How To Build and Maintain a Data-Driven Organization

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You’ll need an effective business model, operating system and culture to get the most out of your information.

A consciousness about the strategic importance of data and data analytics has reached most CEOs these days, but many of them need to work with their CFOs and other top lieutenants to strategize how to access, analyze and effectively harness their ever-growing trove of data.

Their success starts with recognizing and heeding the modern imperative—for pretty much any company, of any size and orientation—to optimize data. And then following a roadmap that already has been proven by companies including Amazon.

“Being a data-driven organization means culturally treating data as a strategic asset and then building capabilities to put that asset to use not just for big decisions but also for everyday action on the front line,” says Ishit Vachhrajani, enterprise strategist at Amazon Web Services.

“Organizations that are successful in this way focus on capturing, cleaning and curating meaningful data, making that data available widely across the organization, having the skill set and proficiencies to convert that data into actionable insights, and then having the culture that allows people to take action on those insights.”

Through Amazon Web Services, Amazon is helping thousands of customers around the world successfully navigate a transition to an effective business model, operating system and culture for getting the most out of their mountains of data.

Company leaders should follow a four-pronged process, says Wesley Story, an AWS enterprise strategist:

  • Align the leadership team on “how to define being ‘data-driven’ and make sure your priorities are understood” across the board.
  • Recognize the importance of data quality. “The stronger your data strategy, the stronger and more agile your business can be,” Story says.
  • Regard data as “an organizational asset that aligns to your business strategy, talent and cultural priorities.”
  • Infuse developmental opportunities so your workforce “can become more organizationally ready” for a data-driven approach “and for using it to drive outcomes you expect in the future. It’s all about democratizing innovation.”

Innovation today—especially the kind of rapid innovation required to keep companies vital in a fast-moving age—depends on “using data to drive smart business decisions,” says Mai-Lan Tomsen Bukovec, vice president of block and object storage for AWS.

And that holds true not just for old, huge legacy enterprises but for venture-backed startups and every other size and type of company in between, says Brian Taptich, vice president of the worldwide specialist organization for AWS. “It’s easy for leaders to fall into the trap of thinking this is just for large enterprises,” Taptich says.

Business leaders must harness the most effective technologies to advance this journey. They have “the obligation to use whatever cutting-edge technologies you have to solve your biggest and most important problems, whether they are internal challenges or external problems,” Taptich says.

That’s where the important factor of leadership comes in. Company heads must migrate their entire management of the company’s data to the cloud as quickly as possible, these AWS executives say. They also should separate data storage itself from the set of services that their staffs use that govern how the data is accessed internally, Story says.

Leaders need to get their teams and functions to adopt a fundamentally new “mental model” about storing and accessing data on the cloud, Bukovec says. “You get to think about data as a ‘data estate’ and, separately, over time, evolve how you want to interact with the data and get your operations close to it.”

Sometimes large organizations reach such points of intersection over data strategy and then “struggle with decision-making velocity, because it seems like very big decision must roll up to the senior-executive level, and they bottleneck,” Story says. “Or you may not see any clear decision-maker or decision-making framework, so things churn unnecessarily.”

Amazon has prevented such roadblocks with its own data strategy in part by following a handful of company-wide leadership principles. They include, “Disconfirm Your Beliefs” —meaning, constantly test your decisions to see whether, in reality, they’re the right ones. “Speed Matters.”

Also, “Work Backward” to define desired outcomes from a data strategy, then figure what needs to be done at various intervals in the future to achieve them. And, perhaps most important, “Hire and Develop the Best.”

Then, says Bukovec, “Push down the spirit of innovation to all levels of the organization so the next good ideas don’t come from you or your direct reports, but from smart people across the company.”

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