Emergency operations centers are a vital resource for state and local governments, and they are starting to expand to their next logical iteration: virtual EOCs. These online, often cloud-based centers allow remote stakeholders to see what’s happening at a brick-and-mortar EOC. Virtual centers can also serve as EOCs in their own right, providing a virtual space for stakeholders to coordinate and share information.

Interest in virtual EOCs and virtual access to EOCs predates the pandemic. However, the events of the past year have reaffirmed the importance of being able to bring stakeholders together remotely, as well as the value of collaborative, real-time data analysis. In addition, virtualization enables participants to maintain social distancing without compromising their ability to work together to manage a crisis.

Many business and IT leaders understand the value that data analytics can provide but struggle to achieve the benefits. In some cases, organizations generate lots of data and create dashboards to visualize it, only to make an unfortunate discovery: They haven’t produced any insights that are actionable.

Deriving value from analytics requires insights around measuring specific changes or driving a particular action that the organization wants to take. This requires a few key steps.

Organizations use data analytics in a variety of ways: A health insurance company may want a way to identify emerging risk factors for disease in its patient populations; a nonprofit that connects bone marrow donors with people requiring transplants may look for ways to slash the time it takes to identify a likely match; a national retailer may seek to better understand the shopping preferences and habits of its target customers.

On the surface, at least, there’s little in common among these organizations and what they hope to achieve, but they each must excel at the same thing to succeed: They have to be adept at organizing and analyzing data, and they need a data strategy that ultimately works for them.

Organizations keep their data in a lot of different places: onsite, in the cloud (another person’s data center) or in an all-in-one data warehouse. Often, this data is siloed. But if an organization could harness the power of its data and become a data-driven organization, it would be able to grow and compete more effectively. The company could move mountains — or so the idea goes. So why do data projects fail, and how can changing the organization’s culture turn things around?