Redefining 'Data-Driven' for Intuitive Thinkers
What are the uses of data? This is a timeless question. It might even seem simple. However, a while ago, one of my colleagues brought it back to life by asking, 'How should I begin learning data analysis to become qualified as a product manager?'
It was a simple yet profound question, and it made me realize that if we don't clearly understand the uses of data, how can we decide how to learn it? When we think about the uses of data, the first word that usually comes to mind is decision-making. We use data to make better decisions. But this is not the only use.
This article looks into the main uses of data. I will then give an easy-to-understand definition of what it means to be data-driven in a way that is meaningful even for intuitive thinkers.
Uses of Data
Let’s start by identifying the core functions data serves.
In the 1930s, Bell Telephone Laboratories was working on improving long-distance telephone communication when it noticed a noise (i.e., data) from an unknown source. This led to the question, "What is causing this interference in our signals?" The investigation eventually revealed that the noise came from the Milky Way, not any man-made source. This story exemplifies how data can lead to new questions.
But data doesn’t just spark questions, it also plays a central role in answering them. For instance, when trying to understand why the churn rate has increased, we gather and analyze data in different ways to uncover possible causes.
Beyond supporting questions and decisions, data now plays a third role. Today, it is processed, packaged, and offered directly as a product to users—a concept known as 'Data as a Product' (DaaP). Large language models, such as ChatGPT, are prominent and well-known examples of this.
So, the core uses of data include:
1. Finding answers to questions
2. Discovering new questions
3. Developing DaaPs (Data as a Product)
You might wonder why decision-making isn’t listed separately. That’s because decisions are typically composed of a few key questions or ambiguities. By finding the answers to these questions, data supports decision-making rather than standing apart as a separate use.
Redefining 'Data-Driven'
If we view 'finding answers to questions' and 'discovering new questions' as the fundamental uses of data, then a data-driven person is someone who engages with data in both ways.
To be data-driven is to engage with data both to answer existing questions and to uncover new ones.
Being data-driven isn't only defined by your latest data-informed decision. Instead, ask yourself, "When was the last time data led me to a new question?"
In fact, discovering new questions is an essential tool for exploration. We seek answers to resolve current uncertainties, and we use new questions to push into unexplored areas.
Reconciling Data and Intuition
In this section, I’ll explore the relationship between data and intuition and how they can be reconciled. Understanding their relationship shows that being data-driven doesn’t contradict intuition.
As noted earlier, while some answers directly support decisions, other questions arise purely from curiosity.
If we think of data as a vast library, then questions are like book titles. Some books we read to support decisions; others we pick up out of curiosity, even if they don’t lead to any concrete outcome.
Let’s explore these two types of questions: those that guide decisions and those driven purely by curiosity. This helps us understand the relationship between data and intuition.
Questions that Guide Decisions
If an answer influences a decision, it means we already have an idea of how it will be useful. Assume you have questions about a feature that has been recently added to the product: What percentage of users have tried the new feature? What percentage are being engaged?
Answers to these questions can help shape a decision. In other words, a decision stitches the answers together and turns them into action. For example, we might decide, "If 30% of users try the feature and engagement is at least 50%, we’ll continue its development". This shows how data provides answers to questions and how decisions turn those answers into action.
This helps clarify the relationship between data, questions, decisions, and actions. However, it might distract us from the intricacies and enormity of the "uncertainty space" of businesses. Often, even with enough data, the right decision isn’t immediately clear. In reality, decisions often go through a long and complex process before they become actionable.
Many people assume they know which actions will produce the desired results. As a result, they skip over defining the decision and jump straight to the action.
In business—especially in startups—many decisions are time-sensitive, and we often can’t afford the time required to answer every question. A well-timed action can make all the difference. For example, if we don't deliver a product on time, we might fail to capture the market. This underscores the role of intuition.
"The easiest way to be the best is to be the first."
— Gaurav Misra
Intuition helps make faster decisions, take earlier actions, and shorten the learning process. Taking an action usually quickly provides a lot of data. In essence, the power of taking action is finding answers to questions that have not been posed yet.
The power of taking action is finding answers to questions that have not been posed yet.
This is where the long-standing debate between data and intuition often emerges. Undermining data brings you closer to the chasm where failed businesses are buried. Dreams and opinions—masked as intuition—have led to the downfall of countless businesses.
Instead of debating data versus intuition, we should focus on how to balance them. Ask yourself, "How much should I rely on data versus intuition in this decision?" Striking this balance depends on several factors: the decision’s complexity, its strategic importance, the decision-maker’s amount of uncertainty, and the scale of potential risks.
Here, one key point is that uncertainty and unknowns depend more on the decision-maker than on the decision itself. Give the same decision to two people, and the one who feels less certain will find it more difficult. The same goes for how important the decision feels to someone or how risk-averse they are.
Therefore, one might be able to rely more on intuition, while another might leverage more data for a safer and more accurate decision. Understanding this can help resolve the tension between the two approaches. To help other decision-makers, we should share how intuition and data have guided our decisions. This helps prevent people from leaning too heavily on one or the other and encourages balance.
Questions from Curiosity
We often ask and answer questions without knowing their true purpose. In reality, we even confront data without having a question in mind. Our intuition might extrapolate a pattern from the data, or a piece of data might lead to a creative idea.
Returning to the library metaphor, posing questions is like scanning book titles. Each title (question) targets a part of our uncertainty. Answering a question is like taking a book out of curiosity without knowing where it would be helpful.
This is where data and intuition meet. We ask questions out of curiosity. Data provides the answers. Later—perhaps unexpectedly—intuition turns them into insights or decisions. To have a stronger intuition regarding a matter, you should expose yourself to more data and experiences.
This is where data and intuition meet: We ask questions out of curiosity → Data provides the answers → Intuition turns them into insights or decisions.
It bears emphasizing that questions from curiosity can have hidden downsides. Much of the data (many of the books) may be fun to explore but rarely benefit the business. This playful use of data can take different forms. For instance, someone might flip through pages aimlessly—ignoring the book’s title, lacking a clear question or intention—and walk away with nothing of real value.
Another dark side of data is being confined to what is accessible. Imagine trying to solve a complex problem using only the books currently on your desk. This restriction limits your perspective.
Intuition can be a game-changer. Rather than only exploring what's on hand, intuition lets you dream beyond it. It’s like soaring beyond barriers, freeing your mind from the constraints of accessible data. It helps you discover higher summits—far beyond the reach of the data around you. It is like exploring other areas (books) or creating a solution that never existed.
Conclusion
We can be data-driven and simultaneously rely on our intuition. But finding a universal balance between them may be impossible. Anyone who champions either side is simply prescribing what they believe works for themselves, based on their unique knowns and unknowns.
Being data-driven goes beyond answering questions; it includes discovering new ones. Whether qualitative or quantitative, data appears in many forms. What matters most is using it consistently and continuously.