time - the optimal alternative routes for shipments should certain options become less feasible (such as with air freight).
The ability to be agile and operationally cost-effective during times of crisis is key, and incremental gains from AI insights can help businesses stay ahead of their competition. Use of specialized AI platforms can enable customers to save 50 percent on their direct logistics costs, which can have a profound impact on short-term profitability.
It’s clear that the future of AI in logistics is filled with enormous potential, and the time is ripe for its widespread adoption. AI will accelerate progress towards more automated, proactive, and personalized processes across all parts of supply chain management, for both global organizations and smaller direct-to-consumer outfits. AI implementation enables businesses to make intelligent decisions which drive profit and growth, and thrive in an increasingly competitive market.
Matei Beremski, co-founder and chief product officer, 7bridges