In early 1811, a secret society of textile industry workers in Nottingham, England began breaking into textile mills and destroying the new-fangled wide-frame looms that were suppressing weavers’ wages and putting so many out of work. Their watchword was, “King Ludd sent me,” and so they became known as the Luddites. They ravaged textile mills throughout Nottingham, Yorkshire and Lancashire before London dispatched several army regiments to guard textile mills, and passed the Frame Breaking Act in 1812 making destruction of looms a capital offense.
Some believe today we stand on the precipice of another industrial revolution (the 4th!) that is every bit as dramatic and impactful as the one the Luddites were struggling with in early 19th century Britain. KPMG claims that an estimated capacity equivalent to 130 million workers’ work will be automated by 2025 (KPMG, 2017). A sizeable number of economists believe that much of the job loss in the US and Western Europe in recent years has been more to do with automation than offshoring or unfair competitive practices. Indeed, there are indications that automation is putting a dent in outsourcing revenues for providers.
Clearly, something big is happening. And the consensus among providers is, we ain’t seen nothin’ yet.
But if this revolution in automation – AI, machine learning, RPA, etc. – is already underway, then why haven’t we seen skyrocketing productivity? In fact, according to FRED, non-farm business productivity has been flat, or erratic at best since 1990. Some consultants have suggested that the problem is some consulting firms biting off more than they can chew – trying to automate processes that are really too complex to automate, or that the focus has become lost in technology, forgetting process altogether. Others have suggested that it’s too early for us to see the real gains from automation, that productivity will eventually catch up. An example might be when a sales team starts out with a new CRM system, and for some time must manually enter contacts into the system; there’s a period where the new tool is labor-intensive with little return. Others point to external factors, such as an overabundance of college degreed workers in the more advanced economies.
It could simply be we’re all a bunch of slackers. But that would include our new robotic overlords too.
Is the problem that we’re not measuring productivity correctly? Traditionally, productivity – efficiency – is measured as Δ output/Δ input, but in an age where more and more workers are white collar workers, what’s output? (Isn’t that the very point of automation, to free up human labor to focus on more complicated tasks?) The Bureau of Labor Statistics defines productivity as “the ratio of the output of goods and services to the labor hours devoted to the production of that output,” but again, this is a definition best suited to manufacturing. (BLS, 2017) And inputs in economics refers to capital and knowledge or technological change as well as labor. Is hours per labor input, or the cost of labor, really a full measure of inputs for productivity?
These are academic arguments and as yet, unresolved, but the impact now on clients is very real and with implications for their future. It’s not just an issue of what processes to automate, but – and this is where consultants can really add value, above and beyond technology – it’s about helping clients fundamentally rethink their workforce paradigm, how and why they employ (and deploy) human beings and machines. Efficiency is always a key goal, but it’s not simply 21st century Taylorism. It’s maximizing the humanity of the production process remembering that production – business – is all about humans, both those on the input side (employees) and the output side (customers). That was true in 1811, and is still true in 2017.
“Cognitive Automation, the Dawn of Digital Labor,” (2017). KPMG; Retrieved from: https://advisory.kpmg.us/managementconsulting/issue/operative-effectiveness/digital-labor.html?gclid=CjwKEAiA0fnFBRC6g8rgmICvrw0SJADx1_zAqHwPrbGAQKW43tEVgqfG8XVNCZgloAIo8-aRG51UbhoC0Vfw_wcB
“Labor Productivity and Costs,” (2017) Bureau of Labor Statistics (BLS); Retrieved from: https://www.bls.gov/lpc/faqs.htm
“Slow…labor…productivity…growth,” (2017). The FRED (Federal Reserve Bank of St. Louis Economic Data) Blog; Retrieved from: https://fredblog.stlouisfed.org/2017/02/slow-labor-productivity-growth/