The Break-Up: When Staffing and Compensation Practices Split

What can you do when your compensation survey data is wrong?  When you create ranges at market median pay levels, but you are bleeding talent as competing offers for prospective and current employees come in well above your range maximums?

I hear this question at increasingly regular intervals.  Often as not, there is nothing wrong with the data per se -- assuming you are using credible, quality survey sources.  The problem often lies with your choice and use of data, and the fact that staffing and compensation practitioners no longer have a common understanding of what constitutes your talent pool.  And so when tension erupts between staffing and compensation, when each is seen as an obstacle to the other's success, I often find that there is a disconnect in their visions of the type of talent their practices are meant to attract and retain.

Let me share a few examples.

Your company has traditionally competed for technical talent in a mostly local labor pool.  As your strategy moves the business in new directions, you suddenly face the need to draw talent from the tech sector and from across the country.  Do your market benchmarking practices reflect this shift?

As a manufacturer, your company has historically drawn talent from your own industry.  Increasingly, however, because of the similarities in operational challenges, you are finding that some of the best candidates for key operations positions are coming from a particular sector of the energy industry -- a sector that pays at a significantly higher level.  Is there a need for different survey sources to benchmark pay practices in this sector?

Software engineers represent critical talent for your company.  You set pay levels for this job family using survey data for the general classification "software engineer."  The position, however, demands experience and expertise in a highly specialized sub-field of software engineering, requiring your staffing compatriots to find and entice the proverbial "needle in the haystack."  And plenty of other employers are chasing this hard-to-find skillset.  Will you be able to attract and retain them with the ranges your benchmarking choices have created?

Your company runs "fast, lean and mean."  Which is another way of saying that there isn't a lot of management support.  As a result, there is little assistance and a very short runway for new employees in key professional and managerial jobs to ramp up in their responsibilities.  Consequently, you have migrated to a preference for staffing these positions with very experienced people -- far more seasoned and credentialed than the "qualifications" stated in the job descriptions would suggest.  Does the benchmarking underlying your ranges allow this practice to succeed?  Should it?

What we are facing in these cases is not so much bad compensation survey data as data that is "divorced" from the reality of our staffing needs and practices.  The solution, of course, is to get staffing and compensation practices in alignment.  That requires not only effort to clearly identify where the disconnects lie but also to get agreement from the right people on where staffing and compensation must intersect.

And, not to dodge responsibility here, but this isn't always the fault of staffing and compensation professionals.  Sometimes organizational leaders create the disconnect (or allow it to continue) by setting an incompatible set of expectations.  They want the Silicon Valley high tech talent for the local general industry price.  Then our job becomes one of information gathering and education.  

There are other stories and examples of staffing and compensation break-ups out there.  Let's hear yours!

Ann Bares is the Founder and Editor of the Compensation Café,  Author of Compensation Force and Managing Partner of Altura Consulting Group LLC, where she provides compensation consulting to a range of client organizations.  Ann serves as President of the Twin Cities Compensation Network (the most awesome local reward network on the planet) and is a member of the Advisory Board of the Compensation & Benefits Review, the leading journal for those who design, implement, evaluate and communicate total rewards.  She earned her M.B.A. at Northwestern University’s Kellogg School, is a foodie and bookhound in her spare time (now reading John Green's "The Fault in Our Stars"). Follow her on Twitter at @annbares. 

Creative Commons image "Broken Heart Grunge" by free grunge textures

Comments

[iwilliamsPHR]

A year ago I changed roles from recruiting to compensation so I can appreciate the importance of the two working together. Good read.

[E. James (Jim) Brennan]

Excellent advice, Ann. Just because numbers may be real and accurate, that doesn't mean that they are automatically appropriate for a given application. It is wise to confirm understandings before proceeding with a recommendation: i.e., diagnosis should always precede prescription.

[Jules]

The best comp package I create is always done with the recruiter who knows the market. I give survey data information and he tells me what the market rate is at and we hammer out the details together. I miss doing that a lot!

[Ann Bares]

iwilliams:

Nothing like having walked in both sets of shoes to give you perspective!

Jim:

Exactly right - finding and using data is not the same as finding and using the right data.

Jules:

Sounds like a great collaborative process!

Thanks, all, for the comments and experiences!