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What does data benchmarking have in common with antique collecting?

My husband buys and sells antiques. His specialties include advertising, tobacco, and general store items from the late 1880s to the early 1900s. He dabbles online, sells in stores, and exhibits at shows. Collectors will go to great lengths to find what they desire – even rising in the early morning hours to scour estate sales, swap-in-shops, or flea markets.

In my role as a benefits manager for PGi, I constantly hunt, scour and dig, too. I consider myself a data collector of sorts because I keep every piece of benchmarking data I can get my hands on.

In the antiques marketplace, one of the most deceiving and difficult hobbies is collecting Coca-Cola period items. Reproductions are everywhere and woe is the collector who invests time, money, and energy in an item, only to find out later the worth is less than they anticipated. Collectors are cautioned to learn, research, and examine items carefully so they will not be disappointed. The same goes for benchmarking surveys – the data, and how it is collected, can be different for each survey, and if you don’t go to great lengths to examine the numbers, you could be bushwhacked.

If you review a survey, take the time to preview the what, how, and types of information that it collected. If the data collection details aren’t included, ask the authors. Industry is important, too.  If you happen to be in manufacturing, your workforce, earnings, and operations will be quite different than the financial services industry – and so will your health plan expenses. A survey that has a large number of high-tech respondents may have lower expenses, as they usually employ a younger workforce.

Another key area of comparison is whether the survey summaries health plan expenses represented in gross claims or net costs. There’s a big difference between the two, as the net should remove all sources of funding (COBRA, associate premiums, rebates, refunds, etc.). If you drill down your net costs per employee and compare it to a survey that reports gross claims, your plan will probably look rosier than it is – and that’s not true to you, or your management team.

Once I opened up a survey that looked promising, only to discover in the fine print that the participating employers had 200 employees or less, and only 80 or so responded. If I used this data to compare with my plan, which had 1,000 members at the time, the comparison wouldn’t have been reasonable.

I’m pleased that technology has proven to be useful in my hunt as a benchmark data collector. At the click of a mouse, I can readily find a variety of survey resources available, without having to wake up at 3:00 a.m. to rummage through a flea market like my hubby does! Regardless, the hunt will be never-ending for me and I don’t mind one bit!

Karrie Andes, SPHR, CBP, is the senior benefits manager for PGi and a savvy self-funding health care gal.  She’s located in the Kansas City area and can be reached at karrie.andes@pgi.com.

What's your advice or pet peeve about decoding benefits benchmarking data? Share your thoughts in the comments.

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