The Analytics Power Hour #281

Episode Title: Analytics: The View from the Corner Office with Anna Lee
Date: September 30, 2025
Guests: Anna Lee (CEO, Flybuys)
Hosts: Michael Helbling, Moe Kiss, Tim Wilson, Val Kroll, Julie Hoyer

Episode Overview

In this episode, the Analytics Power Hour team brings Anna Lee, CEO of Flybuys (Australia’s leading loyalty program), into the spotlight for a candid “corner office” conversation. The discussion centers on how analytics and data-driven decision-making play out at the executive level, what it takes to drive true data culture throughout an organization, and the importance of evidence-based leadership. Anna draws from decades of experience in finance, operations, and executive roles, sharing her personal philosophies on productive curiosity, informed pragmatism, and the realities—opportunities and challenges—of being a data-led business today.

Key Discussion Points & Insights

Flybuys, Anna’s Background, and the CEO Perspective

• [02:07]–[03:43] Anna introduces herself: Chartered Accountant background, extensive experience as CFO/COO before stepping into the CEO role at Flybuys, Australia’s largest retail coalition loyalty program (jointly owned by Coles and Wesfarmers, ~10 million active members, 95% brand awareness).
  • Anna’s journey: “I think CEOs come in different shapes and sizes. It really comes down to what is suitable for the business at its time.” [04:21]
  • Digital and data-driven transformation is at the heart of her mandate as CEO.

The Value—and Challenge—of Resetting Organizational Stories

• [06:45] Anna: The need to challenge and reset long-held organizational “myths” about data and performance, inherited over 30 years at Flybuys.
  • "Over time, some of those stories just become, you know, they become myths rather than fact." [07:13]
  • Emphasizes the importance of separating story from evidence within large, established brands.

Leading with Data from the Top

• [08:10]–[12:55] Anna on embedding a data-first culture:
  • Importance of CEO modeling: “You have to acknowledge there’s a CEO, you have the biggest way of influencing how it’s extraordinarily powerful. And I think being very clear that data plays such an important role in making decisions, that’s super important.”
  • Introduces key concepts:
    • Productive Curiosity: Encouraging curiosity with purpose—“You don’t want to be curious to the point where it’s just a wasted effort... There’s a real skill around productive curiosity.”
    • Informed Pragmatism: Balancing the data practitioners’ desire for precision with business trade-offs—“At some point you’ve also got to decide what are the decisions that absolutely need precision and what are the decisions actually just need enough to validate that it’s kind of legit and it smells right.” [10:50]
  • Structure at Flybuys: Centralized platform/data hygiene teams plus democratization of data skills across the org.

How Leaders Can Avoid Creating "Swirl"

• [14:07] Moe & Anna: Discussing leadership self-awareness in data requests.
  • Moe: “Sometimes folks in leadership... don’t realize like, teams hear that and they hear I need you to look at X and I need an answer… with like 100% confidence.”
  • Anna: “It’s got to always feel like this should only take you an hour or two. If it takes you longer than that, stop.” [14:44]
    On why it's essential to frame questions with context and understand the complexity behind analytical asks.
  • The importance of problem framing: “What is the problem you’re trying to solve here?” [15:11]
  • Encourages analysts to seek pragmatic solutions rather than just responding to direct, potentially unproductive requests.

Building Data Literacy and Evidence Seeking Across the Org

• [18:09] Anna: Vision is to ensure everyone at Flybuys has sufficient data competency—“They don’t necessarily have to have found it, but they need to know what to do with it.”
• [19:07] Val: How org design can hinder cross-functional evidence gathering.
• [20:42] Anna: Key levers for data culture:
  • The balance of consistent, disciplined reporting (e.g., regular value-driver tree meetings) and space for questioning/adding value.
  • “It grounds people in the right evidence. But the forums that which you talk about them create the space for people to ask the questions.”
  • Value-driver trees help prioritize and focus discussion: “That branch contributes 85% of everything; let’s make sure we talk about that." [24:04]
  • CEO intentionally attends and models effective data conversation, tying quantitative results to business impact.

The Bottom-Up: What Makes a Strong Data Team?

• [25:43] Anna: Looks for clear narrative and actionable insights—not raw tables.
  • “One of the most important things... is what is the so what? And if there isn’t a clear so what then actually just take the table out.” [25:45]
  • The “so what?” mindset—pushing for clarity, actionability, and reducing cognitive load on stakeholders.

Advice for Analysts: Staying Strategic and Connecting to the Big Picture

• [29:14] Anna: Encourages analysts to connect unit-level metrics back to overall business goals.
  • Describes embedding analysts with ops directors at The Iconic, with everyone tied together via OKRs on cost per order:
    • “There was a beauty around the fact that you could have a group that focuses on [specific metrics]… but then every month we would come back and actually review what everyone contributed.”
  • Fostering trust and collective problem-solving: “Creating this culture that we’re all in together and collaboratively can solve it. Rather than create silos…”

Who Owns Data Culture? Why It’s Not the Analyst’s Job

• [34:08] Anna: “It should never be the role of the data insights team to be driving the culture.” [34:08]
  • Leadership must role model both culture and data-driven behaviors; otherwise specialists will burn out on “unfair” expectation.
  • “All of those insights will tell you that if you put the onus on specialist teams to drive deep cultural behaviors that you expect of everyone… it’s going to end in tears.”

Making Purpose Tangible—Tying Data to Business Vision

• [36:48] Anna: Authenticity in vision/purpose—Measuring member value in tangible, data-driven ways.
  • “If we’re going to be real and say we’re here to help Australians get more value... then shouldn’t we be demonstrating that we’re actually providing them more value?”
  • Emphasizes not letting vision statements become meaningless—measure and communicate progress with data.

Org Structure for Data Teams: Centralized, Embedded, or Hybrid?

• [39:17] Anna: “The most important attitude is what’s right for the business at the time.”
  • Flexibility is key—at The Iconic, embedded analysts worked best; at Flybuys, a hybrid system (squads + centralized insights/platform) fits current needs.
  • “I really hate reporting lines. Like I just think great businesses…it should just be spiderwebs.”
  • Relationships and informal networks ("spiderwebs") across the org often matter more than formal structure.

How Analysts Lose (and Keep) Executive Trust

• [45:23] Anna: Keys to building credibility:
  • Letting go of the need to present all data work—focus instead on the “killer message.”
  • Coaching, rehearsal, and contextual preparation are vital before presenting to senior stakeholders.
  • Recommends people leaders empower and debrief analysts, reducing anxiety and framing first-time exec presentations as safe learning experiences.

How to Quantify the Value of “Learning”

• [52:16] Anna: Measuring intangible ROI (e.g., value of learning, experimentation) is inherently hard—sometimes it’s about enablement narratives, sometimes about intuition and risk tolerance.
  • “There are some things that are just going to be really easily tangible... and then you will have ones that have much...slower payback.”
  • Not everything must be precisely quantifiable, but decisions should still be as evidence-informed as possible.

Memorable Quotes

• On Productive Curiosity:

  “There’s a real skill around productive curiosity. Embedding that type of mindset, that’s what I kind of demonstrate as lead by example. It’s like being very, very disciplined about the types of questions I ask.”
  – Anna Lee, [09:30]

• On Analyst Requests from Executives:

  “It’s got to always feel like this should only take you an hour or two. If it takes you longer than that, stop. Because it’s not like the value of what you’re going to come back with is not worth more than two hours.”
  – Anna Lee, [14:44]

• On “So What?”

  “One of the most important things... is what is the so what? And if there isn’t a clear so what, then actually just take the table out.”
  – Anna Lee, [25:45]

• On Driving Data Culture:

  “It should never be the role of the data insights team to be driving the culture... Leadership must role model everything.”
  – Anna Lee, [34:08]

• On Organizational Structure:

  “There is just no right or wrong answer. You’ve really got to understand where the business is at and meet it there to form the right structure... I really hate reporting lines. Like I just think great businesses...it should just be spiderwebs.”
  – Anna Lee, [41:27]

• On Judgment and Evidence:

  “Not everything needs to be precise and completely evidence-based. We’re not here on a criminal case where the burden of evidence is so high. Sometimes it’s about being able to complement those hunches...”
  – Anna Lee, [54:02]

Notable Moments & Timestamps

• [04:21] Anna’s take on CEO backgrounds and the value of coming from finance.
• [06:45] The need to “reset stories” in long-established data cultures.
• [10:50] “Productive curiosity” and “informed pragmatism” defined.
• [14:44] Time-boxing analysis and being up-front about the “business value” of a data question.
• [18:09] Vision for universal organizational data fluency.
• [24:04] Implementation of regular value driver tree meetings to anchor decisions to high-impact metrics.
• [25:45] “So what?” as a defining question for data presentations.
• [34:08] Why data culture must be led from the top, not by analysts.
• [39:17] Organizational “spiderwebs” over strict reporting lines.
• [45:23] On preparing analysts for executive presentations and protecting them from first-time mishaps.
• [52:16] Discussing the struggle—and necessity—of quantifying the “value of learning.”

Summary for Listeners

This episode offers a rare executive-level perspective on analytics and business transformation, with Anna Lee articulating how true data-led cultures thrive when leaders are deliberate, curious, and pragmatic. The conversation is filled with practical wisdom—on balancing rigor with action, on clearing away data mythology, and on fostering both trust and learning across the business. Anna’s blunt assertion that data teams cannot, and should not, be the sole drivers of data culture is a key takeaway, as is her insistence on always answering the “so what?” before presenting data to the C-suite. The episode is laced with compassion, actionable advice, and relatable anecdotes from both Anna and the hosts, making it a must-listen for analytics professionals looking to elevate their influence and organizations aspiring to harness the true power of their data.

Key Takeaways

• Executive sponsorship and modeling is essential for real data culture.
• Move from “data for data’s sake” to actionable, business-changing insights: Always answer “so what?”
• Balance rigor and realism: Not every decision needs perfect precision.
• Build structural and informal connections (spiderwebs) for organizational analytics, rather than rigid silos.
• Leadership must create psychological safety and learning opportunities for analysts to communicate up the ladder.
• Data teams can—and should—lose the burden of “owning” culture alone.

Further Exploration

• James Clear, Atomic Habits: Anna’s favorite book for its wisdom on action and changing perspectives ([58:23])
• [Value-driver tree meetings as a performance tool] [20:42]
• [The importance of flexible, context-sensitive data team structures] [39:17–44:03]

This summary is designed to bring the heart and substance of the episode to those unable to listen in full. For more insights, check out the full transcript or visit the Analytics Power Hour website.