What does dentistry have to do with data analytics? More than you'd think. Thais Cooke went from cleaning teeth to cleaning datasets and her unconventional path turned out to be a superpower. In this episode, Thais joins Juan and Tim to talk about why subject matter expertise is the ultimate force multiplier, how to build trust with stakeholders (hint: "I don't know" is a valid answer), and why the best data professionals aren't technical specialists — they're problem solvers.

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This is the takeaway episode where Thais Cooke joins Juan and Tim to talk about why subject matter expertise is the ultimate force multiplier. Oh, and what does dentistry have to do with data analytics? More than you'd think!

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Your dashboards show you what's happening. Process mining shows you why — and what to do about it. In this episode, Bobby Brill sits down with Dan Grady to demystify process mining: what it is, how it works within the ServiceNow platform, and why organizations using it are uncovering years of hidden inefficiency they never knew existed.

Dan walks through real customer stories — from a double approval process for printer toner that was costing 2 days per request to a single form-field change that saved 7 years of manual work per month — and explains how process mining moves you from raw data to actionable insight faster than any traditional approach.

Dan Grady has a technology career that spans over 25 years. The last 10 spent at ServiceNow. In his current role as Director of Product Management, he is focused on helping customers identify process improvement opportunities through the use of ServiceNow's Process and Task Mining solution. Outside of the office, he enjoys spending time with his wife and 3 girls, public speaking, bad NY sports teams, a good happy hour deal, and storytelling.

Whether you're new to ServiceNow or a seasoned admin, this episode will change how you think about your workflows.

🔗 Get started with Process Mining: https://www.servicenow.com/community/process-mining-article/servicenow-process-mining-formerly-process-optimization-faq/ta-p/2309083

📄 Learn more about ServiceNow: https://www.servicenow.com/docs/

🎓 ServiceNow Docs YouTube Channel: https://www.youtube.com/channel/UCQjE37R-Y4DTq7kUWPO83Wg

Chapters
0:00 – Introduction & Dan Grady's Background
1:13 – What Is Process Mining? (The X-Ray for Your Business)
2:08 – Why Dashboards Alone Aren't Enough
3:56 – From Raw Data to Actionable Insights
4:59 – The Printer Toner Story: Removing a Step, Saving Two Days
6:01 – The Spaghetti Bowl: Visualizing Your Processes
7:34 – The "47 Years" Moment That Shocks Every Customer
8:43 – Finding Automation Opportunities with Process Mining
10:49 – Best Practices: How to Avoid Getting Overwhelmed
12:35 – Getting Started: First Steps on the Platform
15:11 – Real Customer Use Cases (Approvals, Routing & More)
17:59 – Why You Never Stop Needing Process Mining
20:50 – The Analytics Stack: Operational Reporting → Platform Analytics → Process Mining
22:45 – Closing & Where to Learn More

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Want to get the honest no bs scoop of what happened at the Gartner Data & Analytics in Orlando, then this short and sweet episode is for you. This was an impromptu recording where Sanjeev Mohan and Ryan Dolley join Juan and Tim to share what they learned.

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Juan and Tim rant about whats on their mind going into Gartner Data and Analytics conference: "Context" is going to be the word of the week, The Execution Gap, Decision intelligence might be the bridge and the thing nobody's talking about yet: context lock-in.

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The Human in the Loop | Ethical AI with Di Le
ServicveNow Insights Podcast - hosted By Bobby Brill

What does it actually mean to build AI responsibly? Not the buzzword version. The real version. In our latest episode, I sat down with Di Le — AI Ethicist and Human-Centered AI Strategist at ServiceNow — and she broke it down in a way I hadn't heard before.

Most people use Ethical AI, Responsible AI, and Human-Centered AI interchangeably, and Di breaks down exactly where each one lives and how they apply to building AI that aligns with our societal values. Fairness. Transparency. Bias. Beyond evaluation and technical talking points, these are also design decisions with real consequences for real people — and operationalizing them is harder than most organizations want to admit.

One line from Di that stopped me: "People have crossed oceans and built monuments in honor of our capability to think. And I just want people to preserve that and not surrender it so freely." That's the episode in one sentence.

To learn more about Ethical AI and reseatch from Di Le and more - https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1020&context=sighci2025

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1025&context=sighci2024

https://www.youtube.com/watch?v=QhVY-85A-Wk&t=5s

ServiceNow Insights Podcast 🎧 The Human in the Loop — now available wherever you listen to podcasts.

0:00 – Introduction & Di Le's Background
1:35 – Is Ethical AI Just About Preventing Skynet?
2:22 – Responsible AI vs. Ethical AI vs. Human-Centered AI
6:34 – Why All Three Are Deeply Interconnected
8:39 – When "Amazing" Tech Goes Wrong: The Adobe Example
10:07 – Fairness, Transparency & Accountability Explained
12:06 – The Mug Factory: Understanding Bias in AI
14:52 – Transparency & Interpretability in AI Design
16:48 – Keeping Humans Genuinely in the Loop
18:06 – Accountability & Human Oversight
20:39 – Why Bias Isn't a Bug You Can Just Fix
22:30 – How ServiceNow Approaches Responsible AI
23:11 – Why Di Chose ServiceNow (The Origin Story)
27:09 – One Thing Everyone Should Do With AI 28:38 – Closing

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Most data and AI initiatives don't fail on technology — they fail on meaning. In this episode, Juan and Tim chat with Säde Haveri, who makes the case that metadata is the bridge between systems and people: the language and structures that help humans understand, trust, and use data in their daily work. Her focus isn't on building smarter pipelines, but on turning complexity into shared understanding so that data actually drives decisions and behavior change. Because if your data doesn't speak your language, it simply won't work for you.

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This is the takeaway episode with Säde Haveri where she makes the case that metadata is the bridge between systems and people. Most data and AI initiatives don't fail on technology — they fail due to the lack of meaning. If your data doesn't speak your language, it simply won't work for you.

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