Measuring the impact of automation is a critical starting point for a community or company. Determining the potential job and wage losses and gains in a region matters obviously to the community’s economic development and political leadership. It matters as well to company’s considering locating in a region—they need to understand the economic vitality of the marketplace but also the economic opportunity in targeted industries. The Montrose Group, LLC developed the Montrose Automation Index to measure the job and wage impact of automation. The Montrose Automation Index is relatively simply- a region’s occupations are research from federal government, U.S. Department of Labor, sources to determine the number of these occupations and the wages they pay. Those region’s occupations are then compared to the over 600 occupations that Professors Carl Benedikt Frey, and Michael A. Osborne of Oxford University’s outlined in their landmark study, The Future of Employment: How Susceptible are Jobs to Computerisation?, September 17, 2013.
The Montrose Automation Index Score was generated out of 100 points by subtracting from 100 the percentage of wage loss for a region. The higher the score, the better the city will fare against Automation in terms of wage loss. Wage loss is the critical measure as it keeps the focus on high-wage jobs to a larger extent. The Montrose Automation Index means that a city with a higher score is positioned better with high-wage jobs that are less likely to be automated than a city with a lower score. The United States has a Montrose Automation Index score of 70.42 which is considered the average score. The table below illustrates the Montrose Automation Index for Ohio’s major cities. Dayton has the highest score and Youngstown the lowest.
Dayton’s winning score is clearly related to the strong role of Science, Technology, Engineering and Mathematics (STEM) occupations in the region. Dayton has a higher per capita of STEM jobs than any other city in Ohio and benefits from the location of Wright Patterson Air Force Base, the U.S. Air Force Research Lab and other technology companies associated with those defense related industries. It is worthy of note that no Ohio city scores as high as the national average on the Montrose Automation Index so the party should not last too long for any major city in the Buckeye State.
Unless checked through economic development strategies and/or market changes, the impact of automation on the Buckeye state could be devastating. As the table below illustrates, larger cities such as Cincinnati, Cleveland and Columbus will see the largest wage loss—although they by far have the largest total wage pot. Columbus and engineer heavy Dayton will fare the best under this analysis while Youngstown will be impacted the worst with a 40% wage loss from automation.
The table below outlines the top ten occupations by wage-loss that will be impacted by automation in Dayton, Ohio. 507 occupations were reviewed in Dayton, Ohio for the impact automation may have. The occupations constituted 356,040 jobs providing a total mean wage for Dayton of $27,648,610. Automation, according to the Oxford University study, in Dayton is slated to impact 194,244 jobs and create an annual wage loss of $ 9,972,253 creating a regional wage loss of 36%.
The Montrose Automation Index also permits a region to look at which occupations will be impacted and how the region will be impacted by the wage loss from automation. The chart below provides such a list of top jobs that could be lost to automation ranked by the highest paid in the region. As will be discussed later, these high-wage occupations are previously untouched by past automation that are now in jeopardy based upon computer hardware and software developments involving AI and machine learning.
When this happens is a matter of prediction. Most analysts see the brunt of the automation impact occurring over the next decade. A couple important notes to discuss the limits of the Montrose Automation Index. It does not and cannot predict how the impact of automation can be limited by economic development and market strategies designed to address this challenge. It also does not measure the impact of a growth in a new industry or increased manufacturing jobs driven by public policy measures or market conditions. Finally, it also does not take into account policy or technology conditions that could slow the implementation of automation. That being said, the Montrose Automation Index should be a wake-up call for all regions and states.