Any given Tuesday after the hype: what really breaks when startups and giants compete for the same customer
While reports celebrate the “collaboration” between corporations and startups, a bank director, a doctor, a retailer, a fleet operator, and a university president are all grappling with the same problem: their business models no longer fit reality. This article is a live autopsy of five industries, told from a workday no one will ever put in a pitch deck.
The Hook: Five Emergency Calls Before Coffee
It’s 8:07 in the morning and Laura still hasn’t finished her first coffee when her phone rings for the fifth time.
Laura runs a business unit at a large Spanish bank. Glass office, boardroom with a view, bonus tied to ROE. In theory, one of the system’s winners. In practice, today it feels like the red phone in a war room.
- The CFO forwards her some news: the shadow banking system now moves more money than traditional banking and is nearing record figures. The Financial Stability Board talks about vulnerabilities, leverage, lack of liquidity. Meanwhile, global financial assets hit $503.7 trillion. The world is swimming in money… but every euro is harder to raise.
- The head of factoring reminds her of the pressure: in Spain, invoice assignment has reached almost €270 billion in 2025, close to 25% of GDP if you add factoring and confirming. Manufacturing, commerce, and transport are the main users. And every one of those euros is fertile ground for a fintech that has no branches, no paper files, and no powerful unions.
- A VC friend sends her a demo of an embedded‑finance app: credit, payments, and insurance built into a mobility marketplace. The app doesn’t say “we’re a bank.” The user doesn’t ask. They just know they travel, buy, and pay without thinking.
- The risk department is talking about the 2023 financial crisis, bank failures, and liquidity that evaporated in hours. They’re asking her for more capital, less risk, more controls.
- The innovation committee is pushing to launch “yet another” app because “young people prefer everything on their phones.” No one dares to say that the problem is no longer the phone, it’s the model.
Laura hangs up, looks at the screen, and thinks something she won’t say in the committee: “We’re not competing against startups. We’re competing against a reality that changed without warning and that our Excel sheets don’t know how to model.”
That Tuesday doesn’t belong only to Laura. It’s the same Tuesday for:
- Marta, medical director at an overwhelmed hospital.
- Carlos, CEO of a retail chain watching e‑commerce eat his margins.
- Diego, head of operations at a transport company seeing value flow to platforms.
- Ana, vice‑chancellor at a university losing students to online courses done from the couch.
Five people, five industries, and the same discomfort: the “startups vs giants” narrative no longer explains what’s happening.
The Genesis: How We Built Excel Castles on Shifting Ground
For years we were told a simple story:
Slow giants with marble and branches vs. fast startups with apps and hoodies.
It was comforting. It let incumbents see themselves as stable and startups as cute experiments. But reality became less aesthetic and more uncomfortable.
- Traditional banks kept optimizing branches while non‑bank intermediation grew to 51% of global financial assets by 2024.
- Hospitals kept thinking in beds and operating rooms while virtual consultations proved that part of medicine doesn’t need walls.
- Physical retail doubled down on store refurbishments while users were training their finger on “Buy now.”
- Transport companies invested in fleets while value migrated to platforms managing demand.
- Universities obsessed over rankings and campuses while people started learning on their phones with short, practical courses.
Meanwhile, startups embraced the opposite narrative:
Hypergrowth, disruption, winner‑takes‑all, network effects.
Both sides defined themselves by opposition, not by reality. And that’s how we reached 2023‑2025 with a global financial crisis, rising interest rates, historic rotation of capital from the US to Europe, slowdown in emerging economies like Mexico, and one quiet figure: 85% of Spanish startups don’t survive their first three years.
The myth was binary. The market wasn’t.
The Invisible Conflict: No One Designs the Business Model for the Bad Tuesday
Back to Tuesday.
- Laura (banking) isn’t thinking about blockchain. She’s thinking about how to sustain factoring and confirming margins when platforms emerge that can offer the same without the drag of branches.
- Marta (healthcare) doesn’t dream of a clinical metaverse. She wonders how to care for chronic patients when the hospital is full, doctors are burned out, and patients expect immediacy.
- Carlos (retail) isn’t debating omnichannel in the abstract. He’s looking at a P&L where rents are rising, in‑store traffic is falling, and online sales don’t make up the difference.
- Diego (mobility) isn’t fantasizing about flying cars. He’s fighting tiny margins while an app sets the customer’s final price.
- Ana (education) isn’t obsessed with blockchain diplomas. She fears her master’s programs will be empty because people prefer short, cheap, up‑to‑date programs.
The part almost no one mentions at conferences:
Most business models —of giants and startups— are designed for the good day in the cycle, not for the violent shake‑up.
What’s Missing From the Conversation
- Real economic resilience: What happens when rates rise, investment falls, and easy capital disappears?
- Dependence on invisible third parties: APIs, regulators, investment funds, tech giants. Few people put them into the “business model.” Until they fail.
- Misalignment with the real customer: users want their problem solved; they care little whether it’s by a giant, a startup, or a cooperative.
- Time: business models have been tuned for growth; almost none have been tuned for endurance.
With this in mind, let’s look at the five industries through the uncomfortable lens of that Tuesday.
Financial Services: When the Money Exists but the Model No Longer Fits
Laura’s Tuesday
At 10:30, Laura joins a call with an e‑commerce marketplace that wants to offer credit to its sellers. Before, that was natural banking territory. Today, the partner’s question is different:
“Can we embed your scoring and your credit inside our platform? The customer shouldn’t leave our app.”
Laura hears and understands the subtext: “We want your balance sheet, not your brand.”
Context and Players
- Universal banks, former savings banks turned into banks, insurers, investment funds.
- Rise of embedded finance: payments, credit, and insurance built into retail, mobility, or software platforms.
- Non‑bank intermediation (shadow banking) surpassing traditional banking in assets.
Business Models in Friction
| Aspect | Incumbent Financials | Startups / Fintech / Embedded Finance |
|---|---|---|
| Value proposition | Safety, wide product range, regulatory compliance, “seriousness” | Seamless, almost invisible experiences; specific products (BNPL, micro‑loans, PFM); integration into other journeys |
| Customer segments | Mass market, with bias to banked clients and mid‑/large‑sized firms | Underserved, young people, freelancers, micro‑businesses, platform users |
| Revenue streams | Interest, fees, service charges, spreads | Transaction commissions, subscriptions, revenue share with platforms, freemium models |
| Cost / asset structure | Branches, physical network, staff, legacy systems, regulatory capital | Cloud infrastructure, small teams, proprietary tech, reliance on third parties for licenses or balance sheet |
| Scalability / geography | Constrained by local regulation, licensing, rigid structure | Fast via APIs and partnerships, but fragile in regulation and funding dependence |
What the Excel Sheet Misses
- Factoring and confirming in Spain account for nearly 25% of GDP. A huge volume that can be repackaged as a fintech product.
- Shadow banking leads in debt instruments (61.4%), while traditional banks still dominate loans (81.3%). Credit is fragmenting.
- In Mexico, financial and insurance services are already the third‑largest sector by remuneration. Lots of jobs, little flexibility.
Laura’s biggest mistake wouldn’t be ignoring fintechs. It would be to keep thinking her “competition” is only banks and neobanks, when part of the business is drifting, almost silently, to e‑commerce, mobility, and SaaS players acting like banks without calling themselves banks.
Healthcare: When the Consultation Has Already Started on the Patient’s Screen
Marta’s Tuesday
It’s 11:15. Marta leaves an ICU exhausted. She has three emails in her inbox she doesn’t know where to put:
- A telemedicine startup offers a 24/7 video consultation pilot.
- The IT department is pushing for a new electronic medical record system.
- A group of young doctors sends her a message thread: “Our patients already use apps for glucose tracking. Why does the hospital ignore that data?”
Marta doesn’t hate technology. She hates solutions that don’t fit her shifts, waiting lists, and budget.
Context and Players
- Public and private hospitals, clinics, insurers.
- Digital health startups: telemedicine, remote monitoring, wellness apps, appointment platforms.
Two Ways of Understanding “Caring for Someone”
| Aspect | Traditional Healthcare System | Startups / Digital Health |
|---|---|---|
| Value proposition | In‑person care, high complexity, comprehensive diagnosis and treatment | Remote access, convenience, prevention, continuous monitoring, real‑time data |
| Customer segments | General population, with priority to emergencies and complex chronic patients | Digital patients, working population, rural areas, people with limited time |
| Revenue streams | Fee‑for‑service, insurance, public funding | Subscriptions, pay‑per‑online‑visit, device sales and related services |
| Cost / asset structure | Heavy physical infrastructure, expensive equipment, large staff, rigid rosters | Tech platforms, small teams, some external doctors, variable costs per use |
| Scalability / geography | Limited by facilities and medical posts | High scalability in low‑complexity segments, relatively easy international expansion |
The Common Blind Spot
Startups tend to overestimate their ability to “replace” the hospital; hospitals underestimate their ability to complement with hybrid models.
Marta can’t virtualize an ICU, but she can outsource part of chronic patient follow‑up to a digital platform. The question is no longer “telemedicine yes or no”, but:
Which part of the care model can leave the building without collapsing quality or economic margin?
Retail / E‑commerce: The Margin Leaks Through the Checkout You Don’t See
Carlos’s Tuesday
At 13:00, Carlos gets the monthly report: stable sales, shrinking margins, falling in‑store traffic. Online is growing but doesn’t offset logistics or digital marketing costs.
Meanwhile, a local e‑commerce startup, without a single physical store, has just closed a big round. It sells lower volume but has better data insight, lower fixed costs, and more room to experiment with pricing.
Context and Players
- Large retail chains, supermarkets, brands with store networks.
- Global marketplaces, direct‑to‑consumer e‑commerce, quick commerce apps.
Two Cash Registers, Two Models: Physical vs Invisible
| Aspect | Traditional Retail | Native E‑commerce / Startups |
|---|---|---|
| Value proposition | Physical experience, human service, immediate availability | Huge variety, convenience, algorithmic personalization, home delivery |
| Customer segments | Local customers, shoppers who like to see/touch, less digital audience | Mobile‑first users, time‑sensitive buyers, price and variety seekers |
| Revenue streams | Direct sales, in‑store promotions, private labels | Online sales, marketplace commissions, subscriptions (prime‑style shipping), ads, affiliates |
| Cost / asset structure | Rents, store inventory, large staff, traditional logistics | Central warehouses, last mile, tech, heavy digital marketing |
| Scalability / geography | Slow: needs new stores and leases | Fast: expansion via logistics hubs and local agreements |
The Trap of Misunderstood “Omni”
Carlos hears the same consulting advice every week: “You have to be omnichannel.” Translation: add channels without touching your cost and margin model.
The problem isn’t choosing between physical and e‑commerce. It’s that many incumbents try to run two marathons with one pair of legs: they carry the cost of a physical network and the cost of digital logistics with structures designed for a single reality.
Meanwhile, startups burn capital on customer acquisition. And when rates rise, the cost of capital stops forgiving those mistakes.
Mobility / Transport: Who Keeps the Value When the Vehicle Is a Commodity
Diego’s Tuesday
It’s 15:30 and Diego is reviewing the numbers at his transport company. Trucks, buses, drivers, fuel. Pain every time diesel goes up.
At the same time, an international app wants to use part of his fleet to offer urban services under its brand. They bring demand; he brings the asset and the risk. In return: tight fares, strict conditions, limited visibility.
Diego sees the play:
“If I accept, I survive in the short term but give up price control. If I don’t, I lose volume now and maybe the market tomorrow.”
Context and Players
- Traditional operators: freight transport, intercity buses, regulated taxis.
- Platforms: ride‑hailing, car‑sharing, multimodal apps, logistics aggregators.
Wheel Model vs Screen Model
| Aspect | Traditional Transport | Mobility / Platform Startups |
|---|---|---|
| Value proposition | Physical transport capacity, regulatory compliance, reliability | Orchestrate demand, unified user experience, route and price optimization |
| Customer segments | Companies, public sector, local users | Hyper‑connected users, tourists, e‑commerce needing flexibility |
| Revenue streams | Regulated fares, service contracts, B2B deals | Per‑ride/shipment commissions, dynamic pricing, deals with cities or retailers |
| Cost / asset structure | Own fleet, maintenance, fuel, salaried staff | Tech, marketing, data; fleet owned by third parties (drivers or partners) |
| Scalability / geography | Limited by licenses, fleet, capital | Potentially high, but subject to local regulation and supply availability |
The Dirty Trick
Platforms sell “flexibility” to drivers and “convenience” to users. In reality, they are shifting value from the physical asset to control of demand and data.
Diego can be replaced by another operator. The platform, if it gains scale, can’t.
Education: Selling Degrees When People Want to Sell Skills
Ana’s Tuesday
At 17:00, Ana sits in an academic committee debating a new master’s program. Two years, on‑site, expensive, with a syllabus that will take another two years to update.
Meanwhile, an online platform launches a six‑month “nano‑master,” 100% remote, job‑oriented, with mentors from tech companies. Cost: less than half. Time from idea to market: months, not years.
Ana knows universities still think as if their monopoly over degrees were worth as much as ten years ago. But the job market isn’t buying just “degrees” anymore, it’s buying skill signals.
Context and Players
- Public and private universities, business schools, technical institutes.
- Online course platforms, bootcamps, specialist academies.
Eternal Degree vs Iterative Learning
| Aspect | Traditional Education | Startups / Edtech |
|---|---|---|
| Value proposition | Official degrees, prestige, campus experience, broad curricula | Flexible, fast training focused on specific skills, employability‑oriented |
| Customer segments | Young people seeking university degrees, elite professionals in postgrads | Career‑changers, self‑taught learners, people who can’t stop working |
| Revenue streams | Tuition, exam fees, public subsidies, donations | Course fees, subscriptions, B2B deals with companies, revenue share with instructors |
| Cost / asset structure | Campus, classrooms, permanent faculty, academic bureaucracy | Tech platform, content, marketing, flexible instructor network |
| Scalability / geography | Slow, regulated, dependent on accreditation | Very fast, especially in unregulated content |
Recurring Myopia
Ana sees many programs designed around supply (what the university can teach) rather than demand (what companies need). Meanwhile, edtechs make the opposite mistake: designing only for immediate demand and neglecting depth, rigor, or research.
The result:
- Expensive degrees that age badly.
- Cheap courses that sometimes overpromise.
The gap between the two models is the real opportunity, but exploiting it requires changing incentives, not just platforms.
Cross‑Industry Table: The Silent Scoreboard of Winners and Losers (for Now)
Imagine we could see our five characters’ Tuesday as a single board.
The Winners vs. Losers Scorecard (Today)
| Industry | Who controls the customer relationship | Who carries more structural risk | Who’s more exposed to the economic cycle |
|---|---|---|---|
| Financial services | Fragmented: traditional banks + embedded‑finance platforms | Regulated banks and leveraged funds | Banks and unprofitable fintechs |
| Healthcare | Hospitals and insurers, but startups gaining ground in low complexity | Hospitals (infrastructure) and professionals | Public/private systems and insurers |
| Retail / e‑commerce | Marketplaces and e‑commerce platforms | Physical retail and logistics operators | Indebted brick‑and‑mortar retail |
| Mobility / transport | Mobility apps and aggregators | Operators with their own fleet and drivers | Asset‑intensive companies |
| Education | Still universities for official degrees; edtech for upskilling | Universities (fixed costs) and indebted students | Private centers and students paying high fees |
Notice something uncomfortable:
- Customer relationship control is moving towards platforms and digital experiences,
- while hard risk (assets, regulation, stable workforce) stays with incumbents or peripheral players.
Evidence and Insights: When Numbers Turn Into Daily Friction
We don’t need more slogans. We need to fuse numbers with what Laura, Marta, Carlos, Diego, and Ana live.
- Non‑bank intermediation already accounts for 51% of global financial assets, while central banks shrink their balance sheets. Translation: part of the business escapes to less regulated, more fragile, more profitable areas… until it stops being so.
- Factoring + confirming handle in Spain a volume close to 25% of GDP. Huge opportunity for fintech; direct pressure on bank margins.
- 85% of Spanish startups die before three years, due to lack of funding and strategic errors. Heroic narrative, awful P&L.
- Collaboration between traditional companies and startups is already a mantra: in real estate, more than 60% on both sides see it as key to growth. But… almost no one debates who keeps the data, the extra margin, and pricing power.
- The 2023 global financial crisis showed the obvious that everyone pretended to forget: financial innovations are fantastic while the cycle helps. When rates rise and liquidity tightens, model resilience is tested in real time.
- Mexico is an example of an economy with a heavy weight of financial and insurance services in wages, but hit by tariff threats, a 39% drop in foreign investment, and GDP growth falling to nearly a third from one year to the next.
Yet both incumbents and startups still plan as if all this were a series of anomalies, not a new structural regime.
The Strategic Shift: Stop Copying Pitch Decks and Redesign Tuesday
If you’re Laura, Marta, Carlos, Diego, or Ana, you don’t need more theory. You need to change how you think about your Tuesday.
1. Redefine Who Your Competitor Really Is
- Laura doesn’t just compete with neobanks. She competes with any platform that can embed credit or payments.
- Marta doesn’t just compete with another private hospital. She competes with apps turning chronic patients into users with continuous data.
- Carlos doesn’t just compete with the store at the mall. He competes with the phone feed.
- Diego doesn’t just compete with another bus company. He competes with whoever controls the route map on the user’s phone.
- Ana doesn’t just compete with another university. She competes with whoever offers the training that your HR team is already recommending to employees.
Uncomfortable action: draw your competitive map without your industry’s logos. Only customer journeys: information, decision, payment, use, renewal. You’ll see who slipped in.
2. Change the Risk Model, Not Just the Interface
- Banks can’t keep lending their balance sheets to third parties without rethinking how credit risk and profit are shared.
- Hospitals must consider partnerships where the startup takes on part of outcome risk (e.g., pay for health outcomes, not just consultations).
- Retail needs to stop seeing logistics as a cost center and admit it’s part of the product; maybe share risk with last‑mile operators.
- Mobility operators must renegotiate platform contracts so they’re not just commoditized suppliers.
- Universities need revenue‑share models with edtech and companies tied to real employability.
3. Stop Optimizing for a Single Economic Cycle
When rates were low and money was cheap, almost everything went. Not anymore.
- Models based on growing at a loss without a clear destination are dead in almost every industry, except true emerging monopolies.
- Incumbents must stop hiding money‑losing projects in vague budget lines.
Uncomfortable action: rebuild your financial models with higher interest rates, lower growth, and constrained capital. If the model doesn’t hold, it’s not a model; it’s a bet.
4. Redefine Incumbent‑Startup Collaboration
Stop using “collaboration” as a filler word. Questions that should be in every deal:
- Who keeps derived usage data?
- Who sets the final customer price?
- Who bears regulatory risk?
- What happens if funding dries up and the startup dies?
If you’re a startup, you should also ask:
- What if the incumbent decides to build my product in‑house after learning from me?
- Where in the chain do I capture defensible value, not just temporary revenue?
Actionable Insights: The Minimum Manual to Survive Next Tuesday
For Incumbents
-
Re‑architect the business model
- Define which part of your business is regulated / capital‑intensive core and which part can be orchestrated via platforms or partners.
- Don’t try to “be a startup everywhere”; choose 1‑2 areas where a portfolio‑of‑bets logic makes sense.
-
Data and customer relationship governance
- Never sign a partnership where you lose usage visibility or the ability to contact the end customer.
- Build a “data P&L”: what revenue does your information on customers and operations generate, directly or indirectly?
-
Orderly shutdown capability
- Design from the start ways to switch off projects that don’t reach escape velocity. Most corporates don’t kill projects; they let them languish.
-
Explicit financial resilience
- Stress‑test your model with 2023‑style scenarios: liquidity crunch, investment drop, capital rotation.
- Adjust dividend, buyback, or capex policies to less optimistic realities.
For Startups
-
Less PowerPoint, more unit economics
- If your model only works with infinite capital and subsidized CAC, you don’t have a model.
- Measure ruthlessly: payback period, margin after cost to serve, reliance on a single distribution channel.
-
Avoid the “interface but not the flow owner” trap
- If you’re just a pretty layer on top of others’ infrastructure, they can copy you whenever they want.
- Identify at least one chain node where you’re critical, not replaceable: algorithm, data, community, regulatory know‑how, etc.
-
Design for cycles, not for rounds
- Your horizon isn’t the next funding round, it’s the next economic cycle. We’ve already seen how a Fed speech can move whole markets.
-
Choose your giant wisely
- A bank with a suffocating cost structure may see you as a flotation device — or as disposable material.
- An overwhelmed hospital may want your solution… as long as it doesn’t touch internal incentives.
For Both
- Measure Tuesday, not the slide deck: how much of what you say in strategy meetings shows up in actual calendars, calls, and pricing decisions?
- Change the internal narrative from “defend market share” to “reposition our role in the value chain.”
The Bigger Picture: Maybe Neither Giants Nor Startups Will Win
Back to Tuesday, almost night.
Laura looks at the city from her office. Marta leaves the hospital with her phone buzzing again. Carlos checks unsold inventory. Diego calculates the cost of renewing part of his fleet. Ana replies to an email from an edtech platform seeking a “strategic” agreement.
Somewhere in their minds, they all think they’re in a win‑lose game against the other side.
Reality is more cynical:
- When business models don’t fit the real economic cycle, customers lose: expensive loans, waiting lists, inflated prices, poor‑quality services.
- When both sides assume capital will always be there, workers lose: precarious gig work, hospital burnout, underpaid lecturers, squeezed drivers.
- When no one pays the cost of designing resilience, the system loses: financial crises, bank failures, zombie startups, overstretched public infrastructure.
The cliché said: “Startups will win; giants will fall.”
The polished version said: “They’ll collaborate and everyone will win.”
The honest version might be this:
Only those who redesign their Tuesday, not their slide deck, will win.
Those who accept that their real competitor is economic reality, not the other side’s slogan.
If anything, the 2023 global crisis, shadow banking overtaking traditional banks, capital rotation, the collapse of startups without unit economics, and the slow siege of classic business models have taught us that the system doesn’t forgive arrogance.
Not marble arrogance, not hoodie arrogance.
The brutal, simple question for next Tuesday is:
If tomorrow capital becomes even more expensive, regulation tighter, and customers even more impatient, is your business model still alive — or was it just a quirk of the last cycle?
Ask yourself that before your competitors do. Or the market will ask it for you, without anesthesia.
References
- Financial Stability Board (FSB). Global data on shadow banking and worldwide financial assets, 2024.
- Cinco Días / El País. "La cesión de facturas en España asciende a 269.885 millones en 2025".
- Cinco Días / El País. "La banca en la sombra mueve ya más dinero que la banca tradicional y enfila cifras récord".
- Autonomosyemprendedor.es. "El 85% de las startups españolas no supera los tres años de vida".
- Corresponsables.com. "Mayor colaboración entre startups y empresas tradicionales inmobiliarias".
- El País (branded content). "Las finanzas integradas revolucionan los servicios financieros".
- Banco Santander Chile. "Optimismo del mercado se sacude ante un endurecimiento en el discurso de la Fed".
- Cinco Días / El País. "Los gestores aceleran la rotación de la renta variable de EE UU a Europa".
- El País México. "Menor inversión y actividad industrial: la economía mexicana muestra focos de alerta".
- Wikipedia. "Crisis financiera global del 2023".
- Wikipedia. "Economía informal en México" (context for financial and insurance services sector).
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