On October 25th, Faculty – spoke at the Applied Machine Learning Days (AMLD) on how we helped the NHS navigate the Coronavirus crisis and their similar work helping other organisations build resilient supply chains.
The AMLD is a global platform for AI and machine learning experts to share insights from the forefront of the technologies and showcase their real-life applications. The session covered the role artificial intelligence plays in resilience across industries, specifically covering the creation of the NHS’ Early Warning System (EWS), Faculty’s approach to AI in supply chain management and the importance of AI safety within these solutions.
Below is a brief overview of the topics covered during his talk and some of the insights shared with his audience.
The NHS Early Warning System
Faculty has worked with the UK’s National Health Service since the beginning of the COVID-19 pandemic to forecast future demand for the healthcare system with AI. The EWS predicted potential strain on essential infrastructure and services. This meant decision making, policy and risk assessment could be made with a greater level of accuracy and much greater agility, helping NHS staff save thousands of lives.
But building life-saving technologies that are trusted by the humans using them is yet another challenge our team had to tackle. During our presentation, we explored the technical challenges associated with AI safety and how Faculty’s Operational Intelligence Suite curbs this problem by providing accurate forecasting decision makers can be confident in.
Build supply chain resilience with AI
Protecting workers and citizens during the global crisis required access to specialist equipment and resources, such as PPE and ventilators, both of which were scarce when the first wave of the pandemic swept across the UK. With EWS forecasting key metrics such as hospital admissions and bed capacity up to three weeks in advance, the national supply chain could ensure all hospitals had sufficient oxygen and ventilators available for patients.
With EWS forecasting key metrics such as hospital admissions and bed capacity up to three weeks in advance, the national supply chain could ensure all hospitals had sufficient oxygen and ventilators available for patients.
Creating supply chain resilience under the pressure of a readily-evolving global pandemic and a host of other external factors necessitated a new approach. Many organisations rely heavily on technologies weighed down by poor performance, that garner limited confidence amongst their users and promote reactive decision-making. AI-based solutions (like Faculty’s Operational Intelligence Suite) provide accurate data sources, trustworthy forecasts and actionable insights – but only when organisations are prepared to use AI for the supply chain forecasting.
If you’d like to learn more about Faculty’s work with the NHS and how we use AI for supply chain planning, get in touch with us through our contact us form.