Compensation costs are a big part of any company’s overall expenses. The cost of getting compensation wrong can be steep. These days, employees and job candidates have plenty of access to salary information and they know their market value. To effectively compete for talent in a tight market with educated candidates and employees, business owners need to use market data to price your jobs and adjust your compensation plan quickly when the market shifts.
Mid-sized businesses have unique challenges that traditional compensation benchmarking approaches don’t serve well. Axios HR has designed a modern compensation benchmarking process designed to help mid-sized businesses compete in a tight market.
1 – Hybrid Positions: Many mid-sized businesses do not have the scale to have every role be specialized and many positions wear multiple hats. Matching hybrid positions to compensation data gathered around specialist roles from large employers can be challenging. A market-based compensation data sourced from employees at mid-sized companies performing these types of hybrid responsibilities is required.
2 – Dynamic Skills: Mid-sized businesses have to be nimble and adjust quickly to client and market conditions. This often means changing job responsibilities within a calendar year. Adding specific software or technical skills often changes compensation benchmarks in significant ways. Compensation benchmarking processes have to be simple and efficient to keep pace with the dynamic and fast-paced evolution of jobs.
3 – Real-time vs. Dated: Mid-sized businesses need to keep a pulse on the market and understand if wages are rising as it is happening. Most compensation surveys that can be purchased are only updated once or twice a year. It is quickly dated in a fast-moving market and doesn’t allow business owners see stay competitive in the market.
4 – Micro-market Geography: Mid-sized businesses often operate within a very specific geography. Understanding the national average, the average in the state, or even in a region is not specific enough to pinpoint the market average in a specific city.
5 – Company Size: Smaller companies generally don’t pay the same as large companies. The differences vary based on the demand of the skills for a specific position. Comparing to companies of the same size can help leaders see where to place their average by position relative to what other similar companies have done.
It is all about the right tool, data, and process…and the tools are changing.
Some compensation databases are crowdsourced from employees all over the nation. The largest database has 54 million salary profiles. By administering a real-time salary survey they are able to gather an average of 5,000 new survey records a day. This nightly refresh routine makes crowdsourced pay data the most reflective of the market throughout the year. This dataset is always real-time.
With the scale of the data feed into crowdsourced systems standardization and validation is vital. A combination of artificial intelligence, modern data science processes are used to maintain this abundant database. This data is scrubbed and compared against large employer compensation sources and data scientists are regularly validating data to ensure it is a pure representation of the market. The market matching process to a position is a unique combination of machine learning, ever-improving prediction and matching algorithms, as well as dynamic data modeling to enable better job matches and pay predictions.
Crowdsourced data is clearly superior to traditional compensation surveys for mid-sized businesses who need to stay close to the market. However, they still have a place with larger employers and when compensation strategy projects are the focus vs just basic position benchmarking.
Have questions about how your compensation plans compare to the market? Contact us!
April 12, 2018
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