Protect against disruption by becoming a better partner

The supply chain will never be immune to disruptions — some things are simply unpredictable.

But one thing is certain: the ability to rapidly innovate and adapt will be vital for companies in the supply chain ecosystem. In this increasingly complex industry, the supply chain never sleeps. With new challenges on the horizon, companies should equip themselves with the talent, tools and resources to navigate any disruptions and deliver real results. 

Digitisation, advances and access to technology that enable highly-digitised supply chains is now accessible to all sizes and sectors of the supply chain industry. While we’ve been talking about the potential of the digital supply chain for more than two decades, the balance is finally shifting from future potential to current benefits in terms of delivering collaborative, fast, agile supply chains with data-driven precision. Based on my experience from managing complex supply chains and leading logistics crisis, here’s some insights into how supply chain organisations can embrace digital technology to mitigate risk from supply chain disruption and become more strategic and valuable partners to their customers.

Predictive analytics elevates risk management

Weather-related, environmental, geopolitical, or countless other factors can significantly impact the flow of goods across the supply chain. Predictive analytics gathers data from multiple areas to analyse external trends and suggest how these factors and potential risks are likely to increase costs, delay the flow of goods or cause additional issues. This insight helps improve risk management and mitigation planning in the supply chain.

For example, each year, storms put an incredible strain on the supply chain as flooding and power outages close ports and prevent trucks from entering affected areas. Predictive models can provide a look at what the atmosphere is going to look like in the coming days, so companies can make data-informed decisions like whether their trucks should hit the road or not. And while predicting the path and impact of storms is not a perfect science, leveraging analysis from previous storms arms companies with important information like which roads to approach and avoid, where utilities are likely weakest, and the most efficient path to the destination.

SEE ALSO:

• Top five coolest women making waves in the supply chain sector

• What's next for the logistics industry?

• How American Express uses Big Data to transform operations

• Read the latest issue of Supply Chain Digital here!

Supply chain managers can use predictive analytics while monitoring shipment events to accurately predict estimated time of arrivals (ETAs) and facilitate proactive resolution of disruptions by planning the movement of their goods accordingly. Meanwhile, the application of prescriptive analytics will allow systems to flag any exceptions and make informed predictions to improve supply chain performance, resilience, and responsiveness.

IoT to improve the flow of products 

Connected devices and IoT-enabled solutions are giving us more data than ever to make better decisions — connecting the legs of the supply chain path while simplifying information exchange. To improve the flow of products and information from point A to point B, shippers are adding sensors on almost everything, not just the most expensive equipment.

IoT devices can help address some of the inefficiencies associated with visibility challenges. They can be attached to vehicles, storage containers or goods and provide a constant update of their location. Access to this live location data enables organizations to track their deliveries with real-time shipment visibility, providing insights into first- and last-mile pickups, delivery milestones and shipment status across all modes.

Integrating AI & Machine Learning for supply chain optimisation

Artificial intelligence plays an important role in optimising the modern supply chain, and in our advancing field, business leaders who aren’t already implementing AI run the risk of falling behind and will struggle to maintain, or obtain, a competitive edge. For example, natural language processing (NLP), a technology that helps computers understand and even interact with human speech via AI and machine learning, reduces administrative overhead in the supply chain. And among its many benefits to the field, NLP can eliminate language barriers, which in turn improves supplier relationships and customer service by allowing for smoother communications and seamless interactions regardless of the situation, locations or parties involved. AI technology is also essential to planning transportation routes for containers when there is severe weather in the forecast. In this situation, a modern, digital supply chain would be able to quickly reroute containers to circumvent the weather because the supply chain technology took into account data from accurate weather forecasts.

But implementing AI will take much more than slapping a machine learning overlay atop a transportation management system (TMS). Supply chain leaders who are just getting started with AI implementation can begin by identifying their operational challenges and prioritizing them. Is the most pressing challenge getting goods from point A to point B in a timely manner? Is it predicting the required quantities of goods six months in advance? Once supply chain leaders know where they need to first direct their attention, they can apply the best data to coming up with a solution.

For more information on all topics for Procurement, Supply Chain & Logistics - please take a look at the latest edition of Supply Chain Digital magazine.

Follow us on LinkedIn and Twitter.

By Ronald Kleijwegt, Vice President of Sales for EMEA, Blume Global