Disruptive Technologies that are changing the Supply Chain and Logistic industry
“AI will determine the new normal in how global supply chain and logistics companies run their businesses, in a manner that’s automated, intelligent, and more efficient.”
The current COVID-19 situation has disrupted the supply chain and logistics business like we have never seen before. Enterprises are placing their focus on securing their personnel and reviewing supply chains in an attempt to achieve some kind of business continuity amidst the chaos. This situation has made us realise that right now, more than ever, the market needs faster and more flexible systems to cope. The ever-growing demands have caused complex supply chains to lose oversight and visibility, which are currently being worsened by the residual effects of the pandemic.
While these issues need to be addressed, there are already several existing gaps where we see an increased need for AI-based innovations.
“McKinsey & Company expects businesses to gain between US$1.3tr and US$2tr a year in economic value by using AI in their supply chains.”
Innovation need #1: Understand and anticipate consumer demands
Knowledge based recommendation engines with predictive analytics
E-commerce platforms are evolving at hyper speed. From purchase to delivery, we are seeing innovators like Alibaba staying ahead by providing an omnichannel experience that is seamless and fuss free for the customer.
“Jack Ma of AliBaba predicted a seamless merger of offline, online and logistics for a dynamic new world of retailing. His vision now can be seen in the millions of mom-and-pop stores throughout China that are taking on new life as order-and-delivery stations for e-commerce.”
E-businesses managing supply chains today need to stay ahead by creating demand instead of following it. This can be done through studying consumer purchase patterns, similar audience profiles and creating anticipatory scenarios to recommend ‘what’s next to buy’ or ‘you might like these’. These demand creation tactics that we see today used in the electronic store ‘Best Buy’ to show recommendation in Netflix is achieved through a knowledge based recommender engine. Coupled with predictive analytics, it makes it easy for analysts and administrators to gleam the insights and act on them.
An example of course recommendations based on user’s browsing history
Innovation Need #2: Better collaboration between retailers and delivery teams
AI cloud sharing systems
There is a crying need for more mature innovation in cloud platforms or cloud sharing to provide faster and flexible last mile services to cope with dynamic conditions in the market. Many companies now outsource their last mile deliveries to Uber / Grab in new markets where labour strikes are frequent or when in house talent costs are higher. An integration or sharing platform is vital so that information can be transmitted smoothly.
Two major disruptor companies – InstaCart and Shipt – have now been attempting to fill this gap. Traditionally, shops or supermarkets outsource the delivery of your order to a third party vendor as we have mentioned, and sometimes orders get lost or delivery information is not communicated. InstaCart and Shipt offer personalised shoppers to visit these places to purchase your items for you, and then make the delivery to your doorstep so these problems are omitted.
Traditional logistics systems are also being challenged year after year, leaving companies to crack their heads on how to stay creative, marketable and in turn profitable. Even Logistics Giant DHL was not spared! They also had to think out of the box to partner up with various events companies to showcase their innovative solutions for complex logistics tasks in sport, arts and culture arenas. These world-class events enhance the profile of the DHL brand and provide an excellent platform to experience DHL logistics “live”.
If there is a more efficient cloud sharing system to prevent the loss of data transfer between the retailers and delivery companies, larger volumes can be handled and costs can be reduced significantly.
Innovation Need #3: To cope with rising operating costs and competition
Autonomous transport and storage systems
It will be a worldwide challenge to find a greener fuel alternative that is more eco-friendly and sustainable long term than their volatile fossil fuel relative. Reducing their carbon footprint has become a priority for some of the largest logistics operations in the world, such as Heineken, Walmart and L’Oreal, because there is a need to reduce fuel consumption globally.
The introduction of electric vehicles or hybrid vehicles will lower operating costs for companies. For eg, Amazon has ordered 100,000 electric delivery vehicles from Rivian, a Michigan-based producer of emissions-free electric vehicles as a more sustainable option in the long run.
As the supply chain and logistics industry continues to grow, naturally an efficient storage and processing analytics system would be required to optimise schedules and storage facilities. Logistic processes are complex and include the integration of various elements and data points for a smooth workflow.
For eg, PSA is using an AI-powered vessel traffic management system that is able to predict congestion hotspots and assists vessel route planning at the new Tuas mega port.
AI powered chat and extraction for customer operations
Logistic work is a no-fail, ’round the clock’ operation thus many organisations deploy time zone friendly offices to manage the heavy paperwork involved.
AI today can augment this and bolster efficiencies and lower error rate in document processing. This automation can be done through a document extraction system that can read and identify key information from unstructured documents, clean the ‘noise’ of scanned document and populate a CRM or billing collection system. Vendors can submit these information through a virtual assistant that can facilitate the extraction process could further reduce cost in customer service operations.
An example of an invoice or document in a cloud system: the data points extracted are highlighted in yellow in the document viewer
For more information about TAIGER AI solutions, click the button below to schedule a product demo with us.