Yes, you saw that correctly.  An analysis of your compensation while doing a self audit, at least an overview in the manner typically done in a desk audit by the Office of Federal Contract Compliance Programs (OFCCP), can be relatively simple.  Not because the agency lacks the skills to conduct complex compensation analyses, but because of the sheer number of audits the agency investigates every year makes running complex compensation or regression analyses impractical with every desk audit.  While it is imperative to ensure a company’s pay is in all respects nondiscriminatory, surviving an audit, as anyone who has been through this process can tell you, often takes one additional, preliminary step.  That is to approach your self analysis in the same manner as an OFCCP compliance officer.  This step is critical, but is not at all difficult. This allows you to see exactly what the compliance officer is likely to see, take any corrective action ahead of time and present the information in the light most favorable to your company. 

 Why is this important, when your analysis will ultimately show that your company is paying its employees fairly?  Because it helps avoid getting to a point where you are trying to explain anything to the OFCCP.  It is always better to be on offense than on defense.  Everyone knows that the most successful teams get to know and understand their opponents in an effort to predict their behavior and win the game.  While it is no game, common sense suggests that the same practice will add to the likelihood of success in an audit.  Assuming everything will be fine because one is confident that one’s company is not discriminating is a mistake seen over and over again and often taken advantage of by the OFCCP.  By the time a contractor gets to that defensive position, the agency is invested in the audit with time and resources and they are much less likely to let go of the matter. 

Therefore, it is critical to think about all analyses from an OFCCP compliance officer’s perspective, even before the audit begins. When doing this, there are a few important items to consider.  The auditor may know much, but more likely, knows very little about your company, and even less about your compensation system.  Auditors investigate a wide variety of industries, such as manufacturing, engineering, technology, finance and transportation, just to name a few.  It can be challenging just to understand how pay systems work among entry level personnel such as an IT help desk position or call center representative, but understanding complex, higher level positions such as senior mechanical engineers, certified project managers or commission only sales personnel is often very troublesome for the agency, even among experienced personnel, especially since pay systems vary so much from company to company. 

Not only do compliance officers conducting routine desk audits often know little about your particular company or your particular pay structure unless you tell them, they also typically are not specialized in compensation analysis.  Remember, they are investigating a wide variety of industries for compliance with a number of laws and regulations in addition to compensation, so it makes becoming an expert in one area less likely for any generalist.  Further, the data the OFCCP has in response to the scheduling letter is very limited.  It includes not much more than annualized or actual pay data, gender, race/ethnicity, hire date, job title, EEO-1 category and job group.  Therefore, take the opportunity to self audit and present your data in the light most favorable to your company.  Show the OFCCP what you want them to see and give them what they need to close your audit.

In order to sort through the thousands of audits the agency does every year, the OFCCP needs to have some sort of systematic or practical approach even though the companies under audit are so vastly different.  They need to start somewhere with pay and it is typically with an overview.  While there is of course no way to predict exactly what a compliance officer will do in every case, human nature is to take the path of least resistance, and this is no different for a government employee.  So run the same test when looking at an overview of your compensation in a self audit that a compliance officer often will run in a desk audit.  This simple method is how the OFCCP might find a difference in pay at first glance.  The OFCCP defines what a difference is in its FAQs:


 









So let us get through the steps on how to analyze and then present your compensation from a practical perspective, while bearing in mind the agency’s definition of what constitutes an actionable “measurable difference plus sufficient evidence.” Using the data that the compliance officer will have, start comparing the average salaries between appropriate pay groupings based on race, ethnicity and gender.  (We will discuss appropriate pay groupings in just a bit.)  When you do this, you can see who is being paid above and below the average in each group by a difference of either 2% or $2,000, an often-used “measurable difference” by the agency in desk audits.  You can then begin your research to understand why that employee or those employees might be paid more or less than the average.  Here is an example.  If you are looking at all of your professionals by gender, you would add up the salaries for the males in this job group and divide by the number of male employees in this job group and then do the same separately for the females.  Is there a difference that fails the OFCCP standard (2% or $2,000)?  With professionals, probably so.
 


There are several things to think about at this point.  What are the likely groupings the agency will use?  Should they consider all of your professionals together?  Right now, all the OFCCP has to develop pay groupings are job titles, job groups and EEO-1 Categories.  No matter what, when using such a small difference as a comparator, there will likely be differences of 2% or $2,000 somewhere in your workforce.  The first question to ask when looking at an indicator is whether the comparative groups should be analyzed together in the first place.  If no, then why not?  How can you better present this data to the agency so that these employees are not grouped together?  You might relook at your job groupings or job titles.  Also, look at the patterns in your data.  If, no matter the job, one group is always making 2% or $2,000 more, then there may be an issue with pay that needs to be remedied, regardless of how the employees are grouped.  However, if there is only an issue when the employees are grouped a particular way, then find a reason to support why these employees should not be compared against each other.  That is, there is likely a nondiscriminatory reason for the difference in compensation. 
 
The second question to ask, if the groupings are appropriate, has two parts.  What is the nondiscriminatory reason for the impact within that group and will the OFCCP be able to find it in your submission?  When you run your analysis and you have a disparity in pay of 2% or $2,000, take a look at your outliers and figure out why they are above or below OFCCP’s line.  This is the OFCCP’s cohort analysis.  
 
Let us work through some common examples.  Some industries have large waves of layoffs and rehires and it could be beneficial to differentiate these employees in the submission as those rehired usually start at a higher wage than new hires.  Security clearances are another example.  Individuals that already have certain clearances from military or law enforcement experience are often desired. Perhaps it is a special certification, skill, overtime, location or the individual was promoted from another position only recently.  Often difficult to show is that a high starting salary was needed to draw a particular person away from his or her last job or to keep them from being poached.  Do you need to track prior salary for your employees?  Perhaps.  What about performance increases?  Think about the records OFCCP would want to see to support pay differences within personnel files. The ultimate key is, whether there is nondiscriminatory support for pay differences for all employees, i.e., not only why a particular employee is eligible for a higher pay, but why his or her peers are not.  Remember that the absence of evidence is very often “sufficient evidence” of discrimination.

The examples above are just a few of the common issues that come across the desks of the compliance officer that might be easily explained.  Perhaps if you are aware of them in your self audit, you can present the facts to the agency so that the auditor can get a clear and accurate picture of why individuals are being paid the way they are in your organization up front. While often it is not recommended to provide the agency with more information than they have requested, it could be appropriate to provide some information to separate a certain group or to explain pay differences in the beginning in order to sidestep additional questions beyond the desk audit.  Of course, in some situations, additional requests cannot be avoided and OFCCP may regress the data or reach out to you for additional information regardless of how well prepared you are. 

It is important to note that much of the success that OFCCP has had in identifying systemic or individual cases of compensation discrimination have really been an issue of placements versus an actual discrepancy between pay.  For example, women were “funneled” into lower paying jobs, yet paid appropriately for this work.  This is outside the scope of this article.  However, when you run your compensation analysis in the manner described in this article, you should be able to see overt patterns of funneling in your organization if they exist.  Are there comparators, individuals of both genders or of different races/ethnicities, in the grouping?  If not, then there may very well be a placement issue. Not necessarily, but it is certainly something into which one should look. 

When doing a self audit, before you ever receive the scheduling letter, you will have compared the average salaries by race, ethnicity and gender of appropriate groupings in your workforce and will have identified and remedied any issues consistent with the laws and regulations enforced by the agency.  It may seem overwhelming at first, but taking it step by step and thinking about it practically from a human perspective should simplify this task. You will know who the outliers are in your compensation data and of course you will have your evidence ready to support your compensation decisions.  This preparation gives a good snapshot of the state of compensation in your organization and shows you what the OFCCP would probably see in an audit, putting your company ahead of many others.


 






Copyright © 2017 The Kaiser Law Group, PLLC  All rights reserved. Not to be reprinted without express, written permission. 



**********************************************************************************************************************************Tools for Your Toolbox – Keeping up with OFCCP Regulations
Lisa Kaiser
The Kaiser Law Group, PLLC

 
If you are like most federal contractors, keeping up with the changes coming from the Office of Federal Contract Compliance Programs (OFCCP) can feel like a full time job.  There seems to have been a flurry of new rules over the past few years, each one more burdensome than the last, and it can sometimes feel overwhelming just reading all the new materials, let alone figuring out how one is going to comply.  However, it is important to keep in mind that the material obligations of federal contractors have not changed much since nondiscrimination laws first appeared. 

Certainly, there is no doubt that getting through an audit has become exponentially more complicated and time consuming, but this is because the agency has become smarter about its audits.  Federal contractors that are only looking to the regulations have lost sight of the ultimate objective, which is, of course to eliminate discrimination, which is accomplished by identifying and remedying indicators or patterns of discrimination within their workplace in real time. 

You already know that as a federal contractor, to comply with the regulations that are subject to OFCCP enforcement, your company must not discriminate against someone based on certain traits, and you must positively recruit (affirmatively act) in order to generate applicants or pools that consist of certain groups that have historically been victims of discrimination or otherwise disfavored because of a particular characteristic.  What has evolved quite a bit since the inception of the regulations enforced by the OFCCP are the forms of discrimination that OFCCP has discovered and how subtle it can be, and with that, OFCCP’s sophistication of being able to recognize, investigate and prove these subtle forms and patterns of discrimination.  The regulations, directives, updated compliance manual, etc., are the tools that the agency has refined to help them conduct investigations based on what they have learned in audits.  The OFCCP has not changed their audit practices based on the regulations, but has revised the regulations based on the evolving audit practices.  Adapting a business practice therefore to the regulations is a difficult and impractical task.  If one learns to properly self-audit their own data, compliance with the regulations naturally follows. 

In order to more easily understand where to look for subtle forms of discrimination (as OFCCP does) so that we can apply some easy methods to determine whether there is a problem that needs further investigation, let us start with some important distinctions.  There are two types of discrimination cases investigated by the OFCCP, disparate treatment and disparate impact.  The difference between the two terms is that disparate impact cases do not require the contractor have intent when discriminating.  Yes, a company can discriminate without intent!  This often surprises federal contractors. 

So what difference does the type of discrimination make and how is this relevant to the regulations?  Think about it from an auditor’s perspective.  Is your company intentionally discriminating? No.  Is there adverse impact?  That question may be harder to answer.  In order to figure this out, you can run an easy analysis to spot check all movements in your company.  A hiring analyses, sometimes called a hiring table, is one great tool and an easy way to take a quick look at many patterns in your data to determine what groups are favored versus disfavored.  It absolutely is not limited to hiring.  This analysis can be applied to not only promotions and terminations easily as well, but anywhere you want in order to look for patterns in your data.  You can analyze particular hiring managers, how dispositions are assigned, whether a particular group is favored when it has a preferred characteristic, such as an employee referral, or how a test affects your group.  The possibilities to check for patterns are endless.  This tool is extremely easy to run for anyone that has a basic knowledge of how to use a pivot table. Excel will even put it into a handy chart or graph for you with a few clicks if you want to get fancy.

This analysis helps one see a snapshot of many rates side by side versus just numbers or standard deviations.  At your company, for example, you might have hired or promoted roughly an equal amount of men and women at your facility last year, so it feels fair.  Or perhaps, your workforce is consistent with availability.  However, when you look at those that applied or who were eligible for promotion, then you might better see problem areas.  For example, if you have a pool of 100 eligible women for promotion into a particular job, but only 65 men with about an equal number of promotions, say, 15 each men and women, then there is obviously a problem.  When you lay all of these numbers out in one table side by side, you might then see a rate for women of 15 percent, but 23 percent for men.  You might see a bigger problem when looking at African American females, but perhaps rates are fine for African American males.  Good enough to have hidden a disparity.  You will also see how all the other groups by race, gender and ethnicity fall into place.  What looked harmless a few minutes ago becomes a bit alarming.  When we look at each minority group by race and sex, we see the disparities among each group and patterns in the workforce will emerge.  We see what groups fall above and below the overall rate.  This analysis is a tool used by OFCCP in certain regions in every case that goes beyond the desk audit.  Since OFCCP is using this tool regularly, it may be a good idea to consider using it too.

Once you get into the habit of spot checking data as you run your required analyses every year, or at other key times, you will see that this is an easy tool to look for patterns in your data so that you are not surprised in an audit.  If you are aware of patterns in your data and problem areas, you can remedy or support them with records before that audit letter ever comes.  More importantly, by running a few easy tests, you have your finger on the pulse of what is happening in your workforce and can address any concerns before they become a problem.  Of course you need to ensure you maintain all other areas of compliance such as outreach, posting jobs and proper recordkeeping.  Also, good (and required) annual training to make sure everyone understands his or her role and the importance of following policy, should never be underestimated.  These technical aspects are critical of course, but understanding and addressing patterns in your data and within your workforce ensures that there is no unintended discrimination and naturally aligns your practices with the intentions of the regulations, making compliance as a whole a much easier process.

No one will tell you that it is easy to be a federal contractor, but there are certainly less cumbersome routes to get from point A to point B.  With the right tools in your toolbox, perspective and practical understanding – and perhaps some methods of analyses that OFCCP often uses in its audits – compliance can be an easier mountain to climb. 

 This article is intended for information only.  It is not legal advice and should not be relied upon as such.  For more information, please contact Lisa Kaiser at Lisa.Kaiser@Kaiser-Law-Group.com.


©2016 The Kaiser Law Group. All rights reserved. Not to be reprinted without express, written permission.

This article is intended for information only. It is not legal advice and should not be relied upon as such.  It does not establish an attorney client relationship and is not intended to provide particular advice or professional services in any respect. This article may not be reproduced without express written permission by The Kaiser Law Group, PLLC.  

For more information, please contact Lisa Kaiser at Lisa.Kaiser@Kaiser-Law-Group.com

Remember that the absence of evidence is very often “sufficient evidence” of discrimination

​Tools for Your Toolbox – A Compensation Overview Made Simple
Lisa Kaiser
The Kaiser Law Group, PLLC


The Kaiser Law Group, PLLC

Show the OFCCP what you want them to see and give them what they need to close your audit.

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What constitutes a “difference” in compensation that could result in a violation?

OFCCP may investigate any observed differences in pay, other earnings or benefits, job assignment/placement, training/advancement opportunities, differences in opportunities to increase compensation, or other unexplained differences. In situations where there are sufficient data to use regression analysis, a measurable difference generally means a statistically significant difference of two standard deviations or more, consistent with Title VII. When analyzing whether there are discriminatory compensation disparities among small groups or individuals, OFCCP will determine whether there is a measurable difference plus sufficient evidence that the difference is due to discrimination, according to Title VII law. Statistical evidence is not required in all compensation cases; other evidence may be used to evaluate potential discrimination in pay.