Just as Gutenberg’s movable-type printing press transformed a mostly illiterate European populace into a body of readers, so too do we need a printing press equivalent for enterprise data. However much we may like to proclaim the possibilities of data for enabling digital transformation, without growing data literacy those possibilities will fail to be realized. Fortunately, there are ways to improve data literacy among employees and customers.
Why data literacy is important
Though we often focus on the technologies that enable big data, from Apache Iceberg to Google BigQuery, those technologies fail without people to understand the data behind them. As Gartner’s Svetlana Sicular declared over a decade ago, “Learning Hadoop is easier than learning the company’s business,” or its data.
The nuances of data—knowing which questions to ask of that data and getting some sense of signal amongst all of the noise—are critical to master and serve as a precursor to mastering data technologies. Hence, a more recent Gartner article continued, “[B]eing data-literate—having the ability to understand, share common knowledge of and have meaningful conversations about data—can enable organizations to seamlessly adopt existing and emerging technologies.”
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Unfortunately, as a large Accenture survey found, just 21% of the more than 9,000 people surveyed felt they were data literate. Without data literacy, the deluge of data will drown us, rather than transform the way we care for customers or engage employees. So, how do we increase data literacy?
Tips for increasing data literacy throughout your organization
Among other sources, Gartner offers a range of suggestions for how chief data officers can construct a data literacy program for their organizations. Other tips for increasing data literacy company-wide involve focusing more on data over technology, especially in decision-making processes.
Focus more on data versus technology
As an MIT Sloan School of Management analysis described, it’s important to understand the goal. Data literacy is the ability to read, work with, analyze and argue with data. The emphasis needs to be on understanding and using data, not necessarily the tools used to ingest or analyze that data.
“If we’re spending 80% now on technology, 20% on data, flip it—make the technology super easy so that you can spend more time on data,” said Cindi Howson, chief data strategy officer at ThoughtSpot.
The basis for any good data literacy plan is a strong focus on data, not technology.
Establish data skills training
With this in mind, the next step is to establish a data skills academy within the organization, preferably with executive support. Rather than attempting to instill a general-purpose vision of data’s importance, the program should be tailored to the particular needs and data sources of a given enterprise.
In a similar fashion, the company should use examples that are cross-functional in nature and make it clear how data can be useful across the enterprise. Though some of the skills, like statistics or lookups, can seem daunting, emphasizing their successful use can make the learning of them seem both advisable and attainable.
Include data in decision-making processes
Next, ensure that data is a key and obvious part of decision-making. Data literacy is as much a cultural phenomenon as anything else, and when executives insist on interrogating their own decisions with potentially adverse data, it sends a message that data is important.
This becomes doubly so if the enterprise puts data in the hands of employees through dashboards and other means, such that they’re empowered to use data to support or challenge decisions being made. In other words, the more managers and other executives demonstrate dependence on data, the easier it becomes to inculcate a data-driven culture more generally.
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How to raise data literacy among your customers
Data-savvy customers can be your most loyal customers if data is used to help them make informed decisions. For example, I love U.S. federal regulations that compel national chain restaurants and other food providers to provide caloric information. It helps me make thoughtful decisions about what I’ll eat.
Yes, this means I’m almost never going to eat that 1,000-calorie burger from Shake Shack or, at least, not get the fries and shake with it, but this yields more data to the vendor as to what prospective customers want. By offering data to inform customer decisions, it helps the company to become even more data driven.
The food example is a simple one to understand, which is the cardinal rule for helping increase customers’ data literacy. Just like data literacy within the enterprise, customer data literacy depends on making data approachable, easy to find and easy to interpret. This is one of the initial innovations that AWS brought to cloud computing: easy-to-understand, pay-as-you-go pricing. You didn’t need a Ph.D. to understand the model or the data behind it.
In short, successful companies will treat data literacy as a key component of the product they’re selling. By enabling both employees and customers to make more informed, data-driven decisions, companies position themselves to earn employee loyalty and customer trust.
Disclosure: I work for MongoDB, but the views expressed herein are mine.