KisStartup

 

 

(Trend, Technology, and Growth Model Analysis 2024–2025)
Compiled, analyzed, and edited by KisStartup

In the world of alternative proteins, Mosa Meat isn’t the loudest name — but it’s one of the few that has mastered turning science into product, product into regulatory standard, and standard into market. Its journey — from the world’s first cultured burger in 2013 to submitting a Novel Foods dossier to the European Commission for cultivated beef fat on January 22, 2025 — sketches a rare deeptech growth curve: slow and steady at the foundation, then accelerating precisely when society is ready to shift dietary habits.

However, to see Mosa Meat merely as a “lab burger company” misses the essence: this is an organization that knows how to commercialize science within existing legal frameworks, using regulation as a runway for its first product, and building bridges of trust toward mainstream adoption. From the historic 2013 tasting to the EU submission for cultivated beef fat in 2025, Mosa Meat connects three deeptech fragments that rarely align: science → regulation → market.

Ingredient-first: The fastest route to the dining table

Rather than launching an ambitious 100% cultivated steak, Mosa Meat adopts an ingredient-first strategy, starting with cultivated beef fat. This ingredient enhances hybrids (e.g., burgers, meatballs, bolognese), providing authentic aroma, taste, and mouthfeel at a lower regulatory threshold. By submitting fat as the first Novel Food, Mosa Meat accelerates market entry within approved frameworks. An EFSA-reviewed fat dossier also serves as a “social proof” for retailers and regulators across other regions — effectively shortening the commercialization path.

Regulation as a growth lever — not a barrier

Few startups see regulation as a growth channel. Mosa Meat does. Beyond the EU Novel Foods filing, it became the first cultivated meat company certified as a B-Corp (September 2023) — a strong ESG signal in Europe’s retail landscape. Mosa Meat also expands through multi-region regulatory pathways (EU, Switzerland, UK), leveraging “sandbox” tasting programs to collect data and trust, while cutting down isolated trial time and market education costs.

Market education through experience, not just messaging

Since the 2013 London tasting — designed as a “press conference for the palate” — Mosa Meat has consistently promoted the “see–understand–taste” model: public R&D updates, transparent process explanations, and controlled tastings with pioneering chefs. As consumer behavior shifts (2024–2025) toward short videos, on-site experience, and transparency, this model outperforms traditional advertising. The €1.5 million crowdfunding in February 2025 (raised in 24 minutes) turned supporters into early adopters and brand storytellers — converting social consensus into capital.

Scaling is not just more bioreactors — it’s unit economics

Mosa Meat’s 7,340 m² Maastricht campus, with 1,000 L bioreactors, establishes a full R&D → pilot → pre-commercial chain. But true scalability lies in cost curves and productivity, not facility size: serum-free media, higher cell productivity (g/L/h), and stable differentiation cycles. Costs have dropped ~80× since the $330,000 burger, approaching commercial viability. The company distinguishes between “image scaling” and “economic scaling”, prioritizing the latter.

Environmental impact: Potentially strong, but conditional

LCA studies show major emission, land, and water reductions if cultivated meat reaches scale and uses renewable energy. Benefits fade under fossil-heavy grids. The real sustainability lies in system design: clean energy, circular media, and waste management. Reduced livestock dependency also restores soil and biodiversity, but cultivation processes must manage chemical and material footprints carefully.

Social impact: Ethics, jobs, and culture

Cultivated meat eliminates large-scale slaughter and creates skilled biotech jobs but also requires just transitions for traditional workers. Mosa Meat’s ingredient-first, hybrid approach respects food culture — upgrading familiar dishes rather than replacing them entirely. Still, concentrated IP ownership (cell lines, media, bioreactors) risks forming “Big

Food 2.0”; open standards and fair licensing are essential for inclusive industry growth.

Transparency on long-term safety

Though EU/UK/Singapore frameworks are rigorous, long-term consumption data remain limited. Mosa Meat’s approach — proactive transparency, public LCA assumptions, and post-market monitoring — builds credibility in an evolving landscape.

Takeaways for Vietnamese Biotech Startups

• Start ingredient-first. Focus on components (cultivated fats, fermented flavor molecules) to enhance familiar dishes like phở, bún bò, or bánh mì rather than full meat replacements.
• Design legal runways early. Align datasets with EFSA/FDA standards even for local pilots; propose regulated tasting sandboxes with traceable QR data.
• Educate via controlled experiences. Combine chef-led tastings, short videos, and transparent safety sheets to let consumers see–understand–taste.
• Report unit economics quarterly. Share media cost/kg, productivity, and batch cycles to build trust with investors and regulators.
• Blend diverse capital sources. Mix climate VC, public funds, and community crowdfunding with measurable KPIs (LCA, safety, cost).
• Localize the supply chain. Develop domestic inputs for media and bioreactors to reduce cost and import dependency.

Sources:
EU Submission (22/01/2025): Mosa Meat filed Novel Foods dossier for cultivated beef fat (Mosa Meat).
B-Corp (09/2023): First cultivated meat company to achieve certification (Forbes).
Scale: 7,340 m² campus, 1,000 L bioreactor (Mosa Meat).
Market education: From London 2013 tasting to transparent R&D communications (eitfood.eu).
Crowdfunding (02/2025): €1.5M in 24 minutes; social consensus turned into market traction (Cultivated X).

 

In the previous three articles, we explored the journey of Lean Startup as a mindset of learning-based management, the use of MVPs to understand the market, and—most importantly—how to awaken organizations to real data. But Lean cannot survive long if it only lives at the product or process level.

Ultimately, Lean must go through people.

Each Build–Measure–Learn loop is not only a cycle for products—it is also a cycle for team development. No matter how high-tech a startup is, it is still a story of people: founders who dare to dream and learn, early employees who believe in what no one else sees, and a culture that accepts mistakes as part of finding the right path.

After ten years of working with hundreds of startups in Vietnam, KisStartup has found that one of the key factors determining a startup’s resilience lies not in ideas or capital, but in how they build their team and learning culture. Lean Thinking has become the most powerful tool for developing “entrepreneurial people” — fast, flexible, humble in failure, and bold enough to try again.

Lean doesn’t just teach product building — it teaches people management

Eric Ries wrote, “Entrepreneurship is management.” Yet few realize that “management” in Lean refers not just to managing systems, but to managing people under uncertainty.
A startup in its early days often lacks an HR department, formal training programs, or clear KPIs. Everything is created “while doing and learning.” And within that chaos, organizational culture takes root.

When coaching startups, we often start with a simple question:

“If you hire one more person tomorrow, what do you want them to bring — skills, energy, or a new perspective?”

This question helps the team identify assumptions about people—just like identifying assumptions about customers.
Many founders realize they hire people “like themselves” for comfort, but what a startup needs are complementary people—those who can ask hard questions, challenge old habits, and fill gaps in capability.

Lean thinking teaches founders to test, measure, and learn — so why not apply the same cycle to recruiting and developing people?

Drawing the “Team Persona” — A Lesson from Lean Personas

In Lean Startup, we use the concept of Customer Persona — a profile of the target customer, built from real data. At KisStartup, we expand this into Team Persona — a profile of the ideal person for the current stage of the startup.

An agricultural startup we coached once made the mistake of hiring “senior managers” too early—experienced professionals who lacked an experimental mindset. Conflicts quickly arose: the original team wanted to “test and learn,” while the newcomers wanted to “make things professional right away.”
After several failed iterations, they returned to the Team Persona exercise, defining who they really needed for the next six months—not an experienced manager, but a data-driven engineer who embraced trial and error.

Once they made that shift, the team atmosphere changed dramatically.
They stopped evaluating people by title and started valuing them by how quickly they could learn and adapt. Most importantly, they began to view recruitment itself as a Lean experiment: each hiring round as an MVP, each candidate as a hypothesis, and each probation period as a Build–Measure–Learn cycle.

Co-founders and the Trust Loop

Nothing is leaner than a small founding team that truly understands one another. Yet a co-founder is not just someone to share the workload with — they must share the same learning philosophy.
KisStartup has seen many projects fail simply because the founders didn’t learn at the same rhythm. One wanted to “act fast,” the other wanted to “research more.” One wanted to prove the idea, the other wanted to learn from data. When learning loops are out of sync, teams fracture.

A tourism startup we supported had to pause operations after a year. The issue wasn’t the lack of customers, but disagreement between two founders: one relied on intuition, the other insisted on data.
After taking time to “pause and learn,” they came back with a new mindset:

“We don’t need someone to be right — we just need the data to be right.”

They agreed that every debate would end with a small measurable test. When both committed to the Build–Measure–Learn loop, trust grew stronger. Lean thus became a management framework for trust — not blind trust, but trust validated by action.

A Culture of Failure — and Learning from It

There is no Lean without failure. Yet in Vietnam, “failure” remains a heavy word. Many founders speak of Lean but avoid confronting real data for fear of bad results. They prefer surveys showing “positive signals” and reports of “steady growth,” but rarely ask the hard question: “Why did customers leave?”

At KisStartup, we organize Learning Review sessions where teams openly examine what didn’t go as planned. For many, it’s their first time “failing in public.”
One founder said, “I thought Lean was to avoid failure. Turns out Lean is to fail the right way.”

That realization marked a turning point.

Accepting failure doesn’t mean ignoring mistakes—it means transforming them into learning assets.
In one edtech team, after their first MVP failed, they held a “Failure Learning Ceremony.” Each member shared what they learned, rewrote initial assumptions, and analyzed why they were wrong. That Failure Report became a valuable resource for their next test. Six months later, they successfully raised funding.

A culture that accepts failure doesn’t just strengthen resilience—it unleashes creativity. When people aren’t afraid of being wrong, they dare to propose, experiment, and learn. Lean cannot thrive in judgment; it only grows in psychological safety.

From “Doers” to “Learners”

Startups often seek “people who can get things done,” but Lean teaches us to seek “people who can learn things fast.”
In a world where technology changes rapidly, specific skills can become obsolete overnight, but the ability to learn quickly and adapt remains invaluable.

A smart agriculture startup in Đồng Nai struggled as its technicians were used to taking orders, not experimenting. After joining KisStartup’s mentorship program, they restructured internal training: each new engineer received a learning problem instead of a technical task.
For example, instead of “calibrate the sensor,” they got “investigate why soil humidity readings fluctuate.” Each week, they presented what they learned—not just results. Within two months, the technical team began proposing proactive improvements. They no longer waited for directions—they built their own Build–Measure–Learn loops.

Lean doesn’t create “perfect employees”; it creates people who know how to self-improve.

Lean Culture — From Process to Habit

Many companies try to “install Lean” through checklists, KPIs, and processes, forgetting that Lean cannot be imposed. It’s a collective habit, formed by small, repeated actions.

When KisStartup supported a software company scaling from 10 to 50 people, the biggest challenge wasn’t technical—it was maintaining the try–measure–learn spirit as they grew.
They decided to keep three weekly rituals inspired by Lean:

1. Monday Learning Hour: Each team shares one insight from customer data or feedback.
2. Thursday Experiment Day: Four hours to test a small idea without needing approval.
3. Friday Reflection: The whole team answers three questions: “What did we learn this week?”; “What surprised us?”; “What will we test next week?”

These simple, low-cost rituals sustained a rhythm of learning and openness. When people feel they have the right to learn and the right to fail, Lean spreads naturally—no enforcement needed.

Lean for People — Not to Cut Costs, But to Grow Teams

In Vietnam, “lean” is often misunderstood as “cutting people, cutting costs.” But in the Lean philosophy KisStartup follows, lean means eliminating waste so people have more space to learn and create.
Every startup begins with limited resources. Each person must be a doer, a learner, and an improver.

In a small ecotourism startup in Lâm Đồng, unable to afford a marketing specialist, the founder trained tour guides to tell product stories and manage the fanpage. Within three months, not only did they save costs, but they also built an authentic and relatable brand voice.
They weren’t perfect—but they were flexible enough to learn whatever was needed to survive. That’s Lean in its most vibrant form.

Connecting People and Organizations — The Double Learning Loop

A truly Lean organization is where both individuals and the system learn. Individuals learn to adapt; the organization learns not to repeat mistakes. KisStartup calls this the double-loop learning:

• The first loop is do–measure–learn.
• The second loop is learn how to learn—reflecting on whether the learning process itself is effective.
• Many startups fail after three years not because the market changes, but because they stop learning how to learn. When reflection stops, Lean dies quietly within old habits.

Lean Begins with Products, but Matures Through People

After ten years, KisStartup has seen Lean Startup in Vietnam evolve—from a method to a mindset, from products to culture.
If the MVP is a tool to learn about the market, people are the tool to learn about ourselves.

A startup may change its product ten times, but if the team learns nothing each time, all effort is wasted. Conversely, a learning team will always find new products, new models—even new companies.

Lean teaches us that agility is not about speed, but about the ability to learn and unlearn when data proves us wrong.
And only when people are freed from the fear of failure can organizations truly become lean.

“A startup that learns from failure is still alive.
An organization that learns from its people will live long.”
— KisStartup, 10 Years of Lean Startup in Vietnam

© Copyright KisStartup. Any reproduction, citation, or reuse must credit KisStartup.

If Lean Startup is a philosophy of learning amid uncertainty, then MVP (Minimum Viable Product) is the tool to learn the fastest, cheapest, and most truthfully. But “minimum” does not mean “half-hearted,” and “viable” does not just mean “can survive.” A true MVP is Meaningful – Valuable – Practical: meaningful in its learning goal, valuable to real users, and practical within available resources.

Over 10 years of practicing Lean Startup in Vietnam, KisStartup has witnessed many ventures that began with a “small” MVP but unlocked entirely new business models. Conversely, some failed because they “loved their product more than the market.” These lessons reveal that MVPs are not meant to prove you are right, but to discover what is right for the market—even to redefine what “product” really means.

MVP Is Not a Product – It’s a Question Materialized

One of the most common misunderstandings about MVPs is to treat them as the “first version” of a complete product. In reality, an MVP is the cheapest way to answer the most expensive question: Do customers truly need this solution?

Tony Hsieh, founder of Zappos, did not launch a full e-commerce platform, buy inventory, or write code. He simply photographed shoes from nearby stores and posted them online. When someone placed an order, he went back to buy and ship them himself. That MVP taught him the key insight: people were willing to buy shoes online even without trying them on.

Dropbox did something similar. Before building any software, they created a short video demonstrating how it would work. The three-minute clip attracted tens of thousands of sign-ups—clear proof of real demand.

These classic cases teach us that an MVP is not an “unfinished product,” but a carefully designed learning experiment. It measures not “technical quality,” but the market’s readiness.

A Meaningful MVP – When the Product Helps You Learn What Matters Most

From KisStartup’s experience, the value of an MVP lies not in whether it succeeds or fails, but in what the team learns and can act upon afterward.
We’ve worked with many founders who believed they needed a “complete version” before selling. But testing with MVPs often revealed that the market wanted something entirely different—sometimes just a component, a complementary service, or even data they had unintentionally created.

An agricultural startup once spent nearly two years developing farm management software. Encouraged to test an MVP by selling only the soil moisture sensor module, they unexpectedly received large orders from fertilizer companies interested in monitoring soil quality. That “small” MVP not only generated sales but also opened a new B2B model—selling intermediate products instead of final ones.

Such cases convinced KisStartup that MVPs help expand the definition of “product.” Intermediate goods, data, accompanying services—all can be “products” if they create customer value and fit current capabilities. MVPs free founders from the “perfection trap,” shifting them from product-oriented to market-oriented learning.

Meaningful – Valuable – Practical: The Three Pillars of a Living MVP

Meaningful – Focused Learning

A meaningful MVP must help you learn something specific and measurable. It’s not about “seeing who likes it.” “Meaningful” means each experiment must link to a clear hypothesis and decision criterion.

If you launch a website without knowing what you’re testing—pricing, messaging, or distribution—you’re running a guessing exercise, not an MVP.

Being meaningful also means accepting the truth, even if it’s uncomfortable. If data show customers don’t care, that’s not failure—it’s cheap tuition for an expensive lesson.

KisStartup once guided a food startup to run an MVP through a free tasting session. Sales were low, but feedback revealed that customers preferred traditional flavors over the “modern” ones the founders had assumed. The next version succeeded precisely because they learned the right lesson. The MVP wasn’t flashy, but it was meaningful—it taught them what mattered.

Valuable – Real Value for Real People

An MVP meaningful to you may not be valuable to customers. “Valuable” means your MVP must deliver real, tangible value to users, however small. No one wants to participate in an “experiment” unless it benefits them somehow.

Value can be functional, emotional, or experiential. Dropbox’s simple demo video wasn’t a working product, but it clearly conveyed value: syncing files effortlessly.
In Vietnam, many teams mistake MVPs for “internal demos,” tested only among friends or employees—not real users. Data from such contexts are fake data. A valuable MVP must be exposed to the real market, face real reactions, and handle real feedback.

In our programs, we often ask founders: “Why would someone spend time trying your MVP?” If you can’t answer that, you don’t yet have a valuable MVP.

Practical – Feasible with What You Have

Even the most meaningful and valuable MVP will fail if it’s not practical. “Practical” doesn’t mean oversimplified; it means achievable within your current constraints—money, time, technology, and team capacity.

Many Vietnamese startups fall into the “perfection syndrome”: waiting until they have enough funding, people, and time to start. But Lean Startup teaches that learning doesn’t require “enough”—only “enough to learn.”

A herbal tea cooperative in Lào Cai wanted new packaging, a registered brand, and an online shop before launch. Instead, they tested a practical MVP: temporary labels, direct sales at a fair, and feedback recorded manually. Immediate responses revealed their real target audience—elderly consumers, not young people.

Practical means doing it now with available means. A practical MVP sustains continuous learning and prevents endless “preparation loops.”

When MVP Makes You Love Data More Than Products

The magic of MVPs is that they shift founders’ love from products to data. When you truly aim to learn, you stop trying to prove your product is great—you start trying to understand why users react the way they do.

A community-based tourism startup in Sơn La once spent months designing full service packages. When they ran an MVP by inviting a small group to stay with local families, they learned travelers loved the food and culture but disliked poor sanitation and comfort. The insight: invest in service standards, not infrastructure. The result—lower cost, higher impact.

When MVPs are executed with the Meaningful – Valuable – Practical mindset, data becomes the compass, and the market—not your plan—becomes the teacher.

MVP as a Never-Ending Learning Loop

An MVP doesn’t end when you make your first sale. It ends only when you stop learning. At KisStartup, we call this the “learning saturation point”—when the product, market, and behaviors are clear enough to move from exploration to optimization.
Yet even then, the MVP spirit continues. Every marketing campaign, every feature tweak, every new version can be seen as a new MVP—a new learning loop. Successful startups maintain a learning velocity faster than the market’s change velocity.

Three Practical Principles for Building a Meaningful MVP

There’s no universal formula, but from hundreds of cases, KisStartup distills three core principles:

• Ask right before acting right. Every MVP should begin with the question: “What assumption, if wrong, would collapse my plan?” Identify your riskiest assumption first—then design to learn about it.
• Start small but measure seriously. A 100-user MVP with real behavior data beats 10,000 views with no measurement. Tie your data to actions: clicks, purchases, feedback, returns.
• Stay flexible. MVPs are not for defending your idea but discovering opportunities. If customers want to buy intermediate goods or rent instead of own, treat that as insight, not deviation. Many great business models emerged from such small turns.

MVP as a Mirror of Awareness

A meaningful MVP doesn’t just generate quick revenue—it reveals unseen realities. It’s a mirror that strips away illusions, narrowing the gap between expectations and actual customer behavior.

After 10 years of Lean Startup practice in Vietnam, what KisStartup values most isn’t the successful products but the transformation in founders’ mindsets—from “making what I like” to “learning to make what the market needs.”

Meaningful – Valuable – Practical aren’t just words; they represent three levels of founder maturity:

• Meaningful: I know what I’m learning and why it matters.
• Valuable: I know who truly benefits from my product.
• Practical: I act within my limits, yet continuously expand my learning capacity.

MVPs are meaningful because they help entrepreneurs fall in love with data, not illusions—observe rather than assume—and, above all, learn by doing.

“The market doesn’t speak in words; it speaks through behavior. MVPs are how we listen.”
— KisStartup, 10 Years of Lean Startup in Vietnam

© KisStartup. Any form of copying, quoting, or reuse must credit the source.

In the previous lesson, we explored the journey from “teaching” to “doing together.” In this second one, KisStartup raises a crucial point: Lean Startup is a philosophy of managing learning amid uncertainty. In Vietnam, the hardest part is not technology or ideas, but rather the discipline of data and management capacity to turn every experiment into validated learning.

We believe deeply in the entrepreneurial spirit of Vietnamese founders – quick to spot problems, resourceful, and adaptive to technology. But after ten years in the field, KisStartup has seen a paradox: technology is ready, but businesses are not. The Build–Measure–Learn loop often breaks at “Measure” and “Learn,” because market data, consumer behavior, and customer feedback are neither collected, standardized, nor managed as assets. When data doesn’t live, Lean becomes only a slogan.

The Core Philosophy of Lean: Learn Fast — With Evidence — and Decide with Discipline

Lean does not mean doing less for efficiency’s sake. It means doing just enough to learn the right thing. “Just enough” is not minimalism; it is optimizing the ratio between learning signals and testing cost. A good MVP is not the cheapest demo — it’s the smallest experiment that yields the strongest evidence about a key business assumption at the lowest possible cost.

From KisStartup’s perspective, the Lean philosophy can be distilled into three principles:

• Everything is an assumption until proven by strong data — ideas, personas, distribution channels, pricing models, all of it.
• Experiments are the unit of progress, and data is the unit of learning. No measurement, no learning.
• Decisions require discipline. Every iteration needs clear branching criteria (pivot or persevere) and operational definitions for metrics.

In short: Lean is management of learning. Management here doesn’t mean paperwork — it means designing a system where assumptions → experiments → data → learning → decisions flow coherently, repeatably, and verifiably.

Invisible Frictions in Vietnamese Startups: From Intuition to “Data Debt”

Vietnamese founders are fast adopters of technology. Many are eager to use chatbots, AI-driven marketing, or automated ad optimization tools. A recent survey found that 74% of Vietnamese SMEs claim to have or be implementing a digital strategy — an impressive figure.

But once you step into the data room, the story changes. Information is scattered across platforms, with no single source of truth. Sales teams have customer lists but no record of service history; marketing tracks campaigns but not the customer journey; production tracks quality metrics but not post-sale feedback. Many still store screenshots of customer chats in Zalo — dead data.

As a result, AI can only skim the surface. Not because it’s weak — but because it has no clean data to feed on. Forecasts miss the mark, product recommendations fall flat, dashboards look beautiful but say nothing. “We’ve gone digital” — perhaps, but digital transformation ≠ data transformation. Without a solid data foundation, digital strategy is just a coat of paint.

This leads to what we call data debt — like technical debt in software, it’s the future cost you’ll pay for not collecting or standardizing data early. The longer you delay, the harder it becomes to fix. When startups raise funds or expand, data debt appears instantly: inconsistent metrics, missing traceability, and no credible growth story. Investors don’t just look at revenue; they assess the quality of the data behind it.

Another friction comes from weak management skills. Vietnamese founders have sharp market instincts — a great strength — but intuition cannot replace disciplined management. Lean demands founders who can set hypotheses realistically, choose leading indicators wisely, stop at the right time, and measure correctly. Many teams “run Lean” by feel — repeating tests without learning because they lack measurement definitions, baselines, or review rhythms. Lean becomes a “spin cycle of experiments for fun.”

Entrepreneurial spirit exists — data and management do not. That’s where Lean returns as a discipline, not a trend.

Vietnamese Entrepreneurial Spirit: A Real Advantage — If Paired with Data Discipline

In KisStartup’s programs, we often see founders who identify problems quickly, sense opportunities across supply chains, and customize products for local markets. Their tech skills are also accelerating: building and testing prototypes or AI/no-code tools within hours.

But “speed” becomes sustainable only when paired with data-driven learning cycles.

A herbal cooperative in the highlands once pivoted its entire product direction after three weeks of testing a self-built landing page. Data showed that their most loyal customers were urban families with young children seeking natural products — not tourists as they had assumed. This small, data-backed insight freed them from illusions and set a foundation for real growth.

Conversely, an e-commerce startup heavily invested in AI forecasting but suffered losses because of fragmented historical data — leading to wrong demand predictions and stock mismanagement. Their mistake wasn’t using AI; it was using it in the wrong order — they needed clean data before intelligence.

KisStartup’s consistent message: make data instinctive in daily business, as naturally as a craftsman reading the wood grain before carving. When this “data instinct” forms, Lean truly lives in the organization.

From Philosophy to Practice: Lean Data in 90 Days

We propose a 90-day Lean Data roadmap — minimal, practical, and focused on learning, not grand data projects.

Month 1: Define what you want to learn
Start with business questions, not tools.
“What do we need to validate in the next 4 weeks to decide on price/positioning/channel?”
Choose 1–2 key assumptions. Write operational definitions for each metric — how to measure, from where, how often, and what threshold triggers a decision. This is your team’s data contract.

Month 2: Bring data together
Pick one single source of truth (even a well-managed spreadsheet or minimal CRM). Aim for consistency, not perfection. All orders, feedback, and marketing experiments flow into this source. Review weekly — don’t let data die in screenshots.

Month 3: Run 2–3 fast learning cycles
Each lasting 10–14 days. Before starting, define branching criteria (continue, adjust, stop). After each cycle, write a short “lesson learned” linked to actual data. Don’t change 5 things at once — change one, learn deeply.

The goal: build data muscles, not buy AI toys. Once the muscles are strong, AI will work naturally — not the other way around.

Innovation Accounting: Measuring Learning, Not Vanity

When founders hear “accounting,” they think finance. Innovation accounting is bookkeeping for learning. It answers:
“What evidence shows we’ve moved from A to B? So what’s next?”

KisStartup uses a simple but powerful framework:

• Key assumption: e.g., “Customers will pay 159,000 VND for a 7-day trial.”
• Experiment design: channels, messages, test samples, lead collection.
• Leading indicators: click-throughs, signups, paid conversions.
• Decision thresholds: e.g., CR ≥ 4% → continue; 2–4% → adjust message; <2% → stop and revisit positioning.
• Lessons learned: 1–2 short insights tied to data, not feelings.

The power lies in repetition and traceability. After 6–8 weeks, you have a chain of evidence showing your learning journey — enough to convince teammates, investors, and yourself.

Building a Learning Organization: When Lean Becomes a Habit

Lean fails if it depends on one data-loving founder. It must become an organizational discipline. KisStartup recommends a few small but transformative habits:

• 1 learning hour/week: no interruptions, focused on reviewing experiment data. Ask: What did we learn? What surprised us? What one thing do we change next?
• 1-page data dictionary: define all metrics (“What does ‘active user’ mean?”). Keep it visible. Never have two definitions for one metric.
• Field immersion ritual: once a month, product, marketing, and sales teams must talk directly to customers. No one builds for customers from behind an Excel file.

These habits foster a culture of evidence-based dialogue. People debate with data, not feelings. That’s when Lean truly comes alive.

AI: A Jet Engine Only Works on a Plane with a Frame

We love AI — we use it daily to accelerate Build–Measure–Learn loops: prototype generation, content testing, feedback analysis, segmentation. But even the strongest engine needs a solid frame — clean data, clear metrics, and disciplined decisions.

In practice, KisStartup starts with a data MVP: a minimal event table (viewed, added to cart, purchased, churn reason), basic consent/privacy setup, and a one-page dashboard. No need for complex BI; what matters is a continuous data flow. Once the pipeline runs, AI can truly perform.

Policy and Ecosystem: Learning Fast at a National Scale

Many countries already treat data as growth infrastructure for SMEs, offering support packages to reduce friction in building data foundations. The best models emphasize:

• targeted support (standardization, implementation consulting, right tools),
• discouraging vanity reporting,
• linking funding with data discipline (requiring minimum data standards for eligibility).

In Vietnam, KisStartup advocates a “Lean first – digital later” approach: before pushing expensive tools, help SMEs build basic data discipline, measure key leading indicators, and complete 2–3 real learning cycles. Local governments, support organizations, and universities can serve as learning platforms — places to train “data muscles” before scaling up.

Two Real-World Snapshots: When Data Changes Direction and Saves Cash Flow

Case 1 – Pivoting through Data Insight
A personal care startup positioned itself as “premium gifts.” After three small test rounds (pre-orders + interviews with non-buyers), they found that the main reason for rejection wasn’t price — it was lack of safety proof. They shifted their MVP from “luxury packaging” to “simple clinical evidence” (test certificates, ingredient transparency, process videos). Sales didn’t skyrocket, but conversion doubled. Data revealed a truth: customers buy trust, not boxes.

Case 2 – Cash Flow Saved by One Leading Metric
A fresh-food retailer struggled with inventory. They wanted AI forecasting; we suggested tracking one simple leading metric: repeat orders within 7 days. Data showed nearby customers reordered far more when receiving push notifications between 4–6 p.m. Targeting that “golden hour” sped up turnover, reduced waste, and revived cash flow. AI later helped — but one measurable truth saved them first.

Conclusion

Lean Startup in Vietnam will go further once we accept this truth: ideas and technology are abundant — disciplined learning is not.

When businesses treat data as fuel, not decoration; when teams dedicate weekly hours to learning from evidence; when every decision has branching criteria — Lean stops being a slogan and becomes a way of life.

KisStartup believes in the Vietnamese entrepreneurial spirit — flexible, resilient, hands-on. And we believe that spirit, placed within a disciplined Lean framework, will produce sustainable businesses — not just fast runners, but long-distance contenders.

When more enterprises “work with data” instinctively, AI will cease to be a magic wand and become a jet engine on a well-built aircraft. Innovation will no longer belong to a lucky few — but become the shared capability of an entire ecosystem.

© Copyright KisStartup. All reproduction, citation, or reuse must credit KisStartup as the source.

For many years, discussions about digital transformation have focused mainly on productivity, efficiency, and economic growth. Yet, through the practical journey of the IDAP – Inclusive Digital Adoption Project, KisStartup has discovered a deeper dimension: digital transformation not only reshapes economies but also preserves and enriches culture – the very soul of communities.

In the highland villages of Lào Cai and Sơn La, technology has not arrived as a foreign wave but has gradually become a bridge that brings local identity to the world. It helps revive cultural heritage in new forms — digitized, shared, and passed on to younger generations.

When Technology Becomes the Storyteller of Identity

Through IDAP’s training programs, many artisans, teachers, and ethnic minority youth have learned how to record, store, and present their cultural heritage using digital tools. Small classes on video production, product photography, and content design have become creative spaces where locals learn to “tell their cultural stories” in their own voice.

In Sơn La, lecturer Lò Thị Ngọc Diệp and her students at Tây Bắc University have worked together to digitize Thai cultural traditions — from performances to instructional videos shared on social media.

Such efforts are turning YouTube into an open classroom where cultural values transform into creative products and services — music classes, cultural tours, ethnic embroidery workshops, and traditional handicraft lessons.

In Lào Cai, Dr. Đặng Thị Oanh and her team of lecturers and students are documenting and promoting the spiritual traditions of the Dao people. Meanwhile, Ms. Vàng Thị Mai has been collecting ancient then songs of the Tày in Bản Liền, inspiring others to join her efforts. Her small class has evolved into a community-run hub, where locals teach, learn, and share their traditions online through YouTube and Facebook.

Digital Technology – The Companion of Heritage

Around the world, technology has become humanity’s extended memory, helping to preserve and revive what once seemed lost.

In Guatemala, Duolingo added the K’iche’ language of the Maya people, reviving a tongue once on the brink of extinction. In Bolivia, the OEI App preserves five indigenous languages with pronunciation guides and e-dictionaries, allowing mountain children to reconnect with their mother tongues.

In Australia, Canada, and New Zealand, technologies such as VR360, 3D scanning, and virtual reality are used to recreate festivals, stilt houses, pottery, and ancient dances — allowing global audiences to walk through indigenous spaces from across the world.

Some projects even experiment with blockchain to protect community intellectual property — from textile patterns and indigo-dyeing recipes to traditional medicines — ensuring that traditional knowledge is shared fairly and safeguarded from commercial exploitation.

Emerging technologies like AI, virtual reality, cloud storage, digital linguistics, and blockchain are helping cultural heritage to live again in interactive, accessible forms. Yet, these tools only gain true meaning when local communities themselves are the storytellers.

Lessons from IDAP: When Communities Lead the Digital Journey

Experiences from Lào Cai and Sơn La show that when digital transformation begins with culture, it creates stronger and more lasting connections than any technical project could.

In Bản Liền, the Tày community not only digitized the production process of ancient tea but also used short videos to tell its history — sharing traditions of leaf-picking, tea-making, and festive tea ceremonies. Their fanpage “Hương Trà Bản Liền” (The Fragrance of Bản Liền Tea) has become more than an online shop — it’s a living cultural classroom.

In Bản Lùn, the Thai community organized folk song classes with livestreams, where children learned to sing, film, and edit videos, adding captions and descriptions. The entire village joined in — each person playing a role — creating a community-built digital archive of ethnic music.

IDAP calls this approach “community-led digital transformation” — where technology is localized and owned by the people, not imposed from outside. This allows culture to evolve naturally, while also generating new economic value without losing authenticity.

Preserve to Develop – Develop to Spread

Technology can preserve, but its ultimate purpose is to bring culture back into modern life.

Music lessons, cultural tours, storytelling videos, and handcrafted souvenirs are ways of transforming heritage into tangible value. Each song, dance, and weaving pattern no longer sits behind glass or in research books but is digitized, shared, and becomes a source of inspiration for new generations.

When a student in Sơn La can teach the tính lute on TikTok, or an artisan in Bản Khảo hosts an online indigo-dyeing class, culture has truly entered the digital age — in the most human, patient, and creative Vietnamese way.                            

Challenges and Vision

Digital transformation in culture poses significant challenges: balancing preservation with commercialization, openness with protection of traditional knowledge. Without proper guidance, technology can distort or exploit heritage. Therefore, the core principle must be that ownership of knowledge and content belongs to the indigenous community.

KisStartup and IDAP’s partners aim for a model of sustainable cultural development, where technology plays a supportive role — helping communities to tell their own stories, share them widely, and create their own value.

The Road Ahead

From small filming classes in Sơn La to cultural tourism products in Lào Cai, digital transformation is rekindling the creative flame within each community.

When technology becomes a tool of culture, not its replacement, we can envision a future where national identity does not fade — but finds new life in the digital world.

“Digital transformation does not blur tradition – it gives tradition a new voice.”

And it is the young people, artisans, teachers, and small enterprises in the mountains — together with KisStartup — who are writing this next chapter: making culture more vibrant, more widespread, and more valuable in the digital era.

© Copyright KisStartup. Content developed under the IDAP Project – Inclusive Digital Adoption Program. Any reproduction, quotation, or reuse must cite KisStartup/IDAP as the source.

Image source: https://steveblank.com/2015/05/06/build-measure-learn-throw-things-again...

When KisStartup began disseminating the Lean Startup methodology in Vietnam in 2015 after the Vietnam-Finland Innovation Partnership Programme - IPP2, hardly anyone was talking about MVP, validated learning, or innovation accounting. Most startup classes at the time revolved around writing business plans, and the numbers founders presented were based on intuition rather than evidence. Ten years have passed, and if we had to summarize that journey, KisStartup would choose two words: "co-learning." We didn't teach startups how to "do Lean," but rather lived Lean with them, experimenting together, failing together, and learning to adapt together. And through that process, KisStartup also became a "Lean organization"—a continuous learning organization, operating leanly, and constantly evolving.

Lean Startup – A Mindset for Learning and Management in Uncertainty

Eric Ries's book, The Lean Startup, was born from the author's own failed startup experiences in Silicon Valley. Ries didn't write about "secrets to success," but about how to reduce risk when you don't know what's right. He laid the foundation for the concept of "management of uncertainty"—a type of management where the goal is not to maintain stability, but to learn quickly to adjust quickly.

The five core principles of Lean Startup—from "Entrepreneurs are everywhere" to "Innovation accounting"—became the compass for the first generation of Vietnamese startups that KisStartup supported. But we quickly realized that Lean only truly makes sense when it is reinterpreted to suit the Vietnamese context, where resources are scarce, data is limited, and perseverance is the most precious asset.

For KisStartup, "Lean" does not just mean technical efficiency; it is a mindset of economizing and intelligently using all available resources: time, money, knowledge, people, and especially trust. In a country where most startups begin with small personal savings, loans from friends, or family capital, "Lean" must mean "enough to try, not too much to break."

Lean thus became a philosophy of practice, not a slogan. It reminds us that every decision is a hypothesis that needs testing, every step should generate data, and every failure is a lesson cheaper than a big failure later on.

KisStartup's Choice to "Work Together" Instead of Just "Teaching"

When starting out, KisStartup realized that if they only "taught Lean," the Lean Startup would easily become a theory on paper—easy to understand, but difficult to execute. This is because Lean is not a tool, but a habit of action: getting out to meet customers, asking the right questions, running small experiments, and measuring in a tangible way.

Instead of organizing courses that "talk about Lean," KisStartup chose to design real Lean workshops—where startups had to find customer insights themselves, generate hypotheses, create MVPs, and receive real feedback. We read data together with them, analyzed signals, and many times witnessed the "aha moment" when a founder realized: what they thought the customer wanted and what the customer actually needed were two different worlds.

This "co-working" approach is what made KisStartup different. We did not stand in the position of "instructor" but became the second learner, going through each Build–Measure–Learn cycle with the startup. When startups experimented with products, we also experimented with coaching methods. When they measured customer feedback, we measured the effectiveness of our support activities. And when they failed, we learned how to redesign our service model.

From hundreds of workshops, KisStartup gradually formed its initial incubation models—models that also went through their own Lean cycles: small tests, measuring effectiveness, scaling if successful, and "sunsetting" if they failed to generate learning value. It is thanks to this spirit that KisStartup has been able to survive and thrive for 10 years without becoming "bloated" or falling into the bureaucratic spiral often seen in innovation support organizations.

Lessons from Practice – When Lean Becomes a Mirror

After a decade, KisStartup has accompanied hundreds of founders and organizations on their Lean journey. There are success stories we are proud of, but also many incomplete stories that we still cherish as hard-earned lessons. Over 10 years, KisStartup has encountered every scenario: eager startups, discouraged startups, surprisingly successful startups, and seemingly viable models that quickly collapsed.

One tech startup in the tourism sector was passionate about perfecting their app with all features—maps, booking, payment—only to discover that their target customers—homestays in the mountains—had no need for it. It was only after trying an "MVP without an app"—using just a Zalo group and Google Form—that they truly understood the value they could offer. This lesson became a prime example in KisStartup's training program: The MVP is not a technological product, but a learning product.

Conversely, there were also startups that persevered with experimentation and achieved surprising success. A processed agricultural product team used Lean to identify the "flavor and packaging specifications" most favored by consumers. They didn't invest in a large production line from the start but ran small batches, measured feedback, and then scaled up. After two years, their product was sold in many markets—not due to luck, but due to the discipline of learning.

But it is from these differences that we have distilled three core lessons:

1. The MVP is not a technical product – but a learning product.Many startups in Vietnam spent months perfecting features but never asked customers what truly created value. Lean helped them reverse this: test the value before building the feature.
2. No measurement, no learning.Some startup teams "run Lean" but fail to collect quantitative data—all decisions are still based on gut feeling. We learned how to set up minimal "innovation accounting": clearly define the hypothesis – the metric – and the decision threshold before each experiment cycle.
3. Failure is not scary, only the failure to learn is.The models that stopped the earliest often left the most valuable data—because they showed which hypotheses were wrong, thereby opening up new directions.

“There is no failure, only an incomplete loop.” (KisStartup internal note, 2019)

From these successes and failures, KisStartup draws a simple principle: Lean cannot save every startup, but Lean helps every startup know why they failed. And only by understanding the cause can they get back up on the right track.

When Lean Meets Design Thinking and Effectuation – "Lean with Vietnamese Identity"

Throughout the process of practicing Lean, KisStartup realized that there is no single template for innovation. Lean Startup is very strong in the experimentation and measurement phase, but to deeply understand customers and create true value, it needs Design Thinking, and to start in resource-constrained conditions, it also needs Effectuation—the entrepreneurial mindset focused on achieving results from available resources.

Design Thinking: people at the center of leanness

If Lean Startup answers the question "How to learn fastest?", Design Thinking helps us answer "What to learn from people?" Design Thinking begins with empathy—deeply listening to people's difficulties, needs, and motivations—and from there forming ideas, testing solutions, and continuing to learn from feedback.

By combining Lean with Design Thinking, KisStartup helps startups create products that are not only "market-right," but also "people-right." For example, in community tourism projects in Son La and Lao Cai, instead of starting with the question "How to sell tours?", we guided local groups to start with the question "What are visitors truly seeking when they come to our village?" That question opened up a series of observations, conversations, and service experiments—and each subsequent Lean cycle became deeper because every experiment was based on genuine human insights

Design Thinking, therefore, does not oppose Lean, but complements the "emotional" part of the learning loop—so that the product is not only optimized but also meaningful.

Effectuation: leanness from available resources

While Design Thinking starts from the customer, Effectuation—the theory of entrepreneurship by Professor Saras Sarasvathy (Darden School, University of Virginia)—starts from the entrepreneur themselves. Instead of setting a big goal and then figuring out how to mobilize resources, Effectuation teaches us to start with what we already have: knowledge, relationships, small assets, and belief.

When KisStartup applied Effectuation along with Lean, we saw "leanness" reaching a new depth. Founders no longer worried about "lacking capital," but focused on "what do I have in my hands to start the first test cycle?" A founder in the mountainous region started producing herbal tea from her own family garden. Without waiting for fundraising, she tried selling via Facebook, recorded feedback, adjusted the flavor and packaging, and then scaled up. This is Lean originating from Effectuation—learning by doing, within the constraints of real resources, but full of creativity.

For KisStartup, this spirit is especially suited to Vietnam: don't wait until you have enough to start—start to learn and find a way to get enough.

When AI Accelerates Build–Measure–Learn

In 2025, AI is completely changing the rhythm of Lean Startup. If each Build–Measure–Learn cycle previously lasted weeks, AI now helps shorten it to hours or days:

• Build: Create content, mockups, and simulated scenarios using AI and no-code tools.
• Measure: Automatically collect user behavior and analyze real-time feedback.
• Learn: AI suggests pivots, identifying hidden insights in small data.

Thanks to this, startups—and KisStartup itself—can experiment faster, deeper, and more accurately. But even as technology changes, the Lean spirit remains the same: genuine learning, avoiding "vanity metrics," and making evidence-based decisions.

Lean within KisStartup – The Learning Organization of Co-Learners

When KisStartup helps startups learn Lean, we also apply Lean to ourselves. Every program (such as IDAP – Inclusive Digital Transformation, GEVA – Green Export, or DormLab – Student Laboratory) is built as an organizational MVP: starting small, with a hypothesis, a measurement method, and criteria for adjustment.

If a program brings learning value to both participants and KisStartup, it is scaled up. If not, it is improved or terminated. This approach has allowed KisStartup to maintain the flexibility of a startup throughout 10 years of operation, avoiding operational inertia or dependence on a single model.

It is through this journey that KisStartup understands that leanness is not about reducing scale, but about optimizing meaning—doing less but learning more, doing things right for people, and creating a more lasting impact.

MVP 2025 – Learning from Action, Not Plans

After 10 years of practice, KisStartup has developed the MVP 2025 framework—the "minimal but valuable" version of Lean Startup, suitable for the era of AI and automation.

Today, an MVP not only needs to be "minimal" but must also have a clear learning objective. A good MVP is not the cheapest product, but the product that can generate the strongest signal from the market at the smallest cost.

We often ask founders three questions before they start:

1. Which hypothesis do you want to test first?If you don't know what you're testing, your experiment is meaningless.
2. How will you measure it?No data, no learning.
3. What will you learn if the result is unexpected?Each Lean cycle is only valuable if there is a plan for... failure.

Today, "MVP" is not just "Minimal Viable Product"—it is "Meaningful, Valuable & Practical." The table below is the checklist KisStartup uses when working with startups and designing new services:

Criteria	Verification Question	Practical Example
Core Hypothesis	What are we testing? (need, pricing model, distribution channel?)	“Are customers willing to pay for Product X?”
Learning MVP	Does the experimental version help collect real data?	Selling first via a landing page instead of investing in a website.
Measurement Metrics	Have the pivot/persevere decision metrics been clearly defined?	Number of trial orders > 30 in 2 weeks = continue.
Learning Loop	Is there a plan for improvement after each experiment cycle?	Weekly result review, canvas update.
True Insight	Does the collected data help understand customers deeply, not just "count clicks"?	Analyze feedback to understand why they didn't buy.

When startups can answer these three questions, they have a true MVP in hand. And when they maintain a disciplined Build–Measure–Learn cycle, they are creating a sustainable foundation for learning—not just product development.

The Lean Mindset is Not Outdated, Just Evolving

After ten years, KisStartup realizes that Lean Startup remains one of the most powerful mindsets for dealing with uncertainty. But Lean cannot exist alone. It needs the human element of Design Thinking, the flexibility of Effectuation, and the profound understanding of people in every learning cycle.

Leanness—in its deepest sense—is about living with limits but not being limited, having the ability to learn fast, adapt quickly, and create long-term value even with the smallest resources.

In the AI era of 2025, the Build–Measure–Learn cycle can happen in hours instead of months. But speed is only meaningful when accompanied by depth of learning. That is what KisStartup continues to pursue—not just to help startups succeed, but to build a learning, adaptive, and sustainable ecosystem, where every experiment is directed toward a bigger goal: developing people and businesses in a changing world.

“Lean doesn't mean less—it means learning faster, adapting better to create more sustainable value.” — KisStartup, 10-year reflection

© Copyright belongs to KisStartup. Any form of copying, quoting, or reuse must clearly state the source KisStartup.

Many businesses tend to think of VSS as a “ticket” and ESG as a “scorecard.” In reality, it should be the other way around: ESG is the operational architecture from within — it determines what you produce, how you produce it, how you manage risk, and how you measure performance. Once that internal system operates stably, VSS becomes merely a verification and standardization step — a shared language with buyers. Rigid trade barriers like MRL or EUDR will continue to exist. Therefore, to go far, businesses must turn market requirements into internal capabilities — namely, data, traceability, and SOPs (Standard Operating Procedures).

From ESG to Business Model Design and Renewal

ESG doesn’t make a business “spend more” — if done right, it helps reduce risks, stabilize operations, and enhance credibility. ESG has a profound impact on three core design blocks: value, cost–productivity, and risk–governance.

It forces us to redefine the value proposition — shifting from “cheap and fast” to “stable, transparent, and safe.” By standardizing processes (e.g., saving water, reducing inorganic inputs, segregating and tracing production flows), quality variability decreases, which in turn lowers risk costs — the often-invisible but expensive burden in export. At the same time, ESG builds a “data discipline” that enables businesses to manage technical barriers (for instance, when the default MRL is 0.01 mg/kg if a substance has no specific limit in the EU) and policy risks (as the EUDR requires geolocation of production areas and segregation between compliant and non-traceable goods).

Two Case Studies – From Field to Model

Let’s look at two real-world examples introduced by Dân Việt newspaper to understand how farmers are moving toward sustainable, green production. In practice, ESG is not a PR slogan; it is a set of technical and management decisions — covering soil, water, fertilizer, labor, and data — that lead to stable productivity, lower risk costs, and “audit readiness.”

Case 1 – A Ngum (Bahnar, Gia Lai):
Since 2022, he has eliminated synthetic chemicals, switched to organic–microbial farming, practiced intercropping, and focused on soil ecosystem health. Results: reduced pests, stable yields, over 3.5 tons of coffee beans per hectare, and nearly VND 300 million net income per year. His farm has become a community learning site, showing clear social (S) impact. In terms of the business model, he repositioned his value from “chemical-intensive, yield-driven” to “safe, consistent, ecosystem-based.” With minimal record-keeping and traceability, his natural model aligns well with VSS frameworks that emphasize soil health and farmer welfare.

Case 2 – Nguyễn An Sơn (Đắk Lắk):
Since 2020, he has adopted multi-stem pruning and drip irrigation with a weekly “nutrition menu”, achieving about 40% water savings, 15–30% less inorganic fertilizer, and five-sixths labor savings. Yields reached ≈5.5 tons/ha (about 1.5 times traditional yields), producing 130 tons in 5 years, worth about VND 8.5 billion, with nearly VND 1 billion in annual profit — along with an OCOP 3-star brand. This is ESG through precision farming: saving resources (E), ensuring labor safety (S), and enforcing procedural and data discipline (G). As a result, meeting VSS and technical requirements becomes much easier.

From Practical Cases to the VSS Roadmap

There are no “shortcuts” to VSS compliance. There are two sustainable paths:

• (i) ESG-first – transform technical and management practices to generate standardized data, or
• (ii) Micro-lot-first – start small but compliant to learn fast and minimize “tuition costs.”

Both converge on data–traceability–SOPs.

When ESG practices become routine processes, requirements like MRL, microbial limits, or EUDR become ordinary management indicators. At that point, VSS serves as a “seal of approval” verifying that the system runs effectively — not a “lifebuoy” in crisis.
Certification investment also becomes easier to budget, as actual costs depend on context and scale, including preparation, evaluation, and maintenance — not just the “audit fee.”

Seven Suggested Steps

• Step 1 – Choose “high-impact, low-cost ESG levers”: irrigation, fertilizer, post-harvest hygiene, and labor safety. Identify 2–3 measurable indicators (moisture, fertilizer dosage, PPE work hours).
• Step 2 – Standardize a small pilot process (micro-lot 5–10%): set short SOPs, assign batch codes, separate storage; do it right, fully, and consistently for one crop season.
• Step 3 – Keep disciplined minimal records: digital or paper farming logs, store input receipts, score compliance weekly.
• Step 4 – Measure core technical indicators: test 1–2 lots for MRL, microbiology, heavy metals; refine processes accordingly.
• Step 5 – Make value transparent: use QR/batch codes linked to field photos, geolocation, simplified SOPs; tell the story of “saving water/reducing fertilizer/ensuring food safety.”
• Step 6 – Cross-check with VSS and test negotiation: compare micro-lot results with 15–25 minimum criteria of a target standard; test-tiered pricing with buyers (small contracts, seasonal improvement clauses).
• Step 7 – Tell your story: share authentic, transparent experiences to build a community of practice. Consolidated data will provide a full picture when proof is needed.

These seven steps effectively “package ESG” into business modules — each creating a data asset and a new operational capability — the very elements VSS measures and customers pay for when you can prove them.

Avoid Two Common “Traps” in VSS Implementation

In reality, costs often “inflate” because of mindset traps, not the standards themselves. Businesses tend to avoid action or fall into one of these traps, turning VSS into a burden:

• Trap 1 – Substitution Trap: believing that “having certification = exemption” from technical barriers. Wrong — MRL, microbiological, and EUDR rules are hard barriers. VSS merely helps structure your processes to overcome them consistently.
• Trap 2 – Overextension Trap: adopting multiple standards before having strong data–segregation foundations. The solution is to focus on one core standard aligned with your target segment; build a solid micro-lot before expanding.

To join global value chains and retain value, businesses must turn market requirements into internal capabilities. The shortest path is to redesign the business model around ESG, then use VSS to standardize and demonstrate performance.
From A Ngum (Gia Lai) to Nguyễn An Sơn (Đắk Lắk), both cases prove that ESG is a set of technical and managerial decisions that yield stable productivity, transparent data, lower risk costs — and thereby reduce expenses and increase success probability when pursuing VSS certification.

Note: At the time of writing, the EUDR has been announced by the European Commission to be postponed for another year due to technical reasons, pending approval by the Parliament and member states — but the direction toward geolocation, traceability, and supply segregation remains unchanged.

#GreenExportMindset #GreenExport #ESG #GEVA #KisStartup

© Copyright KisStartup. Content developed under the GEVA Project – Green Export Acceleration through Voluntary Sustainability Standards (VSS). Any reproduction, citation, or reuse must credit KisStartup/GEVA.

References

• EU – MRL (0.01 mg/kg default when no specific MRL): European Commission, EU legislation on MRLs (Food Safety)
• EU – EUDR (traceability, geolocation, compliant/non-compliant segregation): European Commission Green Forum, Traceability and geolocation of commodities subject to EUDR
• EUDR – One-year postponement update: Reuters; Financial Times
• VSS – Market trends and data: ITC, State of Sustainable Markets 2023
• Certification cost structure (context-dependent): Rainforest Alliance, How Much Does Certification Cost?; Fee Catalogue for Certification Bodies
• Field example – Gia Lai (A Ngum, organic–microbial farming): Dân Việt; Báo Gia Lai
• Field example – Đắk Lắk (Nguyễn An Sơn, multi-stem, drip irrigation, OCOP 3-star): Dân Việt; Báo Đắk Lắk

On October 14, 2025, the Government and the Ministry of Science and Technology issued Decree No. 264/2025/ND-CP - an important milestone opening a legal framework for venture investment activities in Vietnam.
For those who have worked for many years in the field of incubation and support for innovative businesses, we see this as a meaningful step forward, contributing to strengthening the confidence of the startup community, creating conditions for technology ideas, business model innovation and sustainable development to be better nurtured.
KisStartup wishes to continue to accompany partners, management agencies and investors to promote the Vietnamese innovation ecosystem to develop strongly, transparently and sustainably.

See details of this important Decree
https://thuvienphapluat.vn/van-ban/Dau-tu/Nghi-dinh-264-2025-ND-CP-Quy-d...

KisStartup JSC
Accompanying Vietnamese innovation
#KisStartup #Innovation #VentureCapital #StartupVietnam #OpenInnovation #VentureCapital #StartupVietnam

 

Digital transformation (DX) has become a matter of survival for Vietnamese enterprises, especially SMEs. However, according to recent surveys, the process faces a series of challenges: high investment costs, lack of digital human resources, limited technological infrastructure, reluctance to change, and the absence of a clear strategy. Only 7.6% of businesses have a well-structured digital transformation plan, while 48.8% have experimented with some solutions but failed to sustain them (Annual Report on Business Digital Transformation, 2022).

In this context, universities – with their combined roles in education, research, and knowledge connection – hold great potential to become strategic partners of enterprises in digital transformation. To support universities wishing to engage more deeply in enterprise digital transformation and to leverage their strengths, KisStartup presents a detailed analysis based on Hồ Tú Bảo’s six-step digital transformation framework. For each stage, corresponding university actions or programs are proposed to highlight their role as knowledge transfer hubs within the digital transformation ecosystem.

1. Awareness and Mindset Change

• Enterprise needs: Most SMEs lack a clear understanding of what digital transformation means or what practical benefits it brings. Many believe it simply means “buying new software.” The biggest barrier lies in management mindset and fear of change. According to a 2025 nationwide survey, 69% of businesses only use email or basic accounting software, without adopting more strategic digital solutions (Ministry of Science and Technology, 2025).
• What universities can do: They can organize awareness workshops, publish research reports on technological trends, or develop Digital Maturity Assessment tools to help SMEs evaluate their readiness. This model is common across Europe and feasible in Vietnam. With academic credibility, universities can better persuade business leaders who often distrust private service providers. International example: European universities have developed Digital Maturity Assessment Tools for SMEs.

2. Defining a Digital Transformation Roadmap

• Enterprise needs: SMEs often lack clear strategies or plans. Many initiatives are abandoned midway, causing waste. According to the Ministry of Planning and Investment (2023–2024), micro and small businesses face particular difficulties due to limited capital, human resources, and technical capability.
• What universities can do: Faculties of economics, IT, or management can develop digital readiness assessment frameworks and offer consulting services to build 6-month to 3-year roadmaps tailored to business size. Final-year students can participate as “junior digital consultants,” gaining practical experience while supporting companies.International example: University of Vaasa (Finland) successfully implemented an ecosystem-based digitalization model for local SMEs, yielding mutual benefits.

3. Building Digital Capabilities

• Enterprise needs: The lack of skilled personnel is the most critical barrier. The Enterprise Development Agency (2023) reported that most SMEs lack adequately trained staff to implement digital solutions effectively. External expert services are often unaffordable.
• What universities can do: Design short-term, hands-on training courses using real company data and workflows—for example, training business owners in basic data analytics, marketing staff in digital campaign management, or accountants in data security. International example: IE University (Spain) and Banco Santander launched the “Digitaliza tu negocio” program, providing digital skills training to over 3,000 SMEs. Vietnamese universities can replicate this through short-term certificate programs and online training for broader reach.

4. Identifying Core Technologies

• Enterprise needs: Amid countless ERP, CRM, AI, and IoT solutions, many SMEs struggle to choose the right technology. Wrong decisions lead to wasted investment. Moreover, their infrastructure is often weak and lacks proper devices, software, or cybersecurity systems.
• What universities can do: IT or engineering schools can establish digital technology laboratories where businesses can test solutions before purchasing. Universities can also host technology showcase events featuring multiple vendors, acting as independent technology advisors. International example: The Hartree Centre (UK) partners with universities to let SMEs experiment with AI and supercomputing before making investment decisions.

5. Implementation and Execution

• Enterprise needs: During implementation, challenges arise not only in technology but also in change management: data cleanup, process adaptation, and employee resistance. SMEs often lack mentors to accompany them through the process.
• What universities can do: Deploy research teams, faculty, and students to accompany companies in pilot phases, acting as “light PMOs.” Universities can also establish co-living collaboration models where both sides share costs and co-develop technology applications. International example: Germany’s Mittelstand 4.0 program has proven effective by organizing workshops and coaching SMEs to apply agile and design thinking methods to reduce implementation risks.

6. Business Model Transformation and Operational Adjustment

• Enterprise needs: After applying technology, SMEs must adjust their business models and operations. This is the hardest step, involving organizational culture and long-term strategy. Most Vietnamese SMEs lack experience in using data-driven insights to adapt their models.
• What universities can do: Conduct local SME case studies, organize peer-learning sessions, and support data analysis on customer feedback to help companies refine products, sales channels, and pricing strategies. International example: Utrecht University (Netherlands) collaborated with consulting firms to digitally transform management and learner experience systems—proving that model transformation must be data-driven.

Surveys in Vietnam show that SMEs face major obstacles: high investment costs, shortage of skilled personnel, reluctance to change, weak infrastructure, and lack of clear strategies. In this context, universities have the potential to become strategic pillars—training digital talent, providing applicable knowledge, connecting businesses with technology, and accompanying them throughout the digital transformation journey.

If leveraged effectively, Vietnamese universities can go beyond teaching students to become digital transformation hubs for SMEs, directly contributing to the sustainable development of the national digital economy.

Summary Table

 

Digital Transformation Step (Hồ Tú Bảo)	Vietnamese SME Needs	What Vietnamese Universities Can Do	International Example
1. Awareness & Mindset	Unclear about DX; 69% using only email/accounting tools	Organize mindset-opening workshops; create readiness assessment tools; publish trend reports	European universities’ Digital Maturity Tools
2. Roadmap Definition	Only 7.6% have formal plans; many abandon efforts	Develop readiness frameworks; offer roadmap consulting; involve student consultants	University of Vaasa (Finland) ecosystem-based model
3. Capability Building	Lack of digital workforce; high training costs	Short-term practical courses; “learn by doing” projects; student-SME support bank	IE University (Spain) & Banco Santander – “Digitaliza tu negocio”
4. Core Technology Selection	Hard to choose solutions; weak infrastructure	Build digital labs; host technology showcases; act as neutral advisors	Hartree Centre (UK) AI & HPC testing
5. Implementation	Lack of mentors; employee resistance; messy data	Faculty-student support teams; co-living collaboration models; mentor programs	Mittelstand 4.0 (Germany) agile workshops
6. Business Model Change	Hard to shift culture; lack of data-driven decisions	Conduct local case studies; analyze customer data; foster innovation networks	Utrecht University (Netherlands) management digitalization

 

© Copyright KisStartup. Developed within the IDAP Project – Strengthening an Inclusive Digital Transformation Ecosystem. Any reproduction, quotation, or reuse must cite the source: KisStartup/IDAP.
Source: https://qnu.edu.vn/vi/hoi-nghi-hoi-thao/bai-noi-chuyen-dai-chung-chuyen-...

     

In many discussions with businesses and farming households, the GEVA project has observed a common reality: the concept of Voluntary Sustainability Standards (VSS) often causes confusion. In theory, VSS are designed as voluntary options that businesses can choose to adopt in order to demonstrate their commitment to sustainable development. However, in practice, VSS are increasingly becoming a “soft barrier” that is almost mandatory for companies wishing to enter high-value export markets. In fact, many countries have begun to formalize parts of VSS into legislation to raise production quality standards and facilitate exports.

This shift stems from changes on multiple fronts—governments, large buyers, and most importantly, consumer behavior. Many countries and economic blocs such as the European Union, the United States, Japan, and Canada have integrated sustainability standards, including VSS, into their trade and public procurement policies (ISEAL, 2023). On the private sector side, multinational corporations use VSS as a “common language” to assess and select suppliers. Therefore, even when regulations do not explicitly require a specific certification, commercial practices effectively make VSS an indispensable condition for trade.

It is important to note that achieving a VSS certification does not guarantee customs clearance. Mandatory technical barriers—such as maximum residue levels (MRL) for pesticides, microbiological tests, heavy metal checks, and food safety standards—still apply. For example, in cases where no specific MRL has been established, the EU default level is just 0.01 mg/kg—a very stringent threshold that forces farmers to change their fertilizer and pesticide practices (European Commission, 2023). In other words, VSS help standardize production processes and enhance credibility, but they do not replace mandatory legal requirements.

At the same time, new layers of requirements are emerging. A prime example is the EU Deforestation Regulation (EUDR), which obliges exporters of coffee, cocoa, wood, rubber, and other commodities to prove that their products are not linked to deforestation after December 31, 2020. This regulation requires precise geographic coordinates of the production area and a traceability system that can distinguish compliant and non-compliant batches (European Commission, 2023). Although the enforcement deadline has been extended until the end of 2025 for medium and large enterprises and until 2026 for small enterprises, the message is clear: no transparent data, no export.

In this context, many businesses have adopted short-term survival strategies—selling fast and cheap rather than investing in small but certified batches. This “survival choice” reflects three underlying factors:

• High conversion costs – including investment in data systems, staff training, and certification fees, which are a major burden for SMEs (Rainforest Alliance, 2024).
• Behavioral inertia – particularly in agriculture, where changing production habits is much harder than changing techniques.
• Short-term cash flow pressure – forcing businesses to prioritize large-volume, low-margin sales to stay afloat rather than investing in new models that take time to mature.

However, this approach cannot build long-term competitiveness. The State of Sustainable Markets report by ITC, FAO, and IISD shows that VSS-compliant agricultural areas and production volumes continue to grow annually across crops such as coffee, cocoa, and rubber (ITC/FAO/IISD, 2023). This means that early adopters are steadily gaining market trust and competitive advantage, while those focusing solely on low-cost, fast exports risk being excluded from high-quality supply chains.

The key to overcoming this challenge lies in a mindset shift. Instead of passively reacting to buyer demands, businesses should proactively embrace ESG (Environmental – Social – Governance) as a core business goal. ESG should not be viewed as a cost but as a foundation for operational efficiency, risk reduction, brand reputation, and investment opportunities (CRIF Digital, 2024; EdenSeven, 2023). Meanwhile, VSS should be regarded as a measurement and roadmap tool—helping businesses understand their current status, identify improvement areas, and transparently demonstrate progress to customers.

Initial actions do not need to be complex. Businesses and farmers can start by:

• Assessing current status: compare technical requirements of target markets with actual production conditions.
• Building a data handbook: record farming logs, maps of production areas, and participant lists.
• Product segregation: minimize mixing risks through batch codes and separate storage.
• Testing micro-lots: apply strict standards to 5–10% of production as pilot certified lots.
• Studying suitable VSS: understand core requirements before registering for certification.

In short, VSS are no longer an optional choice but have become a crucial tool for accessing export markets. At the same time, ESG must serve as an internal foundation. The shift from a “fast-and-cheap” mindset to a “proactive-and-sustainable” strategy is the only viable path for Vietnamese enterprises and farmers to increase product value and seize opportunities in global supply chains.

To assess your readiness for green transformation, you can use the tool developed by KisStartup under the GEVA project:
https://greenexport.vn/vi/bo-cong-cu-do-luong-muc-do-tuan-thu-tieu-chuan...

© Copyright by KisStartup. This content was developed within the framework of the GEVA project – Incubating and Accelerating Green Exports through Voluntary Sustainability Standards (VSS). Any reproduction, quotation, or reuse must cite KisStartup/GEVA as the source.

References
[0] ITC/FAO/IISD (2023). State of Sustainable Markets.
[2] CRIF Digital (2024). Integrating ESG for sustainable business growth.
[4] Social Value Portal (2023). Social Value and ESG: What’s the difference?
[5] EdenSeven (2023). ESG as a bolt-on vs. strategic integration.
[11] European Commission (2023). EU Deforestation Regulation (EUDR).
[13] European Commission (2023). Maximum Residue Levels (MRLs) for pesticides.
Rainforest Alliance (2024). Certification costs and assurance system.