COVID-19 has changed the world. We have seen a major shift towards virtual solutions, from telehealth, through remote workplaces, to increased online retail adoption. Consumers spent 50% more money online in August 2021 compared to pre-pandemic times. This, combined with unprecedented transportation uncertainties caused by the pandemic such as travel restrictions, flight cancellations and port lockdowns, has led to a global shipping crisis, characterized by significant delays, and increased shipping costs.
With “necessity being the mother of innovation”, the pandemic has become a driving force in the technological transformation of supply chains. According to the Wall Street Journal, investors are “pumping money into logistics technology”, with total investments in LogisticsTech startups surpassing $24 billion in the first 3 quarters of 2021, up by 58% from 2020.
Fueled by this new capital, the accelerated adoption of cutting-edge transport and logistics technologies is creating a technological revolution. These logistics technologies, based on data accessibility and powered by advanced autonomous algorithms are streamlining processes, promoting efficiencies, and providing a layer of increased resilience and peace of mind to logistics managers across the globe.
Here are some of my data-centric LogisticsTech trend predictions for 2022.
Better transparency and real-time visibility improve control and decision-making
Effective management of operations across supply chains and logistics networks requires real-time data access, shipment traceability, and end-to-end visibility of logistics process data. Data generated by a multitude of IoT sensors at all levels, from entire vehicles, planes, containers, and ships to the micro-level of each individual package and across multiple modalities, enables a new level of real-time insights and decision-making capabilities. Aggregating different data types, including location, condition-related data, fleet tracking and management data, together with operational data from IT management systems such as Enterprise Resource Planning (ERP) software and Transport Management Systems (TMS) ensures the highest level of customer service and improved collaboration between stakeholders across the entire logistics network.
Reducing risk while augmenting resilience
The aforementioned data visibility generates an ongoing stream of crucial data. By applying advanced analytics tools and models to integrated data sets from multiple sources, logistics managers can better prepare for any potential scenario or contingency. Computerized predictive forecasting, planning, and optimization models enable suppliers to decrease operational uncertainties, identify cost inefficiencies, and take advantage of previously inaccessible opportunities. As these predictive digital models are based on real-time data and events, they allow swift and flexible responsiveness, which in turn increases the resilience of the logistics chain– a critical goal for all stakeholders. Highly resilient logistics systems enable suppliers to commit to higher service levels which, subsequently, improves customer satisfaction and company competitiveness.
Streamlining complex processes with robotic process automation
Logistics operations are highly complex, with intermodal transportation and cross-border taxation and regulatory requirements contributing to this complexity. Logistics managers strive to lower complexities to ensure the smooth and optimized management of processes. Robotic Process Automation (RPA) leverages digitization and algorithm-powered automation to streamline various processes, such as order, inventory, and invoice management. These previously error-prone manual processes are now being automated using RPA. Advanced intelligent algorithm technologies are also being implemented in warehouse and stock management. RPA frees up resources that can be better allocated to revenue-generating activities and personalized service management, while decreasing errors and risks, leading to cost reductions and increased profitability.
Advanced analytics software, augmented intelligence and artificial intelligence will reduce financial risks of costing and pricing
Disruptions in the logistic world have resulted in a move away from pre-pandemic fixed pricelists to fluctuating spot pricing. Pricing uncertainties create significant challenges and financial risks for manufacturers and suppliers, as they hamper accurate logistics costing and pricing. Augmented intelligence algorithms offer predictive, automated cost-analysis which enables logistics companies such as freight forwarders to accurately price their services despite cost uncertainties. Logistics service providers are increasingly utilizing these tools to effectively compare carrier and shipper costs. This provides stability that improves their ability to offer end customers accurate and competitive price quotes which counters these recent costing and pricing uncertainties.
Supporting critical last-mile telehealth fulfilment
Telehealth adoption continues to grow rapidly in response to the pandemic, with 38 times higher utilization in July 2021 compared to pre-pandemic times; physician use reached 80% in 2020 compared to 25% in 2018. Refilling prescriptions is the second leading telehealth need, accessed by 26% of U.S. telehealth users.
Direct-to-patient prescription drug deliveries must meet regulatory standards through the last mile- the last part of the delivery journey. Gig-economy-style service providers who cannot ensure reliable regulatory compliance are not an option for prescription medication or crucial medical device home deliveries, which must be delivered in a safe and timely manner. Furthermore, some sensitive medications and devices require maintenance of specific environmental conditions, such as temperature control, throughout the last mile.
Enter last-mile cold chain delivery. Algorithm-powered technology platforms are alleviating the risks associated with regulatory-compliant home delivery of these products. Cold-chain technologies have been a requirement for the safe delivery of billions of temperature-sensitive COVID-19 vaccinations, under strict regulations. This year will see the expanded use of real-time, cloud-connected sensors and AI technologies working together to autonomously predict and pre-empt harmful changes in temperature and humidity, and project delays in timelines. Such changes must be dealt with efficiently, on the fly, to ensure a timely arrival, while meeting stringent standards. These advanced technologies will continue to support the trend of healthcare home deliveries, upholding the same strict requirements within this critical industry in the years to come.
Data-centric technologies crucial in 2022 and beyond
Supply chains have had to quickly evolve in as little as a few months to keep up with the paradigm shifts imposed upon the entire global economy by the pandemic, as well as to compensate for inherent limitations that require effective solutions for today’s trade and supply realities – both locally and globally. Fueled by this huge need for increased resilience and push to adapt, significant investment in, and adoption of, next-generation, data-centric solutions are accelerating, creating numerous opportunities. These cutting-edge technologies will become vital tools across supply chains and logistics networks, through 2022 and beyond.
Written by Eldad Granot, Co-founder & CEO, Amphorica