First-Half 2026 U.S. & Canada Restaurant Closure Report

By RestaurantData | Published July 2026

RestaurantData estimates that 8,171 restaurant locations closed across the United States and Canada from January through June 2026. This report analyzes that closure activity by state, city, county, metropolitan market, ownership structure, service format, cuisine and operating profile.

Reporting period: January-June 2026 | Geography: United States and Canada | Publication type: Research report

8,171Estimated closures, U.S. & Canada

4,253Chain-affiliated locations (52.1%)

3,918Independent locations (47.9%)

1,039Texas, highest state total

On this page: Key Findings · Ownership · States & Provinces · Cities · Counties · Metro Markets · Service Format · Cuisine · Alcohol Service · Meal Periods · Check Average · Restaurant Size · Operating Indicators · Cross-Tabs · What the File Shows · Methodology · FAQ

Key Findings

RestaurantData.com estimates that 8,171 restaurant locations closed across the United States and Canada during the first half of 2026. The analysis reviews closure activity by geography, ownership structure, service format, cuisine, alcohol service, meal period, size and operating profile.

This publication is part of the RestaurantData Research Center, which organizes the company’s location-level studies, methodology papers and recurring market analyses.

8,171 estimated restaurant closures were recorded during the first half of 2026. The estimate covers locations in the United States and Canada from January through June.

4,253 chain-affiliated locations and 3,918 independent restaurants with no known affiliation closed. Chain-affiliated locations represented 52.1% of the estimate, compared with 47.9% for independent locations.

7,593 estimated closures were in the United States and 579 were in Canada. The United States represented 92.9% of the combined total, while Canada represented 7.1%.

Texas recorded an estimated 1,039 restaurant closures. That was the highest state and provincial total and represented 12.7% of the combined U.S. and Canadian estimate.

The New York-Northern New Jersey-Long Island metropolitan area recorded an estimated 491 closures. It ranked first among records with a metropolitan classification.

Quick-service restaurants accounted for an estimated 4,092 closures. They represented 51.5% of records with a valid service-format classification. Casual and family dining accounted for 2,793 closures, representing 35.2%.

Sandwich restaurants accounted for an estimated 2,120 closures. They represented 26.2% of records with a primary-cuisine classification. Bar food followed with 987 closures, and American cuisine followed with 702.

3,934 classified locations had no alcohol listed. They represented 61.8% of usable alcohol-service records. Full-bar restaurants accounted for 1,791 closures, representing 28.1%.

4,617 closures were in the $4-$15+ check-average band. This category represented 58.2% of records with a usable check-average classification.

3,080 classified closures involved locations with fewer than 25 seats. Restaurants with at least 200 seats still accounted for 1,507 closures, representing 19.2% of records with a seat-count classification.

3,013 of the 4,092 quick-service closures were chain-affiliated. Chain locations represented 73.6% of the quick-service category. Independents accounted for 2,318 of the 2,793 casual and family dining closures, representing 83.0%.

The 8,171 estimate measures location closures, not failure rates. Large states and restaurant categories may produce higher counts because they contain more operating locations. Rate analysis requires an active-location denominator.

What the figure represents: The report measures restaurant-location closures, not bankruptcies or company failures. Individual locations can close following lease decisions, relocations, conversions, ownership changes, portfolio adjustments and permanent cessation.

Market Overview

Measure	First-half 2026 finding
Estimated restaurant closures	8,171
Chain-affiliated locations	4,253, representing 52.1%
Independent locations with no known affiliation	3,918, representing 47.9%
Leading state/province	Texas: 1,039 estimated closures
Leading metropolitan area	New York-Northern New Jersey-Long Island: 491 estimated closures
Largest service format	Quick Serve: 4,092 estimated closures, representing 51.5% of classified records
Largest primary cuisine	Sandwich: 2,120 estimated closures, representing 26.2% of classified records
Largest alcohol classification	No alcohol listed: 3,934 estimated closures, representing 61.8% of classified records

All category shares are calculated from records with a usable classification for the relevant field, so individual table totals may sum below the 8,171 headline estimate. The report does not identify individual restaurant brands.

Ownership structure

Closures were split almost evenly between chain-affiliated and independent locations. The records include turnover across both operating structures rather than concentrating in only one segment.

Location type	Estimated closures	Share
Chain Location	4,253	52.1%
Independent Location	3,918	47.9%

“Independent” means a location with no known chain affiliation in the RestaurantData record. It does not imply that the business had no outside investors, partners or related entities.

Country distribution

The United States accounted for most recorded closures. Canada represented a smaller share. Unless otherwise noted, the geography tables include both countries.

Country	Estimated closures	Share
United States	7,593	92.9%
Canada	579	7.1%

States and provinces

Texas recorded the largest raw number of closures, followed by New York, California and Illinois. These are counts, not closure rates. Large restaurant markets naturally tend to generate larger numbers of openings and closures.

#	State/province	Estimated closures	Share
1	TX	1,039	12.7%
2	NY	543	6.7%
3	CA	391	4.8%
4	IL	356	4.4%
5	NC	302	3.7%
6	PA	296	3.6%
7	OH	285	3.5%
8	FL	249	3.0%
9	MI	235	2.9%
10	WA	228	2.8%
11	ON	219	2.7%
12	NJ	213	2.6%
13	TN	212	2.6%
14	VA	201	2.5%
15	MO	194	2.4%
16	WI	184	2.3%
17	MA	160	2.0%
18	GA	160	2.0%
19	SC	148	1.8%
20	LA	146	1.8%

A rate analysis would require an active-location denominator for every state and province. This report therefore avoids labeling any jurisdiction as “best,” “worst” or most at risk.

Cities with the most estimated closures

Houston led the city-level file, narrowly ahead of New York. City counts are useful for identifying concentrations of market activity, but municipal boundaries vary widely and should not be treated as directly comparable market sizes. Cities are counted as city-state pairs, so identically named cities in different states and provinces are ranked separately.

#	City	State/Province	Estimated closures	Share
1	HOUSTON	TX	119	1.5%
2	NEW YORK	NY	117	1.4%
3	CHICAGO	IL	82	1.0%
4	SAN ANTONIO	TX	70	0.9%
5	LAS VEGAS	NV	60	0.7%
6	BROOKLYN	NY	51	0.6%
7	TORONTO	ON	45	0.6%
8	DALLAS	TX	42	0.5%
9	SEATTLE	WA	40	0.5%
10	PHILADELPHIA	PA	39	0.5%
11	FORT WORTH	TX	39	0.5%
12	AUSTIN	TX	36	0.4%
13	PORTLAND	OR	35	0.4%
14	CHARLOTTE	NC	34	0.4%
15	ALBUQUERQUE	NM	32	0.4%
16	INDIANAPOLIS	IN	32	0.4%
17	EL PASO	TX	30	0.4%
18	VANCOUVER	BC	30	0.4%
19	PITTSBURGH	PA	28	0.3%
20	DETROIT	MI	28	0.3%
21	RICHMOND	VA	26	0.3%
22	NEW ORLEANS	LA	26	0.3%
23	COLUMBUS	OH	25	0.3%
24	NASHVILLE	TN	25	0.3%
25	OKLAHOMA CITY	OK	24	0.3%
25	BALTIMORE	MD	24	0.3%
25	SALT LAKE CITY	UT	24	0.3%
25	MEMPHIS	TN	24	0.3%

City shares are calculated against the combined 8,171 U.S. and Canadian estimate. Oklahoma City, Baltimore, Salt Lake City and Memphis tied for the twenty-fifth position.

Counties with the most estimated closures

County totals add a second geographic lens. Harris County, Texas and Cook County, Illinois led the file, followed by New York County, New York and several large counties in Texas and the West. Counties are counted as county-state pairs, so identically named counties in different states are ranked separately.

#	County	State	Estimated closures	Share
1	Harris	TX	172	2.3%
2	Cook	IL	153	2.0%
3	New York	NY	109	1.4%
4	Tarrant	TX	91	1.2%
5	Dallas	TX	85	1.1%
6	King	WA	79	1.0%
7	Clark	NV	78	1.0%
8	Los Angeles	CA	77	1.0%
9	Bexar	TX	76	1.0%
10	Kings	NY	60	0.8%
11	Queens	NY	54	0.7%
12	Wayne	MI	54	0.7%
13	Allegheny	PA	49	0.6%
14	Salt Lake	UT	42	0.6%
15	Orange	CA	39	0.5%
16	Mecklenburg	NC	39	0.5%
17	Philadelphia	PA	39	0.5%
18	Cuyahoga	OH	39	0.5%
19	Travis	TX	39	0.5%
20	El Paso	TX	37	0.5%
20	San Diego	CA	37	0.5%

County coverage was available for most records used in the geographic analysis. County shares are calculated against the 7,593 U.S. estimate, consistent with the state table. El Paso County, Texas and San Diego County, California tied for the twentieth position.

Metropolitan markets

Metropolitan-area analysis groups activity across adjoining cities and suburbs. New York-Northern New Jersey-Long Island had the highest estimated count, followed by Chicago, Dallas-Fort Worth and Houston.

#	Metropolitan area	Estimated closures	Share
1	New York-Northern New Jersey-Long Island, NY-NJ-PA	491	6.8%
2	Chicago-Naperville-Joliet, IL-IN-WI	251	3.5%
3	Dallas-Fort Worth-Arlington, TX	240	3.3%
4	Houston-Sugar Land-Baytown, TX	239	3.3%
5	Washington-Arlington-Alexandria, DC-VA-MD-WV	119	1.6%
6	Seattle-Tacoma-Bellevue, WA	119	1.6%
7	Philadelphia-Camden-Wilmington, PA-NJ-DE-MD	111	1.5%
8	Detroit-Warren-Livonia, MI	107	1.5%
9	Boston-Cambridge-Quincy, MA-NH	102	1.4%
10	Los Angeles-Long Beach-Santa Ana, CA	93	1.3%
11	St. Louis, MO-IL	91	1.3%
12	Portland-Vancouver-Beaverton, OR-WA	88	1.2%
13	San Antonio, TX	87	1.2%
14	Pittsburgh, PA	81	1.1%
15	Austin-Round Rock, TX	79	1.1%
16	Las Vegas-Paradise, NV	77	1.1%
17	Atlanta-Sandy Springs-Marietta, GA	77	1.1%
18	Kansas City, MO-KS	75	1.0%
19	Minneapolis-St. Paul-Bloomington, MN-WI	73	1.0%
20	Miami-Fort Lauderdale-Pompano Beach, FL	66	0.9%

A metropolitan classification was not available for every record.

Service-format distribution

Quick-service restaurants represented just over half of the classified closure file. Casual/family dining accounted for roughly one-third, while fast casual represented a little more than one-tenth.

Service format	Estimated closures	Share
Quick Serve	4,092	51.5%
Fast Casual	861	10.8%
Casual/Family	2,793	35.2%
Upscale Dining	171	2.2%
Buffet	21	0.3%

Values that appeared to belong to adjacent fields were excluded.

Primary-cuisine distribution

Sandwich concepts formed the largest primary-cuisine category in the closure file. Bar food, American, bakery/café, pizza and Mexican/Latin restaurants followed. The result reflects both category exposure and closure activity; it is not a category failure-rate ranking.

#	Primary cuisine	Estimated closures	Share
1	SANDWICH	2,120	26.2%
2	BAR FOOD	987	12.2%
3	AMERICAN	702	8.7%
4	BAKERY/CAFE	511	6.3%
5	PIZZA	479	5.9%
6	MEXICAN/LATIN	435	5.4%
7	COFFEE/TEA	321	4.0%
8	BURGER	294	3.6%
9	CHICKEN	239	3.0%
10	DONUT	229	2.8%
11	ICE CREAM/YOGURT	227	2.8%
12	JUICE/SMOOTHIE	163	2.0%
13	SEAFOOD	109	1.3%
14	BBQ	109	1.3%
15	ASIAN	109	1.3%
16	ITALIAN	109	1.3%
17	SPORTS BAR	100	1.2%
18	CAFE	96	1.2%
19	CHINESE	80	1.0%
20	SALAD	66	0.8%

The table uses Cuisine 1 only. Secondary cuisine fields were not added because doing so would count some locations more than once.

Alcohol-service profile

Among records with a usable alcohol classification, locations with no alcohol listed formed the largest group. Full-bar restaurants also accounted for a material share of classified records.

Alcohol classification	Estimated closures	Share
No Alcohol Listed	3,934	61.8%
Full Bar	1,791	28.1%
Beer/Wine	581	9.1%
Alcohol, Type Unspecified	59	0.9%

Interpretation note: The no-alcohol category produced the largest closure count among records with a usable alcohol classification. This does not establish that restaurants without alcohol service closed at a higher rate. A rate comparison would require the number of active restaurants in each alcohol-service category during the same period.

Blank and structurally shifted values were excluded.

Meal-period profile

Lunch-and-dinner operations and all-day breakfast/lunch/dinner operations dominated the usable meal-period records. This aligns with the heavy representation of quick service, fast casual and casual/family formats.

Meal-period coverage	Estimated closures	Share
Lunch And Dinner	4,023	50.7%
Breakfast, Lunch And Dinner	3,470	43.7%
Breakfast And Lunch	225	2.8%
Dinner Only	195	2.5%
Lunch Only	24	0.3%
Breakfast Only	2	0.0%

Interpretation note: Breakfast-only and breakfast-and-lunch locations appeared less frequently among closed locations than restaurants serving lunch and dinner. This pattern should not be interpreted as a survival advantage for breakfast-focused restaurants. Meal-period categories overlap, the active population differs by daypart, and a rate comparison would require the number of operating restaurants in each meal-period group.

Check-average bands

Lower check-average bands accounted for most classified records. The $4-$15+ band was the largest, followed by $10-$30+ and $15-$40+.

Check-average band	Estimated closures	Share
$4-15+	4,617	58.2%
$10-30+	2,035	25.6%
$15-40+	1,139	14.4%
$25-75+	147	1.8%

Interpretation note: Lower check-average bands accounted for most classified closures. This does not show that lower-priced restaurants faced greater closure risk. Lower-price formats represent a large share of the restaurant population, and the source values are categorical estimates. A rate-based conclusion would require active-location counts for each check-average band.

Check-average values are categorical source estimates, not audited transaction data.

Restaurant size indicators

The records cover a range of operating footprints. Small locations were common, while larger dining rooms and higher-seat-count restaurants were also represented.

Seat-count bands

Seats	Estimated closures	Share
Under 25	3,080	39.3%
25-49	675	8.6%
50-99	1,353	17.3%
100-149	328	4.2%
150-199	903	11.5%
200+	1,507	19.2%

Square-footage bands

Square feet	Estimated closures	Share
Under 1,000	879	11.1%
1,000-1,999	3,897	49.1%
2,000-2,999	558	7.0%
3,000-4,999	1,225	15.4%
5,000-6,999	1,245	15.7%
7,000+	134	1.7%

Operating indicators

Employee and sales estimates provide additional context for the kinds of locations represented. They should be read as profile indicators rather than precise economic measurements.

Food-and-beverage employees

Employee band	Estimated closures	Share
1-5	3,140	38.8%
6-10	1,486	18.4%
11-20	2,656	32.8%
21-30	600	7.4%
31-50	179	2.2%
51+	33	0.4%

Estimated annual sales

Sales band	Estimated closures	Share
Under $0.75M	3,160	39.8%
$0.75M-$1.49M	1,576	19.9%
$1.5M-$2.49M	2,241	28.2%
$2.5M-$4.99M	901	11.3%
$5M+	59	0.7%

Sales figures are presented in millions in the source file.

Year-established profile

Among locations with a valid year-established field, newer establishments were highly visible. That does not prove that young restaurants have a higher failure rate, because the report does not compare the closure count with the number of active restaurants in each age group.

Year established	Estimated closures	Share
Established 2024-2026	1,677	39.9%
Established 2021-2023	689	16.4%
Established 2016-2020	423	10.0%
Established 2006-2015	746	17.7%
Established Before 2006	671	16.0%

A year-established value was not available for every record.

Cross-tab analysis

The cross-tabs describe the composition of selected categories. They identify the types of locations within each segment. They do not measure failure rates.

Service format × ownership structure

Quick-service and fast-casual closure records leaned more heavily toward chain affiliation, while casual/family and upscale-dining records contained a larger independent component.

ServiceType	Chain Location	Independent Location	Total
Quick Serve	3,01373.6%	1,07926.4%	4,092
Fast Casual	58568.0%	27532.0%	861
Casual/Family	47517.0%	2,31883.0%	2,793
Upscale Dining	4124.0%	13076.0%	171
Buffet	944.0%	1256.0%	21

Service format × alcohol classification

No-alcohol locations dominated quick service and fast casual. Full-bar classifications were concentrated in casual/family and upscale dining, producing a distinctly different operating profile.

ServiceType	None	Beer/Wine	Full Bar	Alcohol	Total
Quick Serve	3,22998.7%	331.0%	110.3%	00.0%	3,273
Fast Casual	43559.6%	21929.9%	7510.2%	30.4%	731
Casual/Family	24911.3%	30313.8%	1,61173.5%	281.3%	2,191
Upscale Dining	95.5%	2415.5%	9460.8%	2818.2%	155
Buffet	1383.3%	316.7%	00.0%	00.0%	15

Primary cuisine × service format

The ten largest cuisine categories were not distributed evenly across formats. Sandwich, coffee/tea, burger and donut records were concentrated in quick service, while bar food and American restaurants leaned toward casual/family dining.

Cuisine1	Quick Serve	Fast Casual	Casual/Family	Upscale Dining	Buffet	Total
Sandwich	2,05296.9%	552.6%	100.5%	00.0%	00.0%	2,117
Bar Food	20.2%	40.4%	92295.3%	394.1%	00.0%	968
American	598.9%	568.4%	51777.9%	274.1%	40.6%	663
Bakery/Cafe	44387.3%	5110.0%	142.7%	00.0%	00.0%	507
Pizza	21545.0%	10522.0%	15131.5%	00.0%	71.4%	478
Mexican/Latin	5212.2%	6114.1%	30570.9%	112.6%	10.2%	430
Coffee/Tea	25078.1%	6219.3%	92.7%	00.0%	00.0%	321
Burger	21874.5%	4013.8%	3411.7%	00.0%	00.0%	292
Chicken	14862.5%	3916.6%	4820.2%	20.7%	00.0%	237
Donut	22698.9%	00.0%	31.1%	00.0%	00.0%	229

States by ownership structure

The chain-independent mix varied materially by geography. This table provides a more useful state profile than raw totals alone, although it still does not calculate state-level closure rates.

State	Chain Location	Independent Location	Total
TX	44142.4%	59857.6%	1,039
NY	20437.5%	33962.5%	543
CA	30377.4%	8822.6%	391
IL	17448.9%	18251.1%	356
NC	16855.7%	13444.3%	302
PA	16054.2%	13545.8%	296
OH	16858.9%	11741.1%	285
FL	22289.3%	2710.7%	249
MI	15867.2%	7732.8%	235
WA	7934.6%	14965.4%	228

Each cell shows the estimated six-month count and the row share beneath it. Cross-tabs exclude records without a valid value in both fields.

What the First-Half File Shows

Four patterns stand out in the composition of the closure file. Each describes what the closed locations looked like, not why they closed and not how their closure rates compare with the active market.

Chain and independent closures concentrated in opposite formats

Chain-affiliated locations accounted for 3,013 of the 4,092 quick-service closures, representing 73.6% of that category. The relationship inverted in full service: independents accounted for 2,318 of the 2,793 casual and family dining closures, representing 83.0%. The two ownership structures produced nearly even totals overall, 4,253 chain and 3,918 independent, but they exited through very different kinds of restaurants.

The typical closed location fit a small-footprint, low-check profile

Sandwich concepts alone represented 2,120 closures, or 26.2% of the classified cuisine file, and 96.9% of those sandwich records were quick service. That profile repeats across the operating fields: 3,080 closed locations had fewer than 25 seats, 3,897 occupied 1,000-1,999 square feet, and 4,617 fell in the $4-$15+ check-average band. The first-half file was dominated by compact, counter-service formats rather than large dining rooms.

Recently established locations were highly visible

Among records with a valid year-established field, 1,677 closed locations, representing 39.9%, were established between 2024 and 2026, more than the combined total for every establishment year before 2016. Because the report does not compare these counts with the number of active restaurants in each age group, this describes the makeup of the closure file rather than a measured failure rate for young restaurants.

The chain-independent mix varied sharply by state

Texas led all jurisdictions with 1,039 estimated closures, and its file leaned independent at 57.6%. Florida showed the opposite profile: 222 of its 249 closures, representing 89.3%, were chain-affiliated. Washington sat at the other end at 34.6% chain. State totals alone obscure these differences in who is exiting each market.

Research implications

Closure counts describe one side of restaurant-market turnover. Restaurant formation is examined separately through Restaurant Opening Analysis, which follows new locations from early public signals through verification and company classification.

The closure file is most useful when treated as one side of restaurant-market turnover. It provides evidence about where locations exited the market and what operating characteristics they shared, but the next level of analysis comes from comparing these closures with openings, active-location counts and prior periods.

Geographic benchmarking

State, county, city and metropolitan totals create a practical benchmark for future reports. Repeating the same tables at year-end and in subsequent mid-year periods will show whether closure activity is concentrating, dispersing or changing composition. Adding active-location denominators later would permit closure rates by market rather than simple counts.

Category movement

The cuisine and service-format tables establish a baseline for tracking changes in the mix of closures. A category can rise in raw closure count because its installed base expanded, because market conditions changed, or because a particular operating model experienced unusual turnover. Multi-period comparisons help distinguish these possibilities.

Opening-versus-closure analysis

Pairing this report with verified openings would show gross formation, gross exits and estimated net unit movement. That comparison would be more informative than either figure alone and would allow RestaurantData to distinguish expanding markets from markets experiencing high churn.

Operational segmentation

Seat count, square footage, check average, alcohol service, staffing and sales bands create useful operating cohorts. These fields can support future comparisons between small-footprint and full-service locations, lower- and higher-check concepts, and newer and more established restaurants without identifying individual brands.

The report intentionally stops before making causal claims. The data describes recorded closures; explanations for those closures require additional company, property, financial and local-market research.

The location-level records behind this report, including company affiliation, ownership relationships and full operating profiles, are maintained in Atlas by RestaurantData. Organizations that need the granular data for their own analysis can contact RestaurantData for access.

RestaurantData research principles

RestaurantData’s closure research is guided by a conservative verification standard. The objective is not to classify locations as quickly as possible, but to avoid removing an operating restaurant from Atlas by RestaurantData without sufficient evidence.

Accuracy over speed. When available information is incomplete or contradictory, RestaurantData continues researching the location rather than immediately classifying it as permanently closed.

Human research. Closure determinations are reviewed by human researchers. Automated signals may identify records requiring attention, but they do not independently determine a final closure status.

Multiple sources. Researchers evaluate telephone findings, restaurant and company websites, social media, public notices, licensing information, news coverage, public records and other information available in the public sphere.

Conservative classification. A location generally remains active when the evidence is uncertain. RestaurantData seeks corroborating information before applying a permanent-closure designation.

Continuous verification. Restaurant locations, companies, contacts, ownership relationships, parent-company connections and organizational hierarchies are reviewed throughout the year as part of a broader verification cycle.

Ongoing refinement. Restaurant-industry information changes continuously. Records may be updated when additional evidence, direct confirmation or authoritative documentation becomes available.

Why false positives require special care: An incorrect closure designation can affect more than one location record. It may alter unit counts, brand and franchise relationships, multi-concept operator totals, parent-company structures, executive assignments and other connected research within Atlas.

Frequently asked questions

What qualifies as a restaurant closure?

A restaurant closure is recorded after RestaurantData’s research indicates that a location has permanently ceased operating as a restaurant. Temporary shutdowns, seasonal pauses, renovations, relocations, ownership transitions and short-term interruptions are not treated as permanent closures unless subsequent research supports that conclusion.

How does RestaurantData identify closures?

RestaurantData uses a combination of direct telephone research, restaurant and company websites, social-media activity, public notices, licensing information, news reports, public records and other customer-facing and publicly available evidence. Human researchers compare the available signals before making a closure determination.

Are locations classified as closed automatically?

No. Automated and digital signals can identify records that require review, but RestaurantData does not rely on a single mapping service, website status, disconnected telephone number or social-media signal to classify a location as permanently closed. Human review remains part of the process.

How does RestaurantData reduce false positives?

The research process is intentionally conservative. When practical, researchers seek corroborating evidence from more than one source. When the information remains uncertain, the location generally stays active in Atlas pending additional verification. This approach may delay some closure classifications, but it reduces the risk of removing a restaurant that is still operating.

Can some closures be identified later?

Yes. No location-level database can identify every market change immediately. Some closures are difficult to confirm, some businesses retain active websites and telephone listings after closing, and some operating transitions are not publicly announced. RestaurantData prefers a delayed classification to an unsupported closure designation.

How are franchise locations researched?

RestaurantData independently researches franchise-location activity throughout the year. When Franchise Disclosure Documents are available, the company may also review them as part of its quality-assurance and historical-reconciliation process. FDDs are generally a confirming source rather than the primary mechanism for discovering current closures, because disclosure documents may be published after the underlying location changes occurred.

Why might RestaurantData wait for an FDD and further authoritative confirmation?

In cases where the available evidence is incomplete, RestaurantData may retain a location as active until an FDD, company communication, direct confirmation or further authoritative documentation resolves the uncertainty. The goal is to avoid presenting an unverified inference as a confirmed closure.

Why can historical counts change?

Restaurant-industry records are dynamic. As direct research is completed, businesses respond, public records are updated and franchise disclosures become available, individual location histories may be refined. Future reports may therefore incorporate newly verified information relating to earlier periods.

How often is RestaurantData’s information verified?

RestaurantData performs ongoing research and conducts broad verification of its companies, contacts, locations, ownership relationships, parent-company connections and organizational hierarchies multiple times each year. The First-Half Restaurant Closure Report is produced from that larger, continuing research process.

Why can RestaurantData’s totals differ from other reports?

Published totals may differ because organizations use different definitions, time periods, geographic coverage and source material. Some analyses rely on surveys, bankruptcy filings, government statistics and announcements. RestaurantData’s report is based on location-level research and its own verification standards across the United States and Canada.

Does a location closure mean the company failed?

No. This report measures location-level closures. A multi-unit company may close individual restaurants while continuing to operate and expand elsewhere. Locations also close because of relocations, lease decisions, portfolio changes, conversions, ownership transfers and other circumstances that do not represent company failure.

Why do the opening and closure reports have different geographic coverage?

The closure report includes the United States and Canada. RestaurantData’s new-opening reports currently cover the United States because the research depends on broad, early-stage public information sources that can identify proposed and developing restaurants at the earliest legally available point. Comparable Canadian sources are not consistently available with the same timing, accessibility and volume. For that reason, U.S. opening totals should not be directly netted against the U.S. and Canadian closure total.

About RestaurantData Research

RestaurantData maintains a continuously reviewed database of restaurant locations, operating companies, franchise organizations, ownership relationships, executive contacts, parent companies and organizational hierarchies across the United States and Canada. The research process connects individual location changes to the companies and ownership structures behind them.

The First-Half 2026 U.S. & Canada Restaurant Closure Report is one publication produced from that broader research program. Its purpose is to present location-level closure patterns without identifying individual restaurant brands and without treating every location closure as a company failure.

Methodology and limitations

Reporting period. The report covers the first half of 2026, January through June. The headline and category totals are standardized estimates for the six-month reporting period and are rounded to whole locations.

Research base. The analysis draws on RestaurantData’s closed-location records for the United States and Canada and the company’s continuing location-verification process. Each record represents a restaurant location rather than a company bankruptcy or enterprise-level closure.

Verification approach. Closure determinations follow the multi-source, human-reviewed research process described under RestaurantData research principles, with Franchise Disclosure Documents consulted when relevant. The evidence available for an individual location can vary.

Classification standard. The conservative standard described above is intended to minimize false positives. A location may remain active while additional verification is underway, so the report should not be read as a claim that every closure occurring during the period was identified immediately.

Data preparation. Values were included only when they matched the expected category and a plausible range for the field. Missing classifications were not imputed. Category shares are calculated from records with a usable classification for the relevant field, so individual table totals may sum below the headline estimate. Cross-tabs exclude records lacking a valid value in either field, and rounded subtotals may differ slightly from headline totals.

Analytical limits. The report does not calculate failure rates, bankruptcies, company closures, financial distress or net restaurant-industry change. Those questions require active-location denominators, comparable opening counts and additional event-specific research. The report describes verified and estimated closure activity; it does not assign a cause to each event.

Top 100 Restaurant Franchise Systems: 2022–2025 U.S. Outlet Growth Analysis

Top 100 Restaurant Franchise Systems: 2022-2025 U.S. Outlet Growth Analysis

By RestaurantData | Published July 2026

RestaurantData reviewed newly available 2026 Franchise Disclosure Documents to compare the largest U.S. restaurant franchise systems from year-end 2022 through year-end 2025. The analysis uses total system outlets reported in Item 20, including franchised and company-owned restaurants.

Why this report is being published in 2026: The completed year-end 2025 figures analyzed here are disclosed in Franchise Disclosure Documents issued during the 2026 filing cycle. These records were not broadly available at the end of 2025. RestaurantData assembled and standardized the newly released Item 20 outlet tables after the corresponding filings became available.

164,280

Combined 2025 U.S. system outlets

+5,260

Net locations added since 2022

3.31%

Combined three-year growth

100

Restaurant franchise systems reviewed

The 100 systems in this report increased from 159,020 U.S. outlets at year-end 2022 to 164,280 at year-end 2025. The combined total rose each year while individual systems followed different development paths.

The report compares system scale, net additions and percentage growth. Location change is presented as a multi-year operating record and not as a measure of profitability, franchisee satisfaction or brand quality.

On this page: Key Findings · Full Top 100 Table · Fastest Growth · Largest Net Additions · Item 20 Source Data · Four-Year Trends · Methodology · FAQ

Key Findings

The top 100 systems added 5,260 net locations over three years. Combined location counts rose 3.31% from 2022 through 2025.

Newer growth systems produced some of the largest percentage gains. 7 Brew, Dave’s Hot Chicken, Playa Bowls, Tous les Jours and Teriyaki Madness all expanded sharply from smaller starting bases.

Several established brands also added substantial scale. Dunkin’, Chick-fil-A, Jersey Mike’s, Wingstop and Tropical Smoothie Café each recorded meaningful multi-year gains.

Top 100 Restaurant Franchise Systems by U.S. System Outlets

The complete ranking is based on year-end 2025 U.S. system outlets reported in Item 20. It includes annual totals from 2022 through 2025, one-year change, two-year change and three-year change.

2025 Rank	Franchise System	YE 2022	YE 2023	YE 2024	YE 2025	YOY	2-Year	3-Year
1	Subway	20,576	20,133	19,502	18,773	-3.74%	-6.76%	-8.76%
2	McDonald’s	13,455	13,457	13,559	13,706	1.08%	1.85%	1.87%
3	Dunkin’	8,118	8,297	8,499	8,780	3.31%	5.82%	8.15%
4	Taco Bell	7,759	7,917	8,085	8,233	1.83%	3.99%	6.11%
5	Domino’s	6,724	6,888	7,043	7,210	2.37%	4.67%	7.23%
6	Burger King	7,042	6,778	6,701	6,650	-0.76%	-1.89%	-5.57%
7	Pizza Hut	6,606	6,622	6,567	6,272	-4.49%	-5.29%	-5.06%
8	Wendy’s	5,994	6,030	5,933	5,969	0.61%	-1.01%	-0.42%
9	Little Caesars	4,173	4,218	4,281	4,374	2.17%	3.70%	4.82%
10	KFC	3,918	3,791	3,666	3,519	-4.01%	-7.17%	-10.18%
11	Sonic Drive-In	3,546	3,521	3,461	3,412	-1.42%	-3.10%	-3.78%
12	Papa Johns	3,180	3,220	3,291	3,294	0.09%	2.30%	3.58%
13	Chick-fil-A	2,806	2,964	3,109	3,287	5.73%	10.90%	17.14%
14	Arby’s	3,415	3,413	3,365	3,265	-2.97%	-4.34%	-4.39%
15	Popeyes Louisiana Kitchen	2,946	3,076	3,177	3,229	1.64%	4.97%	9.61%
16	Jersey Mike’s	2,387	2,675	2,989	3,227	7.96%	20.64%	35.19%
17	Jimmy John’s	2,637	2,644	2,689	2,777	3.27%	5.03%	5.31%
18	Dairy Queen	2,756	2,720	2,698	2,730	1.19%	0.37%	-0.94%
19	Panda Express	2,353	2,413	2,502	2,607	4.20%	8.04%	10.79%
20	Wingstop	1,721	1,926	2,204	2,586	17.33%	34.27%	50.26%
21	Panera Bread	2,094	2,151	2,185	2,214	1.33%	2.93%	5.73%
22	Jack in the Box	2,180	2,185	2,190	2,136	-2.47%	-2.24%	-2.02%
23	IHOP	1,683	1,703	1,703	1,693	-0.59%	-0.59%	0.59%
24	Tropical Smoothie Café	1,198	1,372	1,515	1,651	8.98%	20.34%	37.81%
25	Hardee’s	1,707	1,598	1,571	1,485	-5.47%	-7.07%	-13.01%
26	Applebee’s	1,575	1,542	1,507	1,475	-2.12%	-4.35%	-6.35%
27	Buffalo Wild Wings	1,230	1,264	1,323	1,397	5.59%	10.52%	13.58%
28	Cinnabon	958	974	1,030	1,338	29.90%	37.37%	39.67%
29	Firehouse Subs	1,187	1,209	1,248	1,291	3.45%	6.78%	8.76%
30	Denny’s	1,446	1,407	1,334	1,274	-4.50%	-9.45%	-11.89%
31	Auntie Anne’s	1,146	1,167	1,193	1,247	4.53%	6.86%	8.81%
32	Smoothie King	1,103	1,152	1,201	1,242	3.41%	7.81%	12.60%
33	Marco’s Pizza	1,063	1,114	1,159	1,184	2.16%	6.28%	11.38%
34	Einstein Bros. Bagels	1,021	1,003	1,041	1,124	7.97%	12.06%	10.09%
35	Crumbl	691	972	1,059	1,101	3.97%	13.27%	59.33%
36	Culver’s	892	944	997	1,041	4.41%	10.28%	16.70%
37	Papa Murphy’s	1,168	1,127	1,044	1,014	-2.87%	-10.03%	-13.18%
38	Zaxby’s	922	941	969	1,005	3.72%	6.80%	9.00%
39	Baskin-Robbins	1,001	978	976	967	-0.92%	-1.12%	-3.40%
40	Chester’s	1,081	1,002	994	918	-7.65%	-8.38%	-15.08%
41	Scooter’s Coffee	555	750	849	906	6.71%	20.80%	63.24%
42	Church’s Chicken	925	900	873	885	1.37%	-1.67%	-4.32%
43	Bojangles	792	817	830	867	4.46%	6.12%	9.47%
44	Charleys Philly Steaks	672	761	813	836	2.83%	9.86%	24.40%
45	Qdoba	733	747	777	827	6.44%	10.71%	12.82%
46	Checkers & Rally’s	810	786	755	719	-4.77%	-8.52%	-11.23%
47	Jamba	738	734	727	710	-2.34%	-3.27%	-3.79%
48	Tim Hortons	636	642	663	693	4.52%	7.94%	8.96%
49	7 Brew	40	180	321	602	87.54%	234.44%	1405.00%
50	Freddy’s Frozen Custard	456	517	550	580	5.45%	12.19%	27.19%
51	McAlister’s Deli	524	539	560	572	2.14%	6.12%	9.16%
52	Moe’s Southwest Grill	637	612	596	568	-4.70%	-7.19%	-10.83%
53	Captain D’s	535	540	530	518	-2.26%	-4.07%	-3.18%
54	El Pollo Loco	490	495	498	503	1.00%	1.62%	2.65%
55	Caribou Coffee	484	480	487	494	1.44%	2.92%	2.07%
56	Long John Silver’s	589	539	502	479	-4.58%	-11.13%	-18.68%
57	Jet’s Pizza	407	422	450	474	5.33%	12.32%	16.46%
58	Potbelly	429	425	444	470	5.86%	10.59%	9.56%
59	Red Robin	499	496	478	464	-2.93%	-6.45%	-7.01%
60	Wetzel’s Pretzels	360	387	426	458	7.51%	18.35%	27.22%
61	MOD Pizza	531	582	482	449	-6.85%	-22.85%	-15.44%
62	Honey Baked Ham	440	439	439	448	2.05%	2.05%	1.82%
63	Noodles & Company	460	460	463	423	-8.64%	-8.04%	-8.04%
64	Shipley Do-Nuts	337	349	365	393	7.67%	12.61%	16.62%
65	Sbarro	346	369	371	387	4.31%	4.88%	11.85%
66	Steak ‘n Shake	479	436	406	387	-4.68%	-11.24%	-19.21%
67	The Habit Burger & Grill	338	366	377	383	1.59%	4.64%	13.31%
68	Playa Bowls	163	216	291	372	27.84%	72.22%	128.22%
69	Carvel	328	326	336	360	7.14%	10.43%	9.76%
70	Dave’s Hot Chicken	92	163	238	358	50.42%	119.63%	289.13%
71	Golden Corral	362	355	351	348	-0.85%	-1.97%	-3.87%
72	Kung Fu Tea	340	380	389	346	-11.05%	-8.95%	1.76%
73	Taco John’s	368	364	340	327	-3.82%	-10.16%	-11.14%
74	Chicken Salad Chick	224	254	287	326	13.59%	28.35%	45.54%
75	Penn Station	319	323	322	322	0.00%	-0.31%	0.94%
76	Mountain Mike’s Pizza	265	279	299	321	7.36%	15.05%	21.13%
77	Menchie’s	303	296	295	296	0.34%	0.00%	-2.31%
78	Schlotzsky’s	328	317	308	294	-4.55%	-7.26%	-10.37%
79	Dippin’ Dots	239	248	261	259	-0.77%	4.44%	8.37%
80	Perkins	272	263	257	257	0.00%	-2.28%	-5.51%
81	Blaze Pizza	303	296	266	230	-13.53%	-22.30%	-24.09%
82	Bruster’s	187	194	206	220	6.80%	13.40%	17.65%
83	Pizza Ranch	211	218	218	219	0.46%	0.46%	3.79%
84	Häagen-Dazs	208	209	207	215	3.86%	2.87%	3.37%
85	Slim Chickens	148	183	207	215	3.86%	17.49%	45.27%
86	A&W Restaurants	212	214	215	210	-2.33%	-1.87%	-0.94%
87	sweetFrog	221	216	206	203	-1.46%	-6.02%	-8.14%
88	Teriyaki Madness	122	139	158	199	25.95%	43.17%	63.11%
89	Peet’s Coffee	203	202	199	196	-1.51%	-2.97%	-3.45%
90	Hooters	296	292	245	194	-20.82%	-33.56%	-34.46%
91	Tous les Jours	86	107	149	189	26.85%	76.64%	119.77%
92	The Human Bean	145	158	177	188	6.21%	18.99%	29.66%
93	Kilwins	149	164	172	187	8.72%	14.02%	25.50%
94	Rosati’s Pizza	189	189	193	184	-4.66%	-2.65%	-2.65%
95	Wayback Burgers	160	165	180	184	2.22%	11.52%	15.00%
96	PJ’s Coffee	147	169	182	180	-1.10%	6.51%	22.45%
97	Donatos Pizzeria	173	178	176	179	1.70%	0.56%	3.47%
98	Smashburger	217	211	194	172	-11.34%	-18.48%	-20.74%
99	Black Bear Diner	153	156	162	169	4.32%	8.33%	10.46%
100	Bruegger’s Bagel Bakery	187	181	178	169	-5.06%	-6.63%	-9.63%

Fastest Multi-Year Expansion

Percentage growth highlights systems whose footprints changed most rapidly from year-end 2022 through year-end 2025. Smaller starting bases can produce larger percentage gains, so the rate should be read alongside the location totals.

Franchise System	YE 2022	YE 2025	Net Addition	3-Year Growth
7 Brew	40	602	+562	1405.00%
Dave’s Hot Chicken	92	358	+266	289.13%
Playa Bowls	163	372	+209	128.22%
Tous les Jours	86	189	+103	119.77%
Scooter’s Coffee	555	906	+351	63.24%
Teriyaki Madness	122	199	+77	63.11%
Crumbl	691	1,101	+410	59.33%
Wingstop	1,721	2,586	+865	50.26%
Chicken Salad Chick	224	326	+102	45.54%
Slim Chickens	148	215	+67	45.27%

Largest Net Location Additions

Absolute additions show which systems contributed the most new locations over the three-year period. This view gives more weight to franchise systems that expanded from an already substantial base.

Largest Net U.S. Outlet Additions, Year-End 2022 to Year-End 2025

Net change in total U.S. system outlets reported in FDD Item 20. Source: RestaurantData.

Franchise System	YE 2022	YE 2025	Net Addition	3-Year Growth
Wingstop	1,721	2,586	+865	50.26%
Jersey Mike’s	2,387	3,227	+840	35.19%
Dunkin’	8,118	8,780	+662	8.15%
7 Brew	40	602	+562	1405.00%
Domino’s	6,724	7,210	+486	7.23%
Chick-fil-A	2,806	3,287	+481	17.14%
Taco Bell	7,759	8,233	+474	6.11%
Tropical Smoothie Café	1,198	1,651	+453	37.81%
Crumbl	691	1,101	+410	59.33%
Cinnabon	958	1,338	+380	39.67%

How Item 20 Supports the Analysis

Item 20 of a Franchise Disclosure Document provides three years of outlet history for a franchise system. It reports franchised and company-owned units along with openings, closures, transfers and other changes. It also includes contact information for current and former franchisees. RestaurantData’s broader restaurant Franchise Disclosure Document analysis compares additional operating fields reported across leading restaurant systems, including franchised location counts, company-owned mix, average unit volumes, service type and geographic footprint.

Most franchisors update their FDDs annually. Many filings containing completed year-end 2025 outlet information became available from late winter through early summer 2026. RestaurantData reviewed and standardized those newly released records for this report.

FDD outlet tables generally cover the United States and U.S. territories. Public companies may report worldwide counts in Form 10-K filings. Those filings use different reporting periods, geographic scopes and definitions. This report uses U.S. system counts so the franchise systems can be compared on the same basis. RestaurantData’s ongoing restaurant franchise FDD analysis examines these disclosures across the full annual filing cycle.

Example: Item 20 System-Wide Outlet Summary — Popeyes Louisiana Kitchen

The table reproduces the system-wide outlet summary reported in the Popeyes Louisiana Kitchen Franchise Disclosure Document issued during the 2026 filing cycle and covering operating years 2023 through 2025.

Franchised, company-owned and total outlets reported for 2023 through 2025.
Outlet Type	Year	Outlets at Start of Year	Outlets at End of Year	Net Change
Franchised	2023	2,905	3,035	+130
	2024	3,035	3,079	+44
	2025	3,079	3,134	+55
Company-Owned	2023	41	41	0
	2024	41	98	+57
	2025	98	95	-3
Total Outlets	2023	2,946	3,076	+130
	2024	3,076	3,177	+101
	2025	3,177	3,229	+52

These totals carry directly into the ranking below: Popeyes appears at rank 15 with 3,229 U.S. system outlets at year-end 2025.

What the Four-Year Record Shows

Beverage and coffee concepts continue to gain scale

7 Brew, Scooter’s Coffee, The Human Bean and PJ’s Coffee all expanded their footprints during the period. Their growth reflects continued investment in beverage-led formats, drive-through development and smaller-footprint operating models.

Chicken concepts remain active across several size tiers

Wingstop, Chick-fil-A, Dave’s Hot Chicken, Chicken Salad Chick, Slim Chickens and Popeyes all added locations. The category includes both mature national systems and younger concepts that are still building regional coverage.

Fast-casual and specialty systems recorded substantial expansion

Jersey Mike’s, Tropical Smoothie Café, Cinnabon, Playa Bowls and Tous les Jours all expanded during the period. Their growth shows that meaningful development is occurring outside the largest legacy quick-service systems.

System maturity produces different development patterns

Not every established franchisor is pursuing the same unit-growth strategy. Some systems are adding new markets. Others are concentrating on franchisee quality, remodels, unit economics, portfolio management or market optimization. Location change should therefore be interpreted as one part of a broader operating picture.

How RestaurantData Would Extend This Research

This public analysis is intentionally centered on scale and multi-year franchise development. It does not need to include every field maintained in Atlas. Adding headquarters addresses, square footage, average checks, sales estimates and other operating details to all 100 rows would make the page harder to use and would blur the purpose of the report.

Those fields are more useful inside company research. Atlas can connect a franchisor to its headquarters, parent organization, operating structure, executive contacts, franchise relationships, technology assignments and development activity. Company-specific information can then be reviewed in context rather than compressed into one oversized public table.

The same structure can later support links to individual Restaurant Enterprise Index™ profiles as those profiles are published. That would allow readers to move from the broad franchise market to deeper research on selected restaurant enterprises.

Methodology and Interpretation

Independent research notice: RestaurantData independently compiled this analysis from publicly available Franchise Disclosure Documents and other public sources. Rankings, calculations, and commentary represent RestaurantData’s research and are not endorsed by the franchise systems or franchisors identified.

RestaurantData standardized annual system-wide outlet counts from Item 20 of restaurant Franchise Disclosure Documents, including newly available filings issued during the 2026 disclosure cycle. The figures combine franchised and company-owned outlets and compare year-end totals for 2022, 2023, 2024 and 2025. Percentage changes are calculated from the published totals shown in the table.

FDDs may use different fiscal year-end dates and may define territories or outlet types differently. RestaurantData reviews the underlying disclosures before placing the figures into a common comparison. Openings, closures, transfers, acquisitions, refranchising, market exits and reporting changes can all affect annual totals.

This report is limited to U.S. system outlets and U.S. territories reported in FDDs. Global counts disclosed in public-company filings are not substituted into the ranking because SEC reports are not standardized in the same way as Item 20.

Frequently Asked Questions

What is a restaurant franchisor?

A restaurant franchisor grants franchisees the right to operate under its brand and operating system. The franchisee owns or operates the local business under the terms of a franchise agreement.

How were the Top 100 restaurant franchise systems selected?

The Top 100 were ranked by total U.S. system outlets at year-end 2025. The count includes franchised and company-owned restaurants reported in Item 20.

What is Item 20 in a Franchise Disclosure Document?

Item 20 shows the growth and turnover of a franchise system. It includes three years of outlet tables covering openings, closures, transfers and changes in franchised and company-owned units. It also lists contact information for current and former franchisees.

What other important information is contained in the FDD reports?

Beyond the outlet tables and financial disclosures, FDDs contain another category of information that is often overlooked but extremely revealing: the Business Experience section (Item 2). This portion profiles the leadership behind the franchisor, and depending on how the organization is structured, it may include biographies for the Board of Directors, parent-company executives, brand-level C-suite leaders and key regional operators.

Each bio typically lists the individual’s title, name and a concise summary of their professional background. These summaries outline prior roles both within the organization and at other companies. When read carefully, they offer insight into whether the franchisor tends to promote talent internally or prefers to bring in outside leadership.

Because the Business Experience section is updated annually, it can also be scanned for year-over-year changes. Prospective franchisees often look for signs of leadership stability, while others may view new executives as evidence of a strategic shift. For companies that consistently promote from within, the FDD allows you to trace an executive’s progression through the ranks, a pattern RestaurantData examines in its research on restaurant executive changes. Conversely, when leadership is recruited externally, the bios make it possible to follow a manager’s movement across brands and industries on the path to their current role.

What is the source for restaurant location counts?

RestaurantData draws the location counts from Item 20 of each franchisor’s FDD. The system-wide outlet summary provides a structured record of franchised, company-owned and total units for annual comparison.

Why do restaurant franchise location counts change from year to year?

Systems open restaurants, close locations, enter or leave markets, acquire units, transfer ownership and revise development plans. Food costs, labor costs, operating efficiency, franchisee execution and local conditions also affect unit performance and system development.

Are company-owned restaurants included?

Yes. The report uses total system outlets and includes both franchised and company-owned restaurants. Across approximately 300 systems tracked by RestaurantData, franchisees operate about 89% of outlets and companies operate about 11%.

Why can FDD totals differ from public-company reports?

FDDs generally report U.S. outlets and U.S. territories. Public companies may report global restaurant counts in Form 10-K filings. The reporting periods, geographic scope and definitions may differ.

Does a lower outlet count mean a restaurant franchise system is performing poorly?

No. Outlet counts do not measure profitability, unit economics, franchisee satisfaction or brand strength. A system may contract while closing weak locations, refranchising units or changing its market strategy.

When are Franchise Disclosure Documents generally issued?

Most franchisors update their FDDs annually after the close of their reporting year. Many documents containing completed year-end 2025 outlet figures became available from late winter through early summer 2026, although timing varies by company and filing requirements.

Why does a report published in 2026 analyze 2025 outlet figures?

Franchise Disclosure Documents report completed historical operating periods and are generally issued after the reporting year has ended. The documents containing final year-end 2025 outlet totals were released during the 2026 filing cycle. RestaurantData assembled this report after those records became available.

How often is this report updated?

RestaurantData plans to update the report annually as new FDDs and related company records become available.

How is this report different from the Restaurant Enterprise Index™?

This report compares restaurant franchise systems by U.S. outlet count. The Restaurant Enterprise Index™ covers larger restaurant enterprises, including franchisors, franchisees, multi-concept operators and ownership groups.

How is this report different from Atlas by RestaurantData?

Atlas by RestaurantData connects locations to franchisees, franchisors, operating companies, brands, parent companies and ultimate owners. It also includes executive contacts, restaurant technology, operating characteristics and development activity.

Related RestaurantData Research

RestaurantData’s research on multi-concept restaurant operators examines companies that run two or more brands under one ownership structure. A related study identifies restaurant chains crossing expansion thresholds as they move into new size tiers. Development activity across the country is documented in the semi-annual analysis of U.S. restaurant opening patterns. Readers following the current filing season can review the early-bird results from this year’s franchisor releases.

The RestaurantData Research Center organizes the company’s reports, methodology and proprietary indexes, including the Expansion Pressure Index™.

Usage, Citation & Copyright

RestaurantData encourages journalists, researchers, educators, analysts and publishers to reference, summarize and cite this publication with appropriate attribution. Brief quotations and excerpts consistent with fair use are encouraged with attribution.

Preferred citation: RestaurantData.Top 100 Restaurant Franchise Systems: 2022–2025 U.S. Outlet Growth Analysis.” Published July 2026″.

Multi-Concept Restaurant Operators | RestaurantData Research

Published: July 2026

RestaurantData.com Proprietary Research

RestaurantData.com examined 1,339 multi-concept restaurant companies operating 288,239 restaurant units and representing approximately $454.5 billion in system sales. The file covers approximately 6,550 named concepts and 7,432 distinct contacts. The analysis shows that multi-concept ownership frequently develops before enterprise scale: most companies remain relatively small, but their operating structures can include multiple concepts, states, service formats, franchise relationships and management functions.

Key Findings

The 1,339 companies operate 288,239 restaurant units and represent approximately $454.5 billion in system sales.
The source file contains 8,150 person-level records representing 1,339 distinct operating companies.
The companies represent approximately 6,550 named concepts and 7,432 distinct contacts.
The median company operates three concepts, 13 restaurant units and two states.
Operators with fewer than 20 units account for 63.5% of the companies (850 of 1,339).
More than half of the companies (687 of 1,339, or 51.3%) operate in multiple states.
Companies operating across more states generally have larger unit networks, deeper contact structures and higher email coverage.
More than three-quarters of the companies (1,028 of 1,339, or 76.8%) have at least one identified contact with an email address.
The Southeast has the broadest regional operating presence.
Florida, California and Texas are the most frequently represented operating states.
Concept count and company size measure different forms of organizational complexity.

The underlying company, concept, location, ownership and decision-maker relationships can be researched through Atlas by RestaurantData. Figures in this report represent a dated extract and may change as companies add or close locations, enter markets, acquire concepts, reorganize ownership or replace personnel.

Market Overview

The source file is organized as one row per contact person, so company information can appear on multiple rows. Records were consolidated by company identification number before company totals, operating characteristics and geographic coverage were calculated.

Measure	Result
Operating companies	1,339
Total restaurant units	288,239
Estimated system sales	$454.5 billion
Person-level records	8,150
Named concepts in the current extract	6,550
Distinct identified contacts	7,432
Companies with an identified email contact	1,028
Email-contact coverage	76.8%
Average contacts per company	5.55
Median contacts per company	4
Average concepts per company	4.89
Median concepts per company	3
Median restaurant units	13
Median operating states	2

The median company provides a more representative view of the market than the average because the file includes several national and international organizations with unusually large unit networks and concept portfolios.

Most Multi-Concept Operators Remain Relatively Small

Multi-concept ownership is not limited to large holding companies. Smaller local and regional operators may manage several restaurant identities, menus, service models and purchasing requirements while operating fewer than 20 locations.

Company Unit Count	Companies	Share	Median States	Average Contacts	Companies With Email
2–4 units	224	16.7%	1	1.91	60.7%
5–19 units	626	46.8%	1	4.30	74.9%
20–49 units	225	16.8%	3	6.15	82.2%
50–99 units	92	6.9%	4.5	7.17	89.1%
100–499 units	132	9.9%	10	9.58	87.9%
500 or more units	40	3.0%	45	25.07	100.0%

The 850 operators with fewer than 20 locations account for 63.5% of the file. This supports RestaurantData.com’s separate research on the expansion of micro and small restaurant groups and shows that portfolio complexity often develops before conventional regional-chain scale.

Concept Count and Company Size Measure Different Things

A large concept portfolio does not necessarily indicate a large restaurant network. Some hospitality groups create a separate identity for nearly every location, while other organizations operate thousands of units through a limited number of repeatable brands.

Number of Concepts	Companies	Share	Median Units	Median States	Average Contacts
2 concepts	500	37.3%	12	1	4.41
3 concepts	230	17.2%	8	1	4.24
4–5 concepts	239	17.8%	10	1	5.35
6–9 concepts	196	14.6%	13	2	7.40
10 or more concepts	123	9.2%	23	4	10.06
Incomplete or partially populated concept field	51	3.8%	22	2	5.59

Companies operating 10 or more concepts have a median of only 23 units, and median unit counts do not rise uniformly with concept count: three-concept companies show a lower median (8 units) than two-concept companies (12 units). The table separates portfolio complexity, created by managing numerous concepts, from network complexity, created by operating many locations across a broad territory.

Geographic Footprint

The Trading Area field identifies the states in which each company operates. Companies are counted in every region containing at least one operating state, so regional totals are not additive.

Region	Companies Operating There	Share of All Companies	Median Units	Average Concepts	Average Contacts	Email Coverage
Southeast	624	46.6%	20	5.88	7.36	82.2%
Midwest	438	32.7%	30	6.01	8.39	82.2%
Northeast	407	30.4%	20	6.71	8.27	82.8%
Southwest	384	28.7%	33.5	5.92	8.41	82.0%
West	364	27.2%	23	6.70	8.62	83.5%
Northwest	257	19.2%	50	7.23	10.18	91.1%

Regional definitions: Northeast – CT, ME, MA, NH, NJ, NY, PA, RI and VT. Midwest – IL, IN, IA, KS, MI, MN, MO, NE, ND, OH, SD and WI. Southeast – AL, AR, DC, DE, FL, GA, KY, LA, MD, MS, NC, SC, TN, VA and WV. Southwest – AZ, NM, OK and TX. West – CA, HI and NV. Northwest – AK, CO, ID, MT, OR, UT, WA and WY.

The Southeast has the broadest operating presence, while the Northwest has the smallest company count but the highest average concept and contact totals. The Northwest result reflects the presence of national companies operating there and should not be interpreted solely as a measure of locally headquartered operators.

Leading States in Multi-Concept Operating Footprints

State figures measure company presence rather than restaurant-location totals. A company is counted whenever a state appears in its Trading Area field and may therefore appear in several state rows.

Rank	State	Companies Operating There	Share of File	Median Company Units	Average Concepts	Average Contacts
1	Florida	325	24.3%	33	7.10	9.62
2	California	313	23.4%	25	6.61	8.90
3	Texas	304	22.7%	43.5	6.48	9.38
4	New York	243	18.1%	28	7.98	10.13
5	Illinois	229	17.1%	57	7.66	10.87
6	Georgia	211	15.8%	80	6.65	10.77
7	Tennessee	193	14.4%	84	7.26	11.26
8	North Carolina	182	13.6%	93	7.04	11.51
9	Virginia	178	13.3%	113	8.34	12.71
10	Arizona	171	12.8%	84	7.52	11.43
11	Pennsylvania	171	12.8%	80	8.15	12.22
12	Ohio	169	12.6%	119	7.10	12.20
13	Colorado	166	12.4%	106.5	8.16	12.72
14	Nevada	156	11.7%	76.5	8.53	12.73
15	New Jersey	151	11.3%	84	7.77	12.30

Florida, California and Texas each contain a substantial mix of hospitality groups, franchise organizations, regional full-service companies, fast-casual developers and national platforms. States farther down the ranking often show larger median networks because a greater proportion of the companies operating there are multi-region organizations.

Headquarters and Operating Presence

Headquarters location identifies where the corporate office is based, while Trading Area identifies where the restaurant organization operates. These measures should not be substituted for one another.

Rank	Headquarters State or Province	Companies
1	California	180
2	Texas	131
3	New York	111
4	Florida	98
5	Illinois	68
6	Georgia	50
7	Arizona	41
8	Massachusetts	38
9	Ohio	37
10	Washington	32

The distinction is also used in RestaurantData.com’s Restaurant Executive Changes analysis, where corporate location is separated from restaurant market coverage.

Trading-Area Breadth and Organizational Depth

Geographic breadth produces one of the clearest differences in the file. Single-state companies have a median of seven units and average 3.41 contacts, compared with 296 median units and 18.51 contacts among companies operating across at least 20 states.

Trading-Area Coverage	Companies	Median Units	Average Concepts	Average Contacts	Companies With Email
1 state	612	7	3.98	3.41	67.5%
2–4 states	402	14	4.49	4.88	80.1%
5–9 states	129	34	5.50	7.33	88.4%
10–19 states	79	95	8.92	10.30	89.9%
20 or more states	77	296	9.68	18.51	98.7%

This table reflects the 1,299 companies with a fully populated Trading Area field in the extract; the remaining 40 companies could not be assigned a state-count bucket and are excluded here, though they remain in all company-level totals.

As operating territory expands, companies add management requirements involving regional operations, licensing, distribution, construction, facilities, human resources, finance and technology. Contact depth therefore rises more sharply with state coverage and unit count than with concept count alone.

Regional Differences in Service Type and Cuisine

Regional results include both locally based operators and national companies active in each market. They describe the companies operating in a region rather than only those headquartered there.

Region	Leading Service Types	Most Common Cuisine Classifications	Full-Bar Companies
Northeast	Casual/Family, Upscale Dining, Fast Casual	American, Bar Food, Burger, Italian, Seafood	278
Midwest	Casual/Family, Quick Serve, Upscale Dining	American, Bar Food, Burger, Pizza, Chicken	268
Southeast	Casual/Family, Upscale Dining, Quick Serve	American, Bar Food, Burger, Seafood, Chicken	415
Southwest	Casual/Family, Quick Serve, Fast Casual	American, Bar Food, Burger, Chicken, Pizza	222
West	Casual/Family, Upscale Dining, Quick Serve	American, Bar Food, Burger, Seafood, Italian	226
Northwest	Casual/Family, Fast Casual, Quick Serve	American, Bar Food, Burger, Chicken, Pizza	148

American, Bar Food and Burger appear across every region. Differences become clearer lower in the rankings, with Italian and seafood more prominent in the Northeast and West and pizza and chicken more prominent in the Midwest, Southwest and Northwest.

The Contact Structure of Multi-Concept Companies

Multi-concept organizations may require separate or shared responsibility for operations, culinary development, marketing, finance, technology, construction, training and other functions across several restaurant identities.

Contact Function	Companies With Function Represented
Owner	668
Operations	541
Marketing	478
Chief Executive Officer	428
President	407
Human Resources	361
Chef or Culinary Leadership	360
Finance	284
Chief Financial Officer	271
Partner	258
Information Technology	239
Chief Operating Officer	222
Catering	198
Controller	193
Training	177
Construction	155
Development	135
Facilities and Maintenance	131

Owner contacts remain the most common, but the range of functions shows how management structure expands as companies add locations, markets, systems and operating responsibilities.

Large Concept Portfolios Take Several Forms

Companies with large concept portfolios include hotel and casino operators, scalable chain platforms and restaurant groups built around individually branded locations.

About contact counts: Contact counts shown below represent contacts directly associated with each enterprise organization. For multi-concept operators and franchise organizations, additional contacts are often available across their individual brands, operating companies, franchise systems and subsidiaries, resulting in substantially larger organization-wide contact coverage than shown in this table.

Company	Approximate: Concepts	Approximate: Units	States/Provinces	Identified Contacts
Kimpton Hotel & Restaurant Group	58 (In Hotels)	101	26	13
Landry Restaurant Group	90	587	41	15
Station Casinos	89	90	1	16
Lettuce Entertain You Enterprises	62	117	10	28
Tao Group Hospitality	58	66	11	15
MTY Food Group	54	6,489	59*	24
McMenamins	35	54	2	11
Starr Restaurants	34	43	5	14

*MTY Food Group operates in both the United States and Canada; its figure of 59 combines U.S. states and Canadian provinces.

Kimpton and Station Casinos operate large collections of individually named food-and-beverage concepts, while MTY Food Group manages a broad portfolio of scalable brands. Lettuce Entertain You and Starr Restaurants combine original, repeated and market-specific concepts, demonstrating that the multi-concept classification can describe several operating models.

Restaurant Format and Service Mix

Primary Service Classification	Companies	Share
Casual or family dining	613	45.8%
Upscale dining	345	25.8%
Quick service	221	16.5%
Fast casual	156	11.7%
Buffet	4	0.3%

Casual or family dining and upscale dining account for most of the file, helping explain the frequency of full-bar service, catering, reservations, patios and other features associated with full-service and hospitality operations.

Franchise Relationships Add Another Layer

Multi-concept companies may operate proprietary concepts, serve as franchisees of outside brands, franchise their own brands or combine these roles within a larger ownership hierarchy. These overlapping relationships make company-level analysis more informative than public brand lists, which may not reveal the operating entities, parents and affiliated concepts behind the portfolio.

How Multi-Concept Structure Connects to Expansion

Multi-concept status describes a company’s operating structure, not whether it is currently expanding. Concept count, unit count and trading-area breadth should be evaluated alongside recent development activity. RestaurantData.com’s Expansion Pressure Index™ provides a separate view of verified development activity, while earlier research reviewed individual examples of growth and change among multi-concept restaurant operators.

What the Cross-Tab Shows

Organizational complexity develops well before enterprise scale. Many multi-concept companies remain local or regional, but their structures can include several concepts, multiple service formats, franchise relationships, operating states and management functions. The clearest picture emerges when company, concept, unit, geography, ownership and contact information are connected rather than evaluated as separate lists.

Methodology

This analysis is based on a RestaurantData.com extract of companies classified as restaurant multi-concept organizations. Person-level records were consolidated by company identification number. Distinct contacts were calculated from available contact-name and email fields; concepts were taken from the Concepts field, restaurant units from Number of Units and operating geography from Trading Area.

Regional and state counts represent company operating presence, not unit totals, and should not be added together because companies may operate in multiple jurisdictions. Headquarters counts identify corporate location. Companies with incomplete or partially populated concept fields remain in the company total and are identified separately in the concept-count analysis. Companies without a fully populated Trading Area field remain in the company total and are excluded only from the trading-area coverage table.

Continue Exploring RestaurantData.com Research

This report is part of the RestaurantData Research Center, which organizes RestaurantData.com research on restaurant openings, ownership hierarchies, operator companies, expansion activity, executive changes and market development. Readers can also explore the Restaurant Enterprise Index™, which profiles large restaurant companies, enterprise operators, franchise organizations and multi-concept ownership groups using RestaurantData.com’s proprietary research

Usage, Citation & Copyright

RestaurantData encourages journalists, researchers, educators, analysts and publishers to reference, summarize and cite this publication with appropriate attribution.

Preferred citation: “Source: RestaurantData.com, Inside the Multi-Concept Restaurant Market: Company, Concept, Trading Area and Decision-Maker Cross-Tab, published July 2026.”

4 Restaurant Chains Crossing Expansion Thresholds (2026)

RestaurantData identified four restaurant companies that crossed operating thresholds during the November 2025–June 2026 tracking period.

Two operators moved beyond 30 units. Two others moved beyond 70 units. Each advanced into a new operating range based on verified restaurant development activity observed during the same period.

Key Findings

Four restaurant companies crossed operating thresholds between November 2025 and June 2026.
Slice House expanded from 29 to 36 units, adding 7 tracked openings across 3 states.
Juiceland expanded from 28 to 34 units, adding 6 tracked openings.
Walk-On’s Sports Bistreaux moved from 68 to 73 units, adding 5 tracked openings across 3 states.
Guthrie’s Chicken Fingers moved from 70 to 73 units, adding 3 tracked openings.
The analysis compares companies within similar size cohorts rather than against all restaurant operators.

Cohort Size and Threshold Movement

The examples in this post come from larger company-size cohorts. Cohort boundaries are defined per analysis, so companies are compared against operators of similar scale during the same tracking period.

Company-Size Cohort	Companies Analyzed	Operating Range
Emerging	931	3–9 units
Regional	401	10–30 units
Growth	165	31–70 units

Additional cohorts, including operators above 70 units, are tracked in the full index but are not covered in this post.

The 30-unit examples below show operators moving out of the 10-to-30 range. The 70-unit examples show operators moving out of the 31-to-70 range.

Expansion Activity and Business Prioritization

Organizations that serve the restaurant industry often organize coverage by account size, segment, territory, category, or recent activity. Unit count provides one view of business size. Current development provides another view of movement.

This analysis gives structure to that movement by comparing verified expansion activity inside defined size cohorts and tracking periods. The broader methodology and company-level analysis are presented in RestaurantData’s Expansion Pressure Index™.

It does not prescribe a business decision. It presents evidence so readers can interpret the activity within their own planning process.

How to Read the Model

The model compares companies within a selected size segment and tracking period. It weighs recent unit growth, growth velocity, multi-state presence, new-market expansion, recency and momentum, and verification strength.

Factor	Weight
Recent unit growth	30%
Growth velocity	20%
Multi-state presence	20%
New-market expansion	15%
Recency and momentum	10%
Verification strength	5%

Verification strength reflects how many independent source types confirm a company’s tracked activity, such as D/B/A filings, permits, and licensing records.

Scores are grouped into pressure tiers: Very High, High, Moderate, and Watch.

Very High indicates the strongest relative expansion pressure within the segment during the window. High and Moderate indicate active but less concentrated development. Watch identifies companies with minimal tracked development. These are not declining businesses, but operators to monitor for future movement rather than prioritize today.

A higher tier indicates stronger relative expansion pressure within the same size segment during the selected period. It does not measure company quality, financial performance, management effectiveness, or investment potential. For an example applied to a single dining segment, see the Top 10 Upscale Dining Brands Showing Expansion Pressure.

Adapting the Model to Your Own Segmentation

The cohort boundaries shown in this post are one configuration, defined for this analysis. They are not fixed.

Organizations segment their markets differently. Some divide accounts into SMB, mid-market, and enterprise. Others organize by territory, category, or purchasing volume. Stage ranges can be redefined to match an organization’s own account structure and adjusted as coverage models change.

A sales team that treats 50 units as the enterprise line can set the stage range there. A market analyst comparing operators between 15 and 45 units can define that band directly. Rankings, tiers, and momentum are recalculated within the selected segmentation, so expansion pressure is measured against the relevant comparison set.

Organizations interested in seeing the model configured around their own segmentation can request a full demonstration.

Understanding the Unit Counts

RestaurantData’s analysis of 2,698 opening projects from March through May shows the pace at which the record base moves. Counts here may differ slightly from a company’s published total by the time this post is read.

Companies Crossing the 30-Unit Threshold

Restaurant operators passing approximately 30 locations have generally moved beyond the earliest stage of expansion. The threshold provides context for comparing companies inside the 10-to-30 cohort and identifying those moving into the next operating range.

Brand	Units	Net New	States	Pressure	Key Driver
Slice House	29 → 36	+7	3	Very High	Crossed 30 units; added 7 tracked openings; active across 3 states; validated by 1 source type (D/B/A filings).
Juiceland	28 → 34	+6	1	Very High	Crossed 30 units; added 6 tracked openings; validated by 2 source types.

Both companies moved from below 30 units to above 30 units during the tracking period. Crossing an operating threshold identifies movement from one range into the next.

Companies Crossing the 70-Unit Threshold

Restaurant companies approaching 70 locations are at the upper end of the Growth range. The examples below show companies moving past that boundary and into the next operating stage.

Brand	Units	Net New	States	Pressure	Key Driver
Walk-On’s Sports Bistreaux	68 → 73	+5	3	Very High	Added 5 tracked openings; active across 3 states; validated by 2 source types.
Guthrie’s Chicken Fingers	70 → 73	+3	1	Moderate	Added 3 tracked openings; validated by 2 source types.

Both companies moved from the 31-to-70 range to more than 70 units during the tracking period. Walk-On’s combined unit growth with multi-state activity, while Guthrie’s showed steady single-state development.

Research Methodology

This analysis is based on restaurant development activity tracked by RestaurantData between November 2025 and June 2026. Development records are compiled from public records, including legal filings, permits, licensing records, local reporting, and other publicly available sources. The same records are used in RestaurantData’s Restaurant Opening Signals Report and franchise FDD analysis.

Companies are compared within the same operating cohorts and tracking period. Individual openings are treated as development events, while patterns of activity across companies are used to identify movement between operating ranges.

Unit counts measure movement during the study period rather than a company’s exact operating total on the publication date.

Continue Your Research

Additional company-level analysis is available in the Restaurant Enterprise Index™, which covers larger restaurant companies, franchise organizations, and multi-concept operators.

Restaurant locations, brands, parent companies, franchise relationships, multi-concept operators, and company hierarchies are available in Atlas by RestaurantData.

Additional methodology papers and industry research are available in the RestaurantData Research Center.

Usage, Citation & Copyright

RestaurantData encourages journalists, researchers, educators, analysts and publishers to reference, summarize and cite this publication with appropriate attribution.

Preferred citation: “Source: RestaurantData.com, Expansion Pressure Index™ Threshold Movement Analysis, November 2025–June 2026 tracking period, published July 2026.”

Restaurant Executive Changes: Decision Maker Analysis

Restaurant Executive Changes Report: U.S. and Canada Restaurant Chains (2025–2026)

Published: July 2026

Key Findings

1,649Personnel-change records reviewed	770Unique companies represented	53Headquarters states and provinces represented
12 monthsJuly 1, 2025 through July 1, 2026	55.9%Changed decision-maker records	44.1%Added decision-maker records

RestaurantData.com reviewed executive and VP-level personnel changes across restaurant chains and foodservice companies in the United States and Canada. The analysis covers July 1, 2025 through July 1, 2026.

This analysis covers restaurant and foodservice companies operating at three units and above. The record set includes franchisees, franchisors, multi-concept operators, regional restaurant groups and national chains.

The records include added and changed decision makers across marketing, operations, IT, finance, human resources, development, franchising, construction, supply chain, culinary, real estate and related leadership functions.

Important note: State and province counts refer to the company headquarters location in the record. They do not represent restaurant unit locations or market-level store counts.

Analysis Period

Measure	Result
Start date	July 1, 2025
End date	July 1, 2026
Period covered	12 months
Total records reviewed	1,649

The 12-month range gives the analysis a full operating cycle. It includes the second half of 2025 and the first half of 2026. That helps show whether executive changes were spread across the year or concentrated in specific periods.

The second half of 2025 had more activity than the first half of 2026. This is useful when reading the rest of the report because the quarterly and monthly tables show when leadership changes were most active.

Added vs. Changed Decision Makers

Change Type	Records	Share
Changed decision maker	921	55.9%
Added decision maker	728	44.1%
Total	1,649	100.0%

Changed decision makers accounted for 921 records (55.9% of the total). Added decision makers accounted for 728 records (44.1%).

This split shows two types of movement. Some companies replaced or reassigned existing leadership roles. Others added new decision-maker contacts. For suppliers and research users, both types can create a reason to review a company record again.

Quarterly Activity

Quarter	Records	Share
Q3 2025	492	29.8%
Q4 2025	513	31.1%
Q1 2026	351	21.3%
Q2 2026	291	17.6%
Q3 2026 partial	2	0.1%

Q4 2025 was the highest quarter with 513 records (31.1% of the total). Q3 2025 followed with 492 records (29.8%).

Together, Q3 and Q4 2025 accounted for 1,005 records. That equals 60.9% of all executive-change records in the analysis. The first 2 quarters of 2026 accounted for 642 records (38.9%).

Monthly Activity

Month	Records	Share
October 2025	198	12.0%
December 2025	187	11.3%
July 2025	186	11.3%
September 2025	172	10.4%
January 2026	155	9.4%
August 2025	134	8.1%
November 2025	128	7.8%
March 2026	127	7.7%
April 2026	116	7.0%
June 2026	108	6.5%
February 2026	69	4.2%
May 2026	67	4.1%
July 2026 partial	2	0.1%

October 2025 was the highest month with 198 records. December 2025 had 187 records. July 2025 had 186 records. Those 3 months represented 571 records (34.6% of the total).

February 2026 and May 2026 were the lowest full months. February had 69 records (4.2%). May had 67 records (4.1%). The monthly table shows that leadership activity did not move in a straight line across the year.

Headquarters Location of Companies Reporting Executive Changes

The table below shows the headquarters state or province tied to each company record. These figures do not represent restaurant unit locations or market-level store counts.

Headquarters State or Province	Records	Share
California	203	12.3%
Texas	175	10.6%
Florida	158	9.6%
New York	118	7.2%
Georgia	103	6.2%

The top 5 headquarters states accounted for 45.9% of all records. California, Texas and Florida represented 32.5%.

This headquarters view is useful for corporate research. It helps show where parent companies and restaurant offices are based. It should not be read as a store-location table. A company headquartered in one state may operate restaurants across many markets.

U.S. and Canada Breakdown

Country	Records	Share
United States	1,576	95.6%
Canada	73	4.4%
Total	1,649	100.0%

The record set is U.S.-weighted. U.S.-based companies accounted for 1,576 records (95.6% of the total). Canada accounted for 73 records (4.4%).

Canadian headquarters activity was led by Ontario, British Columbia, Quebec and Alberta. The Canada count is smaller than the U.S. count, but it still reflects decision-maker changes across several provinces.

Executive Function Cross-Tab

Function	Records	Share
Marketing	285	17.3%
Operations	152	9.2%
IT	129	7.8%
Finance	115	7.0%
Human Resources	115	7.0%

Marketing was the largest category with 285 records (17.3% of the total). Operations followed with 152 records (9.2%). IT had 129 records (7.8%).

Finance and human resources each had 115 records (7.0%). Together, marketing, operations, IT, finance and human resources represented 48.3% of all executive-change records reviewed.

Executive Changes by Department: What the Numbers Show

Together, these 5 departments represented 796 records (48.3% of all executive changes identified during the 12-month period). The concentration shows that nearly one-half of reported leadership movement occurred within functions tied to restaurant operations, customer strategy, technology, budgeting and workforce management.

Development accounted for 62 records (3.8%). CFO records followed with 61 records (3.7%). Culinary leadership accounted for 60 records (3.6%). CEO changes represented 59 records (3.6%).

Field operations and store management accounted for 57 records (3.5% of the total). This category may include group vice presidents and area managers. RestaurantData captures these roles when identified during research but does not actively track field management as a primary area of coverage.

Franchising, supply chain and construction each represented close to 3.0% of the total. Real estate, procurement, facilities, catering and training represented smaller shares individually. Combined, these functions add visibility into companies that may be reviewing expansion, purchasing, facilities management or operating processes.

The distribution shows that executive movement was not concentrated in one area. Changes occurred across strategy, finance, operations, development, technology, human resources and restaurant support functions.

When evaluated with RestaurantData.com restaurant opening research, ownership records and expansion tracking, executive changes provide another layer of market intelligence for companies operating at 3 units and above.

What the Cross-Tab Shows

Executive changes do not indicate a purchasing decision. They identify shifts in organizational responsibility and decision-making. Leadership transitions often coincide with changes in operating priorities, expansion initiatives, technology evaluations, capital planning, or vendor relationships. The personnel change itself is the observable event. Combined with restaurant opening activity, ownership data, and Expansion Signals, executive movement provides additional context for identifying organizations entering a new planning or investment cycle.

Research Summary

RestaurantData.com reviewed 1,649 executive and VP-level personnel-change records from July 1, 2025 through July 1, 2026. The records covered 770 companies and 53 headquarters states and provinces.

Marketing, operations, IT, finance and human resources represented the largest share of activity. California, Texas, Florida, New York and Georgia led the headquarters count. Q4 2025 was the highest quarter.

Related RestaurantData.com Research

For long-term opening patterns, review the 2020–2025 Restaurant Opening Cross-Tab Analysis.

For recent filing activity, see the Restaurant Opening Signals Report: 1,188 Filings Across 49 States.

For a multi-month view, read March-May Restaurant Openings: Analysis of 2,698 Projects.

For expansion pressure research, see Top 10 Upscale Dining Brands by Expansion Pressure.

For weekly pre-opening coverage, visit New Restaurant Openings.

Continue Your Research

This article is part of the RestaurantData Research Center, where RestaurantData publishes research based on verified restaurant openings, expansion activity, executive changes, operator records, and market intelligence.

The Research Center brings together RestaurantData reports, methodologies, and analysis in one place for readers following restaurant industry development and company movement.

For enterprise-scale operator analysis, visit the Restaurant Enterprise Index™, which profiles large restaurant companies, ownership groups, and enterprise operators. To explore connected restaurant hierarchies, parent companies, brands, and locations, see Atlas by RestaurantData.

Usage, Citation & Copyright

RestaurantData encourages journalists, researchers, educators, analysts and publishers to reference, summarize and cite this publication with appropriate attribution.

Preferred citation: Source: RestaurantData.com, Restaurant Executive Changes Report: U.S. & Canada Restaurant Chains (2025–2026), published July 2, 2026.