Predictive analytics enables companies to predict events ahead of time, allowing for quick and efficient responses to new developments.
In a recent interview with SalesTechStar, Chief Growth Officer, Drew Naukam dives into the impact the COVID-19 pandemic has had on digital transformation. The pandemic has presented businesses with many challenges in terms of decision-making and forecasting. As a result, digital transformation has driven the acceleration of many trends and capabilities, including the focus on artificial intelligence and machine learning (AI/ML) as a tool for predictive analytics.
In order to maximize the potential of predictive analytics, organizations must first modernize the underlying data platform. Data previously stuck in silos is shifting to cloud platforms like Snowflake and Amazon AWS, allowing the data to be harnessed and used for better decision making. Without a centralized location for your data, it’s impossible to tap into the potential it holds.
Applying Predictive Analytics in a Pandemic
Across the country, hospitals were experiencing a sudden burden as?COVID-19 spread. Among them was one of our large North American healthcare clients, the unpredictability of the pandemic was directly impacting their operations. However, with the right data platform and AI/ML capabilities, the opportunity arose to quickly delegate the doctors that could treat respiratory conditions to the hospitals with the most demand.
With the situation changing rapidly, real-time capabilities are needed to match the demand of the hospitals and dictate the best course of action to dispatch physicians accordingly. Once Ness modernized the client’s data platform, the company was able to benefit from a scalable and sustainable platform that provides access to actionable data in real-time. Through the addition of AI/ML capabilities, predictive analytics will use COVID-19 casework growth and trajectory to predict the next hot spot and how the demand for services will change.
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