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Totally Rewarding Chats

Totally Rewarding Chats

By: WRKdefined Podcast Network
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Summary
 The Totally Rewarding Chats Series is brought to you by co-hosts Sean Luitjens, VP of Community Engagement and Strategic Partnerships at WorldatWork, and Paul Reiman, Founder & Managing Partner of Novo Insights. They will be jamming on all things total rewards and compensation technology with category thought leaders.All rights reserved by WRKdefined Economics Management Management & Leadership Politics & Government
Episodes
  • Tech and Life Science Compensation Trends

    Tech and Life Science Compensation Trends
    Nov 12 2026
    How should a company set equity grants when its valuation can triple or collapse in a single quarter? Two executive compensation consultants who advise pre-IPO tech startups and biotech companies explain how they build pay programs that hold up through big swings. Topics include setting grant guidelines by percentage of company ownership, communicating grants as a number of shares, and adjusting vesting schedules and retention grants in down markets. The episode also covers why tech pay bands are becoming more granular, how to explain stock options to employees, how growing companies choose compensation software, and why a 3 percent merit budget rarely does what leaders expect. Chapters 02:35 – Backgrounds in executive compensation and equity advising 12:02 – How biotech pay practices differ from general industry 13:49 – Using percentage of company to stabilize equity grants 15:03 – Why tech pay bands are getting more granular 16:36 – Communicating pay changes to data-savvy employees 17:50 – Switching between value-based and share-based grants 19:56 – Vesting schedules, cliffs, and off-cycle retention grants 22:54 – Explaining stock options and equity value to employees 27:17 – Choosing compensation software: platforms vs point solutions 38:16 – Why a 3 percent merit budget falls short
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    45 mins
  • Choosing the Right Compensation Data

    Choosing the Right Compensation Data
    Oct 29 2026
    This episode explains how compensation professionals and HR leaders can pick, judge, and use salary benchmark data when pricing jobs, especially in mid-market companies that have outgrown spreadsheets but are not ready for enterprise software. You will learn why pay data goes out of date so quickly, how to benchmark the full scope of a role instead of its title, how to handle title inflation, and how to price hybrid roles where one person does several jobs. The conversation also compares the strengths and weaknesses of traditional salary surveys, employee-reported pay data, and aggregated or predictive data sets, and covers what to do when a leader brings you a pay number generated by an AI tool. It closes with why executives still struggle to understand compensation, even though pay is often their largest expense. Chapters 03:49 – Compensation tools for companies outgrowing spreadsheets 13:09 – Why salary benchmark data goes stale so quickly 14:47 – Benchmarking the full job scope instead of the title 17:15 – Pricing the job versus fitting a job to a price 19:59 – Handling title inflation in smaller organizations 21:55 – How to price hybrid and blended roles 26:25 – Pros and cons of traditional salary surveys 28:52 – What employee-reported salary data is useful for 33:29 – Trusting aggregated and predictive pay data 39:37 – Why AI pay recommendations still need human review
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    44 mins
  • For HR leaders navigating new reporting rules

    For HR leaders navigating new reporting rules
    Nov 5 2026
    What happens when the EU Pay Transparency Directive forces companies to report gender pay gaps by worker category, and the math starts flagging problems that may not exist? Labor economist Brian Levine and people analytics expert Helen Friedman of Merit Analytics explain how organizations are getting ahead of EU reporting requirements, why narrow worker categories can backfire under a fixed 5 percent threshold, and why job grades are often the more defensible way to group equal value work. The conversation also covers why pay equity is only one part of workplace equity, how career path choices and promotion decisions create long-term pay gaps, where AI actually helps in pay equity analysis, and how to find the root causes behind pay gaps that keep coming back year after year. Chapters 09:23 – Where pay equity and transparency work stands today 10:51 – Getting ahead of EU directive gender pay gap reporting 13:26 – How to define equal value work and worker categories 19:45 – Will the 5 percent threshold create false flags 23:31 – Why the raw pay gap misses the bigger problem 24:08 – Selection and self-selection in career paths 29:51 – Using data to make fairer promotion decisions 32:10 – What AI can and cannot do for pay equity analysis 36:42 – Finding the root causes of recurring pay gaps 43:16 – Better HR data and evidence-based decisions
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    48 mins
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