Where Data Fails
Companies strive to obtain the best compensation data available for benchmarking, however, few understand that it is only the first step in compensation planning. The common misconception is that data alone will provide “an answer” to recruiting and retention needs. It is important to understand that although market data is a great reference point, it does not replace the need for a compensation strategy against a company-specific labor market.
Data is inherently flawed — it lags the labor market, exact job matches aren’t always available, and it doesn’t speak to company affordability. It is crucial to determine how the available data relates to your company and that comparison is the starting point for a solid labor market strategy.
Data vs. Company
Unfortunately, there is no easy, data-driven answer to a company’s unique and complex funding or growth. As an example, if a post-series A company is wondering how much equity to distribute, the need to consider how they compare against typical company metrics. Series A rounds can raise anywhere from $4M to $80M and considering those extremes comparable is not in a company’s best interest.
The most appropriate dataset to use is one that resonates with management and investors’ perception of company development. As best practice, use a “capital raised” data set for companies with less than $25M in annual revenue and switch to a “revenue” data set when >$25M in annual revenue has been achieved. These financial-based metrics that are typically preferred by the board.
Data vs. Realtime Recruiting
Compensation data will always be viewed in retrospect due to the data collection process. A natural lag will always exist between data and actual real-time. This becomes particularly apparent when the market heats up and recruiters are pushed for stronger offers in lieu of increased rejection rates. As seen in the recent upswing and ongoing competition for technical talent, market data from previous quarters could leave many seats on your development team unfilled.
As the first point of contact between company and potential employee, recruiters have a unique perspective on how market data impacts a company’s hiring goals. As best practice, couple recruiter feedback with your compensation dataset for the most current working knowledge of the competitive labor market.
Data vs. Market Strategy
Survey job titles are designed to be a “best match” rather than an “exact match” because titles and responsibilities vary by company. Each survey has advantages and disadvantages: Specific job titles, but sparse data, great data but limited job titles, cost-prohibitive, but specialized surveys.
Most survey outputs are usable if you understand what the data is saying and how it relates to your labor market needs. The example below illustrates how a company might need to position base salary against data depending on competition. Private company base salaries are not primarily based on data, but on specific labor market competition for top talent.
Data vs. Forecasting
The value of data is in the market comparison, but forecasting is essential to evaluating the affordability of the company’s compensation strategy.Private companies typically have cash and equity constraints so the budget for both current employees and projected hires determines how long available resources will last.
Forecasting requires two key strategies to realize the required budget:
(1) The combination of cash and equity required to compete in the company-specific labor market; and
(2) A retention plan for current employees — especially those with skills critical to company success.
A competitive cash/equity mix should be evaluated based on the anticipated value of the equity in the package. Understand the expected return on equity and how it impacts the cash part of the package. It is difficult for private companies to compete for top talent because they have not adequately projected the cash needed. This becomes increasingly important as a company transitions to a heavier cash compensation strategy necessitated by reduced equity offerings.
Forecasting also defines the most effective use of retention or refresh equity — additional equity grants subsequent to a new hire grant. Retention grants for all employees is a common approach, however, it is not scalable with growth of a company. Effective retention requires a strategy for when are grants awarded and how to they vest to ensure employees with critical skills stay with the company.
Where Data Fails
Problem:
Data fails when a company does not determine how their unique needs relate to a dataset. Data will not furnish a ready-made, strategic response tailored to the uniqueness of your company.
Solution:
(1) Leverage market data as a reference point
(2) Determine how your company relates to the competitive market
(3) Formulate an effective pay strategy targeted at getting and keeping great talent
(4) Communicate your company’s value proposition effectively
Recruiting and retention needs are understood by human resources while forecasting and budgeting is typically overseen by finance. Both functions need to become aligned with the data, modeling, and forecasting needed to grow the company effectively. Option Driver, our strategic compensation platform, integrates data traditionally managed through complex spreadsheets and facilitates planning needed by all functions of an organization.
