Compensation Cafe

Four Compensation Predictions for 2022

This is the thirteenth year I have written a post during the last week of the year. I seldom make predictions for an upcoming year because compensation generally evolves so slowly that any real changes take several years to come to fruition. As we head into 2022, I am going to break that tradition and make a few predictions. I think we have a unique opportunity in front of us and many compensation professionals will relish the challenge.

1. Base pay increases in many industries will be far higher than we have planned.
   if you have planned a 4% budget for 2022 and use a lag, or lead/lag, strategy, please expect to lag from very early in the year. The market is unlikely to cool. Executives are being held to high standards when it comes to growth. Investors have put a ton of money into the market. All of these will factor into increases that will continue to rapidly outpace what has become the 3% norm for the past decade and beyond.
2. Survey providers will be pressured, and perhaps forced, to address the inaccuracy of LTI data in surveys.
   This is especially true in private company data, but expect to see more demand for global granularity, award details like vesting and performance criteria, and better explanations of how values were determined. This is a weak point in the world of compensation and companies are rightfully impatient to see better data.
3. Survey providers will begin categorizing positions into “onsite”, “hybrid”, and “remote”. Survey data without this level of specificity is putting every competitive company at risk. Expect to see the first “pulse” or “spot” surveys on this topic before the end of Q3. Expect this to be a normal part of survey submissions before the end of 2022.
4. Expect to see more companies visibly break the Base/STI/LTI paradigm that has dominated compensation philosophies for 15 or 20 years. At some point, you cannot differentiate your offers with just a bit more base pay. Short-term incentives will likely become shorter to address that speed with which pay is changing. LTI programs are already changing. Leading-edge companies explored more new vesting schedules and LTI plan design elements in 2021 than in any year in recent memory. This information will become more well-known and inspire hordes of other companies to move away from the lock-step adherence to stock options with a 4-year vesting schedule or RSUs that are similarly designed. If the long-time programs worked as advertised our ability to attract people would be higher and our turnover would be lower. It’s time for a change.

I am sure we will see other changes, just like I am sure at least one of the above will prove to be completely wrong. 2022 is sure to be another interesting year. In 2020 we just did our best to react to a world that became almost instantly unfamiliar. In 2021 we weathered a push for hiring unlike any year in recent memory. In 2022, we will get our feet underneath us, gather up our balance and leap forward into a new approach to pay that may provide a foundation for the next 10 years. There is no reason to wait. The future is yours to create.

Dan Walter is a CECP, CEP, and Fellow of Global Equity (FGE). He works as Managing Consultant for FutureSense. Dan is a leading expert on incentive plans and equity compensation issues. He has written several industry resources including a resource dedicated to Performance-Based Equity Compensation. He has co-authored ”Everything You Do In Compensation is Communication”, “The Decision Makers Guide to Equity Compensation”, “Equity Alternatives” and other books. Connect with Dan on LinkedIn. Or follow him on Twitter at @DanFutureSense.

Pre-IPO Equity Compensation: Refresh or Change Course?

It’s getting harder to know exactly what to do about equity compensation at pre-IPO companies. Values have been soaring (there are currently over 800 “Unicorns”, or pre-IPO companies worth more than $1B). There is so much money available that companies can stay private longer and grow bigger than ever before. All of this is challenging long-used models for equity compensation.

Companies and their consultants are rightfully questioning the efficacy of 4-year vesting schedules. Employees are asking for more equity as they become fully vested. Competitors are poaching the best people as they near the end of vesting for their original hire-on grants.

The following is a recent exchange from LinkedIn. The individual asking the question is a very experienced, and very good, compensation consultant who works for a major firm in the space. My answers are simply my opinions, and I am sure others will have different perspectives.

Questioner:

“HI - I am getting more questions about those high-level execs or engineers that are creeping up on their 3rd or 4th year of vesting. If the stock has really taken off since then, what kind of retention strategies are working for companies? Annual refresher grants pale in comparison to some of those original grants or new hire grants. Anything you've seen help people stay interested?”

“Specific follow-up question - does a large amount of unvested stock mean you could be ineligible for an annual refresher. I don't think I've seen that happen before. You?”     

My Response:

“There is so much to cover here...”

“Pre-IPO grants that follow the now ubiquitous 4-year vesting schedule are a real problem in the marketplace. We are often recommending two grants at the same time: 

• One grant with a shorter (2-3 year) vesting)
• Another with a much longer 6-8 yr) vesting.”

“There is no great reason to grant smaller equity awards at hire and then grant refresh grants in the future (for most companies).“

“There is very low risk when using larger, longer-term grants since the company gets the shares back if the person leaves. The refresh concept does not work with current skyrocketing valuations. If a high valuation company must refresh equity, we often recommend RSUs since they get rid of the high exercise price that comes with stock options (but, they have their own issues with prescriptive taxation and other considerations).”

“And yes, the level of “unvestedness” often drives potential refresh grants. When unvested values are really high, it doesn't make a lot of sense to give more unvested equity.  When they are low, something needs to be done ASAP. We often recommend designing a refresh program for grants that will become 75% vested or more in the next 12 months.”

This topic is far more complex than a blog post can cover. The models for granting pre-IPO equity are broken. The “market data” you’ve been using is based on people generally adhering to those broken models. Equity in those models never considered companies worth billions, or staff sizes of several thousand before an Initial Public Offering. Those models do not account for SPACs, Direct Listings, Reg A offers, or IPOs worth $20, or even $50, Billion dollars. Your VC investors have little motivation to change. Your PE investors want to see more performance criteria. Your employees want to see a return to more equitable equity (as long as they make a ton of money). As a compensation professional, you have both a unique challenge and a unique opportunity.

You can follow the path that isn’t working, or you can do the hard work to determine the right path for your company. The process requires some brainstorming and education, but the results can be impressive.

P.S. Please stop using the notional value from your most recent preferred stock to value your equity against market data. That’s not how it’s correctly done.

Dan Walter is a CECP, CEP, and Fellow of Global Equity (FGE). He works as Managing Consultant for FutureSense. Dan is a leading expert on incentive plans and equity compensation issues. He has written several industry resources including a resource dedicated to Performance-Based Equity Compensation. He has co-authored ”Everything You Do In Compensation is Communication”, “The Decision Makers Guide to Equity Compensation”, “Equity Alternatives” and other books. Connect with Dan on LinkedIn. Or follow him on Twitter at @DanFutureSense.

The Person in Front of You Isn’t Headed Where You’re Going

The stories my son Grey finds the most entertaining are those about my father’s legendary lack of direction. He loves hearing how Grandpa would regularly get lost coming home from work, a place we drive to every single day. My father would nearly always end up about seven miles from our house at a restaurant called the “Giant Artichoke.” They sold only deep-fried fresh artichoke hearts. (The 1970s were kind of awesome.) But Grey’s favorite stories are about Grandpa driving around with the whole family.

We would be driving for a long time to a place that didn’t take a long time to get to. When one of us came to the realization that we were once again astray, we’d ask our intrepid drive if he knew where he was going. His most common response? “I’m just following the guy in front of me, he knows where he’s going.” It may sound like a joke, but my dad regularly drove hours out of his way based solely on this “the other guy knows” philosophy.

I direct my team to perform “blind” market pricings whenever possible. Blind pricing is matching a role and pricing it based on all the available details except what the person is currently being paid. This ensures the pricing used is not biased by the current compensation being paid. In my experience, too many compensation professionals choose, weight, or adjust data to align with what an incumbent is already being paid, or what a recruiter has said it will take to fill the position. Like my dad, this assumes the person in front of you knows where YOU are going.

I recently had someone new on my team price some jobs and the data came in a bit lower than the current staff for several positions. When I did an initial review with the client, they were shocked. They were a startup and had been intentionally paying people below market as they waited for funding to come in. We went back to the data and found that Level 1 and 2 positions were similar in price, but the jump to Level 3 was more than 40%! It turns out the Level 3 data and above matched several other surveys, but the Level 1 and 2 data matched the company’s current pay. In this case, the current pay was wrong. We releveled the data, and everything made more sense.

When I dig into analyses done by others, I often see adjustments being made to “bring the market in line with expectations.” Data is data, it is not information. Data is numbers, it is not a rulebook. Do your job analysis. Be confident in the role details. Price to the role, not the current pay levels. Then, evaluate where things stand and what to do. If you are paying below market, but can’t afford more, then just be cognizant of the opportunity that provides competitors. If you are paying above market, but the person is doing a great job, just make sure they know they are being paid well and fix things slowly over the long run. Please stop selecting and modifying data to match your past pay decisions. Just let the market data tell its story and use your own intelligence to decide what to do with that data.

Dan Walter is a CECP, CEP, and Fellow of Global Equity (FGE). He works as Managing Consultant for FutureSense. Dan is also a leading expert on incentive plans and equity compensation issues. He has written several industry resources including a resource dedicated to Performance-Based Equity Compensation. He has co-authored ”Everything You Do In Compensation is Communication”, “The Decision Makers Guide to Equity Compensation”, “Equity Alternatives” and other books. Connect with Dan on LinkedIn. Or follow him on Twitter at @DanFutureSense.

A Tale of Two Markets

As every Compensation practitioner will tell you, sometimes there is no straight answer to a question you’re being asked.  However, the boss who is asking that question will still look to you for not only what the tea leaves say (surveys), but what should management do about the information.  The answers that you may have to offer, though, often aren't simply black or white, but instead show a good deal of grey.  

Ahhh, but management doesn't like to hear about grey.  They don't want you to sit on the fence with maybes, variables and “coulda/shoulda” responses.  They want you to make a call, to raise your hand and your head above the firing line.

So how do you respond when the chips are down, and the ticking clock just ran out?

Consider This Example

A survey shows that there are 350 nonprofit organizations in Florida, and the base market rate for the XYZ position you're analyzing is $150k.  However, that same survey indicates that there are 36 Florida organizations that are same size as yours, and that narrower market is paying only $125k. 

When you consider the variations of data, you are faced with . . ..

• Florida is a large state.  Where are these 350 organizations located, compared to your site?
• Does the survey tell you this?
• These organizations will vary in size (operating budget, employees, number of sites, etc.) a great deal, from much smaller than you to much larger
• Does the survey segment data according to size?
• How many of these 350 organizations are in the same "type" of nonprofit business?
• Does the survey segment data according to type?
• If the data is segmented, which segment is more important to you?  Can you ignore others?
• Do you really care about variations, or does the answer with the most robust data win?
• If you recruit some positions from for-profit organizations as well, should you restrict your analysis to only the non-profit universe?
• Does the incumbent employee’s own base rate affect how you look at the competitive marketplace?

Management is waiting.  How do you answer their question about the market rate for the XYZ position?

Depending on the circumstances your answer might be $150k, or under other circumstance you might say that the answer is $125k.  Both can be considered correct, dependent upon how you read your data sources.  Or perhaps a third figure as well?  However, for the incumbent employee, their market is the $150k.  That's their view of how they should be valued.  That's their view of what they can get from another employer.

The Wannabe Survey Analyst

How your organization defines its view of the competitive market is critical, but most folks outside of Compensation will let that distinction slip right by them.  Grab a survey, flip the pages until you get to the subject job and point your finger at the top-of-the-page figure.  There.  Done.  How hard was that?

I've seen it done that way.  Likely so have you.

The trouble with this approach though, is that's it's all too easy to miss the mark.  If you're a $50M nonprofit food distribution organization in Central Florida, how important is it to know, and include in your analysis what a $150M nonprofit disability organization is paying in the Miami area?

The trick for the wannabe analyst is that often the available survey data doesn't make enough distinctions in the figures being reported.   There may not be enough data (statistically valid) for $50M nonprofit organizations in the Central Florida area.  Never mind food distribution.

So, data on that narrow slice of "same organization" criteria you're looking for is simply not available.

That data on the top of the survey page may not represent your organization at all.  Or you could get lucky.

Broaden Your View

Look at your "market" from two perspectives; 1) what are other organizations - just like you - paying for a subject position, and 2) what are others paying in an organization sized like yours.

You can even add a third component; what about your geographic area?  What you have then is a composite of data points that require interpretation and explanation.  So perhaps your response is buried in the midst of the survey page, not at the highlighted top.

Just to make things a bit more complicated, another consideration for you is the difference between the employment market value of a jobholder (what pay can they achieve out there) and what organizations just like you and sized like you are paying.

This is the "it depends" element of compensation that drives non practitioners crazy.

I can see their point.

Chuck Csizmar CCP is the founder and Principal of CMC Compensation Group, providing global compensation consulting services to a wide variety of industries and non-profit organizations.  He is also associated with several HR Consulting firms as a contributing consultant.  Chuck is a broad-based subject matter expert with a specialty in international and expatriate compensation.  He lives in Central Florida (near The Mouse) and enjoys growing fruit and managing (?) a clowder of cats.

Creative Commons image "Complexity 3," by michael.heiss

Redefining our Approach to Survey Data

Having access to timely salary data is critical to organizations' ability to make informed decisions when it comes to securing talent and maintaining their competitive position. The insights we extract from purchased results are an essential ingredient in being able to defend the why and how in our pay approach.  Herein also lies the question of whether market data is holding up to the demands of supplying organizations with timely, accurate, and reliable insights that will inform pay decisions internally and equip organizations to compete in the talent war.

While I will continue to be an advocate for data, it's worth noting that our dependence on it is demanding a better return on investment.  The environment, our organizations, and its people are moving at an alarming pace. The ability to tap into data that is reflective of your immediate location, of a comparable role match, and (most importantly) is current. is hard to come by.  The inability to benchmark affects our ability to manage and retain talent and subsequently disrupts the integrity of maintaining pay fairness and equity in pay design and administration.  Case in point: bringing in a new hire at a rate that is above the pay grade and that of an existing seasoned professional internally.

For us to regain trust in our survey data, we need to also think of the factors that are causing ambiguity and what measures we will take in response.  Below are just a few examples to open this conversation:

1. Technology – survey platforms need to move at the same pace as many of our compensation management tools (i.e. real time). The data collection process needs to be seamless, effortless, and one that adopts integrative techniques that validate, job match, and facilitate the ability to regularly data update or refresh. Imagine regular data feeds from participant HRIS systems.

2. Time – time is not only a question of survey providers releasing information but also in having the dedicated resources internally to participate in what can be a labor-intensive process. Lack of time, leads to a lack of participation reducing the number of available data points and the size of your sample set, inadvertently affecting the statistical outputs.  For some, this means a lack of data visibility and/or having to resort to a larger peer group.  

3. Job matching – the rate of job creation is faster than what education and employers can keep up with. Hence, the roles you are survey matching to may not be equivalent.  Interpretation of how you benchmark, and in turn use this data is key as to whether you will need to mark up or down the results.  Furthermore, through technology integration and creating an enhanced survey experience, we can facilitate a more continual scan and output of the unique job titles observed.  Additionally, consolidating online job postings could give us a more real-time perspective of the emerging roles of our competitors and the posted pay ranges.   

4. Flexibility – perhaps we need to rethink our longstanding cyclic process of survey participation.  For years it has been the same scheduling of events; this timing is no longer conducive to today’s immediate needs. 

Alternatively, we may need to evolve our pay structures altogether and become more broad-based (if not already) to accommodate for market variability.  Consider also that select cross-functional jobs may not move at the same pace as hot skill or IT positions.  Due to this, there is a degree of data interpretation required when assessing the larger overarching market perspective relative to your organization.

Overall, the need for data will be a persistent one, as is the need to attract, retain, and motivate our talent.  Similar to how we have, in the past couple of years, adopted new strategies to cope with redefined work, we are may not be far behind in how we begin to re-envision our approach in participating in and handling data from surveys.

Reena Paul (CCP, GRP) is a Senior Consultant with LifeWorks Compensation Consulting Team.  She is passionate about all things “total rewards” and has experience in dealing with all stakeholders of an organization and strategizing optimum client-focused solutions.  A lover of data and the story it tells, Reena enjoys the exploration of presenting and discussing compensation with a fresh perspective.  Connect with Reena on LinkedIn, or contact her directly at [email protected].  

Image source: istockphoto with credit to Ivelin Radkov

Are You Sure About That?

That's what a client asked me the other day.   The SVP of Human Resources was mulling over my market pricing report when he said, "These summary averages tell me how my pay practices compare against my competition, right?  And with these individual job comparisons, they tell me what the market is paying against my jobs, right?"  Then a pause, followed by, "And you're sure about these figures?"

In other words, the client wanted a guarantee that what he was looking at truly reflected the competitive marketplace for his organization.   So that he could take my word to the bank.  And fall on his sword if necessary.  Because I have delivered the answers.  Scout’s Honor!

Ahhhh, but it doesn't work that way.  There are no ironclad guarantees, no handwriting in the sky, no finger pointing to an "X."   Practitioners who analyze compensation surveys can only report on what the sources show.  It's how they, and their client interpret and ultimately utilize those reported figures that will advance the story for the organization.

An Imperfect World

Let's consider the possible variables that will prevent you from (honestly) making a pinky swear regarding the figures you've just shown to management.

• The client may be interested in what companies X, Y and Z are paying, but unless they're prepared to sponsor a custom survey what they'll get instead is a broader view that displays what many organizations are paying - some of whom they may not be interested in. And not all of the selected companies may be participating in your survey sources.
• Or perhaps management is only interested in "like" industries, or only like revenue size or like geography (or they want all elements at the same time).  However, matching data slices may not be available.  You may have had to pick and choose your points of comparative analysis.  Choose wisely.
• Surveys never capture what everyone is paying, but only a representative sampling.  A subjective presumption is that your information covers most (even a high percentage) of incumbents.
• An oft-forgotten aspect of surveys is that the input completion process (that dreaded questionnaire) is typically presumed by those on the receiving end as a virtuous document well-scrubbed of any errors or improper job matches. Probably not. A little garbage always slips in.
• Clients tend to think about what the market looks like today, while even the latest commercial surveys are only reporting data that was captured six months ago.  And a typical aging process uses a flat growth percentage figure for all jobs; so, some could be overestimated, or the opposite of what things look like today. The market at the time of data collection could be different (pandemic, recession, global crisis, etc.) than what it looks like today.
• If the client's organization has caught the infection called title inflation, the job matching exercise might lose a bit of precision.

So, the figures you're looking at may not be quite as bright and shiny as you'd like.  You will still have to work with them, make sense of them, and apply a dab of professional judgment.  Use them less as an "x marks the spot" and more as a "let's move in this direction."

What To Do

All a practitioner can do is to present the best information that's available.  That information should then be used by the client as part of their decision-making process (competitiveness, structure change, merit increase process, etc.), not as the whole and sum.  Ugly scenario: picture someone running down the hallway, waving a piece of paper while shouting, “I have the number!” These figures should not be considered the penultimate answer, because they're not.  Of course, it’s always easy to take the short cut and ignore the necessary analysis. But don’t do that.

Unless of course your compensation strategy is simply to follow the leader, whatever everyone else is doing, or whatever the surveys say.  Then again, the client, with their limited understanding of survey mechanics, expects to learn what everyone is paying, but you know that you will never be able to present that figure.

When They Ask for A Guarantee

When management wants some sort of guarantee that what you're showing as the marketplace in your analysis is really the market, as they define it, the best tactic is to take that opportunity to educate them on how surveys work; what they can tell you and what they can't.  Scrape off a bit of the mystique of precision that often surrounds how commercial surveys are marketed.  Talk to them about your professional judgment.

Because there are no guarantees.  And you can only be as positive about those survey figures as the survey limitations allow.

Sorry.

Chuck Csizmar CCP is the founder and Principal of CMC Compensation Group, providing global compensation consulting services to a wide variety of industries and non-profit organizations.  He is also associated with several HR Consulting firms as a contributing consultant.  Chuck is a broad-based subject matter expert with a specialty in international and expatriate compensation.  He lives in Central Florida (near The Mouse) and enjoys growing fruit and managing (?) a clowder of cats.

Creative Commons image "Calculations," by marco_1186

Proceed with Caution: When AI meets Pay

With great power, comes great responsibility.  The now infamous proverb popularized by the Spider-Man comic books is especially meaningful when leveraging Artificial Intelligence (“AI”) in our compensation management.

Admittedly, AI has an elegance to the way it simplifies, automates, and quickly synthesizes our analysis, pointing out all possible areas of contention. We should, however, not be fooled by its sophistication. To some extent, AI encapsulates a sense of ambiguity and therefore a forewarning to proceed with caution.

To use this technology responsibly means being educated; that is, educated in the system's functionality and its intended use.  Say, for example, you are trying to address issues around pay equity.  Are you familiar with the legislation itself and do you know what the expected analysis steps should involve? In the case of using AI’s suggestion for a possible survey job match, how well do you know the context of your internal position? is it a true manager or rather a specialist of a functional area?  With limited knowledge, you could inflate or devalue a position if matched incorrectly. 

Having users equipped with compensation and basic system fundamentals safeguards for correct data interpretation and effective use of AI’s outputs.

To best utilize the strengths of AI, we must feed it with accurate information and data around which we have the full context (consider red circling or other legacy pay scenarios).  As you import, be aware of how your information configures and aligns with the system components.  Have you matched data to the precise fields, have you interpreted the systems compensation elements correctly? Misguided inputs will only lead to “garbage in and garbage out!”  One way to avoid this is by adopting a consistent and standardized format for data uploads.  Doing so will give you the best return of AI’s analytical capabilities.

AI at the end of the day is a tool, meant to assist us to better navigate and handle the complexities of managing compensation.  Whatever it suggests - whether it be an alarming SOS, an invalid read of our data, or a more favorable acknowledgment of us meeting our salary budget – this is not the outcome.  We cannot be too quick to react nor adopt AI’s responses at face value; these outputs form the pillars of insights to guide our decision-making.  Most of us in our profession are analytical by nature, curious and inquisitive.  This is when we need to tap into our own AI tendencies and dig a bit deeper, validate, and investigate. 

Besides, you would not present a salary recommendation or re-structure to leaders, solely credited by the divine intervention of AI, would you?

Reena Paul (CCP, GRP) is a Senior Consultant with Morneau Shepell’s Compensation Consulting Team.  She is passionate for all things “total rewards” and has experience in dealing with all stakeholders of an organization and strategizing optimum client focused solutions.  A lover of data and the story it tells, Reena enjoys the exploration of presenting and discussing compensation with a fresh perspective.  Connect with Reena on LinkedIn, or contact her directly at [email protected].  

Unsplash Photos for everyone by Lukas Blazek

What You Say, What They Hear

When compensation practitioners face the need to develop their first program recommendation for senior management a common mistake often made is for the practitioner to not consider what the audience expects to hear – which can be a fatal mistake.

The inexperienced often presume that they will be viewed as the acknowledged expert, and that their recommendations will carry a great deal of weight.  If they are fortunate, that will be true. However, more than likely running with an ego puffed up with notions of “expertise” will steer you straight into a brick wall.

I know.  I still have the bumps on my head.

What You Say Matters

In my experience members of senior management may not be familiar with compensation techniques, which is probably why they have a need for you.  However, they will still possess a series of personal biases of likes and dislikes, a basic knowledge of company-centric pay philosophies, and those well-developed internal cultural preferences that they feel “work” for them.

And while we’re talking communications, remember that it’s a two-way street.  Just telling someone something is not communicating if they don’t understand or have different perspectives.  So have a care of tripping up when communicating with the decision makers in your senior leadership.  Some terms to be cautious with:

• Average: Compensation practitioners may argue that, in many cases, the use of a Median figure is technically more accurate. But your audience likely may not know the compensation distinction, as in their minds they are thinking Average. Educating them on the difference, especially if slight, will distract the presentation away from its key points while still not changing anyone’s thinking.  You can avoid this potential glitch by using Average.

• Market Data: Most clients will presume that the market data you present is for their own jobs and within their own industry. Often this is not the case, what with generalist surveys, title match challenges and potential restrictions on how finely you can slice the data (industry, revenue size, geography, specific titles). Clarify your market analysis to avoid misunderstandings and later challenges.

• Incumbent Data: Your client will assume that your survey data represents a counting of actual employee incumbent pay rates across your survey sources. They will not understand the usage by some surveys of algorithm formulae to guess/presume/estimate pay levels.

• Quality of Data: Not every survey will deliver the same quality standards that you, and your client, will assume as a given. Small surveys, geographic cuts, industry-centric vs. general surveys and even self-reporting surveys (employees complete the questionnaire) should not be considered as providing data of equal value. But unless you qualify your sources your client may presume that they all offer the same credentials, or if questions arise, leaders may criticize all your sources as flawed.

• Survey Limitations: For many clients, just listing a series of survey sources can be enough to elicit nodding heads at your thoroughness. But every survey is a composite of a list of participating companies who try to match as many job titles as possible.  Therefore every survey will show a different number for the same job. Again, your client will (initially) give you the benefit of the doubt, lacking the knowledge to make critical assessments of the diversity of potential survey sources. It will become your role to educate them.

• Midpoints vs. Market Rates: Many times, a client will automatically presume that the midpoint of a pay range (within the organization’s pay structure) is the going rate (market rate) for that position/title. That they should be paying employees at that rate. Again, your role as educator is to explain the difference between a pay range midpoint and a market rate. And why every employee should not necessarily be paid at the midpoint.

• Smoking Gun vs. Pricing Guide: It will help your education process if you can get senior leadership to understand that survey data is not the holy grail of compensation analysis. That the figures representing your marketplace analysis are not a “smoking gun” but limited data that suggests that many employees (certainly not all) are paid at a particular average rate. In my view this data should be used as a “pricing guide” to aid the organization’s decision-making as to appropriate next steps. The data is NOT an “Aha! moment” that tells you what you should be paying.

As you can see, an ongoing responsibility sitting on your shoulders is to educate the decision-makers on how best to view the market data within your proposal/recommendations.  If left to their own devises your senior leadership may head off in the wrong direction, primarily because of their own biases and because they do not understand your behind-the-scenes analysis.

You need to make sure that they understand. Such educational success will make your job easier.

Chuck Csizmar CCP is the founder and Principal of CMC Compensation Group, providing global compensation consulting services to a wide variety of industries and non-profit organizations.  He is also associated with several HR Consulting firms as a contributing consultant.  Chuck is a broad-based subject matter expert with a specialty in international and expatriate compensation.  He lives in Central Florida (near The Mouse) and enjoys growing fruit and managing (?) a clowder of cats.

Creative Commons image "Mother," by Christopher Wray

Cafe Classic: Competitive Market Surveys Rarely Produce Identical Pay

Editor's Note: Jim Brennan brings us a Classic reality check on pay, the labor market and competitive survey data.

Compensation professionals love to cite “the open market,” while being less eager to admit that every market is different. Despite continual references to reliance on the free labor market, the competitive pay values established between and among employers almost never match. The reasons may be seem obscure to outsiders, but they are clear to those who follow the arcane practices of the wage and salary management field. There is no one single competitive market for pay, even though that phrase is frequently used justify recommendations that are almost always unique.

Organizations follow the competitive market the same the way people heed the outside weather. After considering the weather, you dress as you please. What is considered proper, comfortable and affordable by one is not the same for another. A glance at any sample of people walking by shows how others are dressed, allowing you to adjust accordingly. Examination of the official weather report offers more refined data with greater credibility. Once you check the more precise meteorological details, then you still get to decide what you want to wear. Of course, if you are running a marathon race, you will dress differently than a scuba driver, despite identical conditions of ambient temperature, wind speeds, amount and type of cloud cover, etc., in the area.

The behaviors are parallel: reference information supplies guidance for your informed decision in each situation. But your final decision on how to dress is not based on just “the weather” any more than how you pay people is based on “the market.” There is no one weather report that applies equally well to all employers in all locations in all circumstances. In the same way, there is no one absolutely open competitive market for pay, just as there is not one single street address for “the competition.”

Even when peer organizations share details about their wages and salaries, each enterprise ends up applying the information differently. Each employer using an identical survey published by a reputable professional analytical organization ends up with its own unique number as the appropriate target. One would think that open market exchange of wage and salary information would produce fairly identical equilibrium points … but it doesn't.

Identical pay is highly unlikely. No two enterprises have exactly the same pay rates for any two jobs. Each firm has different reasons for its totally unique value systems. Steel mills don’t place a particularly high value on a mail room supervisor job, for example, while that position can be a critical profit contributor in a direct mail distribution center. Even if the pay planners at the steel mill and the mailing center referenced the exact same pay survey, they would probably draw different inferences from the reported figures and select different market reference points for internal use.

In addition, an employer may select different peer comparison groups for each work group and address them differently. Some set a policy line vector: to lead, lag or match their peers, frequently with refined definitions like “above average” or targeting the 70th percentile. Human organizations also have their own personal internal value structures. Job evaluation can then be applied for discounts or premium variances structured to reflect special priorities set by top management, created by historical precedent or required for internal equity.

Cash compensation supplies a number for comparison but it is still only part of the employee value proposition. Non-cash reward elements can't be reduced to simple numbers. Peer relationships, fringe benefits, perquisites, career progression prospects, working conditions and other circumstances like location also complicate the “total rewards” picture.

Starting with the same input information, each user can and will still come up with a different conclusion about what is right, proper, affordable and persuasive for their organization. The more we try to imitate each other, the more we vary in actual practice. No matter how identical the world we inhabit, we all live it differently. Vive la difference!

Don't hesitate to share this with someone who needs to know the reality.

E. James (Jim) Brennan is an independent compensation advisor with extensive total rewards experience in most industries.  After corporate HR posts and consulting CEO roles, he was Senior Associate of pay surveyor ERI before returning to consulting in 2015. A prolific writer (author of the Performance Management Workbook), speaker and frequent expert witness in reasonable executive compensation court cases, Jim also serves on the Advisory Board of the Compensation and Benefits Review.

Image "Colourful Shopping Bags" courtesy of Hywards at FreeDigitalPhotos.net

THE SPAC ATTACK

Those of you working at “pre-IPO” companies need to learn more about Special Purpose Acquisition Companies (SPACs). SPAC s are also known as “Blank Check” or “Reverse Merger” companies and provide a rapid path to becoming a publicly-traded company. This can create amazing opportunities, but not without the cost of significant effort for those involved.

What the heck is a SPAC transaction? Basically, some investors form a company (Company A) with the express purpose of collecting funds that will be used to acquire another company (Company B). The team of Company A is made up of people with the experience and expertise to find and acquire companies with significant untapped potential. After forming Company A they sell shares in a public offering and raise funds for a future merger or acquisition.

Company A then puts the money from their own IPO in a trust to find, woo, and pay for the acquisition of Company B. Normally, they must get all of this done in 18-24 months. Company A also does a separate funding round, selling warrants or units, to raise additional funds to cover the cost of their IPO and other costs like those related to finding a target company.

Finally, Company A finds Company B and works to acquire it. Once acquired Company B typically becomes the “main” company under the shell left by the already publicly-traded Company A. Presto Magic, Company B is now a publicly-traded company with all of the benefits and challenges that entails!

It sounds easy and elegant, but for finance, legal, HR, and compensation professionals the process can be overwhelming. Traditionally, I advise companies to begin preparing for an IPO at least 18 months in advance of the expected event and begin executing on their project plan 12 months in advance. With a SPAC you may have only 30 days to prepare and 3 months to execute. Yes, your to-do list is basically the same in both cases!

In a best-case scenario, you may have 6 months to build everything you need to be a successful publicly-traded company. This includes pay philosophies, reporting capabilities, transactional support, and market data to survive the scrutiny of investors in the public market. Your finance and legal teams will also have their own daunting list.

Your peers will magically transform from companies that may be known only to you, to those whose names are daily headlines. Your compensation philosophy must change to keep you competitive in this new market. Your broad-based market data will change from pre-IPO and private company data sets to more expensive and expansive survey data for public companies. Your executive compensation must be benchmarked against publicly-disclosed SEC or SEDAR filings. Your equity compensation programs must fundamentally change to allow for transactions on the open market. You will likely want to consider rolling out an Employee Stock Purchase Plan (ESPP) in coordination with your first trading day. The list goes on (and on=, and on). Luckily for you, this article must be kept short. You can always contact me directly for additional information, or just to chat about your transaction. I am sure I will also be writing follow-up articles over the next few months.

Why, you may ask, is this such an important topic now when you have heard so little of it in the past? Well, in 2016 there were 4 SPAC IBCs (Initial Business Combinations). In 2019 there were 28. In 2020 there were 64, and 2021 is looking like it will be an even bigger year. There were more than 240 SPAC IPOs in 2020. Each of these “blank check” companies is on the hunt for their own “Company B” to bring to the public market before the end of 2022! Three years from now this wild phase may have fizzled, but for the next year or two it’s looking like SPACs must be top of mind for pre-IPO companies.

Dan Walter is a CECP, CEP, and Fellow of Global Equity (FGE). He works as Managing Consultant for FutureSense. Dan is also a leading expert on incentive plans and equity compensation issues. He has written several industry resources including a resource dedicated to Performance-Based Equity Compensation. He has co-authored ”Everything You Do In Compensation is Communication”, “The Decision Makers Guide to Equity Compensation”, “Equity Alternatives” and other books. Connect with Dan on LinkedIn. Or, follow him on Twitter at @DanFutureSense.