About This Episode
In episode 10 of Data and AI Heads, host Ian Allison sits down with Ken Tingle, Vice President of Business Intelligence, to unpack a concept Ken calls "data empathy": the practice of connecting the lived experiences and goals of business stakeholders to the reports and dashboards a BI team produces. Ken's perspective is grounded in firsthand experience. He began his career on the sales side, where he received a daily folder of roughly 50 reports that felt disconnected from his strategic objectives, leaving him feeling lost rather than empowered. That frustration became the catalyst for his move into BI and his commitment to building something better.
Ken walks through the practical mechanics of cultivating data empathy, from scheduling regular face-to-face meetings with stakeholders instead of defaulting to email, to pausing at the 80 percent mark of any project to validate assumptions before finalizing a deliverable. He also addresses harder organizational challenges: how to say no without damaging relationships, how to bring multiple stakeholders into the room when data touches several business lines, and how to navigate inter-office politics by keeping every conversation anchored to shared company goals.
The episode closes with a broader warning relevant to any data or AI leader: as automation and AI continue to advance, the empathy component of data work risks being lost. Ken argues that no technology can replicate the trust built through genuine human connection, and that the relationship with a stakeholder is as strategically important as the insight being delivered.
Key Takeaways
- Ken Tingle defines data empathy as connecting the lived experiences and daily goals of business stakeholders to the reports and dashboards produced for them, rather than pushing numbers forward without context.
- Starting his career in sales, Ken received a daily folder of roughly 50 disconnected reports that left him feeling lost, an experience that directly motivated him to move into BI and advocate for stakeholder-centered reporting.
- Building trust with stakeholders takes time and cannot be shortcut by technology; Ken recommends face-to-face meetings and even informal lunches over email because in-person interaction carries emotional and relational cues that text simply cannot convey.
- Avoiding assumption-based logic is a core discipline: Ken advises pausing at approximately the 80 percent mark of any reporting initiative to re-engage the requester and confirm the intended outcome before finalizing the work, because assumed conclusions are frequently wrong.
- When a report draws on data that touches multiple business lines, Ken insists that all relevant stakeholders be present for the discussion, reducing the risk of biased or incomplete narratives even when this slows the process initially.
- Saying no is a legitimate and necessary part of data empathy; because the relationship has been built, stakeholders understand the reasoning behind a declined or deferred request rather than experiencing it as a cold rejection.
- The push for efficiency in BI can erode empathy by eliminating the conversations needed to represent stakeholders accurately; Ken warns teams to pause during automation and dashboard-building projects to ensure the story being told still reflects the people behind the numbers.
- AI and broader technological advancement can mimic empathy but cannot replicate genuine human connection, making face-to-face relationship-building a durable competitive advantage for BI teams as automation expands.
What We Cover
Frequently Asked Questions
What is data empathy and why does it matter for BI teams?
Data empathy, as defined by Ken Tingle, is the practice of connecting the lived experiences and daily goals of business stakeholders to the reports and dashboards a BI team produces. Instead of delivering numbers for the sake of numbers, a data-empathetic team understands how a stakeholder's work influences those numbers and crafts a story that resonates with that individual, their manager, and executive leadership. It matters because reports that lack this context leave business users feeling lost and unable to act on the information.
How do you build trust between a BI team and business stakeholders?
Ken Tingle recommends consistent face-to-face engagement over email or messaging tools, including regular scheduled meetings and informal lunches. Trust is built gradually through mutual conversation about shared goals, not just transactional report requests. When stakeholders know the BI team genuinely understands their day-to-day work, they are more likely to share context early, reducing rework and miscommunication down the line.
How can BI teams avoid being overwhelmed by ad hoc reporting requests while still practicing data empathy?
Ken Tingle ties the ability to say no directly to the quality of the relationship. When a BI team has invested in genuine stakeholder relationships, a declined or deferred request is understood in context rather than perceived as dismissive. The key is to anchor every prioritization conversation to the organization's strategic pillars, so stakeholders understand why certain work must wait, not because the team is unresponsive, but because competing priorities have been clearly established.
Why is assumption-based logic a problem in business intelligence work?
Ken Tingle warns that historical experience can lead BI practitioners to assume they already know what a report will show or what the stakeholder needs, effectively removing the requester from the process. In his experience, assumption-based conclusions are frequently wrong. His recommended practice is to pause at roughly the 80 percent mark of any project, re-engage the stakeholder to confirm the intended outcome, and present findings as open for discussion rather than as a predetermined answer.
How should BI teams handle situations where data touches multiple business lines with potentially competing interests?
Ken Tingle's rule of thumb is that if the data in a report pertains to a business line that is not the one making the request, representatives of that affected group must be present for the discussion. While this can initially slow the process, over time stakeholders come to understand that full representation is necessary to tell an accurate story. Keeping every conversation anchored to shared organizational goals, rather than referencing past political conflicts, is how Ken navigates the interpersonal complexity this creates.
What is the risk of prioritizing efficiency over empathy in BI and data work?
Ken Tingle cautions that the faster a BI team moves in the name of efficiency, the less time it has to engage with the stakeholders who influence the data. This is especially relevant when building automated reports or dashboards: if the team does not pause to understand the story being told to the end user, the output may be technically correct but contextually misleading or meaningless. Efficiency is valuable, but not at the cost of the human context that makes data actionable.
Can AI replace the empathy component of business intelligence and data work?
According to Ken Tingle, AI can mimic empathy but cannot replicate genuine human connection. As automation and AI continue to advance, the empathy dimension of data work is at increasing risk of being deprioritized or assumed away. Ken's view is that the trust and understanding built through face-to-face interaction remain a durable advantage that technology cannot fully substitute, and that BI leaders should consciously protect those relational practices as their tech stacks evolve.
About the Guest
Ken Tingle
Ken Tingle is a Vice President of Business Intelligence who began his career on the sales and business side of organizations before transitioning into BI. His move was directly motivated by the frustration of receiving large volumes of reports that lacked connection to strategic objectives, an experience that gave him a firsthand understanding of how data teams are perceived by business stakeholders. Ken has channeled that perspective into a framework he calls data empathy, which centers on representing the lived experiences of stakeholders in the stories that data teams tell. He has written on this topic for CXO Tech Magazine and actively works to cultivate data empathy within his teams by prioritizing face-to-face stakeholder engagement, cross-functional collaboration, and relationship-building practices drawn from his sales background.
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