Digital transformation has driven the acceleration of many trends and capabilities, especially in the wake of an unpredictable pandemic that has presented businesses with many challenges in terms of decision-making and forecasting. Companies are becoming increasingly aware of the importance of their data and the need to harness it to make better decisions. This has led to renewed conversations about artificial intelligence and machine learning (AI/ML) as a tool for predictive analytics, scenario planning, forecasting, and model building that can enable companies to predict events ahead of time, allowing for quick and efficient response to new developments.
In order to tap into the potential of predictive analytics, organizations must first modernize the underlying data platform. For many organizations, their data is still stuck in silos, either on-premises or in old school data warehouses. There is a major shift in companies modernizing their platforms and taking their data to cloud platforms like Snowflake and Amazon AWS to harness the data they have and use it for better decision making. Without a centralized location for your data, it’s impossible to tap into the potential it holds.
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Applying Predictive Analytics in a Pandemic
One of our large North American healthcare clients was especially susceptible to the unpredictability of the pandemic and it was directly impacting their operations. Across the country, hospitals were experiencing a sudden burden as COVID-19 spread, as well as a surplus of doctors and surgeons that worked in elective specialties which were halted when the pandemic began. However, the client knew that with the right data platform and AI/ML capabilities, this situation could provide an opportunity to quickly delegate the doctors that could treat respiratory conditions to hospitals with the most demand. With the situation on the ground changing rapidly, the company needed real-time capabilities to match the demand signals and status of the hospital – whether they were in a hot spot or had a surplus of doctors – and the best course of action to dispatch physicians accordingly.
Unfortunately, this wasn’t possible with their existing data environment because it was spread out across multiple silos. Once Ness modernized their data platform, the company was able to benefit from a scalable and sustainable platform that provides access to actionable data in real-time. Now we’re able to add AI/ML capabilities to enable predictive analytics that will use COVID-19 case work growth and trajectory to predict the next hot spot and how demand for their services will change.
Monetizing Your Data
Data modernization is only step one in an innovative data analytics strategy. Once the platform is modernized, organizations must consider how to use that data. This is what we call data monetization. Â It’s especially valuable for sales teams, arming them with the information needed to make data-driven decisions.
With a modernized data platform, sales professionals can classify all their data according to a variety of different criteria, allowing them to organize the info by vertical, geography, sales representative, practice area or any other classifier available. This info can be used in real-time, but with AI/ML capability it can also predict future customer behavior that sales professionals can use to respond more proactively to customer trends rather than reactively. For example, email sentiment analysis can alert representatives if a customer is a flight risk, and matching sentiment analysis with pipeline data can inform the chances sales has of winning a deal. This capability can be combined with robotic process automation (RPA) to automate tasks upon a certain trigger. For example, engaging a customer that is at risk of leaving with a customer service check in or an exclusive deal.
The Future of Business is Data-Driven
Organizations are increasingly asking themselves what kind of questions they could answer with better access to all their data in one place. With the answers to these questions, how might they increase revenue? How much more profitable might their deals be? How can they improve customer retention? As a sales leader, my teams need to be able to make the most informed decisions possible. This got harder in the COVID pandemic, but with modernized data platforms and strategic-minded sales professionals, it’s possible to monetize data for informed decision making and more agile operations.
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