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Salary Surveys as a Strategic Compensation Tool. Pawan Singh Chief Science Office r. How Salary Surveys Can Transform Your Organization. www.periscopeiq.com. 610-866-6001. AGENDA. Introduction to salary surveys Salary surveys and market pricing Pitfalls in salary surveys
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Salary Surveys as a Strategic Compensation Tool Pawan Singh Chief Science Officer How Salary Surveys Can Transform Your Organization www.periscopeiq.com 610-866-6001
AGENDA • Introduction to salary surveys • Salary surveys and market pricing • Pitfalls in salary surveys • Best practices in salary surveys • Strategic role of compensation • Summary and conclusions • Your questions answered
Scope of Salary Surveys • Hundreds of salary surveys conducted in the U.S. alone • Survey Scope: National; Industry-specific; Regional; Local; Club. • Large number of salary survey providers including big HR consulting companies. • Government: BLS • New: Self-reported surveys: Payscale; Glassdoor • Benefit policies typically included in salary surveys
Defining Your Market • Your market depends somewhat on: company size, industry, location. • However, real markets are job-specific, not company specific. • Thus multiple surveys may be necessary to meet the needs of these job-specific markets. • Critical jobs and jobs with high compensation value should receive more attention.
Geographic Scope Map High Impact Low • COO • Neuroscientist Regional National • CEO, Biotech Company • Senior Programmer • Stockbroker • Secretary Regional Local • Chemist • Machinist I Skills Low High
Survey Pricing vs. Market Pricing Surveys provide survey pricing. Whether the survey represents the right market, and whether there is enough representation of this market, defines whether survey pricing represents market pricing.
Market Scope vs. Survey Scope Market – Average Salary: $98,400 Survey– Average Salary: $78,600
Salary Survey Quality • Generally, quality of salary surveys remains poor, with some exceptions. Salary data collection and analytics typically do not meet standards of scientific rigor. • Typically, sample sizes, particularly for specific cuts, are too small to be representative of market. • Primary burden on the survey user to select the right surveys and understand the limitations of each. • Benefits are significant part of compensation, but their actual value is typically not collected.
Salary Survey Red Alerts • Prima Facie invalidity. The numbers, based on your experience, do not make sense (e.g., NYC base salary is lower than Jackson, Miss., salary). Includes mathematical errors (e.g., P75 < P50). • Internal incoherence. Some high-value jobs have lower numbers than those for some low-value jobs. • Year-over-year changes do not make sense. • External incompatibility. Survey data is too different than that from another highly-reliable survey. • Job descriptions are too skimpy.
Salary Survey Secrets • Data collection may be based on incumbent data or job average data. The two methods can produce very different results. • The exact same data can produce very different percentile values depending on what percentile calculation method the survey provider uses. • Most survey providers use some type of method to suppress data dominance. Each of these methods can produce different results. Many such methods are poorly formulated. • Some organizations use meta-data (data from various surveys) to create new data, compounding errors.
Salary Survey Secrets • Incumbent data versus job average data. • Percentile calculation method can produce different results. • Methods to suppress data dominance- results are questionable. • Some organizations use meta-data to create new data, compounding errors.
Selecting Right Salary Surveys • Incumbent-based survey versus average data based surveys. • Surveys should represent your markets. • Survey selection should be job and compensation value specific. • Survey job descriptions should be strong (include key elements of job scope) and structured (job levels, sub-families, and families) • Check surveys for data quality. Identify reliable surveys and use those repeatedly.
Survey Scope Map High Overall Comp. Costs Low • National • Multiple • Specialized • National • Regional • Regional • Specialized • Local • BLS Data Business Impact Low High
Using Salary Surveys Correctly • Proper job matching is critical to good market pricing • Choose a benchmark statistic for pricing (weighted average, P75, average of P25 and P50) for your compensation strategy. This benchmark can be different for different job families. • Some jobs may need to be analyzed as compound jobs. • Data should be aged based on appropriate aging rate and survey date. • If possible, use two or more data sources (use averages). • Use market pricing software, if affordable.
Advanced Use of Salary Surveys • Create your own cut: On-demand analysis • Create your own market. Ask for peer group data. • Exclude your own data (typically for large companies) before analysis. • Ask for Pxx (e.g., P60) data rather than interpolating. • Ask for year-over-year reports. • Request raw data in Excel for organizations with internal analytical capabilities. • Get regression curves. Understand their limitations.
Strategic Role of Compensation • Compensation is usually the largest cost component. • Business success depends on having the right people in the right jobs – the right compensation strategy is critical. • Recruiting and on-boarding costs are very high. • Strategic Opportunity Value (SOVTM) methodology can be used to measure the impact of aligning compensation and staffing levels to the market. • SOV can be significant.
Strategic Opportunity Value (SOVTM) A measure of the financial opportunity available through aligning compensation and staffing distribution to the market Opportunities arise from: • Aligning compensation to the market [SOV-Market Cost (MC)] • Aligning staffing distribution to the market [SOV-Labor Cost (LC)] • Aligning both compensation and staffing distribution to the market [SOV] SOV is computed across all levels for each benchmark job
SOV-Market Cost Where: L = the number of levels in a benchmark nic=the number of company incumbents at level i Cic=Company average pay for incumbents at level i Cim=Market average pay for incumbents at level i (P50; P75, etc.; as selected by the user)
SOV-Labor Cost Where: L = the number of levels in a benchmark nic=the number of company incumbents at level i nim=the number of market incumbents at level i Cic=Company average pay for incumbents at level i Cim=Market average pay for incumbents at level i (P50; P75, etc.; as selected by the user)
SOV Where: L = the number of levels in a benchmark nic=the number of company incumbents at level i nim=the number of market incumbents at level i Cic=Company average pay for incumbents at level i Cim =Market average pay for incumbents at level i (P50; P75, etc.; as selected by the user) SOV is not the sum of SOV-MC and SOV-LC
Positive / Negative SOV • Positive SOV • Compensation costs that are relatively higher than a company’s competitive strategy, and/or • Staffing allocations that are skewed to the high side relative to market • Negative SOV • Compensation rates that are below market targets, and/or • Staffing allocations that are skewed to the low side relative to market
Summary and Conclusions • Compensation strategy is critical to business success • The right compensation strategy is the biggest source of cost savings. • Market pricing is key to proper compensation strategy. • Appropriate salary surveys and using optimal methodologies is critical to market pricing success. • Survey data quality varies – it is critical to understand the strengths and weaknesses of each survey relative to your needs
References • Singh, P. , ‘The Basics of Benchmarking in the Great Recession,’ Workspan Magazine, WorldatWork, Sept. 2010 • Singh, P. , Salary Data Red Alert: ‘Do You Know Where Your Compensation Data Came From,’ Compensation Focus, WorldatWork, June 2010 • Singh, P. And Rosen, A., Transform Compensation into a Strategic Driver, Proceedings of the Total Rewards 2007 WorldatWork Conference & Exhibition, Orlando, Florida, May 2007.
Resources For any questions after the webinar, please send an email to the presenter at psingh@periscopeiq.com or call Dr. Singh at 610-866-6001 x123.