HR Data Labs

Discover the transformative power of applying Amazon’s working backwards framework to HR. This episode unpacks how HR leaders can turn employees into loyal customers and leverage AI to create impactful HR products that truly delight. If you're ready to revolutionize your HR tech game, listen now!

Timestamps:
00:00 - Introduction to applying Amazon’s customer obsession in HR
02:00 - Historical perspective: Dell’s direct approach as employee-internal customer model
06:00 - Justifying HR technology investments with ROI examples from compensation software
11:00 - The five questions of the working backwards framework
12:00 - Constructing a true customer persona & insights from HR data
15:00 - Defining the core customer problem in HR: Building confidence in managers
16:30 - Crafting solutions & benefits — example of an AI-powered coaching tool
19:00 - Writing the future press release & internal FAQs to clarify the product vision
21:00 - Iterative testing & how to involve stakeholders in feedback cycles
24:00 - Measuring success & validating assumptions through prototypes & beta tests
26:00 - How AI accelerates customer understanding & innovation in HR
28:00 - Making HR a product team: influencing leadership & fostering customer obsession
30:00 - Conclusion: Start small, ask questions, test assumptions, and keep the customer at the heart

Are you ready to feel the heartbeat of what's next in HR technology? In this episode, Oz Khan from ADP Ventures pulls back the curtain on how AI is transforming workflows, building trust, and reshaping the very fabric of work. This isn’t just talk — it’s a revolution happening right now, and you need to hear it.

In this episode:

Timestamps:

00:00 - The pulse of HR innovation — what’s coming next

02:10 - How ADP’s labs culture sparked real growth

05:10 - Oz shares a fun, surprising fact about himself

06:10 - The seismic shift from AI tools to workflow automators

08:25 - How stability and proven value shape HR tech adoption

09:42 - The co-pilot becomes the control tower — deep dive

11:00 - APIs, data connectivity, and solving enterprise complexity

12:44 - Navigating compliance, risk, and the law in HR AI

13:51 - Why generative AI isn’t ready to replace humans yet

15:54 - The real challenge of trust: transparency, training, guardrails

17:46 - The importance of judgment and experience in AI-driven decision making

20:40 - Building confidence with high-fidelity, deterministic AI solutions

23:38 - The last mile decision — where human judgment still rules

26:11 - The dangers of overhyping AI’s potential — and the truth

29:52 - Education, skills, and the demographic shifts AI will bring

33:53 - The art of flexible, configurable HR tech — how founders navigate ‘craft’

37:16 - From $1M to scale — what it takes to grow AI-driven HR solutions

42:56 - Real-world impact — ADP’s investments in Naya, Emma, and beyond

43:38 - The human side: solving emotional and organizational problems, not just tech

44:22 - The future is OpenClaw and beyond — what’s next in AI bots

Resources & Links:

Connect with Oz Khan:

This isn’t just a conversation — it’s a call to action. Whether you’re in HR, investing, or building the future, you’ve got to understand the truth about AI’s power, limits, and the human judgment that will always be king. Don’t get left behind. Your next big move is waiting — listen now, and be part of the revolution!

Are we truly prepared for the dark side of AI in talent acquisition? In this episode, my great friend, Dara Brenner from Employ drops truth bombs about candidate fraud, the evolution of AI governance, and how organizations can stay ahead in this high-stakes game. If you're a leader in HR or recruiting, this is your wake-up call—trust me, you’ll want to hear this.

Here is the link to the fund set up for Dara's late husband: Please click here.

In this episode:

Resources & Links:

Connect with Dara:

Timestamps:

00:00 - Introduction: The urgent need for trust in AI-driven hiring

02:08 - Dara Brenner’s background and journey through HR tech

03:20 - The fun side: Dara’s unexpected past as a restaurateur

05:45 - The impact of personal tragedy: Creating a foundation for brain tumor support

08:34 - The hidden threat: Candidate fraud in the age of AI

09:49 - How AI can be used nefariously in recruitment

10:56 - Layers of fraud detection: From resumes to deep fakes

12:01 - The staggering cost: $600 billion from resume fraud

14:26 - Organizations’ vulnerabilities: North Korea, bad actors, and real risks

15:36 - Balancing security with talent access: Where to draw the line

22:34 - Governance and compliance: IBM Watson’s role in transparency

23:46 - Constant AI audits: Like having a doctor in your pocket

28:31 - Future of recruitment: From ATS to AI-native systems

29:55 - Building AI into the DNA from day one—code as policy

32:29 - The evolving role of recruiters: proactive, strategic, data-driven

33:53 - Societal impacts: Demographics, immigration, and big-picture workforce planning

36:10 - Dara’s parting wisdom: Evolving trust, governance, and human oversight

Final thought:The future of hiring is not just about smarter algorithms—it's about building a trustworthy system where technology and humanity work hand in hand. Stay vigilant, stay proactive, and never stop asking: are we doing this right? Because the stakes couldn’t be higher.

Are you tired of dealing with outdated recruiting strategies? Wondering if AI can truly revolutionize hiring? This episode dives into the gritty truth about how modern metrics and emerging AI tools are reshaping talent acquisition—sometimes for better, sometimes for worse.Join us as we unpack decades of recruiting wisdom, the pitfalls of cost-per-click, and what’s next in HR tech.

In this episode:

Useful links:

Reach out to Steven Rothberg:

Timestamps:

0:00 - Welcome and episode overview: Are recruitment metrics still holding up?
00:42 - Introducing Stephen Rothberg and college recruiter’s journey
01:14 - The roots of traditional recruiting: From flyers to newspapers
02:25 - Starting a business from a summer job and risk-taking mentality
03:52 - The Winnipeg Jets story: Childhood risks and lessons in boldness
05:23 - The shift from inefficient to performance-based ad models
06:49 - The real meaning of "click" and the confusion across platforms
08:13 - The rise of cost per application and its emotional impact on employers
09:54 - Defining "qualified applications"—subjectivity and its pitfalls
11:35 - Why scaling bad processes makes them worse
13:08 - The evolution of pay-per-click and undisclosed definitions
14:54 - The deadly cycle of bad job descriptions and reposting
16:23 - How hiring for "fit" often misses the mark and costs real money
17:10 - Qualification in hiring: Who judges? The subjectivity of recruiters
18:29 - Scaling broken processes: The airplane manufacturing example
19:54 - The quiet cost of bad candidate sourcing: The ATS funnel
22:17 - The dangerous hype around AI and its current limitations in hiring
23:12 - The black hole of AI decision-making and lack of transparency
26:24 - The importance of honest job descriptions and pay transparency
28:43 - Do employers prefer CPC, duration-based, or new models?
30:01 - The chase for quality candidates and the costs involved
31:27 - How to effectively invest in recruitment—long-term wins over shortcuts
32:28 - The impact of AI on assessments and candidate matching
35:55 - The legal peril of AI-driven hiring decisions and audit trail challenges
37:25 - Final thoughts: Embracing process, transparency, and smart metrics

In this episode, we explore how artificial intelligence is revolutionizing HR, with a focus on building trust through data privacy and security. Join us as we discuss practical steps, emerging challenges, and the evolving role of HR professionals in the AI era.

Key Topics:

Resources & Links:

Connect with Brian Platts:

Timestamps: 

00:30 - Welcome and introduction to the episode

01:15 - Brian Platts’ background in HR and software

02:08 - Flurry’s mission to make data meaningful for HR

03:26 - Fun fact: starting career driving a semi truck

04:44 - AI in HR: privacy, security, and data foundations

05:53 - Preparing your HR data for AI adoption

06:08 - Challenges with data quality and use cases

07:08 - Security considerations: private vs. public data

08:22 - Trusting AI vendors and data-sharing risks

09:15 - Teaching AI to query data securely

10:07 - Data organization and semantic layers

11:29 - Improving chatbots and avoiding misinformation

12:26 - Ensuring process accuracy and data integrity

13:14 - Sharing vs. protecting employee data

14:05 - Re-implementing permissions in AI-driven systems

15:01 - Education and awareness around AI security

16:13 - Learning from SaaS security issues during early cloud adoption

17:18 - HR’s role in AI education and safeguarding IP

18:14 - Balancing productivity gains with security controls

19:06 - AI’s impact on HR future: automation and new workforce roles

20:16 - The concept of the “Meat Layer” and human-AI collaboration

21:02 - Will AI replace HR jobs or empower them?

22:16 - The limits of current AI technology and future innovations

23:03 - Analogies: AI as a horse and the importance of tooling

24:06 - Embracing AI to enhance human work rather than replace it

25:16 - Reinventing HR processes beyond IT-led automation

26:18 - Regulatory challenges and incremental HR AI adoption

27:30 - How HR can lead responsible AI integration

28:03 - Final advice for HR professionals: think broadly and connect the dots

In this episode, we dive deep into the challenges and opportunities of HR data governance, exploring how organizations can improve data quality, ownership, and usability in a rapidly evolving AI landscape. Join us for practical insights from seasoned HR analytics experts on building a data-driven culture that supports strategic decision-making.

Key Topics:

Timestamps:

00:00 - Introduction: Why HR data governance matters today

02:30 - Challenges HR faces with data quality and accuracy

06:15 - Why organizations struggle to demonstrate ROI from HR data

09:00 - Cultural and mindset barriers to effective data management

11:00 - The impact of AI and machine learning on HR data quality

12:30 - Context and system integration challenges across HR tech stack

15:11 - Defining HR data governance: Ownership, stewardship, and quality

17:00 - Creating a data glossary and system of record for HR data

19:05 - Real-world examples of poor HR data visibility and audit issues

21:00 - Using chatbots and AI: risks, benefits, and data consistency

24:00 - The importance of documentation and version control in AI applications

27:40 - Practical steps to start your HR data governance journey

30:00 - The significance of aligning metrics and defining owners

33:00 - Building a culture of data excellence and quick wins

36:00 - Addressing expectations for pristine data and managing realities

37:00 - Final recommendations for HR leaders to improve data governance

Connect with Guests:

🚀 Dive into the future (at least the next 6 months) of HR with the latest episode of the HR Data Labs podcast! In the Season 10 recap, host David Turetsky explores the evolving landscape of compensation, strategy, and people analytics. We recap the current Season 10, where we discuss addressing training gaps, the impact of AI in HR, and other cool episode topics. Then we review our prediction for the past 6 months and make bold predictions for first 6 months of 2026.

Join us for a thought-provoking discussion that prepares you for the challenges and opportunities ahead. #HRInnovation #FutureOfWork #HRDataLabs

Join host David Turetsky and guest Paul Reiman from Novo Insights as they delve into the dynamic world of compensation strategies and pay transparency. Discover how regulatory changes in the US and Europe are shaping the landscape, the critical role of job documentation, and the impact of technology in fostering transparency. Tune in for insightful predictions for 2026 and learn how political climates may influence future pay transparency laws.

Chapters

Quotes:

Craig Friedman, Talent and Skills Transformation Leader at St. Charles Consulting Group and author of Enterprise Skills Unlocked, joins us this week to discuss the shift toward skills-based organizations. He breaks down how data-driven transformations allow companies to move from simple headcount management to true capability management. Craig also shares practical advice on how to prioritize skills projects to ensure they solve real business problems and deliver ROI.

[0:00] Introduction

[5:05] What does a skills-based transformation look like in practice?

[11:57] How different teams leverage skills data differently

[26:14] The impact on Learning and Development (L&D)

[36:20] Closing

Quick Quote

“A lot of the reason we're doing this now when we couldn't do it before is because of these more advanced tools in data analytics and AI and machine learning that actually help us manage data at that scale.”

Link to Craig's book: https://a.co/d/0naqmvh

🚀 Exciting changes are coming in 2026! Join David Turetsky as he shares his vision for HR Data Labs, focusing on positivity and growth. Discover how we're merging brown bag lunches into our podcast and launching something new for HR Data Labs. #HRDataLabs #2026Vision #Positivity

Chapters