Automating Supply Chain Resilience Should Be High on Your Digital Agenda
To benefit from advanced risk identification tools and keep pace with customer expectations, companies need a new approach to supply chain resilience.
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Substantial investments in supply chain resilience have enabled companies to vastly improve their capacity for bouncing back after a disruption. But the digitization of supply chains is introducing new demands on company operations that require a different approach to building supply chain resilience.
With the benefit of digital technologies, companies are using Big Data to identify supply chain risks and create early warning systems with much greater speed and precision. However, the ability to respond to these signals has not advanced at the same pace.
Moreover, the gap between risk identification and risk response promises to become more severe as the rate of digitization accelerates. A survey of 30 global companies in various sectors released in October 2016 by The Center for Global Enterprise (CGE) found that 88% have incorporated elements of the digital supply chain into their business model. All of the companies surveyed were working to adopt game-changing technologies such as the internet of things and robotics.
To keep pace with the changing landscape, companies need to develop ways to automate resiliency.
The Next Level of Resilience
Enterprises use various strategies to make their supply chains more resilient. These include diversification of the supplier base, establishing safety stocks, and planning for spare transportation capacity. These strategies will continue to be important, but building resilient digital supply chains, or cyber resilience, requires a speed of response that can be achieved only through automation and smart software.
CGE characterizes a digital supply chain as “a customer-centric platform model that captures and maximizes utilization of real-time data coming from a variety of sources.” If a potential disruption is detected, the system decides on the best mitigation strategy and executes that strategy.
A relatively simple example is a loaded freight container equipped with sensors that track the temperature and humidity of the goods in real time. The data is analyzed using advanced business intelligence rules and shared with authorized entities in the extended supply chain. These parties can take remedial action should a problem be detected. For example, if the container readings indicate that perishable cargo has been damaged due to an equipment malfunction, an order is automatically placed for replacement supplies while the damaged shipment is still in transit. Such remedial actions are not confined to logistics; financial and contractual terms can also be adjusted when an unexpected disruption occurs.