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Data-driven logistics is the new normal

30 Oct 2022

  By Thilina Siriwardena  After the pandemic, many logistics and freight forwarding sector professionals were quick to pinpoint several weaknesses in their supply chains. These included the lack of visibility of inventory (in-transit or static) and how it could be affected by dynamics that are beyond the scope of its supply chain.  In such a context, the capability to efficiently cooperate with various stakeholders across multiple tiers of the supply chain is becoming increasingly critical. Reliable, precise data shared by and visible to all parties is key to improving results and reducing costs. Logistics is all about networking. These networks include robust partners – both experienced and startups like Envio Global. Regardless of size or experience, companies are progressively turning to emerging technologies like Artificial Intelligence (AI), blockchain, big data, and Internet of Things (IoT) to understand how their supply chain might be impacted by problems with their operations, customers, and suppliers on a more granular, real-time, and physical level.  Since the pandemic started, I have engaged with some of our partners to understand how they use emerging technologies to navigate through these testing times. Here are three areas of focus:    
  • Making supply chains and risk management resilient
    Extreme weather conditions, physical damages to trucks/vessels, or severe cyberattacks could threaten service and critical supply levels of a logistics service provider. In return, customers will lose trust in the company, incurring brand reputational damage and major costs that could impact bottom line performance. Managing both mid-term supply planning and ongoing transport operations with the mindfulness of risks and safety incidents is becoming vital. Many firms have taken steps to digitise their supply chains, but they have not essentially focused on the likelihood of improving supply chain visibility/traceability and resilience planning by incorporating external data. This is why logistics and freight forwarders turn towards big data. Risk management solutions enabled with big data help companies achieve enhanced visibility of potential risks on a global level to supply chain operations and react to near real-time incidents during both planning and execution. It also helps to proactively inform customers of potential delays and delivery disruptions, offering value-added information services, avoiding loss of reputation, and protecting their company’s top line.     
  • Strengthening tracking and traceability
    Modern supply chains are complex. They frequently involve stakeholders from within interconnected networks that span multiple tiers and geographies. From monitoring the transactions and the movement of assets or goods across organisations to detecting the conditions of products, managing these supply chains have become more challenging. For distributed organisational structures and operations, legacy systems of the past will not cut it. This is why many logistics providers are now turning to blockchain that facilitates distributed ledger architecture.   Volvo Cars, for example, became the first carmaker to implement global traceability of cobalt used in its batteries by applying blockchain technology. With the supply chain now visible, traceable, and verified by blockchain, both Volvo Cars and its customers can be assured of the integrity of car parts, responsible sourcing, and compliance with regulations.     
  • Leveraging volumes of data for well-timed decision-making
    Adopting emerging technologies is great. However, what it means is that companies are generating massive quantities of data. For companies, analysing and interpreting such huge chunks of information is a huge struggle. Furthermore, to do that in a limited timeframe to harvest actionable outcomes is hard.  This is why it has become vital to find a suitable balance between machine and human intelligence to capitalise on the value that new enabling technologies offer in day-to-day supply chain operations, with companies increasingly turning to machine learning and AI to enhance the decision-making process. Many consumer goods organisations are leveraging cloud, IoT, and AI to make data-driven decisions. They combine internal and external data to deliver real-time visibility and analytics, whilst utilising IoT and machine learning to drive better predictive maintenance.    Charting the course   There is no doubt that logistics and supply chain processes are meant to become more customer-centric, autonomous, and resilient. However, they will be vulnerable to a variety of risks. With things returning to normal for freight forwarding and logistics companies, they have been offered a unique opportunity to evaluate their supply chain process and put in place the technological foundations. This will let them withstand the shocks and yield significant benefits in the long run.  (The writer is the Chief Executive Officer of Envio Global Logistics) 


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