Why, oh why does the relationship between analytics, automation, profit and employment seem to elude so many people?

A nicely rounded post by Scott Mongeau, “Manager-machine: analytics, artificial intelligence, and the uncertain future of management”, from last October came to my attention today via James Kobielus’ recent response, “Cognitive Computing and the Indelible Role of Human Judgment”. Together, they reminded me again of a real-world problem that has been bothering me since the publication of my book, “Business unIntelligence”.

Mongeau gives a reasoned analysis of the likely increasing impact of analytics and artificial intelligence on the role of management. His thesis appears very realistic: over the coming few decades, many of the more routine tasks of management will fall within the capability of increasingly powerful machines. From driverless cars to advanced logistics management, many more tasks only recently considered the sole remit of humans can be automated. Mongeau also provides a list of tasks where analytics and automation may never (or perhaps more slowly) encroach: he cites strategic decision making, and tasks requiring leadership and personal engagement, although, even in strategic decisions, IBM’s Watson is already making a play. He also offers some possible new job roles for displaced managers. However, he misses what I believe is the key implication, to which I’ll return in a moment.

Sadly, Kobielus misses the same point, choosing instead to focus on the irrefutable argument (at least for the foreseeable future) that there will always be some tasks where human judgment or oversight is required. Such tasks will remain, of course, with humans. A sideswipe at Luddism also adds nothing to the argument.

So, what is the missed implication? It seems self-evident, to me, at least, that manufacturing and increasingly services can be delivered more cheaply in many cases, using analytics and automation, by machines rather than people. As both analytics and automation improve exponentially according to Moore’s Law, the disparity can only increase. Therefore, industry progressively invests in the capital of hardware and software rather than labor, driven directly by the profit motive. Given that it is through their labor that the vast majority of consumers earn the money needed to buy industry’s goods and services, at what point will consumption be adversely affected by the resulting growing level of unemployment? This is not an argument about when, if ever, machines can do everything a person can do. It is simply about envisaging a tipping point when a sufficient percentage of the population can no longer afford the goods and services delivered by industry, no matter how cheaply.

Hence, the equation implied in the title of this post: analytics and automation, driven by profit, reduce employment. The traditional economic argument is that technology-driven unemployment has always has always been counteracted by new jobs at a higher level of skill for those displaced by the new technology. This argument simply cannot be applied in the current situation; the “skill level” of analytics and automation is increasing far faster (and actually accelerating) than that of humans.

So, I use this first post of 2015 to reiterate the questions I posed in a series of blogs early last year. To be very frank, I do not know what the answers should be. And the politicians, economists and business leaders, who should be leading the thinking in this area, appear to be fully disengaged. In summary, the quest is: how can we reinvent the current economic system in light of the reality that cheaper and more efficient analytics and automation are driving every industry to reduce or eliminate labor costs without consideration for the fact that employment is also the foundation for consumption and, thus, profit?

This article was originally published January 5, 2015 on itknowledgeexchange.techtarget.com.