As a part of ongoing scanning, among the many sources I read at least weekly are job ads (there’s a foresight joke in here somewhere, but I’ll leave it for now). To me, the changing nature of work as described in the evolution of required duties and experience levels are an interesting leading indicator, at least of perception. What do companies think they will need, in what quantity, and based on what skills?
Granted, I’m looking at certain sectors that are the apparent leading edge of services, manufacturing and media, but several big shifts seem to be taking place in the way roles are described, and what skills and experience are required by employers to fill them. Some examples:
- Required education levels are getting higher. A BA or BS is becoming the equivalent of finishing secondary school. Master’s degrees are sought after more and more. Leading to…
- A jump in demand for specialized education. A general master’s level degree doesn’t seem to suffice—it has to be specialized in a niche area. Urban planning, design research, astrobiology, early childhood education.
- Transdisciplinary capabilities. It’s not enough to have had a breadth of experience, but one needs to be able to call on both sides of the brain, and all areas of practice, all of the time. Graphic design? Check. Interactive design? Check. Project management? Check. Marketing and communication? Check. Research and insights? Check. On and on, a single department or division, rolled into one person. I suspect this is a sort of risk averse trend whereby many potential needs are crammed into one job, requiring not so much as a “T-shaped” individual as a fantasy firefighter/ninja who will cover the inadequacies of others when faced with an increasingly complex and chaotic environment.
- Analytical capabilities. This is the one that jumps out more and more. Problem solving isn’t sufficient. Being able to assess and analyze “insights,” what industry generally calls half-digested data today, is de rigueur. Increasingly, jobs appear to come with a data set, or a petabyte of data, attached. Be prepared to receive a data dump, and capable of telling a coherent story from it. Which means…
- The ability to weave a narrative. One must be able to always tell a story, craft a use case, layer up a persona, or imagine a segmentation. With increasing levels of disruption around them, organizations of all kinds seem to need to tell themselves a story. Who are we? Who do we serve? What is our backstory? What are our customers’/competitors’ motivations?
The availability of data seems to be driving these latter two elements. As a recent McKinsey Quarterly article called “The Second Economy,” posits, our global economy is in the midst of a sort of molting—the physical economy that grew from the Industrial Revolution has spawned a second economy that is largely invisible, and a product of IT, a data economy. “This vast global digital network that is sensing, ‘computing,’ and reacting appropriately—is starting to constitute a neural layer for the economy.” writes W. Brian Arthur in this piece. “The second economy constitutes a neural layer for the physical economy.”
Arthur goes on to say that this second economy doesn’t require the jobs the first, physical economy did. In his view, the intelligence we build into the system—the algorithms—do a lot of the lifting individuals used to. A clerk isn’t required to draft a report, move a document along, and make a decision. If you apply for a credit card today, or try to book a one-way flight with cash, somewhere an algorithm is sniffing you, matching your behavior to a set pattern, and rendering judgement. Others are coming to a similar conclusion, with much handwringing about how technology is displacing jobs.
But the anecdotal evidence of scanning the job postings suggest otherwise. Our data sets are growing larger as the “aspen root system,” as Arthur calls the sensing tendrils of this second economy, grows more extensive. We can collect more, so we have more not to simply analyze, but contextualize and convert to meaningful narrative. This need to see the patterns in the noise itself may be the catalyst for an even higher (or deeper) level economy—a third economy of sensemaking. Collecting and warehousing massive amounts of data is simply an exercise in hording if we can’t see, contextualize, and use the patterns in the noise. (This article on the growing genetic data glut is a great example.)
This evolution will requre even greater, and more meaningful, analytical ability from workers of the near future. If sensing and collection is ubiquitous, then our ability to be analytical polyglots must be as well. Arthur is correct in that fewer people will be required to push a button or shift a document, but we are in serious trouble if we don’t grow the capability to make sense of what we “know” at a pace relative to the speed with which we can collect. Algorithms can only take us so far, which we are seeing even now.