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Ambitious data projects frequently fail to deliver their promised impact. But it’s rarely due to lack of technical skill or cutting-edge technology.
Instead, the real roadblocks often lie in human factors:
In a recent webinar, Tiankai Feng, Director of Data & AI Strategy at Thoughtworks and author of Humanizing Data Strategy, joined Count CEO Ollie Hughes to explore why these human aspects play such a big role in failing data projects—and how you can ensure your next initiative succeeds.
Here, we give an overview summary of what was discussed on the webinar. Make sure to watch the webinar in full to get all the details.
The interview with Tiankai surfaced a whole range of insights. After watching it back, here are seven points we thought were worth highlighting.
Tiankai shared a practical framework he calls the "5 Cs"—five essential elements for grounding data strategy in real human impact:
These Cs aren’t just principles—they’re a practice. They remind leaders to approach data with both the head and the heart.
🔥 Lesson: The 5 Cs serve as a compass to keep data strategy human, purposeful, and effective.
Data alone doesn’t create change—people do. Tiankai stresses the importance of focusing on human behaviors, motivations, and interactions rather than just technology.
"What we're doing is not only technical transformation—it's human transformation. It's about mindset, it's about behaviors, it's about how people interact." — Tiankai Feng
Tiankai emphasized that without thoughtful engagement from people across the business, even the most sophisticated data models remain unused. It's the emotional and behavioral buy-in that unlocks true impact.
💡 Key takeaway: Prioritize stakeholder buy-in and address human resistance early to ensure lasting impact.
Misalignment between data teams and business stakeholders is common and costly. Empathy, however, can bridge this gap.
"You can't build empathy by guessing—you have to ask. And when you ask, people open up. You learn what they actually care about, not just what you think they do." — Tiankai Feng
He shared how empathy interviews often reveal the unspoken anxieties that block progress. By tuning into these emotional undercurrents, data leaders can co-create solutions that people actually want to use.
🚀 Pro tip: Conduct empathy interviews before kicking off data projects to uncover hidden barriers and motivations.
The most meaningful data work starts where the real business pain lives. Tiankai emphasized that if you want to make a difference quickly, you need to locate and engage with the areas that are hurting the most.
“Follow your pain was a really wonderful thought experiment... that means you need to follow where the pain is.” — Tiankai Feng
Pain is not just a problem—it's an invitation. If people are frustrated, blocked, or overwhelmed, there’s opportunity for data to create real, visible relief. It's the difference between solving hypotheticals and making lives easier.
💡 Key takeaway: Don’t just chase interesting data—go where the pain is. That’s where impact lives.
The most meaningful data work starts where the real business pain lives. Tiankai emphasized that if you want to make a difference quickly, you need to locate and engage with the areas that are hurting the most.
“Follow your pain was a really wonderful thought experiment... that means you need to follow where the pain is.” — Tiankai Feng
Pain is not just a problem—it's an invitation. If people are frustrated, blocked, or overwhelmed, there’s opportunity for data to create real, visible relief. It's the difference between solving hypotheticals and making lives easier.
💡 Key takeaway: Don’t just chase interesting data—go where the pain is. That’s where impact lives.
Projects fail when teams fear admitting mistakes or expressing uncertainty. Psychological safety is critical for successful data initiatives.
"People are afraid to say, 'I don’t understand this,' or 'I think we’re wrong.' That fear kills progress. We have to build spaces where it’s safe to speak up." — Tiankai Feng
He emphasized that when team members feel safe to challenge ideas or share concerns, it leads to better decisions and stronger outcomes. Without this, teams default to surface-level agreement and underperform.
🙌 The result: Teams become more innovative, collaborative, and resilient in tackling complex data challenges.
Ambitious data projects often collapse under their own complexity. Instead, aim for incremental improvements that build momentum and confidence.
"Quick wins matter because they prove you’re not just doing theory—you’re solving real problems. That builds trust." — Tiankai Feng
Tiankai explained that quick wins are trust builders. They help teams see early value and make it easier to secure buy-in for broader transformation.
💡 Key takeaway: Quick wins reinforce the value of data projects, securing support for more ambitious initiatives down the line.
Transforming data projects from technical exercises into meaningful organizational change requires embracing the human element. By focusing on empathy, storytelling, psychological safety, incremental wins, and the 5 Cs, you'll lead projects that deliver lasting, tangible results.
Ready to dive deeper into these insights?
👉 Watch the full webinar to learn more from Tiankai Feng on humanizing your data strategy.
