Data is key in helping to deal with the impact of Covid-19 and intelligent systems can help organisations allocate resources more efficiently.

By Akesh Lalla, SAS country manager

This pandemic has impacted the world, affecting multiple sectors on a global scale. Being able to respond quickly to managing the impact of the virus has been challenging for both the public and private sectors, but Covid-19 modelling can optimise resource allocation.

Combating a global fight

To assist our public and private sector partners contribute purposefully to combating a global fight, SAS approached the disruption of Covid-19 by dividing it into three phases.

In the Response Phase, we provided rapid data management for partners, enabling them to look at a situational analysis within their unique environments like supply chain disruptions. This allowed them to respond and adjust accordingly in areas such as capacity planning, in preparation for disruption.

The Recovery Phase assists partners to go back to familiar processes in unfamiliar environments, modernising their operations within that new normal. This allows them the ability to adapt in areas such as changes to their supply chains.

The Reimagined Phase assists partners in preparing their organisations for the future by planning for new operational models in areas such as virtual communication.

Insights have local impact

Covid-19 is a worldwide healthcare problem that has local impact. Following our Health Minister’s comment that we are now in the eye of the storm, being able to use technology to manage resource allocation is more important than ever and data can help us all.

Insights on the regional impact of non-pharmaceutical interventions during this time, such as social distancing, closing non-essential businesses and schools, is also helpful. Local monitoring is critical because it allows for resource allocation and resource planning.

Our modelling techniques are important to identify not only the magnitude of the impact, but also where our partners are placed within the impact zone. International collaboration is especially vital during a pandemic, assisting our partners to identify what needs to be done within their unique environments to mitigate risk and optimise value.

Software for all scenarios

To identify meaningful trends in the global fight against a pandemic, our outbreak analysis sits at the crossroads between public health planning, field epidemiology, methodological development, and information technologies.

In the case of combating Covid-19, medical resource optimisation means creating optimal operations to maximise impact at a sustainable cost. Our software achieves this by building models on contact tracing and infection chains, for instance, through various information sources, including incorporating telecom data.

Our software generates data that serves partners at all levels of industry, helping them to identify disruptions, anticipate disruptions in their supply chains and forecast demand planning.

Data analytics enable future preparedness

We do not know everything about this virus, but we can look at trends and apply artificial intelligence and data analytics. This uncovers new insights to deal with the impact, assisting partners to optimise resource allocation in view of future preparedness.

Since analytics is interconnected, our software creates risk models that enable partners to scenario plan. For various industries, worst-case, best-case, and average-case scenarios can be built to help organisations allocate resources more efficiently. Covid-19 may very well be the first of many pandemics and the ability to scenario plan could literally save lives.

We are proud of the work we have done, in collaboration with other great minds, during this extraordinary period in our collective history. Our aim is to make analytical capabilities available to extract useful insights for societal good. Our hope is that data-driven decisions can lead the way in saving lives, reopening society, and identifying where the next hotspots are, while combatting Covid-19.