What Data and Analytics Will Look Like in the Post-COVID World

Most organizations are now asking themselves very challenging questions, ones that will change their data and analytics strategies for years to come. Who should have permission to access specific data, and for what purpose? Does our workforce have the requisite skillsets and mindsets needed to work effectively with data? What technologies do we need to adopt for data optimization and utility? How can we effectively execute change management and best leverage our workforce to ensure a smooth transition to new ways of operating that enable short- and long-term success? In essence, how can the organization become truly data-driven?

The Mass Pivot to Cloud and SaaS is Here to Stay

What these organizations are really embracing is the importance of an integrated data and analytic strategy. They’ve quickly realized an integrated strategy is essential to seizing opportunities and making quick pivots to match market volatility that will be the new norm for years to come. And that strategy heavily centers on accelerated adoption of cloud and SaaS.

In fact, most customers we talk to have drastically accelerated their plans for wider deployment of SaaS and cloud-based data and analytics models. This includes the entire data supply chain lifecycle, whether it’s for data storage, ingestion, delivery or self-service analytics. Companies that continue to resist this pivot are going to quickly see erosion in any competitive advantage they may have had previously. Relying on legacy on-premise data environments eliminates the tremendous scalability and cost-savings benefits, along with the nimbleness and real-time access to data, inherent in successful cloud and SaaS data and analytics deployments. Organizations that realize these benefits will be able to invest in other areas that help them outpace more static competition.

However, despite the embrace of the SaaS and cloud-based models, what many organizations forget is this acceleration also comes with inherent cultural challenges. How do you get everyone on board, from line workers to senior executives, so the whole organization embraces a new way of working? And, just as important, how do we get IT and technology specialists – those who manage the data and analytic environments – to embrace a new charter, one that serves a workforce with self-service versus being the data gatekeepers?

Organizations Must Get Outside of Data and Analytics Comfort Zones

Both the C-suite and data specialists are being pushed beyond their comfort zone with respect to data security, sovereignty and governance. Organizations that have started to embrace SaaS and cloud to democratize data are addressing only one of the barriers on the way to creating a data-driven culture. Organizations must also tear down the perceptual and conceptual barriers that pigeonhole workers into binary categories of those who are educated in data and those who aren’t. There are many readily available solutions and approaches to bridge this perception gap. There are great advances in augmented intelligence embedded into analytics platforms to enable nascent users to explore data more confidently and successfully. There’s also been tremendous growth in data literacy initiatives and free training that can improve data skills democratization. Organizations must leverage these tools and trainings to create a culture where everyone, not just the IT specialist, the app developer or the warehouse architect, is more able to successfully work with data.

As self-service analytics is democratized and the workforce gains more access to more data, IT and business analysts must evolve their charter to expand beyond core dashboard creation and setting up data repositories. They need to see themselves as change agents, fostering a culture in which users of all skill levels are empowered to make contributions within the analytic ecosystem. Data specialists should be at the vanguard, exhorting users at every level of the organization to avail themselves of self-service to solve problems and to make ad-hoc use cases. IT has the opportunity to become data stewards and enablers, helping to propose new ways of organizing and providing data, identifying process improvements, scoping business opportunities and driving operational efficiencies.

Data Specialists Become Evangelists and Champions of Change

This can only happen when those holding the keys to the data kingdoms do not see this evolution – from makers and builders to evangelists and champions – as a threat to their value and necessity. Of course, they will still need to be stewards, ensuring that the systems are functioning and that the data and analytic environments are compliant with regulations, from concept to deployment. But, instead of seeing themselves as diminished and marginalized by an increase in data-informed users in their midst, these specialists should see their roles as expanding. They need to recognize that they are becoming catalyzers and galvanizers, marshalling great value for their companies by leading the data literacy charge. And, not just them, but all workers at an organization should feel data enablement as an upward inflection point in their careers, with everyone enriching their careers and helping their companies thrive.

This is the true message that will carry the day into tomorrow. We can become more in times of crisis and challenge by transcending existing ways of doings things, evolving past practices and looking outside the boundaries of convention. As much as we may initially think of COVID and the post-COVID world as a time of contraction and retrenchment, it can also be a time for redefinition and growth. For organizations everywhere, from fledging startups to century-old, multi-billion-dollar international corporations, the moment to embrace new data and analytics models is now.