How data-literate is your organization?

Evaluating your organization’s level of data literacy is the first step toward creating a fully data-driven corporate culture that empowers everyone to perform better.

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Enterprises are sitting on data goldmines that they can harness for unique business value and competitive advantage. But as most IT and business leaders know, becoming a data-driven organization is much easier said than done.

Modern analytics tools, combined with cloud-based infrastructure, provide the underpinnings of a unified, holistic view of data across the enterprise. But what most often trips up data-driven initiatives, as researchers such as New Vantage Partners report, are corporate culture challenges and low levels of “data literacy.” Tools are only as good as the people who use them, and an ongoing analytics skills gap makes it difficult for teams to tap into experience. A critical step toward becoming data-driven, therefore, involves better education and understanding of the value of data, from the CEO on down. The goal is to put data in the hands of everyone and enable them to use data for everyday choices, not just big decisions.

Ishit Vachhrajani, Enterprise Strategist at Amazon Web Services (AWS) and the former Global CTO at A+E Networks, prefers the term “data proficiency” to data literacy, because the goal goes beyond data awareness to knowing how to put it to use. “It’s not just about democratizing access to data,” he says. “It’s about democratizing action using that data.”

Put a stake in the ground

Data-driven organizations share a few common characteristics, says Vachhrajani:

  • They go beyond executive sponsorship to executive engagement by making visible changes, starting at the top, to put data to use across the enterprise.
  • They focus on creating a data-driven culture and building organizational capabilities to support the culture, and they do this at scale beyond just a few islands of excellence.
  • They embrace data-driven experimentation to test many ideas and continually improve their business.
  • They use a strong foundation of data analytics to power transformation using AI and machine learning.
  • They eliminate silos by treating data as an organizational asset, not a departmental property, and by bringing data transparency and accountability to the entire enterprise.

This last trait in particular can make some people uncomfortable. “Groups that have long had responsibility to provide data and insights for others might fear losing relevance or control of the narrative,” says Vachhrajani. “The C-suite must step in to overcome the resistance and organizational inertia.”

Vachhrajani advises against treating the creation of a “data-driven culture” as a standalone initiative. Instead, he says, find an important (but not urgent) use case, then build a hypothesis that can be tested using data and can become a catalyst to similar efforts. This involves seeking out people in the company who are ahead of the curve with using data strategically. Showing examples of their early successes makes change seem less theoretical and more practical.

Vachhrajani speaks from experience. At A+E Networks, it was long accepted that the traditional reporting application the company used to analyze large volumes of rating data was slow and expensive to run. Vachhrajani’s team oversaw an initiative to modernize the legacy application using AWS purpose-built databases and serverless architecture in the cloud, which reduced costs from thousands of dollars a month to $5 a day and made the data accessible in near real-time. To communicate the benefit to nontechnical stakeholders, his team used Starbucks Venti cups to emphasize that the cost of running this application was now equivalent to a cup of coffee, and the time it took to get this information in their hands was less than the time it took to grab a cup of coffee.  

Actions to consider

Vachhrajani suggests taking the following steps to create a data-proficient culture:

  • Investigate how data flows in your organization and what gatekeeping controls are in place. This helps uncover data silos and gauge the level of difficulty for employees to access the data they need.
  • Make sure a senior, well-respected, and empowered leader is driving the cultural initiative to become a truly data-driven company.
  • Treat data as a product, in part by bringing application engineers and data engineers together, and also by very closely aligning data strategy with product and integration strategy.
  • Make IT a key player. IT has a unique view of the end-to-end business cycle, cross-departmental workflows, and transactional systems that hold useful insights. 
  • Create a data governance structure that enables employees rather than restricts them.

Cultural change, of course, takes time. But there are plenty of benefits to capture along the way. “The steps you take will start to deliver wins early on,” says Vachhrajani.  “And you’ll be able to show people how the wins fit in the context of the bigger picture.”

Learn more about the fastest way to get answers from all of your data to all of your users.

For more data and analytics insights from Ishit Vachhrajani and other experts, check out the new Ahead of the Pack podcast.

 

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