Data Analytics and COVID-19
Data analytics is becoming more important than ever as COVID-19 sweeps across the globe bringing chaos in its wake. In these challenging times the economic and societal effects of the pandemic are starting to become evident, as lockdown eases in many countries and the ‘next... Read more
Blog30th Jul 2020
Data analytics is becoming more important than ever as COVID-19 sweeps across the globe bringing chaos in its wake. In these challenging times the economic and societal effects of the pandemic are starting to become evident, as lockdown eases in many countries and the ‘next normal’ becomes a reality.
Many organisations are trying to prepare recovery plans based on data analytics. These analytics can help provide insights into in people’s behaviour during the pandemic and what those changes may mean for any recovery strategies.
Organisations dealing with changing conditions will need to be able interpret where they are now and plan how to move forward. Data modelling can help organisations understand the potential implications of various recovery plans as they decide how to balance evolving demands and changing capacity in the workforce. Analytics can also help support organisations by forecasting customer demand, potential disruptions to supply chains and support services, identify at-risk employees and the impact on finances and other associated KPIs.
Existing data models with the ability to forecast data into insights about behaviour of customers, suppliers and employees will need to be adapted to model any changes due to the spread of COVID-19 and other associated factors as the situation evolves. Financial models could also be adapted to forecast how revenues, costs and cash flow might change during the pandemic, particularly when the recovery phase starts.
Even with short timescales the quality of data analytics can make a significant difference in generating insights that can be used to understand different scenarios:
- Relatively simple visualisations such as bar charts, line graphs or heat maps can be an effective way to understand the effects of the virus and its associated variables.
- Machine learning and natural language processing could be used to examine customer or employee activity and help optimise constrained resources or forecast demand.
- Geographic and demographic data could be analysed to generate behaviour patterns in various regions. Combining this with HR and Operational data could provide insights into items such as sick leave, working patterns and return to work/office schedules.
- An insight based approach to analysis can also be used to stress test the processes included in the recovery plan and be updated based on the forecasted view of inputs and outputs. This can help identify any processes that will struggle to operate with constrained resources.
By understanding the links between analytics and COVID-19, business leaders can make informed decisions on how to bring about beneficial recovery strategies for their organisations.
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