My Data Podcast Just Dropped
My Data Podcast Just Dropped
(Real Stories, Not Theory)
(Real Stories, Not Theory)
(Real Stories, Not Theory)
Hey there, I’ve been having mind-blowing conversations with data leaders for years. Conversations that made me realize there’s a massive gap between what “best practices” promise and what actually works when you’re sitting in a boardroom trying to justify your next data investment. The good news? Some folks have cracked the code on making data actually useful for business decisions. The bad news? These insights rarely make it beyond their immediate teams. That’s why I’ve launched the “Scale Your Business With Data” podcast. Today, I want to tell you about Episode 1 with Nick White, former data strategy leader at Nike, where we dig into: Why determining the “right” KPIs is harder than building your entire data infrastructure How Nike revolutionized their approach to KPI alignment What happens when AI meets governance (spoiler: it’s not what most consultants tell you) Weekly Resource List: If you’re trying to make sense of how other companies are actually transforming with data, here are three stories that caught my attention this week: M&T Bank’s CDO Andrew Foster explains how they’ve created a federated data governance model that strips 200 hours of manual work per month from business operations while establishing a clear value capture framework to measure their investment in data and AI. American Express AI Evolution Ravi Radhakrishnan, CIO at American Express, describes how the company has expanded from 15+ years of AI use in fraud detection to building comprehensive governance frameworks for generative AI, with human oversight in every use case. Attentive’s CEO reveals that 99% of consumers are willing to share personal data for relevant incentives, while 96% are more likely to purchase when brands send personalized messages - but data quality and trust must come first. Tired of spreadsheets pretending to be your data strategy? Crawford McMillan specializes in transforming data from a cost center to a revenue driver for growing businesses. We’ve helped companies achieve 80% reduction in manual reporting and 3x ROI through right-sized enterprise data solutions that actually work. Schedule a discovery call to see if we’re a fit 3 Things I Learned from Nick About Getting KPIs 1. Start with the Decision, Not the Data Most companies fall into the “KPI trap” - they collect every metric possible because they can, not because they should. Nick shared how Nike transformed their approach by asking the brutal question first: “What decision are we trying to make?” Only then did they work backward to identify which metrics actually mattered. The result? Teams spent less time arguing about measurements and more time acting on insights. This simple flip in thinking eliminated entire categories of reports that nobody was using anyway. 2. Human Consensus Beats Technical Perfection Here’s the dirty secret about KPI alignment that expensive consultants won’t tell you - it’s more about psychology than analytics. Nick described how they spent months building the perfect data model, only to watch it fail because stakeholders couldn’t agree on basic definitions. Their breakthrough came when they focused on getting humans aligned BEFORE building anything technical. They ran workshops to hash out disagreements face-to-face, documented the “why” behind each metric, and made sure everyone understood the business logic. The technical implementation became trivial once the humans were on the same page. 3. AI Won’t Fix Your Governance Problems With all the AI hype, many leaders think technology will magically solve their data quality issues. Nick set the record straight on this one. He explained that AI amplifies whatever data practices you already have. If your team is currently producing unreliable spreadsheets, AI will just help you produce unreliable answers faster. The solution isn’t fancier tools - it’s implementing basic data governance that people actually follow. This means clear ownership, documented processes, and regular quality checks. Get these fundamentals right, and then AI becomes a genuine accelerator rather than expensive false hope. That’s it. Here’s what you learned today:
The thread that connects all these insights? Real transformation happens when you focus on the human aspects of data strategy, not just the technical ones. Want to dive deeper? Listen to the full episode with Nick White where we unpack these concepts with actual examples from Nike’s transformation. |
Hey there, I’ve been having mind-blowing conversations with data leaders for years. Conversations that made me realize there’s a massive gap between what “best practices” promise and what actually works when you’re sitting in a boardroom trying to justify your next data investment. The good news? Some folks have cracked the code on making data actually useful for business decisions. The bad news? These insights rarely make it beyond their immediate teams. That’s why I’ve launched the “Scale Your Business With Data” podcast. Today, I want to tell you about Episode 1 with Nick White, former data strategy leader at Nike, where we dig into: Why determining the “right” KPIs is harder than building your entire data infrastructure How Nike revolutionized their approach to KPI alignment What happens when AI meets governance (spoiler: it’s not what most consultants tell you) Weekly Resource List: If you’re trying to make sense of how other companies are actually transforming with data, here are three stories that caught my attention this week: M&T Bank’s CDO Andrew Foster explains how they’ve created a federated data governance model that strips 200 hours of manual work per month from business operations while establishing a clear value capture framework to measure their investment in data and AI. American Express AI Evolution Ravi Radhakrishnan, CIO at American Express, describes how the company has expanded from 15+ years of AI use in fraud detection to building comprehensive governance frameworks for generative AI, with human oversight in every use case. Attentive’s CEO reveals that 99% of consumers are willing to share personal data for relevant incentives, while 96% are more likely to purchase when brands send personalized messages - but data quality and trust must come first. Tired of spreadsheets pretending to be your data strategy? Crawford McMillan specializes in transforming data from a cost center to a revenue driver for growing businesses. We’ve helped companies achieve 80% reduction in manual reporting and 3x ROI through right-sized enterprise data solutions that actually work. Schedule a discovery call to see if we’re a fit 3 Things I Learned from Nick About Getting KPIs 1. Start with the Decision, Not the Data Most companies fall into the “KPI trap” - they collect every metric possible because they can, not because they should. Nick shared how Nike transformed their approach by asking the brutal question first: “What decision are we trying to make?” Only then did they work backward to identify which metrics actually mattered. The result? Teams spent less time arguing about measurements and more time acting on insights. This simple flip in thinking eliminated entire categories of reports that nobody was using anyway. 2. Human Consensus Beats Technical Perfection Here’s the dirty secret about KPI alignment that expensive consultants won’t tell you - it’s more about psychology than analytics. Nick described how they spent months building the perfect data model, only to watch it fail because stakeholders couldn’t agree on basic definitions. Their breakthrough came when they focused on getting humans aligned BEFORE building anything technical. They ran workshops to hash out disagreements face-to-face, documented the “why” behind each metric, and made sure everyone understood the business logic. The technical implementation became trivial once the humans were on the same page. 3. AI Won’t Fix Your Governance Problems With all the AI hype, many leaders think technology will magically solve their data quality issues. Nick set the record straight on this one. He explained that AI amplifies whatever data practices you already have. If your team is currently producing unreliable spreadsheets, AI will just help you produce unreliable answers faster. The solution isn’t fancier tools - it’s implementing basic data governance that people actually follow. This means clear ownership, documented processes, and regular quality checks. Get these fundamentals right, and then AI becomes a genuine accelerator rather than expensive false hope. That’s it. Here’s what you learned today:
The thread that connects all these insights? Real transformation happens when you focus on the human aspects of data strategy, not just the technical ones. Want to dive deeper? Listen to the full episode with Nick White where we unpack these concepts with actual examples from Nike’s transformation. |
Hey there, I’ve been having mind-blowing conversations with data leaders for years. Conversations that made me realize there’s a massive gap between what “best practices” promise and what actually works when you’re sitting in a boardroom trying to justify your next data investment. The good news? Some folks have cracked the code on making data actually useful for business decisions. The bad news? These insights rarely make it beyond their immediate teams. That’s why I’ve launched the “Scale Your Business With Data” podcast. Today, I want to tell you about Episode 1 with Nick White, former data strategy leader at Nike, where we dig into: Why determining the “right” KPIs is harder than building your entire data infrastructure How Nike revolutionized their approach to KPI alignment What happens when AI meets governance (spoiler: it’s not what most consultants tell you) Weekly Resource List: If you’re trying to make sense of how other companies are actually transforming with data, here are three stories that caught my attention this week: M&T Bank’s CDO Andrew Foster explains how they’ve created a federated data governance model that strips 200 hours of manual work per month from business operations while establishing a clear value capture framework to measure their investment in data and AI. American Express AI Evolution Ravi Radhakrishnan, CIO at American Express, describes how the company has expanded from 15+ years of AI use in fraud detection to building comprehensive governance frameworks for generative AI, with human oversight in every use case. Attentive’s CEO reveals that 99% of consumers are willing to share personal data for relevant incentives, while 96% are more likely to purchase when brands send personalized messages - but data quality and trust must come first. Tired of spreadsheets pretending to be your data strategy? Crawford McMillan specializes in transforming data from a cost center to a revenue driver for growing businesses. We’ve helped companies achieve 80% reduction in manual reporting and 3x ROI through right-sized enterprise data solutions that actually work. Schedule a discovery call to see if we’re a fit 3 Things I Learned from Nick About Getting KPIs 1. Start with the Decision, Not the Data Most companies fall into the “KPI trap” - they collect every metric possible because they can, not because they should. Nick shared how Nike transformed their approach by asking the brutal question first: “What decision are we trying to make?” Only then did they work backward to identify which metrics actually mattered. The result? Teams spent less time arguing about measurements and more time acting on insights. This simple flip in thinking eliminated entire categories of reports that nobody was using anyway. 2. Human Consensus Beats Technical Perfection Here’s the dirty secret about KPI alignment that expensive consultants won’t tell you - it’s more about psychology than analytics. Nick described how they spent months building the perfect data model, only to watch it fail because stakeholders couldn’t agree on basic definitions. Their breakthrough came when they focused on getting humans aligned BEFORE building anything technical. They ran workshops to hash out disagreements face-to-face, documented the “why” behind each metric, and made sure everyone understood the business logic. The technical implementation became trivial once the humans were on the same page. 3. AI Won’t Fix Your Governance Problems With all the AI hype, many leaders think technology will magically solve their data quality issues. Nick set the record straight on this one. He explained that AI amplifies whatever data practices you already have. If your team is currently producing unreliable spreadsheets, AI will just help you produce unreliable answers faster. The solution isn’t fancier tools - it’s implementing basic data governance that people actually follow. This means clear ownership, documented processes, and regular quality checks. Get these fundamentals right, and then AI becomes a genuine accelerator rather than expensive false hope. That’s it. Here’s what you learned today:
The thread that connects all these insights? Real transformation happens when you focus on the human aspects of data strategy, not just the technical ones. Want to dive deeper? Listen to the full episode with Nick White where we unpack these concepts with actual examples from Nike’s transformation. |
Still reading? Book a call to grow your business into uncharted territory!
If you want to achieve ground-breaking growth with Enterprise-grade business intelligence as a key part of your success, then you're in the right place.
Still reading? Book a call to grow your business into uncharted territory!
If you want to achieve ground-breaking growth with Enterprise-grade business intelligence as a key part of your success, then you're in the right place.
Still reading? Book a call to grow your business into uncharted territory!
If you want to achieve ground-breaking growth with Enterprise-grade business intelligence as a key part of your success, then you're in the right place.