Often when discussing the internet of things, we tend to go on and on about collecting data and the potential efficiencies that come from understanding that data. The assumption is that much of that understanding will come in the form of an algorithm, but an article by John Hagel and John Seely Brown offers another viewpoint.
Hagel articulates a world where the internet of things requires human intervention because while the computers and data derived by connected objects and processes might show us problems or outliers, it takes a human to see those outliers and redesign the process to eliminate them. It’s that process that drives even more efficiencies. From the article:
The goal is to pull all of the data back into a human sphere where people can add value. We haven’t yet seen good examples of this, but imagine a beverage company that faces fairly frequent stock-outs that cause customer dissatisfaction and lost sales. A year’s worth of data shows that the stock-outs typically occur in conjunction with local and hyper-local events. Now the company has the opportunity not only to track and respond to stock-out situations faster, but to program the inventory-replenishment system to cross-check with event calendars, weather reports, and Twitter feeds to prepare. Companies’ skills in tapping use data will determine the data’s value, but the potential is greater than just cost efficiencies.
Not only does his worldview leave a role for humans even as the mainstream press is more and more worried about robots and automation stealing jobs, but it also recognizes that throughout history we have always ascribed more capabilities to our technology than it can really provide without a lot of human interaction and tweaking. So as we head into Labor Day, check out his article for a sense of how labor may change thanks to cheaper access to data and automation, but will still require a human touch.