Data Curiosity: How To Cultivate An Inquisitive Workforce

A group of three men examining a chart on a computer screen.

Fostering a data curious environment will be critical to digital transformation.

Deagreez | Bigstock

As data is made available to more people within organizations, we’re seeing an increased emphasis on the importance of data literacy and data storytelling. Both of these data skills are essential to democratizing data and extracting value from your data investments. However, between these two skills sits another crucial ability that hasn’t received as much attention. Data curiosity is the connective tissue that ties these two key areas together.

On one side, 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 side, 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 general, curiosity can be immensely valuable to organizations. 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.

How do you forge a data-curious culture?

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 curiosity.
  • Data must be 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 to 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.”

CliqStudios – Data Curiosity in Action

Andy Juang, 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.

CliqStudios’ data culture also embraces experimentation. Employees are constantly asking “what if we did this?” For example, its marketing team questioned whether the generic landing pages for its paid search campaigns should feature more keyword-specific content. After rolling out a number of tests, they discovered the keyword-specific content made a material difference in their marketing efforts, generating better quality leads and optimizing ad spend. The cabinet manufacturer’s culture also acknowledges it’s okay to be wrong when you’re curious. For example, when its analytics team developed a model to predict the likelihood of a customer to buy from them, the first outputs were incorrect. After discovering one of the inputs was reported differently than expected, they were able to adjust the model and obtain deeper insights into their business. Curiosity and learning go hand-in-hand. Data curiosity will be quickly extinguished if mistakes are punished.

In a recent report by Splunk and TRUE Global Intelligence, “55% of an organization’s data is ‘dark’—unquantified and untapped.” As organizations foster data cultures that are more inquisitive, this unused data can be gradually transformed into strategic assets. As a curious workforce probes deeper and deeper with more challenging queries, this underappreciated data will become critical to unlocking new insights. Until then, it will sit dormant, providing no value. Whether you’re a small company like CliqStudios or a behemoth like Amazon, data curiosity won’t just happen on its own. Leadership plays a key role in fostering an inquisitive workforce, and it must be nurtured over time. If you’re a leader, are you curious about what insights are hidden in your company’s data? More importantly, is your workforce also curious? It may make the difference between being a top performer or just another player in your market.

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As data is made available to more people within organizations, we’re seeing an increased emphasis on the importance of data literacy and data storytelling. Both of these data skills are essential to democratizing data and extracting value from your data investments. However, between these two skills sits another crucial ability that hasn’t received as much attention. Data curiosity is the connective tissue that ties these two key areas together.

On one side, 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 side, 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 general, curiosity can be immensely valuable to organizations. 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.

How do you forge a data-curious culture?

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 curiosity.
  • Data must be 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 to 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.”

CliqStudios – Data Curiosity in Action

Andy Juang, 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.

CliqStudios’ data culture also embraces experimentation. Employees are constantly asking “what if we did this?” For example, its marketing team questioned whether the generic landing pages for its paid search campaigns should feature more keyword-specific content. After rolling out a number of tests, they discovered the keyword-specific content made a material difference in their marketing efforts, generating better quality leads and optimizing ad spend. The cabinet manufacturer’s culture also acknowledges it’s okay to be wrong when you’re curious. For example, when its analytics team developed a model to predict the likelihood of a customer to buy from them, the first outputs were incorrect. After discovering one of the inputs was reported differently than expected, they were able to adjust the model and obtain deeper insights into their business. Curiosity and learning go hand-in-hand. Data curiosity will be quickly extinguished if mistakes are punished.

In a recent report by Splunk and TRUE Global Intelligence, “55% of an organization’s data is ‘dark’—unquantified and untapped.” As organizations foster data cultures that are more inquisitive, this unused data can be gradually transformed into strategic assets. As a curious workforce probes deeper and deeper with more challenging queries, this underappreciated data will become critical to unlocking new insights. Until then, it will sit dormant, providing no value. Whether you’re a small company like CliqStudios or a behemoth like Amazon, data curiosity won’t just happen on its own. Leadership plays a key role in fostering an inquisitive workforce, and it must be nurtured over time. If you’re a leader, are you curious about what insights are hidden in your company’s data? More importantly, is your workforce also curious? It may make the difference between being a top performer or just another player in your market.

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I'm the Sr. Director of Data Strategy at Domo, which is a cloud-based, self-service BI platform. In addition to my background in digital marketing, I have over 15 years

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