WARN Act Layoffs in Peru, Indiana

Analysis: Layoffs in Peru, Indiana

# Economic Analysis: The Layoff Landscape in Peru, Indiana

Overview: Scale and Significance of Workforce Displacement

Peru, Indiana has experienced meaningful workforce disruption over the past two decades, with 15 WARN (Worker Adjustment and Retraining Notification) notices affecting 671 workers. While this figure may appear modest compared to larger industrial centers, the impact on a small city must be understood within the context of Peru's economic base and population. The concentration of layoffs among a handful of major employers means that individual plant closures or substantial reductions represent significant shocks to the local labor market.

The 671 affected workers captured in WARN filings represent only a partial picture of layoff activity. WARN notices are filed for mass layoffs of 50 or more workers, meaning smaller reductions escape official tracking. Nevertheless, the data provides a reliable indicator of major structural economic changes affecting the community. For Peru, a city with limited economic diversification, the loss of nearly 700 jobs through major employer contractions points to vulnerability within the local industrial base.

Schneider Electric's Dominance and the Utilities Sector Collapse

The most striking feature of Peru's layoff pattern is the overwhelming presence of Schneider Electric, which alone accounts for 382 workers across three separate WARN notices. This represents 57 percent of all workers affected by major layoffs in the city over the analysis period. The company's impact is further underscored by nine subsequent revision notices spanning from June 2019 through February 2020, all reporting zero additional workers. These revisions indicate ongoing adjustments to an initial reduction announcement—a pattern common when companies modify implementation timelines or ultimately avoid some planned cuts.

The revision notices themselves merit analytical attention. Rather than indicating new layoffs, these filings represent administrative adjustments to previously announced reductions. The frequency of revisions (nine over an eight-month period) suggests uncertainty in Schneider Electric's operational planning or possible negotiations with union representatives or local officials over the pace and scope of workforce reductions. Such volatility creates particular hardship for affected workers facing extended periods of uncertainty.

The utilities sector dominates Peru's WARN notice data, accounting for 11 of 15 notices and 321 of 671 workers affected. This concentration reflects the sector's historical importance to Peru's economy. However, the utilities category masks significant compositional change. Schneider Electric, a multinational manufacturer of electrical equipment and automation solutions, operates manufacturing facilities rather than traditional utility infrastructure. The classification suggests that Schneider Electric produces components for utilities or power distribution systems rather than generating or distributing electricity directly.

This distinction matters because it points to structural challenges in manufacturing supply chains serving the energy sector. As utilities increasingly automate operations, digitize infrastructure management, and consolidate operations, demand for certain manufactured components may decline. Schneider Electric's reduction of 382 workers suggests overcapacity in Peru's facility relative to current market demand, a pattern consistent with broader automation trends in industrial manufacturing.

Secondary Players and Manufacturing Diversification

While Schneider Electric dominates the data, two other manufacturers also filed significant WARN notices. Trellborg Automotive, a Swedish-headquartered automotive parts supplier, filed one notice affecting 180 workers, making it the second-largest single layoff event in Peru's recent history. This reduction represents approximately 27 percent of all workers affected by WARN notices.

Heraeus Electro-Nite Co., which specializes in advanced materials and components for automotive, industrial, and dental applications, filed one notice affecting 109 workers. Together, Trellborg Automotive and Heraeus Electro-Nite Co. account for 289 workers, or 43 percent of total WARN-reported layoffs. This means that manufacturing represents Peru's entire layoff footprint—no retail, healthcare, professional services, or other sectors appear in the data.

The presence of two automotive suppliers (Trellborg Automotive and Heraeus Electro-Nite Co.) alongside an electrical equipment manufacturer (Schneider Electric) reveals Peru's economic specialization within industrial supply chains. This is characteristic of mid-sized manufacturing cities across the Midwest, which historically developed as satellite production centers for larger automotive and industrial equipment manufacturers. The geographic clustering of complementary suppliers created advantages in transportation costs, labor market depth, and supply chain coordination.

However, this same specialization creates vulnerability. When automotive production contracts, multiple suppliers feel the impact simultaneously. When manufacturers consolidate or relocate facilities, entire networks of dependent suppliers face reduced demand. Peru's layoff data suggests exactly this pattern: separate companies reducing workforce capacity at different times, likely responding to common upstream pressures in automotive manufacturing and industrial equipment markets.

Temporal Patterns and Economic Cycles

The temporal distribution of WARN notices reveals important patterns about Peru's economic trajectory. Single notices appear in 2008, 2009, 2017, and 2018, with one in 2019. This sparse distribution across nearly a dozen years indicates that major layoffs hit Peru episodically rather than continuously. The 2008 and 2009 notices align with the global financial crisis and subsequent recession, when automotive production and industrial demand contracted sharply.

The clustering of Schneider Electric revisions between 2017 and 2020 suggests a separate, company-specific adjustment cycle distinct from broader economic cycles. The initial reduction notice preceded the revision cycle, indicating that the company announced major workforce reductions, then spent nearly two years refining implementation details through repeated WARN revisions.

Notably, the analysis period (which appears to span roughly 2008-2020 based on the data provided) includes both the deep 2008-2009 recession and the subsequent recovery period through 2019. The relative scarcity of WARN notices outside the recession years suggests that Peru's major employers avoided large-scale layoffs during the moderate economic growth of 2010-2019. This pattern differs from the national narrative of constant disruption and implies Peru may have experienced genuine employment stability during the post-recession expansion.

However, the absence of notices in recent years (post-2020) does not necessarily indicate improved conditions. WARN notices track major reductions, but plant closures, automation-driven attrition, and smaller downsizings often escape official documentation. The true scope of Peru's economic transformation is almost certainly larger than the WARN data alone reveals.

Local Economic Impact and Community Vulnerability

The loss of 671 jobs through major layoffs represents substantial disruption for a city of Peru's size. Without current population data, the precise employment impact cannot be calculated precisely, but historical census figures suggest Peru's population hovers around 12,000-13,000 residents. If labor force participation and employment rates approximate state and national averages, the local labor force encompasses roughly 5,500-6,000 workers. This means WARN-reported layoffs affected approximately 11 to 12 percent of Peru's total workforce.

This concentration becomes more severe when considering that these layoffs were not distributed evenly across Peru's employment base. The vast majority affected manufacturing workers, likely concentrated in specific plants and concentrated among workers with specialized skills in production, assembly, and technical roles. For workers in affected plants, the loss rate approached 100 percent, meaning entire departments and work crews faced simultaneous displacement.

The economic multiplier effects extend well beyond the directly affected workers. For every manufacturing job lost, supporting positions in logistics, quality control, maintenance, and administrative functions are also eliminated. Suppliers of materials and services to manufacturing facilities experience reduced demand. Commercial establishments relying on manufacturing workers' consumer spending face declining customer bases. Property values in neighborhoods surrounding major manufacturing facilities may decline as neighborhood conditions reflect reduced employment opportunity.

Schneider Electric's 382 workers represent the single largest employment shock. If this reduction occurred at a single facility (which the three separate notices suggest might be the case), Peru lost access to the wages, tax revenue, and economic activity generated by a workforce of that scale. Assuming average manufacturing wages of $18-22 per hour with benefits, the annual wage loss likely exceeded $10 million, with corresponding losses in payroll tax revenue, sales tax collections, and consumer spending.

Regional Context and Indiana's Industrial Challenges

Peru's experience reflects broader patterns across Indiana's manufacturing-dependent regions. The state has long specialized in automotive manufacturing, engine production, and industrial equipment fabrication. As automotive manufacturers increasingly relocate production to lower-cost regions (Mexico, China) or consolidate facilities following mergers and acquisitions, supplier networks across Indiana face cascading pressure.

Indiana's unemployment rates and labor force participation trends suggest statewide manufacturing has contracted significantly since 2008. Cities like Peru, which depend on a small number of large manufacturers for employment, experience greater volatility than more diversified economic regions. A city with substantial employment in healthcare, education, professional services, and retail faces less disruption when any single large manufacturer downnsizes, because the employment shock is distributed across a larger and more varied economic base.

Peru's apparent lack of diversification—the WARN data shows no major layoffs in sectors beyond manufacturing—suggests limited employment alternatives for displaced workers. When Schneider Electric or Trellborg Automotive reduce workforce capacity, affected workers cannot necessarily transition to growth sectors within the local economy. This forces outmigration or extended periods of unemployment and underemployment.

The revision notices from Schneider Electric spanning 2017-2020 suggest the company engaged in extended planning around its Peru facility. The repeated adjustments indicate management revisited its workforce reduction strategy multiple times over eighteen months. Such delays and revisions sometimes indicate company-level negotiations with local economic development authorities, union representatives, or state workforce development programs aimed at minimizing layoff impact. Understanding the drivers of these revisions would require access to company communications and local policy records beyond the scope of WARN data alone.

Peru's layoff experience, while modest in absolute terms, reflects the fragility of manufacturing-dependent communities facing global competitive pressures, automation-driven productivity improvements, and industry consolidation. The concentration of employment among a handful of major manufacturers creates both economic advantages during periods of growth and severe vulnerability during contractions.