Enterprise

Enterprises are rushing to be data-driven. It’s harder than it sounds.

Leaders from Google Cloud, PayPal and JPMorgan Chase talked to Protocol about how to build the data-centric organization of the future.

Data in the enterprise poses new challenges.

Data in the enterprise poses new challenges.

Image: Getty Images

Most CEOs believe becoming a data-driven organization is paramount for the success of their business. That transition, however, takes more than just a pronouncement from the top. And many think their organizations are failing at the effort. That's why it's now falling to data leaders to handle the many facets of creating an effective data strategy and sustaining the overhaul.

The rush to digitize operations means companies have information coming in from everywhere: productivity and collaboration tools that employees are increasingly relying on to do their jobs, contracts that are notarized and signed online, sensor-enabled machines on the manufacturing floor and transactions on ecommerce storefronts, just to name a few. Increasingly, much of that information is being stored on the cloud, systems that often come with built-in features that help organizations manage their data and who has access to it.

Now, the push is to enable employees, many of whom may have no prior experience in fields like data analysis, to begin to use that stored information in a meaningful way. The trend is evident in the success of business intelligence vendors like Snowflake and Databricks. But becoming a data-driven organization requires a broader change in mindset outside of IT. It's why industry leaders say relatively minor steps, like opening up hackathons to non-developers, can begin to create a more engaged workforce.

The goal is to "invite people who have not been thinking about this topic to really think about it in their day-to-day work," Kristie Chon, PayPal's chief privacy officer and its global head of data governance, said Tuesday at an event hosted by Protocol. "It really creates the culture of control, culture of responsibility and understanding."



But that's only one part of what Chon and others say needs to become an enterprise-wide effort. And that is taking many different forms. Across corporate America, for example, barriers between teams are being removed. In the past, research teams might have dictated product demands to technologists, who then built to those specifications and sent it back for feedback. Now, companies are creating teams with members from both of those parts of the organization who work side by side, day in and day out. And that's changing the discussions around, for example, how data can serve as a foundation for new products or features.

"Anytime that you see silos, it's usually a sign that there is going to be some reorganization," said Google Cloud Chief Information Security Officer Phil Venables. Now, "it's very hard to differentiate between who are the technology people and the non-technology people. It's just one continuum."

That's also the case at the executive level. Chief data, privacy and security officers are working more closely with technology and product heads to galvanize around a strategy that ties the terabytes of data to a measurable outcome aligned with the broader goals of the organization.

"You'd be hard-pressed to find someone in the organization that you don't have to interact with," JPMorgan Chase Chief Data Officer Melissa Goldman told Protocol.

But even creating that strategy can be a barrier. The data framework, for example, has to be flexible enough to accommodate a quickly-changing regulatory environment that is increasingly empowering the consumer to have more control of their information, while also firmly establishing rules for who can access what information and how outcomes will be monitored to determine success.

"If there is a way to stand up the foundation from the beginning really right, then there is less effort to get that infrastructure, get that baseline foundation corrected every time something new comes out," said Chon.

That means addressing basic challenges, like where the information is stored and in what format, to avoid costly and time-intensive data cleansing efforts down-the-road.

"All data isn't created equal," said Goldman. "Being able to understand that and what needs to be applied from the beginning avoids having to do retroactive remediation."

While the challenge is immense, so is the reward. JPMorgan CEO Jamie Dimon has attributed the success of the institution partially due to the billions of dollars it's invested in technology and data-driven tools. Of course, not every organization is the size of JPMorgan. But nearly every business has recognized the need to go digital. And addressing those challenges to becoming a more data-driven enterprise at the beginning of the journey can pay dividends in the future.

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