By: Mike Shields, Mohona Siddique, and Andrew Strohmetz
Date: October 7, 2020
Automation in Greater Philadelphia's Food Economy
For the first installment of the Automation Nation series, we take a closer look at the automation potential within Greater Philadelphia’s food economy. The Economy League has deep expertise about the regional food economy including, its growth and the impact of the pandemic on its future. As discussed in the 2019 Good Eats report, Greater Philadelphia’s food-based businesses fuel extensive commercial activity and create thousands of jobs in the region. Yet many of these jobs offer minimal pay and few sustainable career trajectories. Since many occupations within the food economy are also characterized by a high number of routinized daily tasks that are susceptible to automation, the sector may act as a benchmark for comparison among other regional industries.
The Leading Indicator
With Greater Philadelphia’s food economy encompassing roughly 15 percent of the region's total employment as of 2019 [1], we took a closer look at the automation potential of food economy occupations by sector. Using an “automation potential” probability score—developed by Brookings and the McKinsey Global Institute—we calculated the average automation potential within each food economy sector and compared it with the metropolitan region as a whole (see Figure 1).
FIGURE 1
NOTE: Data were obtained from Brookings’ 2019 Automation and Artificial Intelligence: How Machines are Affecting People and Places Report.
Figure 1 demonstrates that the region’s food economy has an overall higher-than-average susceptibility to automation. When de-aggregated by sector, automation potential is exceedingly high in the regional food economy’s Processing and Hospitality sectors, higher-than-average for the Distribution sector, and below average for the Production, Retail, and Waste sectors.
To further elucidate these automation potential scores, Figure 2 illustrates the spectrum of food economy occupations within each sector by their individual automation potential score.
FIGURE 2
NOTE: Data were obtained from Brookings’ 2019 Automation and Artificial Intelligence: How Machines are Affecting People and Places Report. "Low" automation potential is any occupation with a probability less than 33.34%, "Medium" automation potential is any occupation with a probability between 33.34% and 66.7%, and "High" automation potential is any occupation with a probabilty greater than 66.7%.
Occupations colored blue have a low automation potential, meaning that daily tasks are less likely to be replaced, diminished, or redistributed due to the introduction of new technologies. Most of these occupations are specialized because they require advanced educational credentials, or they are higher-tiered management or supervisory positions. Some outliers include the Refuse and Recyclable Materials Collectors in the Waste sector and the Laborers and Freight, Stock, and Material Movers in the Distribution sector. The commonality among these occupations is that their daily tasks are not routinized enough to be predicted and replicated by machines. Machine learning and artificial intelligence have not reached the point where they can conduct scientific experiments on crop rotation methods, nor are their computer programs that can navigate the intricacies of workplace disputes and conflicts. Even the refuse and recyclable materials collectors must consistently adapt to changes in their daily routine like new weather conditions, new routes, changes in the weight or size of their daily pickups, or changes to their drop-off sites. The variability of their daily tasks makes it difficult for automation.
Occupations with medium automation potential are colored purple and include a variety of jobs. Unlike the low automation potential occupations, medium automation potential occupations have lower educational requirements and less variability in their daily tasks. In fact, some of these occupations have already been altered by the introduction of technology in their daily work. It was not too long ago that cashiers were required to punch-in item prices, be aware of all sales and markdowns, and keep track of inventory. The introduction of automated scanners and new computer programming diminished the tasks of the human cashier to primarily assisting with checkout and bagging. Many of these occupations may further be altered by new technologies.
Finally, the high automation potential occupations are colored red. Many of these occupations can be found in the Processing, Distribution, and Hospitality sectors. These occupations only require foundational-level skillsetsand minimal educational training. Their daily tasks also have a higher chance of being routinized within minimal variability. These occupations face the greatest risk of seeing new technologies replace, diminish, or redistribute their daily tasks. Greater Philadelphia's food economyis one of the largest employers within the region. Its high automation potential signals that many of the foundational skilled and entry-level occupations are highly susceptible to being upended by new technologies. Thousands of employees within our region are at risk or being replaced or downgraded because of the adoption of a new technology. In this time of economic upheaval, there is an opportunity for the emergence of new workforce development strategies that will alleviate the burden of automation.