Turning Qualitative Input into Quantitative Insight
When organizations recognize the need for change but lack clarity on how to move forward, traditional data sources often fall short. Financial metrics and KPIs tell us what’s happening, but they rarely explain why and they’re not enough to align leaders on what to do next.
That’s where qualitative inputs can be powerful; not just to inform storytelling, but as a form of measurable insight. When done right, qualitative data can be structured, organized, and turned into quantitative patterns that help senior leaders prioritize, act, and align the broader team around the path forward.
This article explores how we do that: turning input from your team into organized data sets that gives actionable insights. We’ll share two recent examples where this approach helped our clients gain alignment, accelerate decision-making, and build momentum for change.
Our Approach
We don’t just listen to people so that they feel heard, we listen because we believe there are valuable insights we can learn from them. We view our conversations with stakeholders as opportunities to learn what the organization does not know. Team members can offer us valuable learnings if we ask the right questions the right way.
So what are the right questions? And what is the right way? Questions will be different depending on the project, but a question is right if it gives us context into the problem we are trying to solve. We want to understand where there are pain points, why the team members think those pain points exist, and what ideas team members have for solving the pain points. Does this mean that we act on whatever we learn? Not at all. We want to gather a large enough data set to confidently draw learnings and build strategies from it. As we increase the number of team member inputs, we increase the likely accuracy of the data set – i.e., it becomes a statistically significant data set. We do this through interviews, focus groups, listening sessions, sentiment surveys and other traditionally qualitative ways to gather information.
Once we have enough qualitative data, we then translate what team members say into something we can measure, prioritize, and act on. Translating the data in this way is what makes it useful to leaders and usable across the organization. What makes it powerful is that we can then say to a leadership team:
“37% of feedback focused on X”
“This pain point was mentioned 18 times, more than any other”
“The top 2 recommended solutions for this issue were A and B, mentioned by 43% and 31% of team members respectively”
That’s the shift, from anecdotes to patterns. From conversations to measurable data. And that’s what makes the insights persuasive; they enable action and increase adoption. We regularly see that engaging employees to shape project solutions helps stakeholders across every level be much more prepared for the coming change than they would be if the solution was prescribed.
So how does this practically work? Below we’ve outlined the high-level steps.
Step 1: Gather qualitative input, categorize, and quantify the input
Work collaboratively with the project team and senior leadership to align on what we are solving for and which questions need to be asked to gather the right data
Listen to team members across levels, regions, and functions through ways that work best for your organization (interviews, focus groups, town halls, surveys, etc.)
Identify challenges and proposed solutions, then group pain points and ideas into categorized themes
Measure the impact of each theme relative to all feedback received. This is typically based on measuring how often a pain point or solution was mentioned, then verified with senior leadership
Step 2: Build alignment through the numbers
Once we’ve quantified the input, we use it to frame decisions and focus areas. These are simple numbers that point to what matters most and why, all backed by the people closest to the work.
That’s it at a high level. It almost sounds too simple. The catch is that the right questions need to be asked, the right people need to be included, and the analysis of the data should be rigorous and done in such a way that leadership aligns with the takeaways. Ultimately, the data should provide clarity around our go-forward plan, whether that is for a transformation project roadmap or how to support stakeholders through organizational change. It’s important to note that this employee sentiment data is often used in conjunction with financial data and other organizational KPIs to design a holistic solution.
Example 1: From Interviews to a Roadmap
At two recent clients, one in financial services, one in manufacturing, we gathered input across functions, roles, and geographies on current state pain points and ideas for how to solve them. Hundreds of pain points and ideas were shared.
For each category (pain points and ideas), we grouped the data into themes and calculated two things:
How many pain points or ideas were in each theme
How many times each pain point or idea was mentioned
That gave us the ability to say, “This issue represents 22% of total feedback, and this specific pain point came up 14 times.” Same for solutions: we were able to say, “This idea came from 47% of those we talked to. It’s your #1 team-recommended solution.” Pairing this with industry data enabled us to design customized solutions tailored to their companies culture.
Ultimately, this data simplifies into a roadmap. Team members tell us who we need to become and how to get there. For each of these clients, the roadmap looks similar to an equation. For example, “1 + 2 = Becoming what you need to become.” The 1 might be what the organization already does uniquely well; it’s critical not to lose that through the transformation. In fact, we can build on it. The 2 might be the two areas the organization most critically needs to address to become what is needed. For each of these three inputs, we identify the top 3-5 recommendations the organization can implement to activate the input in the equation.
Example 2: Quantifying Readiness for Change
At another client, we ran a change readiness assessment to gather stakeholder sentiment on how prepared various stakeholder groups felt they were to adopt changes that were being implemented.
We asked consistent questions across categories like clarity of understanding for what they need to do, confidence in being able to take action, and the support they felt like they needed to be able to do what was asked. We then segmented the data based on role, level, function and seniority to understand where each group needed additional support.
That allowed the project and leadership teams to align quickly around where to focus. Instead of general concerns, they could see, for example, “Only 28% of stakeholders said they feel clear about what’s changing,” or “54% of responses flagged training as the biggest gap.”
By shifting the qualitative data to quantitative, the insights became more tangible. Leaders and team members could hold onto numbers better than they could hold onto ideas; and this enabled better decision-making and stronger buy-in.
Conclusion
The value of qualitative input doesn’t stop at hearing people out. It comes from organizing what they share, putting numbers to it, and using those numbers to guide decisions. When we quantify what people are saying, it builds clarity, credibility, and alignment. Through this approach, we help leaders understand what matters most, show teams that their voices matter, and build momentum to empower the right next steps. That’s how we make insight actionable and drive change adoption.