Here’s a question for you — when did you learn to read and write? Odds are it was one of the first things you remember learning, and that makes sense: learning to read and write is foundational for all other knowledge you acquired.
Literacy. We usually think of it as the ability to read and write, but in reality, the term is much broader than that. Beverly Moss, in her work “Literacy Across Communities” writes “There is still much discussion and disagreement on definitions of literacy…” and further notes that, despite the many disagreements, the field has landed on a definition which “links literacy to a complex web or network of social practices.”
Essentially, our definition of literacy is expanding, and to that list, I would like to add what I believe is the most important kind of literacy anyone can have in the modern world. Data.
As data-driven decision making is revolutionizing the functioning of organizations and society by pushing the frontiers of efficiency and timeliness of decision making.
With the deluge of digital data made available to more people within organizations and society, we’re witnessing an increased focus on the importance of data literacy and data storytelling. Both of these data expertise is essential to deciphering data and extracting value from one’s data investments. However, between these two skills sits another crucial ability that hasn’t received as much attention. Intellectual data curiosity — the connective tissue that ties these two key areas together.
On one hand, without a basic level of data literacy, people won’t understand the data sufficiently to be inquisitive with the numbers (at least not in meaningful ways). On the other hand, if people aren’t able to explore the data, they won’t uncover insights that will even necessitate data storytelling. Rather than expecting data curiosity to occur naturally, organizations need to cultivate the right skills and environment for it to happen.
“In my opinion, every single topic is interesting. If we just go deep enough into it, we’ll find astonishment.”
Blending data curiosity with expertise in data “literacy” and data “storytelling” drives decision making with insights gained from the analysis. You need to be data literate to be curious about the data, and you can’t tell data stories if you haven’t found insights that need to be shared with others.
Curiosity, an integral part of the efficient functioning of any organization, and more generally of society at large. In a Harvard Business survey of more than 3,000 employees conducted by behavioral scientist Francesca Gino, “92% credited curious people with bringing new ideas into teams and organizations and viewed curiosity as a catalyst for job satisfaction, motivation, innovation, and high performance.” Despite these perceived benefits, inquisitiveness isn’t always encouraged by managers as many of them feel it can lead to increased risk and inefficiency. As a result, Gino found “only about 24% reported feeling curious in their jobs on a regular basis, and about 70% said they face barriers to asking more questions at work.”
In his most recent shareholder letter, Amazon CEO Jeff Bezos noted how curiosity (or “wandering” as he phrased it) is a critical counter-balance to efficiency, and his company’s success has relied on both. He stated, “The outsized discoveries — the ‘non-linear’ ones — are highly likely to require wandering.” If we expect individuals to wander through the data on their own, it’s going to take more than simply plugging in a shiny, new analytics tool. You need to cultivate an environment that supports and encourages data curiosity.
“I have no special talent. I an only passionately curious.” Albert Einstein.
If your organization hasn’t yet developed a data-curious culture, here are some key building blocks to consider:
People must be data literate
One of the biggest challenges facing organizations today is a lack of data literacy. While most companies have the technology to be data-driven, many of their employees are still data illiterate. It’s difficult to extract value from analytics tools when your staff isn’t able to read, understand or use data. To address this gap, Gartner predicts “by 2020, 80% of organizations will initiate deliberate competency development in the field of data literacy.”
Relevant data must be accessible
If the right data isn’t readily available, it will be difficult for employees to get far in their questioning of the numbers. Without an adequate depth of detail, they may get frustrated and abandon what they’re searching for. It’s important to provide people with a solid foundation of role-specific data to whet their intellectual curiosity.
Data must be of good quality
Nothing will shake the confidence and trust of inquisitive minds like bad data. If you want people to rely on the numbers, they need to be reasonably trustworthy. Even though no data will be entirely perfect, quality standards and processes should be put in place to protect and maintain the quality of the data.
Tools should be easy to use
Rich amounts of data are hard to navigate if you only offer analytics tools that were primarily designed for analysts or data scientists. When the learning curve is too steep, you lose people who are genuinely curious but lack the time or patience to learn advanced platforms. In addition, you need tools that can respond quickly to questions when they occur and fuel deeper curiosity. In some cases, it may make sense to provide a tiered approach with tools in which employees can obtain more firepower as their skills and needs advance.
Systems should be responsive and flexible
Questions feed more questions. If the process for getting answers takes too long or is too taxing, people will lose interest and curiosity will diminish. The more employees are empowered to get answers on their own and in the moment when they need them (e.g., on their phone while commuting to work), the more curious they become.
Leaders must lead the way
When employees aren’t held accountable for key metrics, companies can’t expect people to have much interest in exploring the data. However, when leadership shows a keen interest in the numbers, it’s not surprising when data curiosity propagates throughout an organization.
Inquisitiveness should be rewarded
Often the behaviors that are embraced and sought after are the ones that are recognized and rewarded. In general, data curiosity should be celebrated whenever the discovery of a key insight has a significant impact on the business. Kellogg Professor Tom O’Toole even suggests curiosity should be a criterion for advancement. He advocated for it to be evaluated as a mindset in how individuals “advance the business in new ways using data.”
Andy Juang, the founder of CliqStudios, an online seller of semi-custom kitchen cabinets, places a high emphasis on data curiosity. You could say his business was founded on inquisitiveness. Several years ago, the serial entrepreneur and technology executive couldn’t understand why his own kitchen remodeling project was so difficult. He saw an opportunity to completely reinvent the remodeling process, and his curiosity led him to acquire a cabinet dealer for $2 million so he could better understand the kitchen cabinetry business.
Emulating the DNA of its inquisitive leader, CliqStudios has developed a learning, curious culture. Leading by example, Juang is constantly using data to inform decisions, not justify them. He’s also curious about all aspects of the business from sales to marketing and production to IT. Juang expects everyone to know their function and the overall business, holding them accountable for their results. To help democratize the data, CliqStudios rolled out a robust data platform (Domo) and opened up data access so business users were more empowered to ask questions. Having the data freely available enabled the teams to have conversations about performance and speak a common language. After initial concerns about losing control, its analytics team has seen significant success across its teams that they admit wouldn’t have happened with more restrictive data access. The analytics team also provided training sessions and weekly office hours to further support employees with their data curiosity.