Salary Survey Insanity in Small Markets – Are You Looking for the Wrong Data?

Author:
Warren Heaps – Birches Group LLC

Benchmarking compensation in smaller countries is challenging.  The usual approaches often do not work well, mostly because the market is small!  If the country is developing (most small ones are), then economic and social instability and immature labor market conditions contribute to the problem, too.

Some of the most common problems expressed by our clients include:

  • Not enough employers in my sector
  • Insufficient job matches for my company
  • Volatile results from year to year
  • Gaps in coverage, with a lack of information for specific levels

There are lots more, but you get the idea.

Survey Insanity
Albert Einstein once defined insanity as doing the same thing over and over again and expecting different results.  I think there is a lot of salary survey insanity – companies looking for data in smaller countries using the same, big country approaches they always do.  When it fails (see the list above), they try again, perhaps by calling a different survey provider, or commissioning an expensive custom survey, but always looking for the same thing — sector-based data for specific occupations unique to their company.  And so the cycle continues, and Einstein must be laughing at us all.

Stop the Insanity!
How do you stop the survey insanity?  Try taking a different approach instead.

  1. Remember Your History
    The world of work is well-defined, and despite what you may have heard, has not changed as much as you think.  The basic approach from the medieval guilds — Apprentice, Craftsman, Journeyman, Master — continues to exist today for professionals.  After all, isn’t this very similar to Technical Career Ladders?  Fancy description for what was actually created around 1300.  Military classification is another example of long standing, well-defined work role definitions.
  2. Break Out of Your Sector
    In smaller markets there aren’t enough employers in any one sector to provide the granular data you are seeking, so get over it.  Instead, focus on the leaders in all sectors.  Look for companies with whom you compete for talent, and in developing countries, don’t overlook international public sector employers such as the World Bank and the UN.  A small survey of the BEST employers beats a bigger one with all the sector “dogs” any day.
  3. Go Generic for your Job Matches
    In the majority of companies, salary ranges are set by grade level or band, and all positions assigned to that band share the same salary range.  There are Accountants, Brand Managers, IT Professionals, Engineers, Admin Managers, etc. all in the same band and sharing the same salary range.  So why is it so important to match specific occupational data in a survey?  If your internal job evaluation is done right, the assignments to your bands will be correct for your organization.In our surveys, we capture many different occupations, but the most robust data are the generic “roll-ups” by grade level, which include the jobs for which there are sufficient matches to report separately, plus the unreported data at that level.  More data points yield better results.  So it’s OK to use generic matches.  After all, your pay bands cover multiple occupations already!  And if you need to, you can tweak the data for those special occupations afterwards, when you build your scales.
  4. Think More Broadly
    Recently, a client requested information about our survey data for the media and information industry in several small markets in the Middle East and North Africa.  The media market in these places is fairly small, but their job list was full of very specific media industry roles.  I expressed some concerns about our ability to gather enough data to provide a reliable result.  But, I also made the observation that many of the roles were essentially skilled process support roles.  Instead of roles in accounting or HR, they were in TV production and media, but in the end, they were still support roles. We have plenty of matches for our more common support roles in our survey, and I suspect that data would be just fine for the client.In addition, we challenged the client to think more broadly about where appropriate job matches might be found.  For example, large embassies often have fully developed public information departments staffed with roles quite similar to those found on a newspaper or television station.

As you can see, the small market survey conundrum can be solved if you are willing to think differently about how surveys are “supposed to work.”  To act differently is to perpetuate salary survey insanity.

Please share your challenges in a comment below.

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6 Responses to Salary Survey Insanity in Small Markets – Are You Looking for the Wrong Data?

  1. Pingback: Salary Survey Insanity in Small Markets – Are You Looking for the Wrong Data? - International HR Forum - Member Blogs - HR Blogs - HR Space from Personnel Today and Xpert HR

  2. An excellent post, Warren – and straight to the core of things. Many of my clients face that “insanity” every day, and often feel uncomfortable thinking outside the box. Perhaps that’s because they report to more senior folks who themselves not only don’t have a clue either, but hold biases based on their US experience. And dealing with senior management bias can be a career challenge.

    Regardless, your suggestions for creative thinking are spot-on!

  3. Warren, solid advice as comes with all your interventions. Having spent a significant time designing comp and bene structures in the sahelian and francophone West and Central Africa zone a couple of ideas come to mind as well, as too often I’ve seen organisations peg their new structures on comp and bene comparisons that were not in same market (deciding to be @ 90% of UN levels – which will kill many smaller agencies), or as you say comparing salaries to non competitive orgs (the dogs). I think there is validity in inner regional comparisons for some countries – ie comparing Burkina Faso, Niger, Mali and Benin. However in the same vein, comparing Ghana to to Senegal may lead to false conclusions. Cheers,

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