5 ways to foster data curiosity in your business

Reading Time: 2 minutes

Just as early humans survived on curiosity to discover fire and invent the wheel, today’s organizations built on data need to know their data terrain well to survive and stay on the top. They need to understand what data resources are available to them and what challenges they face from disruptors, who always keep them on their toes.

There’s an enormous effort, investment, and focus placed on data analytics. However, the reality is that companies are still struggling to figure out how, in practice, to connect analytics to business outcomes. There is, of course, no shortage of tools for analyzing data. The issue has always been the ability to surface actionable intelligence via a dashboard that just doesn’t give any ‘real’ information.

The unfortunate reality is dashboards kill your curiosity and tax you every time you ask a new question. This means that just having access to data doesn’t directly lead to an organization becoming more data-driven. People have to have a data orientation and a curious mindset. As Gartner puts it, “data can only take organizations so far. The real drivers are the people.”

Humans have inquisitive minds eager to explore. Similarly, data curiosity is the secret ingredient for a successful data-driven organization. Curiosity-driven analytical thinking leads to data-led innovation.

So how can you foster data curiosity in your business?

  • Treat data curiosity as a resource, not a constraint: Curiosity is a resource for relevant background knowledge that supports analytical thinking. It’s also crucial to be curious about perspectives and the context. Contextual guidance can bring a new level of meaning to your analysis that broadens your team’s capacity to solve problems and propel data-led innovation. The goal is to interpret data differently and ask questions that can have a transformative effect on your business. Strong analytical thinkers are always curious.
  • Associate success with ‘questioning’ everything: Because the goal is to discover hidden insights, correlations, and patterns in the data that a person didn’t think to ask for, there is a high level of ambiguity in the data science field. Exploration often involves questioning the status quo and might not always produce relevant information or possible answers.
    Conversely, it also means not settling for the first possible solution or yielding to better remedies. By asking questions, we promote more meaningful connections and more creative outcomes. Being passionate about data, finding answers, and not taking something at face value will make your team succeed.
  • Expand your spectrum of inquiry to make it more inclusive: Curiosity thrives best in an open, collaborative environment. Asking the right questions involves domain knowledge and expertise, coupled with a keen ability to see the problem, understand the available data and underlying context and match the two. It also requires communication and empathy to consider all aspects of the information to arrive at the most appropriate answer. Without getting bogged down by data, functional or institutional silos, cross-functional teams exploring and questioning data can open up a plethora of opportunities that you might miss working individually.
  • Promote a culture of curiosity: Employees of data-leading organizations are open to experimenting with data. They anticipate their workers to bring data to meetings and make opinions grounded on those insights rather than guesswork. The best way to make the most of your data analysis is to encourage constant questioning in your company.
    To get the most from your team, it’s crucial to empower and enable people to say, “How can I use data to answer this change or optimize that process?” Companies must also be flexible enough to allow employees time to explore topics that are of interest. Furthermore, having a culture of constant questioning is valuable regardless of whether the question has apparent application or immediate revenue prospects. The rewards for a culture of curiosity are tangible and positively impact every facet of your business. Encouraging a questioning mindset regarding data will go a long way in establishing a data-driven mindset in an organization.
  • Curiosity must be allowed to exist for curiosity to flourish: Leading companies are the ones that give data science & data analysis its own freedom to evolve and thrive. Many leaders say that they want employees to be inquisitive, but in reality, they like employees to follow the status quo and not ask ‘too’ many questions. Leaders think that if people are inquisitive, it will lead to a costly mess. It takes thought and discipline to stop stifling curiosity and start fostering it.
  • According to the HBR report on the Business Case for Curiosity, one way “leaders can model curiosity is by acknowledging when they don’t know the answer. That makes it clear that it’s OK to be guided by curiosity.”

    Curiosity killed the cat–or did it?

    Companies that struggle to get meaningful insights from their data are often not asking the right questions. The better the quality of your questions, the more valuable your insights will be. “Curiosity killed the cat…” is just half the idiom we’ve heard. It’s actually: “Curiosity killed the cat, but satisfaction brought it back.” Now you know the real deal!

    Curiosity allows one to embrace unchartered territories, ask questions, and dig a little deeper to make more informed decisions. The best companies— the game-changers- question their data, look at it from all sides and interpret what stories it might be telling.

    Be curious. Seek the light.


Ankita Asthana

Product Marketing Manager, Lumin by Fosfor

Known as a creative individual, Ankita has a knack for thinking out of the box. She is known for creating compelling stories and use cases around products to generate interest and create long lasting impressions for the audience. In her current role, she enjoys bringing Lumin- an augmented analytics product, part of Fosfor suite, to life in fun and captivating ways.

A founding member and advocate of Product Marketing Alliance (PMA), Ankita has dabbled in brand and digital marketing and loves to hone her storytelling skills in her free time

Latest Blogs

See how your peers leverage Fosfor + Snowflake to create the value they want consistently.

A tale of two events: Inside Snowflake’s and Databricks' marquee events

The simultaneous timing of the events did raise some eyebrows in the industry, and soon it became evident that a fierce competition was unfolding between the two powerhouses, both vying for a similar target audience and a larger partner ecosystem. While Snowflake’s spectacular show in Las Vegas boasted over 12000 confirmed attendees, there was an equally palpable excitement in the air for the Databricks event happening in San Francisco.

Read more

Accelerate your production ML journey with Refract

As we all know, production ML (Machine Learning) is more engineering than machine learning. Building a prototype in machine learning has become very simple nowadays, all thanks to different open-source projects like sci-kit, TensorFlow, Keras, etc. But operationalizing that model to get the insights from the model which can be used in day-to-day business decisions is challenging and needs more engineering knowledge than data science knowledge.

Read more

After-market sales & service: Warranty analytics for HVAC manufacturers

For manufacturers seeking to improve their financial performance and customer satisfaction, the quickest route to success is often a product-quality transformation focusing on reducing warranty costs. When fulfilled while backing exceptional product quality, product warranties positively impact sales, profitability, and customer loyalty. On the other hand, when warranties are backed by sub-optimal products, it results in large warranty reserves that directly impact the organization’s profitability. This negatively impacts the organization’s brand, Image, and equity.

Read more