Every employer likes to think they pay people to do The Right Thing. They do NOT pay according to the theoretical value of potential mistakes or even remotely possible errors. Knowing in advance just what is “the right thing to do," however, can be an arcane and quite difficult task.
How one makes good decisions is a surprisingly poorly researched topic. On the other hand, mistakes are more frequently discussed, perhaps because they are so much more common. One article in this blog on the Value of Mistakes addressed in greater detail some of the various theories about what is important for job evaluation, such as Time Span of Discretion. That particular factor considers how long it takes before anyone will know if your decision was correct. It involves how frequently work output will be weighed for adequacy. For example, one quickly discovers if the receptionist properly handles the visitor, but the impact of long-term decisions by a board chair may require many years before the results are known. Obviously, there is a very high positive relationship between this factor and compensation. The farther out in time that your job requires you to predict, as if you had a crystal ball, the more you tend to be paid.
So, how does one hop on this gravy train powered by predictive accuracy? Foreseeing the future with an accurate eye is a daunting task where good input is essential. The old acronym GIGO comes to mind. Whether one is forecasting salary budget increases or planning long-term organizational strategic objectives, the accuracy of the output produced depends on the accuracy of the input applied. That means using valid raw data to produce properly analyzed information for useful practical application.
That sounds like a job for an analyst, but new times may call for new titles. On an ancient NPR Conversations from Wingspread radio show in 1981, I predicted the emergence of a new job, a position like an answer-finder, described as a human search engine (this was the pre-PC era), as a dramatically important job of the future. It would be someone who doesn’t have to possess all the answers but simply knows where to go to find them. Similar to a research librarian, it would do reference work while not being dependent on books alone. Sources could include individuals, data bases, print media, etc. A universal consultant, an informational ombudsman or a “finder” of some kind may be needed who can access and explore new fields of knowledge.
Informatics (making full use of Big Data) is one of those new fields. It could be the best descriptive category for such intensive research. But let’s get back into the compensation corner. What might such a job be worth? Value in the competitive marketplace for labor is typically contingent on cost/benefit balances involving need, supply/demand and commercial profit. A practical example is the old story about being paid for where to strike when you hit malfunctioning equipment with the hammer.There are many fables about the value of superior information applied for maximum leverage. One would expect that a position whose effect is focused by conscious intent, using knowledge as a force multiplier, should bring a market pay premium.
Surveys don’t show any job title that specifies those tasks, though, so it may be difficult to learn much about how the open competitive market for talent would compensate that function.
What would your organization pay for a finder?
E. James (Jim) Brennan is Senior Associate of ERI Economic Research Institute, the premier publisher of interactive pay and living-cost surveys. After over 40 years in HR corporate and consulting roles throughout the U.S. and Canada, he’s pretty much been there done that (articles, books, speeches, seminars, radio/TV, advisory posts, in-trial expert witness stuff, etc.), serves on the Advisory Board of the Compensation and Benefits Review and will express his opinion on almost anything.
Creative Commons image "Examining Clouds" by katerha