The Importance of Asking the Right Questions
"As we know, there are known knowns... But there are also unknown unknowns—there are things we do not know we don't know." —Donald Rumsfeld
Data is everywhere, yet businesses often struggle to turn it into actionable insights. While some challenges are well understood, others fall into the category of known unknowns—problems companies recognize but don’t fully understand. In data analysis, success isn’t just about having more data; it’s about identifying what information is missing and asking the right questions to uncover it.
Consider an insurance company that was struggling with rising claims processing costs. At first glance, the situation made no sense—claim processing times were decreasing, and staffing costs hadn’t changed. Instead of immediately diving into complex data analysis, leadership took a step back and asked a simple but crucial question: What are the costs associated with processing claims? A thorough review revealed that interest on delayed claims was driving up expenses. Although most claims were being processed faster, complex ones were being ignored for weeks, accruing high interest. The next key question—Why are these claims taking so long to be approved?—uncovered a hidden issue: employees were incentivized based on the number of claims processed, unintentionally leading them to deprioritize complex cases. This discovery highlighted a misalignment between incentives and business goals, revealing that the root cause of higher costs wasn’t processing speed, but overlooked complex claims.
This situation is a perfect example of how businesses can misinterpret data trends without asking deeper questions. Many companies get lost in the sheer volume of data they collect, unsure of where to begin. Instead of sifting through endless reports, they should start with clear, strategic questions that align with their business goals. For example, a retail company shouldn’t ask, What does our sales data look like? but rather, Which customer segments are driving the most profit? A logistics company shouldn’t just examine delivery times but ask, What factors most frequently cause delays?
To frame better analytics questions, businesses should focus on three key principles:
Tie questions to business objectives. Before diving into the data, define what success looks like. Are you trying to improve customer retention? Reduce operational costs? Expand into new markets?
Avoid overly broad or vague inquiries. Asking How can we increase revenue? is too general. Instead, focus on specific drivers like Which marketing channels yield the highest customer lifetime value?
Challenge assumptions and look for root causes. The biggest insights often come from digging deeper. If sales are dropping, don’t just ask Why are sales down?—ask Which products are underperforming, and what external factors might be influencing this trend?
Businesses today have more data than ever, but data alone doesn’t create value—questions do. By shifting the focus from “What data do we have?” to “What do we need to know?” companies can turn raw numbers into actionable insights, leading to smarter decisions and better results.