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Independent Technology Review Issue 001 · July 2026 · 100 Montaditos

100 Montaditos revolutionized low-cost dining. Now let's imagine its next evolution.

We analyzed its in-store experience, website, ordering, loyalty, operations and data to imagine a possible technological evolution — while respecting what already works.

Reading time~8 minutes
DateJuly 2026
ReferenceXR-001
Analysis confidenceMedium-high · public sources only
+300 M€
annual revenue of the network
+400
locations in Spain
25 years
as an iconic brand
13
opportunities identified
3
priority proposals

Figures from public sources (financial press and corporate communications). Some magnitudes correspond to the network as a whole or to the Restalia group, not only to the brand.

Chapter 00 / 09

Chapter 00 · The big idea

The next leap isn't changing what works. It's connecting better every part of the business.

Customer, order, payment, kitchen, pickup, loyalty, data and prediction. Today each piece can live separately. The opportunity is to turn them into a single system where every order feeds the next.

Customer
Order
Payment
Kitchen
Pickup
Loyalty
Data
Prediction

It's not a rupture — it's a smarter continuity. In the following chapters you'll see the three opportunities with the greatest impact, the system that makes them possible and how they would be validated with data.

Chapter 01 · Opportunity A CPPA proposal

A second round shouldn't require a second queue.

Today, the table QR leads to the menu. The possible evolution: that it also lets you order and pay, without going back to the counter.

Today
  1. The table QR shows the menu
  2. To order, you have to go to the counter
  3. You queue
  4. You order and pay
  5. You pick up
Possible evolution
  1. Scan the QR
  2. See the menu
  3. Order and pay from your phone
  4. The kitchen receives it
  5. Your phone notifies you
9:41Table 12
M
Your table
ORDER · PAY · NO QUEUE
Montadito Nº1 · Ham
CLASSIC
1,50€
Montypizza
MONTYS
3,50€
Cruzcampo pitcher
DRINK
2,50€
Pay 7,50€
9:43#A-204
M
Your order
IN PREPARATION
Paid9:43
Received in kitchen9:43
Preparing~4 min
Ready for pickup
Order another round
Less friction More capacity at peak More second rounds First-party data

Metrics to validate in the pilot

Time to order Adoption of the QR Ticket QR vs counter Rounds per table

Hypothesis To check on-site

  • Actual queue time at peak hours
  • Current second-round process
  • Integration with POS and kitchen

Chapter 02 · Opportunity B CPPA proposal

Finding what you can eat shouldn't require opening a PDF.

A digital menu that adapts to each customer and each location.

Today Verified
  1. Allergens in PDF
  2. Lengthy documents
  3. Scattered information
  4. Ask the staff
Proposal · filters
  1. Gluten-free
  2. Lactose-free
  3. Vegan
  4. Availability by location
9:41Menu · your location
M
Menu
FILTER BY YOUR DIET
GLUTEN-FREELACTOSE-FREEVEGAN
Cajun chicken + BBQ
GLUTEN-FREE
2,20€
Bacon + cheese
GLUTEN-FREE
2,20€
Wine-braised pork cheek
GLUTEN-FREE
2,50€
SHOWING 5 OF 100 · AVAILABLE AT THIS LOCATION
Official assistant · AI
What can I order gluten-free here?
At this location there are 5 gluten-free montaditos, served with gluten-free bread. Source: official product database · location availability For a severe allergy, confirm with the staff.
Safeguard: the information always comes from the official product database and does not replace the location's food safety protocols.
More clarityMore trust Fewer repeated questionsMore inclusion

Chapter 03 · Opportunity C CPPA proposal

A brand with this volume of customers should be able to recognize those who always come back.

Loyalty, history and promotions based on real behavior.

Club Monti · digital card
Hi, Fran
140 points
Order history · reward at 3 stamps
Illustrative example
“Fran usually orders 3 montaditos and a pitcher on Wednesdays.”
Today, your usual combination has a reward.

It's not a mass discount: it's a targeted offer, built on real history and preferences.

IdentificationFrequency HistoryPreferences Cross-sellingRetention Reclaim the data from third parties

Chapter 04 · The invisible system

What the customer sees is simple. What makes it possible, is not.

A single brain for the in-store channels and the delivery platforms.

Counter
QR at table
Kiosk
Glovo
Uber Eats
Just Eat
Order orchestrator
integration layer
POS
KDS · kitchen
Order status
CRM
Analytics
It's not about replacing the internal systems without knowing them, but about creating a compatible integration layer with the existing technology — one that orchestrates orders from all channels toward a single kitchen and a single database.

Chapter 05 · Quick wins

Improvements that could start before touching the operational core.

Only quick, low-risk improvements, without touching the POS or the kitchen. Everything that touches the operational core lives in the strategic chapters.

01

Digital allergen menu

Filters by diet and availability by location, built on the official product database.

ImpactHigh
ComplexityLow
HorizonWeeks
DependencyProduct database
02

Restaurant finder

Locator with filters: open now, terrace, gluten-free, delivery.

ImpactMedium
ComplexityLow
HorizonWeeks
DependencyLocation data
03

Navbar, contrast and legibility

Readable menu on scroll and accessible contrast across the whole site.

ImpactMedium
ComplexityLow
HorizonWeeks
DependencyFrontend
04

Accessibility (WCAG)

Keyboard navigation, labels and visible focus on the site and menu.

ImpactMedium
ComplexityLow
HorizonWeeks
DependencyFrontend
05

SEO and metadata

Titles, descriptions and structured data for search engines and social networks.

ImpactMedium
ComplexityLow
HorizonWeeks
DependencyContent
06

Performance (Core Web Vitals)

Load speed, visual stability and interactivity measured and improved.

ImpactMedium
ComplexityLow
HorizonWeeks
DependencyFrontend

Chapter 06 · Data vision

Every order can improve the next one.

Sales data could feed demand prediction, stock, shifts, waste and kitchen times.

Operations panel · weekly forecastSimulated data
Sales · next hour
312
estimated tickets
Kitchen load
78%
capacity
Euromanía demand
+34%
vs average day
Forecast sales by hour — Wednesday
121314152021222300
Critical stock
Montadito breadrestock
Beer (keg)ok
Montypizza baselow
Gran reserva hamok
Staffing recommendation
Add +1 person between 20:00 and 22:00 on Wednesday.

All values in the panel are simulated data for illustrative purposes. The real impact would depend on the quality of the internal sales data.

Chapter 07 · Roadmap

From digital clarity to intelligent operations, in three phases.

Phase 1

Digital clarity

0–3 months
Goal
Visible value without touching the operational core.
Scope
Digital menu · website · AI assistant · prototypes.
Metrics
CWV, filter usage, resolved queries.
Decision: continue only if there's adoption.
Phase 2

Connected pilot

3–9 months
Goal
Validate the loop order → kitchen → loyalty.
Scope
POS/KDS · QR · status · loyalty · 5–10 locations + control.
Metrics
Peak wait, QR ticket, identified sales.
Decision: scale only with a proven result.
Phase 3

Intelligent operations

9–24 months
Goal
Data-driven operations at network scale.
Scope
Personalization · direct channel · prediction · stock · shifts.
Metrics
Forecast error, waste, retention.
Decision: rollout in waves, location by location.

You don't scale a hypothesis.
You scale a proven result.

Chapter 08 · Complexity and dependencies

No financial figures. Only complexity, time and dependencies.

We rank each initiative by real difficulty, not by price. The investment would be defined in a discovery phase with access to the systems.

InitiativeComplexityTimeDependenciesImpact
A menu that understands youLowWeeksOfficial product databaseHigh
Web quick winsLowWeeksFrontendMedium
Club Monti (loyalty)MediumMonthsCRM · customer identityHigh
Data-driven operationsMediumMonthsSales dataMedium-High
Order and pay at the tableHighMonthsPOS · kitchenHigh
Connected systemHighMonthsPOS · KDS · deliveryStructural
This X-RAY does not include a budget. Any investment estimate would require a technical discovery phase and access to the existing systems.

Chapter 09 · Validation and visit

A good analysis doesn't pretend to know what it doesn't know.

Verified Facts with public sources

  • Self-service model with a buzzer
  • Delivery supported by third-party platforms
  • Allergens in PDF; gluten-free only at participating locations
  • No public evidence of modern loyalty
  • Recurring promotional peaks (Euromanía)

Hypothesis To validate on-site

  • Actual queue time at peak hours
  • Second-round process
  • Order-ticket system and presence of KDS
  • Manual re-entry of delivery orders
  • Technology of the incumbent POS

From public analysis to operational reality.

Time the actual queue in three time slots
Observe the second-round process
Identify the order-ticket system and whether there's a KDS
Check whether delivery orders are re-keyed
Verify the real availability of gluten-free options
Review accessibility, cleanliness and table turnover

Just a conversation

If any of these ideas connects with your company's vision, we'd love to talk.

No commitment. No endless presentations. Just a conversation between people who are passionate about building better products.

Let's talk whenever you like →
If this level of analysis is possible with public information alone, imagine what we could discover working alongside your team.
CPPA X-RAY · XR-001 · Independent Technology Review