Technologien, Märkte und Kundenbedürfnisse verändern sich schneller den je. So schnell, dass Wettbewerber in kürzester Zeit ganze Branchen umkrempeln können.
Wer nicht kontinuierlich neue Lösungen entwickelt, verliert Differenzierung, Margen und im Extremfall seine Existenzberechtigung im Markt.
Innovationskraft ist in Zeiten wie diesen also essenziell. Und sie ist keine Initiative, sondern eine Führungsaufgabe.
Eine der wirkungsvollsten Hebel dafür ist die strukturierte Zusammenarbeit mit Startups.
Startups bringen spezialisierte Technologien, hohe Geschwindigkeit und neue Geschäftslogiken ein. Sie arbeiten fokussiert an klar abgegrenzten Problemen und sind gezwungen, Lösungen unter realen Marktbedingungen zu validieren. Für etablierte Unternehmen bedeutet das Zugang zu externem Innovationspotenzial, ohne alles selbst entwickeln zu müssen.
Die Form der Zusammenarbeit hat dabei viele Gesichter. Von „Testkunde“ bis Joint Venture oder Beteiligung hat dabei jede Variante eigene Chancen, Risiken und Anforderungen. Entscheidend ist, das passende Modell zur eigenen Strategie, Kultur und Risikobereitschaft zu wählen und es professionell zu orchestrieren, statt „einfach mal ein Startup zu testen“.
Die wichtigsten Kooperationsmodelle mit Startups
Die folgenden Modelle unterscheiden sich vor allem im Grad der Integration und im Risiko für das Unternehmen. Die Reihenfolge orientiert sich grob an einem steigenden Commitment:
Venture Clienting stellt in der Regel das risikoärmste Modell dar, da Unternehmen lediglich Kunde einer Lösung werden und diese zunächst in einem klar abgegrenzten Use Case testen.
Mit zunehmender Tiefe der Zusammenarbeit steigen typischerweise auch Kapitalbindung, organisatorischer Aufwand und strategische Abhängigkeiten. Modelle wie Corporate Venture Capital oder M&A erfordern daher deutlich stärkere langfristige Verpflichtungen.
1. Venture Clienting
Beim Venture Clienting wird das Unternehmen zum Pilotkunden eines Startups. Die Lösung wird in einem klar definierten Use Case pilotiert und bei Erfolg skaliert.
Vorteile
- Schneller Zugang zu marktreifen Technologien
- Kein Beteiligungs- oder Integrationsaufwand
- Objektive Nachweisbarkeit, dass der Einsatz der Startup-Lösung konkrete Verbesserungen im operativen Geschäft erzielt, z. B. durch Zeitersparnis, Kostenreduktion, Qualitätsverbesserung oder Produktivitätssteigerung
- Kürzere Zeit von der Produktidee bis zur Markteinführung
Herausforderungen
- Das Unternehmen muss organisatorisch in der Lage sein, ein Projekt mit einem Startup durchzuführen. ****In großen Organisationen sind Prozesse stark reguliert und langsamer. Hürden sind zum Beispiel:
- Längere Dauer von Einkaufsprozessen
- komplizierte IT-Freigaben
- Datenschutz oder IT-Security verhindern die Nutzung neuer Tools
- Budgets für kleine Experimente existieren nicht
- Ohne klare Erfolgskriterien entstehen Pilotprojekte ohne Rollout
Sinnvoll, wenn konkrete Problemstellungen vorliegen und eine pragmatische, risikoarme Testphase gewünscht ist.
2. Open Innovation Challenges und PoCs
Unternehmen definieren konkrete Problemstellungen und schreiben Challenges aus, auf die sich Startups bewerben. Die besten Teams werden zu einem Pilotprojekt eingeladen (Proof of Concept).
Vorteile:
- Fokus auf konkrete Business-Challenges.
- Vergleich mehrerer Lösungsansätze.
- Wettbewerb sorgt für hohe Lösungsqualität.
Herausforderungen:
- Aufwand in Scouting, Bewertung und Projektmanagement.
- Risiko, dass PoCs nicht skaliert werden, wenn keine Anschlusslogik existiert.
Sinnvoll, wenn klar definierte Use Cases bestehen und strukturiertes Scouting gewünscht ist.
3. Venture Partnering / strategische Partnerschaften
Hier arbeiten Unternehmen und Startups längerfristig zusammen, oft mit Co-Entwicklung oder gemeinsamen Marktzugängen.
Vorteile:
- Tiefe Integration der Technologie in Produkte, Prozesse oder Angebote.
- Gegenseitige Stärkung: Startup profitiert von Marke, Distribution, Know-how; Corporate von Geschwindigkeit und Innovation.
Herausforderungen:
- Starke Abhängigkeit von einzelnen Partnern möglich.
- Hoher Abstimmungsaufwand (Roadmap, Prioritäten, Ressourcen).
Sinnvoll, wenn strategischer Fit, Roadmap-Kompatibilität und gegenseitige Commitment-Bereitschaft gegeben sind.
4. Corporate Venture Capital
Über eine CVC-Einheit investiert das Unternehmen in Startups mit strategischer Relevanz.
Vorteile
- Frühzeitiger Zugang zu Technologien
- Strategische Option auf zukünftige Integration
- Potenzieller finanzieller Return
Herausforderungen
- Kapitalbindung und langfristiger Investmenthorizont
- Governance, Interessenskonflikte und IP-Fragen
- Strategische Ziele dürfen nicht hinter Renditeerwartungen zurückstehen
Sinnvoll, wenn eine klare Innovations- und Investmentstrategie existiert und entsprechende Governance-Strukturen aufgebaut sind.
5. M&A und Joint Ventures
Die tiefste Integrationsform ist die Übernahme oder Gründung eines gemeinsamen Unternehmens.
Vorteile:
- Volle Kontrolle über Technologie, Team und IP bei Übernahme.
- Möglichkeit, komplett neue Geschäftsfelder zu öffnen.
Herausforderungen:
- Höchster Kapitalbedarf
- Gefahr, die Startup-Kultur zu „ersticken“, wenn Integration schlecht gestaltet ist.
Sinnvoll, wenn strategische Relevanz hoch und langfristige Integration gewünscht ist.
Worauf Entscheider besonders achten sollten
1. Strategischer Rahmen
Startup-Kooperationen dürfen kein Selbstzweck sein. Definieren Sie klar, welche Innovationsfelder Priorität haben und welche Rolle externe Partner darin spielen sollen.
2. Klare Ownership
Es braucht eine verantwortliche Einheit mit End-to-End-Verantwortung von Scouting über Pilot bis Skalierung. Innovation Labs ohne operative Anbindung an Fachbereiche bleiben oft isoliert.
3. Skalierungslogik vor Pilotstart
Definieren Sie KPIs, technische Reifeanforderungen, Security-Freigaben und Budgetpfade vor Beginn eines Piloten. Sonst bleibt Innovation im Teststadium.
4. Professionelles Risikomanagement
IT-Security, Datenschutz, regulatorische Anforderungen und IP-Fragen müssen früh geprüft werden. Gleichzeitig darf das Risikomanagement proportional zum Pilotumfang bleiben.
5. Arbeitsmodus und Kultur
Startups arbeiten iterativ und ressourcenschonend. Unternehmen benötigen klare Ansprechpartner, schnelle Entscheidungen und eine Governance, die Tempo ermöglicht.
Wie Unternehmen Zugang zu relevanten Startups erhalten
Eigene Netzwerke, Konferenzen, Cluster oder Accelerator-Programme erzeugen Sichtbarkeit. Doch Dealflow allein garantiert keine Passgenauigkeit.
Hier zeigt sich die Bedeutung erfahrener Intermediäre.
Organisationen, die sowohl die Logik etablierter Unternehmen als auch die Dynamik technologiegetriebener Startups verstehen, können gezielt matchen, vorselektieren und Innovationsprojekte mitbegleiten. Sie reduzieren Suchkosten, verkürzen Entscheidungsprozesse und erhöhen die Erfolgswahrscheinlichkeit von Piloten.
Gerade im technologieintensiven Umfeld ist fundiertes Scouting, Bewertung technologischer Reifegrade und strukturiertes Matching entscheidend.
INiTS begleitet seit vielen Jahren sowohl High-Tech-Startups als auch Unternehmen bei der Anbahnung und Umsetzung solcher Kooperationen. Die Kombination aus tiefem Zugang zum Startup-Ökosystem und Verständnis für unternehmerische Entscheidungslogik schafft belastbare Brücken zwischen beiden Welten.
Fazit für CEOs und Entscheider
Wenn Sie als CEO nicht nur „Innovation“ als Schlagwort, sondern als Ergebnis sehen wollen, brauchen Sie drei Dinge:
- ein klares Zielbild,
- das richtige Kooperationsmodell pro Use Case
- und eine professionelle Orchestrierung der Zusammenarbeit mit Startups.
Venture Clienting ist dabei ein besonders wirkungsvolles Instrument, um schnell und kontrolliert Business Impact zu erzielen. Eingebettet in eine übergeordnete Innovationsstrategie und unterstützt durch erfahrene Partner aus dem Ökosystem wird aus punktueller Zusammenarbeit ein nachhaltiger Wettbewerbsvorteil.
Die Frage ist nicht, ob Sie mit Startups kooperieren sollten. Die Frage ist, wie strukturiert und strategisch Sie es tun.
Why Entering a New Market Is Like a Second Founding
In strategy decks, international expansion often appears as the logical next step. Product validated. Revenue growing. Home market stable. So let’s scale.In reality, expansion is not a rollout. It is a second founding under different conditions. Underestimate that, and you will pay twice. Once financially. Once strategically. For founders, intrapreneurs and CEOs, a new country is not an additional sales channel. It is a new system with its own incentives, cultural codes and structural constraints.
1. Strategic Fit: Why This Country and Why Now?
Before translating your website, ask the uncomfortable questions:
- Does the same problem exist with the same urgency?
- Does your business model still work under local cost structures, taxes and salary levels?
- Is there a dedicated expansion team, or is this a side project?
Expansion is a capital allocation decision.
Do not try to “go faster” until your core business at home is stable, because expansion will make existing problems blow up faster.
2. Market Research
Professional expansion follows a structured research logic. Three layers. In this order.
2.1 Desk Research
You need to understand your playing field. The goal is to narrow down the options intelligently.
- Market size and growth
- Competitive landscape
- Regulatory environment
- Purchasing power and consumption patterns
- Public funding and support structures
In our recent SCALEup Talk, we spoke with Caroline Schober, founder of neworn. It became clear just how systematic this phase needs to be. The team first analyzed multiple European markets, then prioritized those where sustainability, brand affinity, and market dynamics aligned with their model.
Zoom out. Then zoom in.
2.2 Qualitative Research
Many expansions fail because the founders misunderstood how people actually think and decide. Qualitative research is how you prevent that. Here is what that looks like in practice. First, define your key segments. For a platform like neworn, that meant distinguishing clearly between buyers and sellers. In B2B contexts, it could mean separating economic buyers, technical evaluators and end users.
Second, conduct in depth interviews. Three to five interviews per core segment is the minimum to identify patterns. These conversations should explore:
- How people currently solve the problem
- What triggers a purchase decision
- What creates trust or skepticism toward a foreign company
- How important price, brand, sustainability or convenience really are
- What would stop them from switching
Third, look for recurring themes. Not single opinions, but repeated signals across interviews. Before entering Germany and Poland, neworn spoke directly with parents in both markets to understand buying behavior, brand perception and local dynamics. The outcomes were clearly different.
In Poland, the app needed full translation. English would not have been sufficient for adoption. Brand orientation in Poland turned out to be stronger than pure sustainability messaging. In Germany, the picture was more nuanced. Even within one country, behavior varies. Parents in Berlin tend to place greater emphasis on sustainability and let that influence purchasing decisions, whereas in Munich brand perception plays a stronger role.
These are not marginal details. They affect language, feature prioritization, marketing arguments and pricing communication.
Qualitative research gives you context. And context determines strategy.
2.3 Quantitative Validation: Measure the Hypotheses
Once you have spoken to people in a new market, you will start to see patterns. For example, several interviewees might say they care more about brands than sustainability. Or that buying new clothes is easier because the item is available in all sizes, and they do not have time to look for suitable options in a second-hand store. These are good insights, but they are based on a small number of conversations. Now you need to check if they hold true at scale.
Here is how you do that.
Surveys to test willingness to pay
If 10 interviewees tell you they would pay 5 euros per month for an app that curates suitable and sustainable second hand children’s clothing, that is a promising signal. But it is still only a signal.
To test whether this willingness is real, you can run a simple market experiment.
Send an email to a few hundred people in your defined target group and announce that the app will launch soon. Invite them to join a waiting list and clearly state that access will cost 5 euros per month.
If a meaningful number of people actively sign up under those conditions, you are no longer measuring polite interest. You are measuring real intent.
People who register despite the stated price are demonstrating a concrete willingness to pay, not just theoretical approval.
This type of test helps you assess whether your price point is viable in the broader market before you invest heavily in development or marketing.
Localized test campaigns
Create simple landing pages in the local language with different messages. One focuses on sustainability, another on price, another on premium brands. Run small online ads and measure what people click on. Behavior shows you what really matters.
Competitive data
When conducting a competitor analysis for a new market, start by clearly identifying your direct and indirect competitors. Direct competitors solve the same problem in a similar way. Indirect competitors address the same need through alternative solutions.
Next, analyze their market traction. Use available tools to estimate website traffic, app downloads and visibility. This gives you an indication of demand and market maturity.
Then evaluate their positioning. What value proposition do they emphasize? Price, quality, sustainability, convenience? Study their messaging, pricing structure and target segments.
After that, examine customer feedback. Reviews and comments often reveal weaknesses, unmet needs and recurring frustrations. These insights highlight potential differentiation opportunities.
Finally, assess their business model logic. How do they monetize? Where might their cost structure create vulnerabilities? A structured competitor analysis is about understanding the competitive landscape so you can position strategically rather than emotionally.
3. Market Entry: Focused Instead of Nationwide
When expanding internationally, launching across an entire country from day one sounds logical. If the product works in a market, why not make it available everywhere?
The problem is that markets are rarely homogeneous. Cultural attitudes, purchasing behavior, income levels, and communication styles can differ significantly between regions.
When entering Germany, for example, neworn deliberately avoided a nationwide launch. Instead, the team started regionally with a focus on Bavaria and the Munich area .
This approach has several strategic advantages.
First, it concentrates marketing resources. Instead of spreading budget thinly across the entire country, campaigns can be targeted in one region where awareness can build faster.
Second, it enables faster learning. A focused launch allows the team to test messaging, pricing and product features in a defined environment.
Third, it reflects cultural realities. Even within the same country, preferences can vary widely. For instance, urban areas such as Berlin may respond more strongly to sustainability messaging, while regions like Munich may place greater emphasis on brands and perceived quality. Launching regionally allows companies to understand and adapt to these nuances.
In short, regional entry reduces financial risk and increases learning speed. Once product–market fit is confirmed locally, expansion to additional regions becomes significantly more predictable.
4. Funding and Structural Readiness
Expansion costs more than your initial spreadsheet suggests.
neworn actively leveraged public funding programs to support internationalization and marketing.
Before entering a new market, clarify:
- Funding instruments
- Tax implications
- Need for a local legal entity
- Data protection and sector specific compliance
Regulatory complexity is not an afterthought. It is either a growth barrier or a competitive advantage.
5. A Practical Expansion Checklist
Strategy
- Clear business case per country
- Defined customer segments
- Secured runway and team capacity
Research
- Market size, competition and regulation analyzed
- At least three to five qualitative interviews per core segment
- Willingness to pay validated
Entry Design
- Regional focus
- Localized positioning and messaging
- Adjusted pricing structure
Structure
- Tax and legal framework clarified
- Data protection reviewed
- Funding instruments evaluated
Pilot
- Six to twelve month test phase
- KPIs defined: customer acquisition cost, sales cycle, retention, contribution margin
- Data driven scale or exit decision
Conclusion
International expansion is a new system you have to build.
If you take a structured approach, respect local differences, and test ideas step by step, you are far more likely to succeed.
If you think a translated pitch deck is enough, you will quickly learn how costly that mistake can be.
For a real-world look at expanding from Austria into Germany and Poland, listen to the latest episode of SCALEup Talk with Caroline Schober from neworn. Caroline shares the lessons learned and reveals how being a founder shapes your personality.
Viele Geschäftsmodelle klingen auf dem Papier überzeugend.
In der Umsetzung zeigen sich dann schnell die echten Herausforderungen.
In dieser Folge sprechen wir mit Caroline Schober, Gründerin von neworn und schauen gemeinsam auf den Aufbau eines Plattformmodells in einer Branche, in der Vertrauen, Nutzerverhalten und operative Umsetzung entscheidend sind.
Themen dieser Episode:
– Wie aus einer Marktbeobachtung ein Geschäftsmodell entsteht
– Warum Nachhaltigkeit allein kein Kaufargument ist
– Was bei Internationalisierung oft unterschätzt wird
– Und was Gründen mit einem Menschen macht
Der Podcast richtet sich an Founder, Intrapreneure und innovationsinteressierte Menschen,
die verstehen wollen, wie Unternehmen unter realen Bedingungen entstehen und wachsen.
🎧
———-
Follow neworn:
And Why the Strongest Companies Combine It with Startup Collaboration
In technology-intensive industries, in-house R&D has never been optional.
It protects intellectual property, enables system integration, ensures reliability, and turns complex technologies into scalable products. Many of today’s market leaders like Bosch and Siemens exist because they invested in R&D long before returns were visible.
That remains true.
What has changed is the speed and fragmentation of technological progress.
Important technologies now develop in many different places at once: universities, startups, suppliers, open-source projects, and related industries. No single company, no matter how large or skilled, can track all of this early enough by itself.
In this environment, the strategic question is not whether internal R&D is critical. It is.
The question is whether internal R&D alone can still provide sufficient foresight, speed, and optionality.
The Structural Limits of In-House R&D in Technology-Heavy Contexts
In-house R&D in complex industries is designed for depth, safety, and long-term capability building. It is optimized for robustness, compliance, and scalability.
It is not optimized for early market discovery or fast exploration of uncertain technology paths.
That gap creates predictable limitations.
1. Time Bias Is Amplified by Complexity
In technology-intensive sectors, development cycles are long by necessity.
Hardware dependencies, certification, safety requirements, and system integration stretch timelines. Governance structures exist for good reasons.
But markets, customers, and enabling technologies move faster than internal roadmaps — faster than they have ever moved before.
By the time a new solution is technically mature, the original customer need may have shifted, combined with adjacent technologies, or been redefined entirely.
The result is not failed R&D. It is misaligned timing.
So it can happen that solutions are right but arrive too late.
2. Technical Excellence Increases Lock-In
High-performing R&D teams develop deep attachment to what they build.
That attachment is rational. Complex systems require years of expertise, iteration, and refinement.
But the deeper the investment, the harder it becomes to question the direction.
Early warning signals are often interpreted as integration challenges rather than strategic misalignment. Projects continue because technically they still make sense.
This is how technically sound initiatives survive long after their market relevance has weakened.
3. Capital-Intensive Bets Reduce Strategic Optionality
In technology-heavy industries, R&D investments are large and cumulative.
Once a path is chosen, switching becomes expensive. Not just financially, but organizationally.
Over time, companies unintentionally narrow their future options by committing early to a limited number of technological trajectories.
This creates a dangerous asymmetry:
The cost of continuing feels lower than the cost of changing direction, even when evidence suggests otherwise.
Why This Does Not Argue Against Strong Internal R&D
None of this suggests weakening internal R&D.
In technology-intensive industries, strong internal R&D is indispensable for:
- system-level innovation
- integration of complex technologies
- long-term differentiation
- safety, quality, and regulatory compliance
- scaling beyond prototypes
Organizations without deep internal capabilities become dependent on external actors and lose strategic control.
The issue is not internal R&D. The issue is internal R&D operating without external learning loops.
What Startups Contribute That Corporates Cannot Replicate Internally
Startups operate under fundamentally different constraints.
They build around narrow problems rather than complete systems. They test assumptions before optimizing solutions. They learn from real usage long before technologies are fully mature.
This makes startups effective sensors for emerging shifts.
Not because they are always right. But because they surface weak signals early.
In technology-intensive industries, those weak signals often determine future winners.
The Real Value of Startup Collaboration
When companies access startups in a structured way, three things happen.
Learning accelerates.
Exploration happens outside the core organization, before large internal commitments are required.
Bias is reduced.
External validation provides reality checks that internal teams cannot generate alone.
Optionality is preserved.
Multiple technology paths can be explored in parallel, without prematurely locking the organization into one direction.
This is not about outsourcing innovation. And it is not about copying startups.
It is about improving strategic decision-making under uncertainty.
The Companies That Adapt Best Combine Both Worlds
Across industrials, energy, mobility, and deep tech, a consistent pattern emerges.
Companies that combine:
- strong internal R&D for depth and executionwith
- structured startup collaboration for speed and external learning
adapt earlier and with less disruption than those relying on either approach alone.
They protect R&D from becoming inward-looking. And reduce the cost of being wrong.
The Leadership Implication
For executives in technology-intensive industries, innovation leadership today is about designing an innovation system that can learn faster than competitors.
In-house R&D builds strength and credibility.
Startup collaboration builds awareness, speed, and flexibility.
Together, they reduce the most dangerous risk of all in complex industries:
Realizing too late that the future has already taken shape elsewhere.
Ready to explore how startup collaboration can complement your R&D strategy?
Become an INiTS member and connect with innovative startups that can help your organization stay ahead of technological change. The membership bridges the gap between established companies and emerging ventures, creating the external learning loops that drive strategic advantage.
In the world of academia, many groundbreaking research results unfortunately never leave the university „drawer“. Lithoz, a spin-off from the TU Wien, serves as a powerful counter-example, having evolved into a „Hidden Champion“ and global market leader in the field of 3D printing for high-performance ceramics.
From Dissertation to Innovation
The story began in 2006 at TU Wien, where Johannes Homa and Johannes Benedikt conducted research for several years before founding Lithoz in 2011.
Interestingly, while Homa’s initial goal was simply to complete a dissertation, the project gained momentum when industrial partners like Ivoclar expressed interest in the technology being developed at the university.
Achieving the Technological Breakthrough
The defining challenge for Lithoz was not just making the technology work, but ensuring the 3D-printed parts matched the material properties and strength of conventional manufacturing. Until they reached this milestone, the ceramic parts were too brittle for industrial use.
Their success in achieving industrial-standard strength opened doors to high-stakes applications, including:
- Aviation: Casting cores for aircraft turbines.
- Medical Technology: Bone replacement materials, such as cranial implants.
- Dental: Dental restorations that can withstand the pressure of biting.
- Industry: Highly stressed machine components and multi-material parts combining ceramic and metal.
Scaling a „Family“ into an Organization
Growing from a small founding team to over 100 employees required significant structural adjustments. Homa notes that a company often goes through distinct phases:
- The 15-Person Stage: At this size, the company still feels like a „family“ where communication happens naturally.
- The 50-Person Stage: New management levels and structured information flows become essential as a distance develops between the founders and the employees.
- Constant Adaptation: Lithoz continues to refine its structures, recently implementing medical technology quality standards (ISO 13485) to meet industry requirements.
Lessons in Funding and Sales
Lithoz initially chose to grow without outside investors, driven by a misconception that investors were „evil“ or purely exploitative. While this allowed them to avoid immediate dependencies, Homa now views investors as valuable supporters who provide not just capital but also consulting and „time“ to grow faster.
Furthermore, the team had to navigate long sales cycles, which typically last between one and a half to two years for new customers. In this high-tech sector, „sales“ is often synonymous with technical consulting, requiring a balance between creating hype and maintaining absolute honesty about the technology’s current capabilities.
Advice for Future Tech Founders
Drawing from his experience, Johannes Homa offers three vital tips for those looking to spin off research into a business:
- Prioritize Marketing and Sales: Technology is not everything. You cannot assume people will simply know about or buy your product because it is good.
- Think Like an Entrepreneur: You must understand the „non-technical“ side, including balance sheets and tax requirements, or hire someone who does.
- Hire for Enthusiasm: Place people in roles they are passionate about. A tech-heavy founder should pair with someone who genuinely enjoys the business and sales side.
Ultimately, the path from researcher to CEO is a steep learning curve that requires resilience. As Homa learned, even when a crisis feels like the world is ending (such as a key employee leaving) the world keeps turning, and every problem is an opportunity to find a better solution.
If you want to dive deeper into the full journey listen to the SCALEup Talk podcast episode with Johannes Homa
Deep-tech founders live in two worlds:
the lab, where things behave perfectly under controlled conditions, and the real world, where nothing behaves perfectly.
Most deep-tech projects fail not because the idea is bad, but because the leap from scientific promise to industrial reality is far larger than most teams expect.
There is a simple tool that helps founders stay honest about their progress, brings teams and partners onto the same page, and makes hidden risks visible.
The Technology Readiness Levels (TRLs).
1. What TRLs Measure
And Why It Matters
TRLs are nothing more than a shared language that says:
“How mature is this technology and how much evidence do we have that it works outside the lab?”
Developed by NASA in the 1970s and standardized later (including in the EU’s Horizon programs), the TRL scale spans 9 levels from a basic idea to a fully proven industrial technology.
Think of it like climbing a mountain:
- TRL 1: You’ve observed and documented basic principles.
- TRL 2: You’ve formulated a technology concept or application.
- TRL 3: You’ve made your first foothold through experimental proof of concept.
- TRL 4: You’ve validated the technology in a laboratory environment.
- TRL 5: You’ve validated the technology in a relevant environment.
- TRL 6: You’ve demonstrated the technology in a relevant environment.
- TRL 7: You’ve demonstrated the system prototype in an operational environment.
- TRL 8: The actual system has been completed and qualified through testing and demonstration.
- TRL 9: The actual system has been proven in an operational environment, which means you are ready for scaling in the real world.
Each level is about evidence you can trust.
2. Why TRL Is Essential for Deep-Tech Startups
Founders often assume “it works in the lab, so we’re almost ready.”
That assumption is a major trap in deep tech.
Analyses across sectors show that innovations appear stable in labs precisely because labs artificially suppress variability. Conditions can be 8x more stable than industrial environments demand. Real industrial conditions are messy; labs are greenhouses.
TRL forces founders to face this gap early.
TRL asks:
“What have you actually proven? And what remains an assumption?”
This clarity is a communication tool for teams, customers, and investors.
3. How TRL Improves Decision-Making
TRL turns ambiguity into a sequence of validated checkpoints.
It forces you to ask:
- What is the one experiment that moves us to the next level?
- What is the minimum evidence required to reduce risk?
This means:
- Fewer wasted experiments
- Fewer emotional bets
- Sharper prioritization
TRL can improve how investors assess a deep-tech venture, because it turns technical risk into a transparent roadmap rather than a black box. Startups that communicate their maturity this way often find investor conversations more efficient and focused.
Keep in mind: Investors don’t fund ideas. They fund predictability. TRL turns risk into a timeline.
4. How to Use TRL as a Strategic Tool
TRL needs to live in your daily decisions.
1. Internal Alignment
Every team member knows exactly what test, prototype, or validation is required to reach the next level. This dissolves personal preferences and focuses the team on evidence.
2. Customer Conversations
Industrial partners aren’t afraid of risk, they’re afraid of uncertainty. If you can say “we are TRL 5 and here’s how we’ll get to 6,” you turn ambiguity into a shared roadmap.
3. Funding Strategy
Most deep-tech funding follows a pattern that mirrors TRL maturity, even if investors don’t explicitly use the term.
- Grants and early R&D funding focus on the scientific stages of technology development.
- Seed and Series A investors typically enter once feasibility and early validation are demonstrated.
- Growth and strategic capital appear when a system shows stability in near-industrial or industrial conditions.
TRL helps founders target the right type of capital at the right moment by making risk and maturity visible.
Conclusion: TRL Is a Mirror
TRLs are a reflective tool that answers a deceptively simple question:
“Can this technology handle the weather outside the greenhouse?”
Startups that embrace TRL honestly:
- make fewer costly mistakes,
- communicate more clearly, and
- scale with fewer surprises.
Every technology moves from greenhouse to weather. If you don’t know your TRL, you’re guessing where your risks are. And guessing is the most expensive strategy in deep tech.
TRL helps you see when that transition actually happens.
Want a real-world example of deep-tech maturity in action?
In our SCALEup Talk episode with Johannes Homa from Lithoz (a TU Vienna spin-off), we discuss how breakthrough technology makes the journey from research to industrial deployment.
Watch or listen to the episode here
(The talk is in GERMAN!)
Was passiert, wenn eine wissenschaftliche Entdeckung zu groß ist, um im Labor zu bleiben?
Bei Lithoz führte genau dieser Moment zu einer Entscheidung, die alles verändert hat:
Sie wollten nicht nur publizieren – sie wollten die Industrie revolutionieren.
Heute ist Lithoz ein Hidden Champion im 3D-Druck für Hochleistungskeramik.
Doch der Weg dorthin war alles andere als linear.
In dieser Episode sprechen wir über die Entscheidungen, die man von außen nie sieht, aber die über den Erfolg entscheiden:
– die erste Hypothese, die das gesamte Geschäftsmodell prägte
– wann sich ein Produkt „reif genug“ anfühlt
– wie man eine Labortechnologie industrialisiert, ohne ihren Kern zu verlieren
– warum Lithoz bewusst keine Investor*innen ins Boot geholt hat
– wie man extreme Skepsis überwindet, wenn Technologie als „zu neu“ gilt
und vieles mehr.
Für alle, die Deep Tech nicht nur entwickeln, sondern in die Welt bringen wollen.
🎧 Jetzt reinhören und erfahren, wie aus Forschung ein globales Geschäftsmodell wird:
Website: https://www.lithoz.com/
LinkedIn: https://www.linkedin.com/company/lithoz/
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Every December, something strange happens.
Perfectly rational adults suddenly believe that one single day must unfold like a cinematic masterpiece.
The family will get along. The food will be flawless. The gifts will be meaningful. The atmosphere will glow with harmony.
Reality usually answers with burned cookies, last-minute panic, and at least one emotional plot twist.
This mismatch between ideal and reality is not a Christmas problem.
It is a cognitive bias.
Psychologists call it the “expectation gap”, the emotional drop that occurs when the imagined version of an event is so inflated that reality has no chance of living up to it.
Founders run into the same trap.
- The “perfect launch”.
- The “explosive growth curve”.
- The “investor who absolutely must say yes”.
These expectations are often as unrealistic as a Christmas movie plot.
Let’s unpack what founders can learn from Christmas perfectionism and how to set goals that create momentum rather than pressure.
Lesson 1:
Perfectionism creates stress. Precision creates progress.
Research in organizational psychology shows that unrealistic performance expectations increase cortisol levels and reduce problem-solving accuracy. This explains why stressed teams produce slower decisions and more errors.
Christmas version:
You want a perfect family photo.The kids revolt. The dog escapes. Someone cries. No one smiles.
Startup version:
You want a flawless launch. The server crashes. Your “bug-free” code reveals personality issues. A customer uncovers a use case you never tested.
What actually works:
Set expectations around learning speed, not flawless execution.
The goal of a launch is to generate validated insight. A launch is not a judgment day. It is a data collection event.
When you treat it like an experiment instead of a ceremony, creativity increases and stress decreases.
Practical exercise for founders:
Before every milestone, answer this question:
“What is the minimum useful outcome that would still move us forward?”
This removes perfection from the equation and clarifies your operational reality.
Lesson 2:
High expectations without shared context create conflict
Families fight at Christmas partly because everyone arrives with a different mental model of “how this should go”.
Startups operate the same way.
A founder imagines rapid traction.
The CTO focuses on reducing technical debt.
Investors expect hockey-stick growth.
Customers want stability.
When left unspoken, these expectations collide.
Research from Harvard’s Negotiation Project shows that misaligned expectations are among the largest contributors to team conflict and slow decision cycles.
What works instead:
Make implicit expectations explicit.
Every quarter, align expectations within your team by asking three questions:
- What does success look like for each of us this quarter
- What trade-offs are we willing to accept to achieve it
- What success metrics will we ignore on purpose
This prevents silent disappointment and clarifies where ambition meets capacity.
Lesson 3:
Seeing things too positively clouds your judgment about risks
Christmas advertising tells us everything will be beautiful.
Meanwhile, reality includes logistics failure, emotional volatility, and unexpected costs.
Founders do something similar.
They idealize the “post-funding future” or “after we ship this feature everything will be easier”.
Behavioral economics calls this optimism bias, and it is one of the strongest distortions in entrepreneurial decision-making.
Optimism bias is useful for motivation, but dangerous for planning.
Evidence shows that teams who combine optimism with pre-mortem analysis make fewer strategic errors.
A pre-mortem simply asks:
“It is three months from now, and this initiative failed. What went wrong?”
This exercise does two things.
- It reduces emotional attachment to idealized outcomes.
- It improves risk identification accuracy.
To compare it to Christmas: if you imagined everything that could realistically go wrong with the dinner ahead of time, you would not panic when the oven rebels. You would have backup plans ready.
Founders benefit from the same mental rehearsal.
Lesson 4:
The best moments are rarely the planned ones
If you look back at your most memorable Christmas moments, they were usually accidents.
A funny misunderstanding. A small act of kindness. A moment of authenticity.
Startups work the same way.
Major breakthroughs often emerge from unexpected user feedback, accidental discoveries, or side-project experiments.
Many iconic products started this way.
So:
Leave room for serendipity.
Rigid roadmaps suppress innovation. Flexible frameworks invite it.
Maybe you want to use this weekly ritual:
Review what surprised you.
Then ask: “Does this surprise reveal an unmet need or a strategic opportunity?”
Surprise is information. Treat it as data, not disruption.
Lesson 5:
Progress needs boundaries, not pressure
Christmas comes once a year whether you are ready or not.
Deadlines in startups should work similarly.
A realistic boundary creates progress.
Unrealistic pressure erodes performance.
Evidence from cognitive load theory shows that humans perform best within a zone of optimal stress.
Too little pressure reduces motivation.
Too much pressure impairs working memory, which is fatal in complex problem-solving.
Healthy pressure is specific, time-bound, and directly connected to achievable actions.
Unhealthy pressure is absolute, vague, and fueled by external expectations.
Unhealthy example: “Secure traction before the investor meeting or everything collapses.”
Healthy example: “Talk to ten customers by Friday to understand their purchasing triggers.”
One creates focus. The other creates panic.
The founder takeaway:
Expectation management is a strategic skill
You cannot eliminate expectations.
But you can learn to manage them in ways that help you move forward instead of holding you back.
Ask yourself this week:
- Where am I holding on to a “Christmas perfection fantasy” in my startup
- Where do I expect the impossible
- Where do I assume harmony without alignment
- Where do I plan for the ideal instead of the likely
- Where do I forget that reality always comes with surprises
The founders who master expectation management build more resilient companies.
And they experience less emotional turbulence along the way.
A startup is not Christmas morning.
You are not unwrapping a finished gift.
You are building the gift itself while the world keeps changing the instruction manual.
When you set realistic expectations, keep your team on the same page, think through what could go wrong, and stay open to unexpected opportunities, you’ll build better products. You’ll also save your energy for the long journey of building a startup.
Happy building.
And happy holidays.