Compensation Cafe

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 rpaul@morneaushepell.com.  

Unsplash Photos for everyone by Lukas Blazek

Cafe Classic: Broadbanding in the Age of Equity and Analytics

Editor's Note: It is interesting to watch concepts that came into play and popularity during an earlier era be "rediscovered" (and sometimes even "repurposed") by the profession.  Ah, the arc of history.  Case in point today: broadbands.  

WorldatWork, in its glossary of reward terms, provides us with an appropriately succinct definition.

Broadbanding: A pay structure that consolidates a large number of pay grades and salary ranges into much fewer broad bands with relatively wide salary ranges, typically with 100 percent or more difference between minimum and maximum.

On its surface, the appeal of this is easy to understand.  Fewer "grades," coupled with wider ranges sounds like less structure, less bureaucracy, less administrative work and more flexibility.  In theory, that's true.  In practice, it can be a little more complicated.  The complications arise because broadbanding, at least as it was originally conceived, wasn't designed to support the traditional job-based work and pay program designs that are still the norm at many (perhaps even most) organizations.  It was meant to support more broadly-defined roles, to support and reward lateral growth and career development. 

When you collapse a pay structure into fewer, wider salary bands, at least in the "pure" sense of broadbanding, you effectively give up the control point (market reference or midpoint) of a traditional salary range.  Which makes perfect sense if you've moved away from job-defined work and pay, and are no longer concerned with setting and managing salary opportunity based on the attributes and value of a discrete job - if you are moving instead to managing pay opportunity by the skill, competency and/or performance of individuals within more broadly defined classes of work.

The issue with - and my personal objection to - broadbanding is when it is chosen simply as an easier, more flexible way to manage job-based pay by organizations that have not invested in the processes required to manage individual-based pay.   A pure broadbanding approach leaves these organization with a very wide band of salary possibility, now less a meaningful control point. They've removed the guard rails that control by job used to offer, made the margin for error now alarmingly wide, and created a system whereby effective salary management demands an ability to define and defend how individuals should paid within that wide range of possibility without the necessary support systems.  They encounter issues in areas like career advancement, when expectations born in the age of traditional jobs bump up against the new broadbanding realities and things like promotional opportunities vanish.  And yes, I know that many organizations will address this by adding a series of control points and sub-bands within their broad bands, to provide more guidance and control to salary decisions.  To which I say:  Gosh, that starts to sound a lot like a series of traditional salary ranges.  

Here's the thing though.  As we get better and more sophisticated in HR analytics, in understanding and measuring how employees create value in their work, perhaps we'll have a new data-grounded, person-based valuation foundation to pair up with a broadband approach.  Perhaps an alliance between rewards and analytics will lead us to a new renaissance in banding, featuring rigorous approaches to measuring how people grow in value across a broadly defined work class.  A BroadBanding 2.0 (or 3.0 or 4.0...  this cat's had a lot of lives).

Or perhaps the precision and rigor of analytics, as it gains a stronger foothold in rewards, will lead us in the opposite direction - to more narrow and precise salary opportunities.

Your thoughts?

Ann Bares is the Founder and Editor of Compensation Café,  Author of Compensation Force and Partner at Altura Consulting Group LLC, where she provides compensation consulting and survey administration services to a wide range of client organizations.  She earned her M.B.A. at Northwestern University’s Kellogg School and enjoys hiking, reading and hanging out with family in any spare time.

Cafe Classic: Compensation Work and Having Skin in the Game

Editor's Note:  Is our profession, are our jobs truly designed for success in the age of continuous disruption?  What are your thoughts on this Classic question?

Some fascinating work is being done around navigating human capital risk and uncertainty.  I think it could raise some interesting questions about how compensation jobs and functions are defined and organized. 

Success for businesses increasingly hangs on their people and the structures they create to guide and support their work.  The problem, of course, is that industries and markets can shift quickly and unexpectedly.  Your company might respond with changes in pricing, product offerings, branding or its "go to market" approach -- but how quickly can it transform its workforce to deliver on these changes?

How quickly could you (compensation professional) get your head around the differences in skills, practices and behaviors needed?  How well could you pinpoint the gaps between what you've got going on today and what is needed tomorrow (or this afternoon)?  And how efficiently can you identify the obstacles that your current reward programs -- base pay delivery, incentives, benefit plans and programs -- will toss into the path of the workforce transformation that must now happen?

It's classic Innovator's Dilemma stuff.  And I'm thinking about it today relative to the way we structure compensation roles and work.  

There's a lot to be said for growing and refining your HR analytics capabilities so that they can tip you off to the make-up of and trends in your workforce, and help you identify and respond to the risks that might exist in the people part of your value proposition.  Hopefully we in the compensation profession, as the original data nerds in HR, are taking the necessary steps here.

But I think there's also the reality of how well our compensation jobs allow us to see and understand the day-to-day reality of the work people are doing.  The eyeball-to-eyeball, ear-to-ground reality.  Skin in the game.

To have skin in the game essentially means that you have some share in the costs and benefits your decisions and actions create for others.  Do we?  Should we?  Should our functions and roles be defined to create some sense of it?

How is the compensation function in your organization structured?  Do you -- like some -- have a centralized compensation function that is tucked away in "corporate" where you must rely on HR generalists and advisors to be your eyes and ears on the ground?  Or do you -- like others -- have compensation professionals embedded in the different business units where they have more direct contact and a front row seat to the action.  

Will this become a bigger deal as the pace of change continues to accelerate and navigating human capital uncertainty becomes both more challenging and more important?

Nassim Taleb -- the guru of risk and uncertainty whose books on the topic include The Black Swan and Anti-Fragile and of whom I am a big fan -- feels so strongly about the notion of skin in the game that it is the topic and title of his next, soon-to-be-published book.  I don't have the answer to the question I raise above, but as food for thought I'll leave you with this principle of skin-in-the-gameship courtesy of Mr. Taleb, who holds that skin in the game only happens in decentralized systems.

Principle:  It it always vastly easier to macro BS than to micro BS.

Ann Bares is the Founder and Editor of Compensation Café,  Author of Compensation Force and Partner at Altura Consulting Group LLC, where she provides compensation consulting and survey administration services to a wide range of client organizations.  She earned her M.B.A. at Northwestern University’s Kellogg School and enjoys hiking, reading and hanging out with family in any spare time. 

Creative Commons image "hands group" by Safe.Homes.Rape.Crisis.Coalition

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.

Zooming In On The Data

The use of exit interviews and engagement surveys can shed light from an employee's perspective on several factors tied to their sense of value and attachment to an organization.  For most rewards professionals’ data collection, the analysis and outcome statistics drive us to find solutions and identify the culprit challenging today’s reward programs.

How we assess data got me thinking: beyond acquiring employee insights through surveys and seeking truth in the obvious, why not examine our data and look for the opposite?  For example, what are we doing or providing to our workforce that is making them stay, but may ultimately not be as favorable to the organization?

The intention here is not to pin the employee against the employer, but imagine the scenarios where we have become complacent or have failed to take notice of offerings or practices that have enabled employees to take advantage.  There may be a number of examples, and the following are just a few to get you thinking:

1. Learning and development – while providing employees with the opportunities to seek professional development is highly valued and respected, it is equally important to ensure there is demonstration and application of new skills and qualifications attained. Also important is assessing the trends among roles or grade levels where there is high career progression, which will eventually stall as succession to the next level becomes limited. For most, they will quickly realize that they have acquired sought-after skills deemed desirable in the market and to recruiters.

As employers, we hope to equip our workforce with the skills, knowledge, and aptitude to be successful within the context of the organization, not to be perfected and utilized elsewhere.

2. Hours of work – if you have not already, it's best you assess the usage of overtime (“OT”). Consider the roles, departments, and work seasons where OT usage is highest.  Do the figures make sense? The expense for this can be costly, hence the importance of  deciphering if OT is even necessary.  Given how quickly work has evolved, there is more reason now to revaluate eligibility criteria, minimum thresholds to claim OT, and whether process improvements could eliminate the need for excess human touch.

3. Role clarity – job descriptions are a key proponent in outlining role expectations and are a shared artifact between the employee and employer. The context within is key to effective performance management, however, the challenge arises when the accountabilities no longer reflect how the role is meant to function today. Conveying sub-par performance to an employee is harder when you do not have updated descriptions to base individual accountability on.  To an employee, they might be pulling just enough weight to keep on getting by, while true productivity is suffering.

4. Institutional knowledge – are there individuals that you keep around because of fear of losing the legacy intel they house? If so, like the overtime scenario noted above, it's time to examine what is invested in this retention and put in motion the steps to either have the knowledge transferred or documented.  Better yet, implement a new-shared process.

The next time you delve into the data, see what story you uncover.  While our intentions might be sound in providing the optimum rewards package, be sure that it's in the best interest of all parties.  In the end, we want the right talent in the right spots, doing the right things.

Reena Paul (CCP, GRP) works as a Senior Compensation Consultant.  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 directly on  LinkedIn. 

Image source: Unsplash image with credit to Markus Winkler.

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

Avoiding Analysis Paralysis

To effectively manage reward programs compensation practitioners and their senior management need to understand how competitive those programs currently are.  In making that determination, though, just how precise does the analysis have to be?  To what lengths should one go to increase the level of exactitude in the analysis, and is that effort worthwhile?  Does the effort to squeeze out greater precision bring more meaningful results?

In other words, what's the additional value of dotting the "I's" and crossing the "T's"?

As compensation professionals will tell you, the competitive “marketplace” for reward program surveys is an imprecise animal, subject to numerous variations and interpretations.

• One survey doesn’t use the same companies as the next survey.  Who do you believe?
• The ability to match job descriptions varies from precise to broadly similar roles.  Strange titles are a constant challenge.
• Surveys provide different mixes of industries, geographies, and revenue, and cannot report on the many non-participating organizations. Rates of organization growth are not reported.
• The use of weighted Average/Mean/Median/50^th percentile formats isn't standardized.
• International surveys often fail to provide enough information, as compared with U.S. surveys.
• The process of completing survey questionnaires is often not as carefully conducted as one would hope (perhaps an understatement).

In addition, the market is a moving target as population changes, organization shifts and changes in employee pay are considered.  This means that you’ll need to be careful of “aging” factors, such as adjusting data from date of collection to the current or some future date.   My practice is to "round" to the nearest 100 units of annual currency.  Is that distorting the data?

Pick a Number?

Do you think that a market rate of $47,570 for a job is an accurate reflection of current trends, or simply an arithmetic average of data that looks precise?  Would you fall on your sword over that figure? 

Using three surveys would likely provide three separate figures.  Let’s say your sources report $45,723, $47,612, and $49,375.  If cost, time, and effort are not factors to consider, then you could keep going, searching for that common denominator.  Purchase another (expensive) survey source.  Double and triple check your job matches.  But do you think that the extra source, the extra time and effort will substantially change your initial analysis, or are you simply looking to protect yourself?   Are you playing a defensive game to divert potential challenge?

For most of us a quick and straightforward analysis suggests that approximately $47,500 is reasonable enough.

While not advocating a sore thumb analysis I do suggest that you use a balance of time, effort and cost when conducting market analysis.  What you really need is to understand the market; that’s the key learning point.  Repetition is sometimes just that, more of the same with little increased value.

And what degree of precision are you being asked to provide?  Are your instructions to feel the pulse of the marketplace, to get a sense of what is being paid out there?  Or do you need a more precise result?  Is your audience demanding more?

Is the Market a Number?

What is that market?  Anything within +5% to -5% of a “market rate” figure is close enough for me.  Others believe that variable should be 10%, but in my view that leaves too wide a range that could distort your intent to provide the so-called “going rate” trend.

Caution:  You can find any number of analysis paralysis jockeys out there who advocate increasingly precise techniques to zero in on what they call your true market rate.  Just remember that many commercial survey vendors have built a business around encouraging organizations to slice and dice whatever information is available, trying to define and refine exactly what a “market” is paying, what jobs are exact matches and after a fashion what numbers you can rely on.

Part of their marketing strategy is to use custom designed evaluation techniques and proprietary job matching systems.  Use of such a strategy effectively marries your organization to the vendor, as one often cannot use proprietary language and techniques (the system) with other survey providers - without the risk of comparing apples and oranges.

The Leadership Perspective

From a senior leadership perspective, do you really need that depth of precision to make a business decision?

I think you don’t.

There's a place for precision, and a place for trends - for a “feel of the pulse.”  Usually, senior management wants to gauge the big picture - the overall strategy and its implementation status - letting professional specialists deal with the tactical matters and details.

Have a care in your efforts to be precise, because when you give senior management too many details they tend to dive in almost as a defense mechanism, as if they are expected to ask questions. Where they might otherwise have nodded their heads at key points in your presentation, you can instead find yourself immersed in detailed analytics that can bog down the decision-making process.

When senior management asks a question, office life becomes an “all hands-on deck” fire drill of employees rushing about to get the answers - to questions that might not have been asked in the first place if you had played your cards right.

Management wants your professional judgment.  They don’t want you to defer opinions to what a survey says.  Use survey data as a backup, as anecdotal information to assist the decision-making process.  Don’t feel that you always need to lead with it.

Standing back and pointing at figures is like leading with your chin in a fight. 

You won't like the results.

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 "Forgetting," by Leeks

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 reena.paul@lifeworks.com.  

Image source: istockphoto with credit to Ivelin Radkov

The Rewards Partner

We are accustomed to wearing many hats in the profession of total rewards, whether it be the role of the accountant or that of a communications expert.  Today’s call to action is to play, also, the role of a marketing strategist.  As organizations look towards turning a new leaf in economic recovery efforts, employers are faced with increased pressures to attract, retain, and motivate the workforce.

It will be a tall order to ask of us, but we in the profession know that economic, social, and pandemic-related impacts are forming to be the catalysts in how we reform, re-define and re-brand the total rewards value proposition.

Functioning now as “Rewards Partners”, we must construct a workplace story that evokes emotions of career reward and fulfillment and, more importantly, delivers the realities of it to existing and prospective employees.  There are several strategies which employers can act upon to retain and compete for talent.  The following are just a few examples to facilitate your efforts towards this renewed mindset when it comes to repositioning your organization's total rewards program.

For starters, data analytics and intelligence are key in allowing us to go beyond the surface level.  Descriptive employee data that covers all factors of employee demographics such as experience, education, tenure, job type, etc. is at the heart of helping us understand our workforce makeup.  It enables us to distill the perceived versus persistent gaps that exist in our organizations. If you have not already done so, then you must document, track and extrapolate your human capitals data to outline today’s story.  Only then can the story be filled in by the informed decisions you make herein.

Equipped with data in hand, you have a stronger sense of the multi-generational workforce that exists both internally and externally.  The needs of each generation will vary and this is where the Rewards Partner must excel.  For each cohort, there is a different message and rewards element to sell.  Repackaging the total rewards offering to meet their needs is your blueprint in creating a sense of flexible benefits.  The millennial who has a growing family would much rather hear about the work-life balance and childcare services on offer versus pension plan guidelines for an impending retirement.

Finally, to compete for skilled workers, we must check whether we are prohibiting ourselves from supporting a diverse talent pool.  Diversity, equity, and Inclusion are emerging priorities in the workforce.  A key proponent to this initiative is breaking down the biases.  Providing training to conquer our individual biases is one thing, but we must address the systemic biases that our organization has.  To do so, conducting an audit on our existing HR practices, policies, and approaches towards hiring, developing, and promoting employees is an integral step.  Getting to the root of how we conduct ourselves in these scenarios will shed light as to whether we are operating in a way resulting in certain groups being advantaged and others disadvantaged or devalued.  

As Reward Partners we have the opportunity to support our organizations in carving the pathway towards being an employer of choice, it will be a journey in itself that will be as unique as the story of total rewards we tell.

Reena Paul (CCP, GRP) is a Senior Compensation Consultant.  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 and contact Reena directly on LinkedIn

Photo by Bernd Dittrich on Unsplash

A Primer on Job Architecture-Part Two

Job architecture is a hot topic right now, and I have to admit that I am pleased. The outcomes of the design process can make compensation administration, career development and workforce planning so much more effective. Plus, there is an opportunity for each of us to learn so much about the organization's jobs and reward philosophy during the design process, and to improve employee pay satisfaction at the same time.

In the first part of this article, we looked at the types of organizations that use job architecture and why. If you haven't had a chance to participate in a design process, part two is an overview of the project components. You'll see that there can be different approaches to job architecture.

Here are the basic project design building blocks:

A. Job families. Familiar to all of us, this is where you start--by identifying the groupings of jobs that perform similar work. Traditional examples of job families are Finance, Legal, and Human Resources. You might think that complex companies have a long, complicated list of job families, but that may not always be true. Companies that have worked a lot on workforce planning may have simplified their organizational structure to support their work.

B. Job functions. Again, a familiar step--grouping jobs within a job family with similar responsibilities and skills. Healthcare organizations, for example, may have numerous job functions within a job family. Consider all of the types of nursing specialties there might be in a teaching hospital. Simpler examples, though, would be Accounting and Accounts Receivable/Payable under the Finance job family, or Compensation and Benefits under Human Resources.

C. Focus area/philosophy. This step is where you may see variability in an organization's approach to job architecture (and a difference in project schedule).

For some, the next step is to identify job levels. The projects that work in this way often produce a job architecture that emphasizes compensation administration. Their goal for organization-wide alignment is to create shared compensation levels, either as ranges or bands, that illustrate job levels. Those levels, in turn, are used for talking about career stages within a job function.

For others, the next step is to understand and organize career paths. This starts with sorting jobs within a function by categories like executive, manager, professional, support and so on. Then career levels are defined within each category that differentiate the levels of development over a career.

The descriptions for these levels of development can be immensely helpful for communicating career paths to employees. They can also be useful from an administration standpoint, to use as standardized guidelines for transferring employees among various functions within a job family or building consensus on a promotion, for example. (Standardization also helps build a level of employee trust in these transactions.) Salary alignment across the organization is a complex step in this type of design process as it executes and supports the career path framework.

If job architecture is not in your near future, but you'd like to learn more, almost all of the consulting firms are discussing their practices on a regular basis. (It's a hot topic!) Some of them share more than others, but many will help you learn what's current in our field.

If you have the budget, it's particularly important to partner with experienced firms for this work--the projects involve so much data that they can easily get bogged down. For example, you can get all the jobs slotted and then realize you don't know how to do the next step. I once work with a client who brought me all their job levels on little strips in a shopping bag. They had tried to build their architecture on a wall as a group exercise, and had given up after trying a couple of times to make it work. It's never turnkey, but your insights are going to come faster with firms who've done a lot of this work in your industry. And some firms have far better databases than others.

Margaret O'Hanlon brings deep expertise to discussions on employee pay, performance management, career development and communications at the Café. Her firm is re:Think Consulting. Earlier, she was a Principal at Willis Towers Watson. A former Board member for the Bay Area Compensation Association (BACA), Margaret coauthored the popular eBook, Everything You Do (in Compensation) Is Communications, a toolkit that all practitioners can find at everythingiscommunication.com. She is a member of U.S. Masters Swimming.

Cafe Classic: Black Holes and Compensation Metrics

Editor's Note: Contributor Stephanie Thomas channels her inner astrophysicist to illuminate some pay metrics lessons from the phenomenon of black holes!

It's a little-known fact, but the fields of astrophysics and compensation are closely related. Similarities are particularly apparent between black holes and compensation metrics. Both fields attract theorists and experimental researchers looking for a challenge, and both require a unique combination of empirical fact coupled with imagination. We know that black holes and compensation metrics exist, but the full extent of their innermost mysteries are yet to be revealed.

Taking an interdisciplinary approach can give us new insights into old problems. With that in mind, here are five things black holes can teach us about compensation metrics.

1. Black Holes and Compensation Metrics Suck - a black hole is a region of space from which nothing can escape. Because of strong gravitational fields and magnetic winds, these collapsed stars are impossible to resist. Compensation metrics also have strong gravitational and magnetic fields - it's easy to get sucked into the promise of finding that ultimate metric that will finally give you the perfect compensation system. Like cosmic dust into a black hole, a constant stream of time and money can get pulled into developing and implementing these metrics. If those resources are focused on measuring the wrong things, all that time and money can easily disappear into the singularity, lost forever, without shedding any light on the question at hand.

2. The Information Loss Paradox - when an object falls into a black hole, all of the information about that object is evenly distributed along the event horizon and is lost to outside observers. The same is true for compensation metrics. By their very nature, metrics are designed to aggregate information across observations and distill that information down into meaningful insights. But information is lost in the aggregation process. The primary unit of observation in compensation metrics is the person; people invariably have a rich history full of details that help to explain their current characteristics. Before crossing the event horizon of information processing and aggregation, it's important to think about what secondary information and individual characteristics might be of interest, and come up with a way to preserve that information in the overall metric.

3. Lack of Direct Evidence - by their nature, black holes cannot be directly observed. Astrophysicists looking for black holes have to rely on indirect evidence - usually gravitational interactions of the supposed black hole with its surroundings. Metrics essentially show us gravitational interactions, allowing us to make inferences about the unmeasurable things we really care about. Metrics may provide indirect evidence of problems in base salaries, workload, or management, but they rarely are able to accurately capture the problem itself. Metrics are proxies, and before we draw conclusions about the underlying processes at work, we need to make sure that our metrics are really measuring what we think they're measuring.  

4. Observations Are Influenced By Position Of Observer - one of the most interesting effects associated with black holes is gravitational time dilation. To a distant observer, an object falling into a black hole appears to slow down, taking an infinite time to fall in. But an observer falling into the black hole crosses the event horizon after a finite time, although he doesn't know when (it's impossible to determine the location of the event horizon from local observations). A similar phenomenon is true for metrics - two people could look at the same metric and come to different conclusions. Assume that employee turnover has increased in the last quarter. One person could look at this metric and conclude that the wrong people were being hired in the first place. Another could look at the same metric and conclude that the micromanagement policies implemented three months ago are the problem. Neither is really wrong; the new policies had a negative effect on the incumbent employees, but if individuals preferring micromanagement were hired, turnover would likely decline... The point is, perspective matters in interpreting the metrics.

5. Gravitational Collapse - black holes are created when the celestial object's internal pressure is insufficient to resist that object's own gravity. Metrics, if left unchecked, can lead to the same kind of gravitational collapse. We're assigning more importance to metrics in all areas of our lives - from KPIs at work to tracking 3-D information about workouts at the gym and the quality of our sleep at home in our beds. We love those little graphable sound-bites of information. There's something really gravitational about metrics, and it's easy to get caught up in their pull. But when the reasons for creating the metrics in the first place takes a back seat to the "what-can-we-measure-next" mentality, it's easy to collapse into the singularity of measuring for the sake of measuring.

Stephanie Thomas, Ph.D., is a Lecturer in the Department of Economics at Cornell University. She teaches undergraduate and graduate courses on economic theory and labor economics in the College of Arts and Sciences and in Cornell’s School of Industrial and Labor Relations. Throughout her career, Stephanie has completed research on a variety of topics including wage determination, pay gaps and inequality, and performance-based compensation systems. She frequently provides expert commentary in media outlets such as The New York Times, CBC, and NPR, and has published papers in a variety of journals.