Gender- and race-based pay inequities are proving to be among the most troubling forms of workplace discrimination today—particularly in tech. Today’s business leaders are highly motivated to fix all forms of discrimination within their organizations. But gender- and race-based pay inequity are proving to be among the most troubling elements of this issue today.
The problem is particularly acute in the technology industry. Following previous cases at and , Pinterest and software company Carta have become this year’s most recent . Those companies now face accusations from employees including ; ; and . underscored the importance of fixing this issue now.
This essay illustrates an approach to pay equity that will help business leaders avoid the regrettable paths of Pinterest and others in the areas of racial and gender pay discrimination, in addition to combating such discrimination against LGBTQIA+, disabled, and other employee groups and intersections of these groups. (Please note: This article is not legal advice and should not be construed as such.)
Reduce 'manager discretion'
Without the removal of the underlying sources of bias-laden individual manager judgment, the system will continually reintroduce pay inequity, regardless of how much anti-bias training you do.
Many sources of inequitable pay can be traced back to points in the employee lifecycle during which a single manager or small group of managers (often of limited diversity themselves) exercises discretion over an individual’s pay. Sources include new hire offers; performance ratings; and manager adjustments to compensation changes. At each of these milestones, various biases, such as the “like-me” bias and recency bias, can take hold and influence individual pay outcomes.
My recommendation: . Refine and tighten compensation bands; move to market-based compensation practices rather than manager-driven adjustments; and eliminate the performance rating-compensation linkage entirely. Don’t kid yourself that anti-bias training can solve these problems (although we think it can be part of a broader DE&I approach). found only weak effects of anti-bias training on both implicit and explicit biases.
Further, if you are reading this to yourself and thinking that perhaps you personally can avoid such partiality, please know that the“blind spot bias,” in which you are blind to your own biases, is positively correlated with intelligence and proficiency with data! Decision science expert Annie Duke and Nobel laureate Daniel Kahneman suggest this may be because data-native individuals are adept at assembling disparate observations and facts into a credible narrative. Sound familiar?
Level and promote employees fairly
Ensure you are using consistent standards and language for leveling new candidates and for promoting existing employees.
, is a serious problem in all industries. Underleveling is present when an employee has the skills, experience, and scope of responsibility that warrant a higher title than what she has, relative to her colleagues and peers.
Take the example of a female engineering manager who should actually be a director, because she has experience, team size, and a mandate that are comparable to those of other directors at her company. Such a situation is particularly insidious because the pay gap she experiences would often go undetected. Strictly according to the pay data, if she’s a manager getting paid what other managers are getting paid, superficially there is no problem.
Theorists demonstrate that underleveling happens frequently to women and people of color for a host of reasons. Most notable among them: ; and and conformity to requirements. These differences in language and performance standards are a form of discrimination to eliminate. Instead, create guidelines to objectify and standardize job performance expectations. Several companies, including that help match employees' experience to their compensation. Use them to consistently and fairly level new hires, and to assess promotions. Be leery of going down the slippery slope of making exceptions for individual candidates or situations; that path is teeming with biases. Companies should also couple this standardized leveling language with , devoid of vague open-ended questions like “What was the biggest impact the employee had this year?” Such questions routinely prompt ambiguous and gendered responses. Root out the biased language we so often use when discussing women and people of color, not by unilaterally relying on anti-bias training, but by fixing the underlying systems that enable this bias to creep into the talent assessment lexicon.
Check that the system is working
Pay equity is not a set-it-and-forget-it component of your business strategy, as over time after implementing it at his company. Even with excellent processes in place, you will typically find inequity when you look for it.
On an annual basis, review all pay across your organization to ensure that there are no systemic differences by gender or race. Look as granularly as possible by level and job type. If your organization is smaller, don’t use the small sample size as an excuse to avoid this work. You can still review total pay, inclusive of stock-based equity, of all individuals of a particular level broadly cut by technical and non-technical.
Spend the cash and equity to fix the problems you find. If you find consistent sources of inequity (e.g., promotions at the executive level), identify them and root them out. If there is a leader who will not or cannot change their behavior, part ways.
During the of a company’s development, business leaders must manage through a time of high growth and tremendous potential, but often are lacking in resources and established norms that provide stability and consistency. It can be tempting to defer the nuances of this challenge for another day in favor of hacking a people strategy that meets the most basic needs of hiring quickly. But in fact, building the foundation early is both easier and less expensive than deferring the work. You can fix this gap now and build a better business for women, people of color and all employees. Lastly, we believe professional investors like Renegade Partners and other venture funds have a particular responsibility to support fair pay. Proxy firms ISS and Glass Lewis have begun to address this in the public markets by . Private boards should follow suit and make pay equity a board-level conversation by asking for documented pay practices, promotion and termination distributions, and results of regular pay equity reviews.
Pay inequity is a fundamental, but fixable flaw in the technology industry today. Let’s improve it now.
Susan Alban is operating partner and chief people officer at , an early-stage venture capital fund investing in technology businesses.