In the early ’90s, I had to trawl index cards of candidate notes, then search the filing cabinets for the paper CVs, to identify candidates for a client’s open position. Then there was the four-hour drive to run through those CVs with the hiring manager, going through my intimate, handwritten notes.
Then we had a 200,000-CV database in WordPerfect, which we later moved onto a mobile computer called Colossus, which looked like a boombox, enabling us to search our CV database almost instantaneously. And then, in 1996, we installed our first mailbox system. We could transfer a CV to a floppy disk, take that disk to a server and send the CV electronically to any company that had a similar setup (which, as I recall, was only one at first).
Each of those steps seemed like huge advances at the time. Of course, numerous technologies have transformed the staffing industry over the years since, from vendor management systems, applicant tracking systems, smart phones and integrated office phone systems, social media, LinkedIn — and now artificial intelligence, cognitive learning, robotics and, of course, the human cloud.
And it won’t stop there. Try to imagine five years from now when the technology adoption curve is soaring. Bill Gates once said, “We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next 10. Don’t let yourself be lulled into inaction.”
That’s what I call the expectation gap, and it is well-illustrated in the accompanying diagram.
Buying organizations need to be aware of how technology will drive candidate behavior in the short to medium term and adapt new ways of working if they are to remain competitive in their talent acquisition strategy.
This cycle repeats itself as adoption of technology increases. If we take the human cloud as an example, the following generally accepted adoption diagram is true in as much as we already have the innovators and early adopters on board. There is a slight gap while the majority decide whether or not to adopt; however, during this time we typically see that the technology itself improves. In the staffing sector, of course, candidate behavior changes during this time as well, and we then move into the early majority, late majority and eventually the laggards before we reach the top of the diagonal line in the expectation gap diagram and the cycle starts again.
So the message here is clear: while you may well be running a highly effective talent acquisition program today, you need to question whether your program is robust and adaptable to meet the needs of tomorrow’s technology and candidate behavior. Is it adaptable to the possibility that one day your organization may wish to look at its workforce more holistically — whether those workers be contingent, permanent, SOWs, fully outsourced or even robots?
And finally, is your overall talent acquisition program governance designed to enable you to adapt your future strategy as the business of recruiting, inevitably, becomes far less of a “people” business?