Consumer redlining at Dollar General

“We are awakening to a dollar-store economy,” the New York Times declared in 2011, a culture of fear-induced bargain hunting spurred by the 2008 market meltdown and jobless recovery. More than ever before, anxious consumers are looking to stretch a buck due to the shrinking middle class and a widening gap of economic inequality. Dollar stores thrive in climates of economic uncertainty. In fact, their success is built on the death of the American middle class.

Yet all Dollar General stores are not equal. That was my conclusion in a recent article, after conducing six months of ethnographic fieldwork investigating service relations between dollar store managers, low-wage workers, and their customers. Of the nineteen stores in the district I worked in as a low-wage sales associate, three standout stores emerged as the very worst. Conditions there were dirtier and more hazardous than the rest, with barren shelves, slower customer service, and a tense atmosphere for those who worked and shopped amidst the squalor. I identified these Dollar General locations as consumer redlined stores. 

Identifying consumer redlining

Consumer redlining is a concept first introduced by sociologist Adam Reich. In his 2016 analysis of online Wal-Mart Yelp reviews, Reich found that stores located in lower-income communities of color consistently received worse ratings than those in more affluent, whiter locations. Consumer redlined stores were described by shoppers as the “worst,” “nasty,” “unorganized,” “ghetto,” and having abysmally slow customer service. By contrast, stores located in white communities were commonly described using language such as “typical,” “friendly,” and “smaller.” His findings demonstrated a hidden consequence of Wal-Mart’s expansion into more racially diverse communities. However, he was unable to explain why the racialized gap existed in the first place. 

My own in-depth ethnographic study of Dollar General forges connections between precarious retail work, algorithmic management systems, and consumer redlining. I argue that consumer redlining—evidenced by disparities in payroll, customer service, maintenance, and more—is grounded in cost-reducing strategies implemented by corporate management’s embrace of algorithmic systems of control. In addition, I document how consumers’ constant grievances impacted workers, shedding light on employee-customer relations at redlined stores.

“Flexible” scheduling 

A significant factor contributing to Dollar General’s consumer redlining was their computer-based labor management system. This program standardized “flexible” scheduling across all Dollar General locations. It dictated the number of paid labor hours each store was permitted to schedule each week. The manager, the only salaried employee in each store, had the burden of filling the scheduling gaps. While understaffing dollar stores across the board ensured profit, in my research, Dollar Generals located in poorer neighborhoods, particularly neighborhoods of color, received less paid labor hours. This appeared to be based on the lower purchasing power of the surrounding community. In other words, dollar stores located in areas where customers could afford to buy more received more staffed hours, while those located in areas where customers bought less received lesser hours. 

Erratic work schedules took a physical toll on workers, while the instability in week-to-week earnings ensured a perilous monetary existence. As a result, workers (mirroring the poor customers they serviced) often relied on food stamps and other forms of Public Assistance to get by. According to DG’s Customer Survey, out of the nineteen stores in the district, my fieldsite store was consistently ranked last. In fact, my fieldsite store remained in the “Did Not Meet” customer satisfaction category for my entire six months of research, with the tasks listed in the “Performed Well” column remaining blank. In the “Needs Improvement” column, the lowest satisfaction score was neatness (16.3%), followed by cleanliness (19.4%), overall satisfaction (25.8%), and fresh products (27.3%).

The Southside Dollar General store had the second lowest overall Customer Satisfaction Survey score in the district at 33% and the Westend Dollar General had the third lowest at 35.6%. Including my fieldsite store, these three locations were only about a mile apart from each other and had similar neighborhood demographics. According to census tract data, not only were the majority of their inhabitants in severe poverty (68–90% earning less than $10,000 per year), but they had the highest proportion of black residents (10–26%) in the DG district. Regular customers assured me that the bare shelves, filthy aisles, and a never-ending register line at my own fieldsite store were not a recent occurrence, but had been an ongoing problem for as long as they could remember. 

Many excerpts from my fieldnotes documented how irritated local shoppers were with the inferior store conditions. For example, in two days my fieldsite store received twelve phone complaints from customers about the long register line. As a result, the district manager sent an email instructing all employees to operate the registers during peak business hours, 11 AM to 3 PM. In addition, we are forbidden from taking our meal break during these hours.  However, the store only has two functioning cash registers and was typically staffed by just two workers—a lower-level sales associate (myself) and a manager on duty. It was physically impossible to stay up front operating the register and also accomplish the list of other required work tasks in the store. Given that corporate was unwilling to divvy out more labor hours to staff two cashiers per shift, the problem of a long register line persisted throughout my fieldwork. In fact, nothing was ever done to directly address or permanently remedy any of the service issues our store consistently suffered with. Whatever “power” shoppers believed they had over Dollar General’s organization of work when they complained to management or filled out the Customer Survey, was nothing but an illusion.

Degradation of retail work

Labor hours were a corporate decision based on computer calculations intended to ensure that every Dollar General remained profitable. This labor supply system undermined frontline managers’ authority, and workers’ ability, to resist the week-to-week unpredictable scheduling.  It was not a within-store decision. Therefore, my findings demonstrate contributing factors that further lead to the degradation of retail work. 

This labor management also made it impossible to remedy the source of customer complaints at consumer-redlined stores: systemic understaffing. It was dollar store employees who were blamed for substandard store conditions and viewed as “disposable” while imperiled within the squalor. While lean labor strategies and workplace optimization systems have sought to align retail staffing with real-time consumer demand, my findings demonstrate how just-in-time scheduling software has not been a foolproof system of organization. When staffing is lean, fewer workers face increased demands combined with work speed-up, undermining customer service. Cutting corners on staffing drives down productivity, making unpredictable schedules and its resulting high turnover counterproductive, and generating paltry customer service.

These findings are alarming, given that Dollar General’s financial growth model has been reliant on rapid store openings. Indeed, the mere presence of a particular amenity within a neighborhood is an incomplete indicator of neighborhood investment/divestment. The same organization in different neighborhoods can actually vary quite dramatically. This more nuanced realization raises concerns that not just retailers, but businesses, organizations, and institutions, while appearing similar on the outside, may look quite different across neighborhoods.

Read more

Tracy Vargas. “Consumer redlining and the reproduction of inequality at Dollar General” in Qualitative Sociology 2021.

Image: Keith C via Wikimedia Commons (CC BY-SA 2.0)