Curiosity is a defining human trait. It is such a fundamental component of our nature that we rarely stop to consider its pervasiveness throughout our lives. An internal propulsion system that thrusts us along an insatiable quest to seek to consume new information from the moment of birth. We’ve been described as informavores: beings that produce and consume information. And today, defined by the explosion of data across every facet of life, there’s been no better time to be an informavore.
Curiosity began as a necessity. It has its evolutionary roots in survival. Those that were curious actively sought out information about their environment, thereby gaining greater access to knowledge of nearby resources and dangers. Information pertinent to succeed in daily life.
Eventually, we became curious about more than what is just necessary for survival. We developed epistemic curiosity, an innate love of learning, and the uniquely human ability to ask, “Why?”
We are all familiar with the phrase, “Companies that don’t innovate, die.” Behind every innovation or breakthrough, there is the little question “why?” tempting to be answered. In 1944, scientist and CEO of Polaroid, Edwin Land, was asked by his 3-year-old daughter “why” she couldn’t see the picture he had just taken of her. Four years later and the world saw the first instant-photo Polaroid camera. One little question and one Large Hadron Collider later and the holy grail of modern physics- the Higgs boson – was discovered.
Just as early humans needed to be curious about their environment to survive, today’s organizations built on data need to understand their data environment to survive. They need to know what data resources they have, and what data-dangers, from business competitors to malicious attackers, are out there looking to take advantage of any weakness.
Enter the new role of the data-curious. Those that instinctively seek out data and are driven with an investigative vigor to learn as much as they can to use data in new ways to make a business come to life.
Data curiosity as a business luxury
The problem that most businesses face today is they treat data curiosity as a nice-to-have trait in a few select employees rather than a function of survival that everyone in the organization needs to exercise. In a survey by behavioral scientist and Havard Business professor Francesca Gino of more than 3,000 employees from a wide range of firms and industries, she finds “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.” This is despite findings in the same survey that showed, “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.”
There’s enormous hype and marketing around how data science and analytics will transform a business overnight, opening up treasure chests of golden, glistening insights at the turn of a key. The reality, however, is that a majority of companies don’t understand what data they have, much less how to use it in actual practice to affect business outcomes.
So the solution to-date has been a luxury-driven approach to data. This means placing the charge of data curiosity in the hands of a select few, the “data-affluent.” Those with the means to access and interact with data because of their highly technical skillset. In practice, this translates into indiscriminately hiring data scientists, giving them the fanciest analytics tools on the market, a subtle nod, wink and slight push towards their workstation, and expecting an alchemic transformation of lead data to business value gold.
But this isn’t working out so great. First, the term ‘data scientist’ is quickly outliving its use. It served well as a signifier of change during the digital-transformation era, where all businesses began to see themselves as in the business of data. The data scientist was a living, breathing asset that executives could see with their own eyes and pat themselves proudly on the back for hiring. Walking and talking evidence of their commitment to embracing the new world of data, and all it has to offer.
The original data scientists were expected to be ‘unicorns,’ legendary creatures that were masters of data science, technology, and business. The gap of expectations versus reality led to many ill-fated projects, with business leaders wondering where their immediate results were and data scientists placed in charge of running a data environment with crumbling infrastructure.
Today, businesses are slowly beginning to understand that to truly be a data-driven organization, data curiosity can’t be siloed off and owned by a select few. The lone data scientist is now becoming a data science team, with data analysts, architects, engineers, and data scientists performing more specific functions to meet the business’s needs.
But even beyond that, the organization as a whole must become data curious, which is a deep, cultural change that doesn’t happen overnight. Data curiosity must be woven into the fabric of a business as if it was a critical element of the survival function. Which in today’s ultra-competitive landscape, it is quickly becoming.
Building a culture of curiosity
Imagine a world where data is organized so everyone can be data curious. Data is slowly being made available to more people throughout the organization, and people are getting introduced to the idea of using data in their everyday roles. But it’s the organization’s responsibility to make sure that data means something or has value. Curious exploration of unorganized data leads to wasted time, effort, flawed conclusions and frustrating experiences. Using data is still a foreign concept for many people, so a data curious culture isn’t going to happen organically. It’s up to leadership to both inspire and mandate a culture of curiosity by cultivating the right skill sets in employees and creating an environment that values constant questioning.
Warm up the cold start problem
Mark Twain famously said, “The secret of getting ahead is getting started.” You have your data organized and people are ready to dive in and search for insights. But no one knows exactly how to start. This problem is twofold: users don’t know what they are looking for and products don’t know how to lead users to unexplored places of interest. To address the user problem, we must start building cultures that value inquisitive mindsets and make asking questions normalized. “Why?” should be the most overused word in the organization. Analytics products need to take cues from recommendation engines that trim down the overabundance of options presented to users while generating the best advice for them to follow to reach a quality conclusion.
Give care to quality questions
Leadership should set an example by always asking questions themselves and giving recognition to those who ask good questions. This demonstrates that asking questions in the organization is not only accepted but embraced. It shows that no one has all the answers. During presentations, ask staff how they answered their business problems with data. Make demonstrating the use of data an assumed requirement. And go above and beyond to showcase when someone makes an unexpected discovery with data because they took an inquisitive path to find an answer.
Show how data analytics connects to business outcomes
The easiest way to excite people about the use of data is by showing them how it works. Spend time presenting examples of successful data initiatives from other departments so they can begin to understand how they could use data to improve or optimize their line of business. Show how data has been used to cut costs, increase performance, or provide predictive intelligence. To help usher the process, you can tie some metrics to employee’s KPIs that measure their use of certain data sets in their line of business to reinforce the behavior.
Hire for intellectual curiosity
It’s easier to hire naturally curious people from the start and give them the training to access and work with data than it is to try to teach someone how to be curious. During an interview, place more value not on the answers they give, but rather on the questions they ask. Ask them about the last interesting thing they’ve learned. Who would be more curious? The person who answered with the latest toolkit they learned and how it’s applicable to the job they are interviewing for, or the person who goes on a passionate screed about how underappreciated beavers are since they are an ultimate keystone species of animal, engineer, and ecosystem and how the three-century killing spree of beavers started in the 1500s was one of the greatest ecological travesties in history.
Remove the barriers to data affluence
Accessibility and the ability to understand and engage with data will need to move from the highly-technical few to the data curious masses. This means providing people with the means to understand what data they have access to and letting them ask questions of the data in an interactive, natural way, that doesn’t require knowing esoteric coding languages. Today’s tools are designed by highly technical people, for highly technical people. Data should be brought to life and fun to work with through engaging visualizations and responsive interactions that both lead and follow a user as they dance around new questions fueled by their curiosity.
Provide access to the right data and the right tools at the right time
Often times data analytics tools are used as the first step to become a data curious organization. Without first having at least the beginnings of a data curious culture, these tools sit unused, collecting digital dust. People first must feel comfortable with the idea of questioning everything. Then they have to have an idea of what questions they should be asking. Only then will these new tools make sense in their hands. Make this process approachable by starting with simple, easily solvable use cases related to their lines of business. Don’t ask them to innovate the entire department within a week.
One of the biggest challenges that leadership must embrace is that their directives are often at times in opposition to the cultural change they wish to promote. Employees are conditioned to operate under short-term performance goals and are required to hit certain metrics every month.
Often, they are struggling to just keep the trains running on time. So any “free time” that should be reserved for investigating new ways of solving problems or coming up with creative and innovative ideas sparked by chasing their curiosity is either looked down upon or the employee feels guilty for using.
Radical changes require radical shifts in perception and acceptance, and this is an uncomfortable area for most at the start. Leadership has to realize that more value exists outside of their predetermined metrics and place a small amount of faith in the power of curiosity. Exploration involves time, and that time may not always produce a linear result. But when it does it could be a game-changer for the business.
About the Author
Grant Wernick is the co-founder & CEO of Insight Engines. He is an experienced product-focused leader, founding both commercial and enterprise companies over the past decade. He has focused much of that time on building highly technical teams to solve hard search and NLP problems, most recently for cybersecurity. Grant’s passion is bringing products to market that give non-technical people the means to naturally explore and interact with data.
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