O’Reilly Automotive: Where should the next stores go?
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Student case | Information cutoff: April 24, 2024
On April 24, 2024, O’Reilly Automotive reported first-quarter comparable-store sales growth of 3.4%, following 10.8% in the year-earlier quarter. The company reaffirmed its plan to open 190–200 net new stores during 2024. The decision facing a hypothetical planning committee is how to use the remaining opening capacity: continue the planned pace across dense existing clusters and contiguous markets, concentrate more openings in established clusters, or selectively slow openings until better evidence is available.
This is a classroom planning assignment, not a disclosed O’Reilly decision or internal review. Assume the committee can reallocate the remaining pipeline and request market-level data, but no candidate-site forecasts have been supplied. The challenge is to evaluate the value of another location to the whole network, not simply to forecast its sales.
A growth plan built around a network
O’Reilly opened 186 net new stores in 2023—166 in the United States and 20 in Mexico. Its 2024 plan called for 190–200 net new openings and was intended to deepen penetration in existing markets and extend into contiguous new markets. In the first quarter, O’Reilly opened 37 stores across 20 U.S. states and Mexico. Separately, the January acquisition of Vast Auto added 23 Canadian stores. The company reported 6,217 stores across the United States, Puerto Rico, Mexico and Canada at March 31. The acquisition and organic openings are distinct sources of network growth. [P1, P2]
Management says it selects sites with an eye to geographic clusters, which can support management, advertising and distribution economies. Its stated factors include population and vehicle demographics, repair facilities, competition, traffic, site economics, and the financial performance of adjacent O’Reilly stores. A close-by store might improve customer access and route density; it might also take sales from an existing O’Reilly location. The company does not disclose the weights it assigns to these factors or the forecasts for proposed sites. [P1]
The distribution footprint is substantial: 30 regional distribution centers (DCs), about 12.6 million operating square feet and an average of 152,000 stock-keeping units at year-end 2023. O’Reilly said its DC network could support 150–300 additional U.S. stores, with planned DC relocations in Springfield and Atlanta. Its system includes frequent DC deliveries, metropolitan city-counter deliveries and Hubs that redistribute products and provide stores access to expanded assortments. This is management’s estimate of system capacity. It does not establish that every market has suitable route economics, that capacity is costless, or that a particular new store will earn an attractive return. [P1]
The latest results leave room for competing explanations
First-quarter sales increased 7% to $3.98 billion. Gross margin was 51.2%, compared with 51.0% a year earlier; selling, general and administrative expense was 32.2% of sales versus 31.7%; operating margin was 18.9% versus 19.3%. Comparable sales grew 3.4%, after 10.8% in the year-earlier quarter. The comparable-sales measure covers U.S. stores open at least one year and includes online ship-to-home and pickup-in-store sales, subject to the company’s stated exclusions. [P2]
These figures describe the consolidated business, not the economics of stores opened recently or proposed for the rest of 2024. Slower comparable growth could make management more cautious about committing capital. It could also reflect a normalization from an unusually strong comparison, while a well-chosen new store could serve customers who are not well served today. Rising SG&A as a share of sales may warrant attention, but the public results do not show that openings caused the change.
O’Reilly reaffirmed 2024 guidance that included 3–5% comparable-sales growth, $900 million–$1.0 billion of capital expenditures, and 190–200 net new stores. Guidance describes the company’s current plan and expectations; it does not demonstrate the return on each location or settle how the remaining openings should be allocated. [P2]
The decision is about incremental network value
A store’s gross sales are only one part of its value. A new location could attract customers and professional repair accounts who otherwise would shop elsewhere, improve parts availability, or make nearby delivery routes more productive. Better service convenience may also matter in auto-parts retailing. But the opening could shift demand from existing O’Reilly stores, add lease, staffing and inventory costs, or require extra delivery capacity. A store that appears attractive alone may be less attractive after accounting for effects on nearby stores and the network.
The research offers mechanisms to investigate, not O’Reilly-specific estimates. Holmes’s study of historical Walmart expansion models density benefits alongside cannibalization and highlights how distribution geography can affect store-location value. Walmart’s formats, data and period differ from O’Reilly’s, so its estimates are not inputs for this decision. Pancras, Sriram and Kumar examine retail expansion, site selection and cannibalization in one fast-food chain; the full paper was not accessible for this case, and its reported abstract results should not be transferred. Sen and coauthors study convenience in auto-parts retailing, but only the abstract was available here. It raises service and customer-value questions without establishing the magnitude of any O’Reilly effect. [A1–A3]
The public record does not show the proposed locations, expected sales ramps, store-level contribution, overlap with existing trade areas, local competitor responses, marginal route costs, or capacity by DC and Hub. It also does not establish how Canadian integration, staffing, or the planned DC relocations affect the remaining pipeline. You will need to state which of these uncertainties should determine the pace.
Three planning paths
| Path | Why it could create value | What could make it fail |
|---|---|---|
| Maintain the 190–200 pace and allocate across clusters and contiguous markets | Preserves the stated growth plan and can extend access while building density over time. Suitable sites may be lost if deferred. | The plan total does not show that each marginal site clears an economic hurdle. Simultaneous openings could stretch staffing or route capacity, and new sales may displace incumbent stores. |
| Tilt toward dense existing clusters | Nearby stores may reinforce customer access, advertising and delivery density, while O’Reilly can build on an established presence. | Greater overlap may raise cannibalization; the network-capacity range does not prove the economics of a specific cluster or route. |
| Slow selectively and stage openings | Allows more evidence on store cohorts, local overlap and service needs before committing to less certain markets; capital and execution capacity remain available. | Waiting can forfeit attractive sites, delay service improvements or give competitors time to deepen their local presence. A pause without a learning plan may simply defer the decision. |
The committee need not choose one approach for every market. It can recommend a portfolio, but should explain how a site earns a place in that portfolio and what evidence would lead to reallocation.
Decision assignment
Prepare a recommendation for the hypothetical planning committee:
- How should O’Reilly allocate the remaining 2024 opening pipeline among dense clusters, contiguous markets and a selective slowdown?
- How would you estimate each opening’s incremental value to the network, including effects on incumbent stores, customer service and distribution?
- What counterfactual would you use to distinguish truly incremental demand from sales transferred within O’Reilly or from competitors?
- Which data and decision gates should management require before opening, scaling a market cluster or deferring a site? What result would change your recommendation?
Do not infer company-specific coefficients from the academic studies or treat the DC capacity range as proof of market-level economics. Any numerical thresholds or hypothetical inputs must be labeled as assumptions. Separate reported facts, management statements and your own analysis. No post-cutoff outcomes are part of the case.
Sources and conventions
Company facts are from O’Reilly’s 2023 Form 10-K and its April 24, 2024 first-quarter results release [P1, P2]. Competitor filings provide dated footprint context only; store counts across companies and fiscal periods are not directly comparable and are not used as market share or service-capacity measures [P3, P4]. Academic references are Holmes (2011), “The Diffusion of Wal-Mart and Economies of Density,” Econometrica 79(1):253–302; Pancras, Sriram and Kumar (2012), “Empirical Investigation of Retail Expansion and Cannibalization in a Dynamic Environment,” Management Science 58(11):2001–2018; and Sen et al. (2023), “Convenient = competitive? How Brick-And-Mortar Retailers can cope with Online Competition,” Review of Managerial Science 17(5):1615–1643. Version, access and reading-depth details are in the instructor research packet at site/research/o-reilly-automotive-inc/source-register.md.