Part 3: Factors that Drive the Pace of Automation
This series of blog posts widens the focus on the impacts automation will have on overall employment in in Greater Minnesota, and in particular, West Central Minnesota. Part Three analyses the major factors that may drive the pace of automation in Greater Minnesota.
Five Driving Factors behind the Adoption of Automation
Full adoption of automation technology will take decades. But as the McKinsey’s A Future that Works report notes, the pace of automation rests on five sets of factors dealing with technical feasibility, various kinds of costs and the openness of society and government to these developments. We turn now to briefly consider how a rural setting may impact each of these factors.
1) Technical Feasibility: Particular technologies must already exist and have a proven track record for firms to rapidly apply them to work activities. Various kinds of automated vehicles, robotics, and sorting machinery are available for adoption and have been used in several rural settings. Though fully automated automobiles and trucks are still being tested, firms appear eager adopt them in the decade ahead. In contrast, technologies that can sense emotion and engage in social reasoning are much further behind—hence the lower potential for automating tasks in education, social services and management.
One might assume that technical feasibility would be neutral with regard to regional application. But different areas can offer some advantages. For example, the relatively uncongested airspace of rural settings have made them ideal places to test and implement automated delivery systems, as seen in England and China.
2) Cost of Developing & Deploying Automation: Businesses and organizations will only adopt technology if they can afford it and it’s benefits are large. Given that hardware to automate mechanical processes and large-scale software upgrades are often prohibitively expensive, automation favors larger firms that have access to capital and can envision high levels of potential cost savings in the near future. Thus the economic size of the firm and the potential for return on technological investment are key considerations.
As the tables below show, the Metro area (region 11) has a far higher number and greater percentage of large firms (50 or more employees) than West Central Minnesota (region 4). As these firms have more capital to invest and greater numbers of workers, the business case for adoption is stronger in the Metro and weaker in rural Minnesota.
However, modest software and selective robotic upgrades are generally cheaper to deploy and would seem a better fit for the many firms and government organizations across Greater Minnesota with smaller payrolls and profit margins. Thus, in addition to a slower adoption pace, the scale of software and mechanical automation adoption will be more modest outside the metro area.
But within rural settings, regional manufacturing centers with larger capital and work forces will likely upgrade sooner. In fact, automation adoption by large mechanized industries across the country have already dampened the need for less-skilled workers, as the skill level required of new, computer-centered factory jobs means significant post-high school training for job seekers.¹
3) Labor Market Dynamics: The supply and demand of labor, as well as the skill level of labor, determine how expensive it will be to replace labor with automation. The prevalence of lower wage, non-union jobs across outstate Minnesota further suggest that rural areas would automate more slowly. Looking back to regional employment across job sectors (Table 1 in Part 2), we see that employers in West Central Minnesota consistently pays less than the state average, with a $14,000-$19,000 differential found in the Production area and nearly the same differential in the Transportation and Warehouse sector. Again, with rural firms having fewer employees per firm, automation adoption appears less likely to generate significant savings from reduced labor costs.
However, labor shortages in rural Minnesota create a major push for automation. In a 2012 report (and in follow up reports), DEED reported significant shortages of available workers across nine critical areas of employment.² As the figure below shows, the prevalence of difficult-to-fill vacancies seems more acute in Greater Minnesota than in the metro area. Importantly, the share of difficult-to-fill vacancies in production areas of employment, particularly skilled manufacturing like machinist and computer-controlled machine operators, are far greater (68%) than in nursing and health (32%) or engineering (51%). Thus the low demand by workers for these jobs, as well as a high levels of skill-to-job mismatch, will work to counter the influence of lower wages in slowing automation. If rural businesses cannot find the workers they need, then automation may be a cheaper solution than relocating to other areas of the state, the country or overseas.
4) Other Economic Benefits: The benefits of automation extend beyond the core factors of the costs of technology and labor. In many areas, automation increases profit by reducing errors in production, increasing the rate of production and improving safety. Central to the question of self-driving cars and trucks has been the great potential for improved safety and the more efficient movement of vehicles. Presumably, self-driving trucks would pose lower risks to public safety and thus lead to lower insurance costs for firms. But automation also allows for economic gains through longer drive times (by negating, for example, the regulatory caps for maximum hours per day behind the wheel) and increased fuel efficiency from consistent driving speeds.
Again, the scale of the operations impacts the potential benefits. The gains from safety, production and quality improvements are less likely to matter to smaller firms, while larger production firms would be more eager adopters. This suggests, again, that rural Minnesota is less likely to automate to gain these other kinds of benefits.
5) Acceptance by Government and Society: Last, the McKinsey Global Institute report suggests that automation adoption will depend upon whether government and society approve of the changes. Do labor unions or other associations effectively fight efforts to automate? Are local and especially state governments receptive to changing laws and regulations to facilitate technological adoption? (For example, self-driving vehicles and drone delivery operations will need changes in insurance regulation, legal rules for determining responsibilities for accidents and regulation of low-level drone flight paths.)
Would rural areas be more accepting of automation than metro areas? Rural areas have an extraordinarily long history of automation in farming and mining, as well as the loss of small town businesses from major retail firms like Walmart. Beyond history, rural areas are traditionally averse to restrictive regulation and they lack active labor organizations that might oppose certain forms of widespread automation. While small towns and rural areas vigorously opposed changes to the status quo in farm program, as well as the closure of post offices, the reluctance to regulate suggests business driven automation may not encounter significant popular resistance.
Rural Factors of Distance and City Vulnerability
Two other forces in rural areas are likely distinguish the nature of rural automation adoption from that in large metro areas, though their influence on the pace of adoption is unclear.
Distance: Large parts of greater Minnesota have long distances between centers of activity. The relative lack of density of people and firms should impact the rural adoption of automated vehicles and delivery systems. As a study of the potential for self-driving vehicles in Kings County in Washington state noted, rural areas of the county would not benefit from reduced congestion that could come from the mass use of self-driving cars. However, the greater travel distances may lead more well off residents to become eager adopters of self-driving cars and embrace robotic service delivery.³ The distance of rural industries and jobs from media centers also means that automation will go largely unnoticed by people outside the immediate area.
“One-Industry” Towns: Last, as noted above, larger scale firms have a greater incentive to automate more job tasks. While Greater Minnesota has less large-scale firms, smaller towns do rely more heavily on one or two majors industries for economic vitality. The arrival of automation may thus have a larger, more disruptive impact on some rural communities than found in larger metropolitan areas. In many rural communities, significant workforce reductions in even modest size businesses can have a powerful impact on the viability of downtown business area. So while metropolitan areas will experience more rapid, wide-spread automation, but the impact on community vitality may be greater in the vulnerable towns beyond the Metro Area.
Conclusion: Rural Strengths of Place & Creativity.
This series has suggested the following patterns are likely to lead to a slower pace of automation adoption across Greater Minnesota, compared to the metro area.
- Lower wages and a lack of economies of scale found in the smaller business and organizations across Greater Minnesota reduces the profit potential from automation and will slow the pace of its adoption.
- The persistent difficulty in finding skilled labor ultimately makes significant automation inevitable, even if at a slower pace.
- Given that automation is proceeding quickly within the farming and mining sectors, rural areas will likely adopt automation technologies that work well for sparsely populated areas, such as drone delivery and self-driving vehicles.
- Last, cities and regions reliant upon just a few major producers may be vulnerable, as even modest job losses from automation could weaken overall economic vitality.
Development Planning: As automation moves forward, the approach of rural communities to economic development will need to adapt. The traditional strategy followed by many development authorities to bring new, major industries to their communities will lose some of its appeal as these industries bring fewer jobs with them. Opponents of the proposed PolyMet mine in Hoyt Lakes, for example, consistently cite how few jobs the new facility will create, given the potential environmental risks from copper-nickel mining.
Automation does strengthen the case for attracting and developing creative and place-centered manufacturing and tourism. The work of artists and other creative producers, along with the development of tourist destinations, is likely to create higher numbers of jobs that can only be partially automated. In addition, the booming industry in renewable energy also looks much more attractive, given the need for many workers to build, upgrade and maintain high numbers of windmills and solar facilities, even as some tasks in the renewable field become automated.⁴
Government’s Response: The availability and early deployment of automated vehicles and drones has led many to call upon government policy makers to prepare to assist displaced workers in these sectors.⁵
Of course, the impact of potential job disruption in Greater Minnesota will also depend greatly on how government policy responds to the changing work environment. As with the range of debate over how much disruption automation will create, the range of proposals vary remarkable–from simply amending and expanding job training and education programs, to supporting the temporary “feather-bedding” of jobs in heavily impacted sectors (much like the railroad industry did for workers in decades past), to more radical proposals for a wide-spread minimum income program to offset large-scale losses of meaningful work. Regardless of how aggressive the state and federal response is, it will be critical for Greater Minnesota to speak clearly about the region’s unique needs in these future policy discussions.
Post Script on Future Research – The observations offered in these posts about the potential impact upon Greater Minnesota are tentative and contingent. This reflects that fact that scholars, analysts and developers of automation remain deeply divided over how much job disruption will come from the automation revolution. Regardless, CST hopes these posts will spark interest among some to explore automation’s impact in more detail and to begin conversations about current and upcoming changes that will arrive, even if slowly, to rural Minnesota. Some topics that would be valuable for researchers and development organizations to explore include:
- Studying the automation plans of Minnesota firms, especially through a survey of firms in the West Central region and Greater Minnesota.
- Exploring how automation may impact the provision of government services and distribution of government related jobs.
- Examining how automation might alter attitudes of rural residents towards commuting longer distances and their eagerness to adopt self-driving vehicles.
- Exploring attitudes of residents towards autonomous delivery of “at home” services and its potential impact on community stores.
- Examining possible government responses to employment dislocations and the public’s receptivity towards a range of policy options.
¹ Casselman, March 2016² Department of Employment and Economic Development, 2012
³ Brett, University of Washington, 2016
⁴ The New York Times, April 2017
⁵ Rivlin, Brookings; Brynjolfsson & McAfree, The Second Machine Age
Roger Rose is Center for Small Towns Director and an associate Political Science Professor at the University of Minnesota – Morris.