Data Is Now a Team Sport

Data Is Now a Team Sport

Collaboration, not centralization is the new playbook

This week I participated in an informative event that Cloudera hosted with TechCrunch: Data and the Culture Transformation. The event was moderated by tech industry analyst Maribel Lopez, and we were joined by Shirley Collie, chief health analytics actuary at Discovery Health in South Africa. The conversations focused on how company data cultures are rapidly evolving and delivering new levels of value to businesses with the emergence of data ecosystems.

In more basic terms: we talked about how data is becoming a team sport. 

There are two major shifts happening that are driving this change. One is the macro story, the big picture. Companies are relying more and more on data to make critical business decisions. Just about every company wants to become data driven, but doing so is becoming ever more complicated. The volume of available data is exploding, and businesses need to power hundreds of initiatives, often simultaneously—and each initiative needs access to precisely the right data at the right time. I’m sure you can relate. 

The second shift is at the micro level, within every business down to the team level. Modern data-driven organizations have realized that taking control of their data has to happen locally, within small, agile teams. This requires product thinking – decentralizing control of data and reducing dependencies—and all of this must happen without ever sacrificing security and governance. These smaller teams are now able to collaborate more easily with other small teams, creating greater efficiencies and an increased ability to scale. Through this collaboration, these agile teams are now better able to solve real business problems with data because they have fast, self-service access to reliable data wherever it resides and whatever the source. It’s this level of access across the organization that is driving real value for companies. 

The technology foundation for this is enabling a single view of a data set across every line of business, every country, and every device where the data set is used. Once you’ve created the processes and infrastructure to leverage all the data sources you have access to, you’re ready to advance to connected and collaborative ecosystems. One example is an insurance customer of ours that used to offer auto insurance only in very limited tiers of coverage, like $150,000 or $300,000, because that’s all their actuarial models were set up to do for decades. The challenge they brought to us was, “What if we could offer a customer $87,500 worth of coverage, or some other very specific amount that they wanted?” Along with, “What if we could tune the rates at the zipcode level instead of the state level?” Behind these questions were huge assumptions in the volumes of data they had to process and the responsiveness that they needed from their analytic models. By understanding their business goals, we were able to help them design a data strategy around it.

What is a collaborative data ecosystem? Maribel did an excellent job explaining it: it’s a platform that combines data from numerous providers and builds value through the use of processed data sets. These data sets could be from open data sources or multiple parties within an industry, or they can cut across sectors, data domains, and value chains. This is all possible today, and this culture transformation is happening right now.

Wherever you are on the data journey, collaboration is key, just as it is in team sports. Whatever side of the data exchange you’re on, partner up—within your organization, across teams, and with your data and cloud vendors. You’re all in this together. And we’re with you every step of the way.

Tune in to the replay (coming soon)  to hear more about the changing world of data from industry analyst Maribel Lopez and Shirley Collie, chief health analytics actuary at Discovery Health in South Africa.

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