Webinar-How to Elevate Your Talent Analysis with Multiple Data Sources
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The landscape of compensation data has changed. HR teams and compensation specialists have more choice than ever in what sources they can use in their analysis, and candidates and employees alike are more informed of their value in the marketplace. For some, this has been a shift towards more positive conversations with employees, but it can be a scary prospect without the right data to back you up. Join Michael Diaz, Compensation and Benefits Analyst at Sungevity, and PayScale’s Mykkah Herner as they discuss: - Current market trends impacting compensation - The growing data market and factors to consider when selecting sources - How to integrate new data sources into your mix - The business impact of quicker, more accurate matches
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Webinar-How to Elevate Your Talent Analysis with Multiple Data Sources
- 1. How to Elevate Your Talent Analysis with Multiple Data Sources Mykkah Herner, MA, CCP Modern Compensation Evangelist Michael Diaz Benefits and Compensation Analyst
- 3. www.payscale.com Agenda • Introduction • Why getting it right matters • Data market overview • What to consider • Real-time data in action
- 4. Introduction
- 5. www.payscale.com Michael Diaz Benefits and Compensation Analyst https://www.linkedin.com/in/michael-diaz-a2810568 Mykkah Herner, MA, CCP Modern Compensation Evangelist https://www.linkedin.com/in/mykkahherner
- 6. www.payscale.com PayScale Collects and Analyzes the Largest Database of Salary Profiles in the World Trusted by over 5K businesses to help manage pay for more than 10M employees. Our solutions provide clients an in-depth understanding of their position in the market and how to attract the talent they need to move their business forward. 54m Profiles 5k Customers 10m Employees
- 7. www.payscale.com Market Data Should be Leveraged Cross-functionally Retention Market Data & Analytics Recruitment Efforts Engagement Talent Development
- 8. Why Getting it Right Matters
- 9. www.payscale.com Macro Trends Driving the Market 2.5% July unemployment for college educated 25+ 29% Pay boost commanded by premium skills like Scala 60% Of employees who feel underpaid intend to leave
- 10. www.payscale.com Salary data is more available than ever
- 11. www.payscale.com Turnover costs can run high 20% 150%
- 13. www.payscale.com Building a Clear Picture, Takes a Few Pieces Crowdsourced data Traditional surveys Industry surveys HRIS or internal data Data aggregators
- 15. www.payscale.com Real-time Data in Action Leveraging real-time data for better compensation decisions +
- 17. www.payscale.com Integration and Implementation HR/Comp Team Socialize with Exec Team Gain Buy-in from Recruiting Share with Line-managers Provide to Employees
- 18. The Impact We’ve Seen
- 19. www.payscale.com Speed and Credibility Have been able to deliver answers faster to meet business needs 1 2 Provided greater capability to match a broader base of roles 3 Closed credibility gap that arose from poor title matches
- 20. www.payscale.com A More Responsive Comp Structure Value Experience $50K $75K
- 21. Questions?
Editor's Notes
- Mykkah: Intro Webinar Landing Page Copy for reference: The landscape of compensation data has changed. HR teams and compensation specialists have more choice than ever in what sources they can use in their analysis, and candidates and employees alike are more informed of their value in the marketplace. For some, this has been a shift towards more positive conversations with employees, but it can be a scary prospect without the right data to back you up. Join PayScale’s Mykkah Herner and Michael Diaz, Compensation and Benefits Analyst at Sungevity as they discuss: Current market trends impacting compensation The growing data market and factors to consider when selecting sources • How to integrate new data sources into your mix • The business impact of quicker more accurate matches
- Mykkah: Thank you to Michael. Mention his talk track at Compfrence – come and see us!
- Mykkah: Walk through the agenda
- Quick overview of who PayScale is - likely just click over to next slide here.
- Intro: PayScale operates the longest running salary survey in the world. Our data and software solutions are utilized by thousands of clients to retain and attract their best talent. Key themes: Let the data points speak for themselves We’re a modern approach, but we’re hardly newcomers The market is moving in this direction (customer list and employee coverage) We offer the broad(est) data coverage available and most advanced tools to unlock it’s value
- Talking points: At PayScale, we believe that market data should be at the core of every major HR function area and used continuously throughout the employee lifecycle to meet core organizational goals. Top performing companies like LinkedIn and Google have been developing this practice for years and building data into these processes, but for the majority of companies it’s hard to achieve for a number of reasons. A few of the most consistent obstacles we’ve seen are the data isn’t frequent enough, detailed enough or user-friendly enough to leverage in a productive way and we’re making it a goal to change that.
- Recruitment and Retention remain top concerns for all companies, and it’s no wonder why looking at the current state of the market. We see it in broad economic indices, our own data and consumer trends. It all boils down to the implicit need to rethink how we derive compensation numbers and communicate value throughout the employee lifecycle.
- Talking points: Ball parking salary ranges is a risky strategy. Talent is what makes your business tick, but those on the front line know that it’s highly competitive to build a sustainable talent pipeline. Factors: - Talent markets are tight in key demos across the board: College educated 25+ unemployment rate is sitting at 2.4% in May (http://www.bls.gov/news.release/pdf/empsit.pdf) Unemployment in key demographics is very low – it’s hard to find talent, and we hear this all of the time from our prospects and clients. How can I be more competitive? - Increasingly, skill are being rewarded and driving premiums. The coding language Scale is a great example of this impact showing up in our data Perception is reality at times - our studies have shown that employees who feel underpaid, leave – it’s the number one reason people seek new employment outside of involuntary factors. This means that if you ballpark someone’s salary. Your likely to bleed talent in a tight market to your competition and pay real costs to replace your workforce.
- Talking points: Employers are increasingly holding fewer cards regarding pay ranges and it’s incumbent about managers to have the right data for the right job.
- Talking points: Debates on healthy turnover aside – Turnover costs are very real and can vary widely. Estimates above from CAP and SHRM highlight the very real business cost of loosing and replacing your talent. Sources: See SAGE WP: http://www.sage.com/na/~/media/site/Sage-HRMS/pdf/SageHRMS_ROEI See CAP study: https://www.americanprogress.org/wp-content/uploads/2012/11/CostofTurnover.pdf Also: http://www.inc.com/suzanne-lucas/why-employee-turnover-is-so-costly.html
- Talking points: We are living a data-centric age of business and this is increasingly extended into the world of compensation. We now have a wide variety of data sources we can look to when making compensation related decisions and a new array of problems we are looking to solve. You choice of what data you should utilize should really be determined on the specific problem you are looking to solve.
- Factors to consider: Precision – how specific do you need it to be (job role and skill depth) Breadth – how wide are you casting your talent net and defining your competitive set? (story about airline industry?) Age – how frequently do you need a pulse on the market (do you hire in cycles, constantly etc.) Easy of use (Will this be used by a diverse set of stakeholders or exclusively by compensation experts? Consideration here is how integrated your comp team is with general managers and team members vs an isolated resource. We see this changing, and build reporting with socialization in mind.
- Mykkah: Introduction to Michael and the Sungevity PayScale relationship (Insight customer) Michael: Give a brief overview of Sugevity and current role
- Mykkah: Tell us a bit about the data sources you currently utilize in your analysis. Were there issues that lead you to look for alternate data points? And, how your team is thinking about data in general as sourcing ability has become more varied. Key Talking Points: Traditional survey analytics are not sufficient to address the complexity of modern business Modern data strategy has to involve a multitude of inputs to meet business needs Age and depth of data really matter (PayScale is real time. surveys are often out of date by the time teams get the data to analyze) – getting better, but business need answer now, not last year or last quarter
- Mykkah: What was your experience like introducing crowdsourced data into your analysis process. How was it socialized? Key Talking Points: - How did you introduce new data points into your analysis? - How did you validate each source? - How did you gain buy-in from the various teams and executives?
- Mykkah: So what has been the impact so far?
- Key Talking Points: - Cut weeks worth of work down to a few days – allowing the team to deliver answers when the business needed them - The granularity of the data helped teams speak the same language and validate data - Accuracy supported by field teams seeing the fluctuations in salary ranges in real time
- Key Talking Points: - Built a philosophy of structure with flexibility to allow for volatility in emerging and fast moving talent markets - System creates the opportunity to refresh data at least 2x per year and stay current - Spot checks become possible when recruiting teams report movement in the market sooner than 6 months.
- Sample Questions: (just in case) - Did you get push back from internal stakeholders? Any lingering skepticism - What challenges have you faced since integrating crowdsourced data? - Has you team utilized this data beyond benchmarking positions?