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Leveraging Artificial Intelligence to Rebuild the Sustainability of Global Supply Chains
Leveraging Artificial Intelligence to Rebuild the Sustainability of Global Supply Chains

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08 April 2020

Leveraging Artificial Intelligence to Rebuild the Sustainability of Global Supply Chains

Artificial Intelligence can play a differentiated role in not only predicting an outbreak but also in minimizing or stopping its spread worldwide.

The global healthcare system including pharma manufacturers, medical device companies and hospitals are being hugely disrupted right now. One of the problems to date has been the lack of transparency and open data which governments need to manage such an emergency with care.


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They can’t anticipate how their hospitals are managing to serve any patient at any time. They are lacking equipment and taskforce. Drug makers are forced to make stockpiles, change their main supplier to other second and third options for raw materials, or to diversify their products for vaccines/ medicaments to fight against this new virus, while challenging the FDA requirements in time and issuing quality approvals.

Artificial Intelligence Sustainable Supply Chain

Medical device companies are struggling too, to produce huge numbers of specific products such as CT scanners, smart thermometers for long distance, respiratory machines, masks and gloves to name few. Many global manufacturing OEMs have been striving to find alternative solutions as back up. Cases such as missed deliveries from primary suppliers, moving back some core business priorities to their main headquarters and sometimes re-tooling their production systems to make totally different products more suitable and in high demand for the current crisis.

In such a situation, Artificial Intelligence (AI) can play a differentiated role in not only predicting an outbreak but also minimizing or stopping its spread worldwide. It all depends if the government is welcoming such technology, converged in some applications with Big Data Analytics. And for sure it is, as governments are seeking any solution even from AI. In this context, AI can help to fight the coronavirus through 1) applications including population screening, 2) notifications of when to ask for medical care and 3) tracking how infection spreads around in space, time and numbers.

Some applications or use cases of AI to the outbreak Coronavirus are listed below:

  1. Automatic detection and cancellation of misleading information related to the virus posted on social networks.
  2. Highly accurate and precise chest CT scan machines to detect the virus-induced pneumonia and AI systems that use cameras equipped with computer vision and infrared sensors to predict people’s temperatures in public areas.
  3. 3D printing to produce a massive number of tools/ first aid, urgently useful for local intensive healthcare despite CE approval.
  4. Speeding-up and optimization of clinical trials of drugs and potential vaccines;
  5. Development of robotic systems to clean infected areas at hospitals and distribute food and medicine to patients.
  6. Online systems for the medical assistance of individuals under the category of medical devices as a software, or mobile healthcare for telemedicine.
  7. For production, we can leverage AI to resolve complex activities such as the verification of correct assembly of components and kits with deep learning, especially when coping with an emergency.

AI adoption is a marathon: To drive value with bottom-up insights. Many healthcare organizations are seeking to explore the vast potential of Artificial Intelligence (AI) and its four components — Machine Learning (ML), Natural Language Processing (NLP), Deep Learning and robotics, to transform their clinical and business processes. They hope to apply these advanced technologies to leverage the big data lake and to automate iterative operations that previously required manual processing with self-service AI platforms. In fact, successful implementation of predictive modelling and big data analytics are decentralizing the process by enabling real-time analysis of huge datasets generated through Internet of Things (IoT) and mobile devices at a global scale, leveraging the cloud infrastructure.

In companies adopting AI, their revenues are growing. 44 percent of these companies admit that this technology is bringing costs down. AI-powered applications are expected to add $13 trillion in value to the global economy in the next decade as declared by Mckinsey & Co. New research from HIMSS Media shows how healthcare organizations are turning to AI to keep up with the growing complexities of healthcare. Key finding: 75% of industry leaders reported that AI/ ML will be a greater focus next year, but only 40% rated their current predictive or prescriptive analytics as very effective.

Even if the world was not prepared for COVID-19, the AI community is working hard to deliver applications that contain the virus short term. So, we can evaluate the usefulness of AI technology in an epidemic situation vs the standard thermometers used by health officers to visually check travelers for signs of fever, coughing, and breathing difficulties. In fact, to rebuild global supply chain resilience after COVID-19, companies should explore the usefulness of Artificial Intelligence to create new applications for a fast prediction of emergency scenarios and massive delivery response in convergence with Big Data Analytics for population health management.

Stay tuned and stay safe with more trendy scenarios that can disrupt your global supply chains.


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