HCM Analytics, a la 1911
Posted by Paul Gupta on February 16, 2010
Say you want to be a CEO. You think by working harder, smarter, faster at your job, you will get there.
Will it work? Or, twenty years later, will you look back and ponder what you should have done differently.
I recently had a chance to hear what my friends at LinkedIn have been upto and they had some good ideas in this regard. They are looking at current CEOs and seeing the paths they took to get there. Then offering suggestions grounded in reality: statistical evidence to support career decisions and their likely outcomes. Follow the path most likely to take you to your destination: for example, starting as a software engineer, here are the next steps people took with a % weight attached to each step, and from there onwards. Pretty enticing stuff. I, for one, cannot wait to play around with it.
On a broader note, it seems analytics is all the rage these days, and not just in Talent Management. Competing through analytics, data driven management, why maths is going to rock my world, to name some recent books and articles.
It is worth remembering however, that this concept is not new at all: in fact, using analytics to improve performance predates computers!
Anyone know what I am talking about?
If you guessed Taylor Time and Motion studies, you would be correct. These came about in the early 20th century (1911 to be exact), shortly after the uptake of mass production concepts. Frederick Taylor broke work down into simple, repeatable steps, the emphasis being on repeatability. As an example, Taylor ran time studies to determine that the optimal weight that a worker should lift in a shovel was 21 pounds. Stopwatches were used to time assemply tasks, and each task was decomposed into basic movements, and then reconstituted with the minimum optimal motions necessary.
The result was disastrous. Assemply line workers hated being treated like automatons and being asked to operate at the theoretical designated performance. The issue even made its way to the US Congress. Thankfully, later in the 20th century, management trends moved away from “scientific management” (as Time and Motion studies were euphemistically called) towards a more democratic form, with practices such as quality circles and poka yoke (Japan/Toyota), flexible manufacturing (Volvo), and the Pygmalion Effect – all of which embrace, not negate the potential of the assembly line worker.
So here we are, a century later. It bears remembering a simple lesson we learnt long ago – people do not always relate well to being managed by hard numbers. So whereas I love business intelligence and analytics, but I remain sensitive to the all-important human element in talent development.
What’s your analytical story in human capital management? We would love to hear…
Photo by Bruce Alderson.