Lean startup

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.

Under limited resources, converting an entire farming area or factory to meet Voluntary Sustainability Standards (VSS) at once can drive up costs and risks significantly. The lean startup mindset offers a more sustainable path: start small with a micro-lot (5–10% of output), segregate product streams to prevent mixing, learn by doing, collect real data, and then scale selectively. This aligns with the Build–Measure–Learn principle: instead of lengthy planning, build a “minimum viable product” (MVP) — a pilot batch — measure technical, commercial, and impact indicators, and learn to adjust or pivot before scaling. This approach, systematized in Lean Startup, has proven effective in reducing waste and accelerating market fit.

Micro-lot: A Laboratory for New Business Models

In the specialty coffee industry, a micro-lot refers to a traceable, segregated batch — distinct in origin and process. Its value lies not in size but in controlled, consistent, and transparent management — enabling storytelling, pricing experiments, and new customer relationships.

In supply chain terms, a micro-lot only adds value when its identity is preserved throughout: physical segregation, dedicated records and logs, batch labeling, and controlled handovers — the logic behind identity preservation, segregation, and traceability in agri-food systems.

Segregation: Turning Data into Assets

“Segregation” is essential to prevent micro-lots from dissolving into bulk commodities. Traceability frameworks like ISO 22005 and GS1 GTS emphasize systems for recording and linking each node in the chain to specific batches. Simply put: no segregation, no traceability; no traceability, no value differentiation.

With new regulations such as the EUDR requiring plot-level geolocation and recordkeeping, segregation becomes a must-have for market access. It should be seen not as a cost, but as an investment in data assets that strengthen buyer negotiations.

Micro-lot as an MVP in the Build–Measure–Learn Cycle

Build – Identify a manageable lot (5–10% output) with uniform variety, ripeness, and process. Design a short SOP, assign batch codes, allocate separate storage, and record in simple digital logs (Google Sheets/Excel). This is your MVP — small, distinct, and low-cost to test and learn quickly.

Measure – Select a minimal set of indicators in three layers:

• Technical: moisture/defect rate, MRL/microbiology test results, SOP compliance rate.
• Commercial: offer vs. accepted price, deal closure speed, contract terms.
• Impact/ESG: water/fertilizer reduction, PPE use, farmer feedback.

Focus on actionable metrics — numbers that drive decisions — not vanity statistics.

Learn – Compare unit price differentials, added costs, and risk reductions between micro-lots and bulk batches. If results fall short, pivot: target a new customer segment, adjust processing, or refine the product story and packaging. The B–M–L loop helps avoid “big spend first, lessons later.”

Premium Potential: “Different Enough” and “Clean Enough”

Evidence from specialty markets shows genuine potential: micro-lot prices often exceed local or bulk prices by 74–327%. Yet, premiums aren’t automatic — they depend on sensory quality, traceability storytelling, and batch uniformity.

Still, the “tuition cost” must be acknowledged: segregation reduces blending flexibility and raises management costs. The premium must offset this loss — a reality highlighted by coffee market analysts.

Designing Micro-lots as Business Model Experiments

A micro-lot is a sandbox for testing all business model variables:

• Customer segment: experiment with direct sales to roasters or high-end chains instead of bulk traders.
• Value proposition: offer “uniform–traceable–ESG story” instead of “cheap–fast.”
• Channels & relationships: small but recurring contracts; season-on-season improvements; price differentiation by quality score.
• Revenue & cost structure: separate accounting to identify the “premium break-even point.”
• Impact (E–S–G): measure water savings, reduced chemical use, safety improvements, and data credibility.

This design fits Lean philosophy: test fast – learn fast – iterate fast instead of perfect plans first.

Suggested 90–180–360-Day Roadmap

• 90 days: select a micro-lot; create short SOPs, batch codes, and separate storage; log data and photos via Google Sheets/Excel for collaboration.
• 180 days: measure key indicators (technical, commercial, impact); conduct representative lab tests (MRL/microbiology); test tiered pricing with 2–3 buyers.
• 360 days: review the B–M–L loop; scale selectively (from 5–10% to 20–30% of output) if premium–risk–cost results are positive; align with ISO 22005/GS1 standards for full traceability and VSS readiness.

Common Risks & Mitigation

• Micro-lot without segregation: loss of identity → loss of premium. → Solution: strict labeling, separate storage, handover documentation per ISO 22005/GS1.
• Tracking vanity metrics: attractive numbers that don’t guide action. → Solution: focus on 5–7 actionable indicators tied to pricing, volume, or cost decisions.
• Premium not offsetting costs: weak story or quality differentiation.→ Solution: improve process, pivot customer segment, or refine product/packaging.

Micro-lot and segregation are not just technical measures — they reflect a Lean experimentation mindset: Build–Measure–Learn. Start small to learn fast; standardize data and processes for reliability; scale up with evidence. When micro-lots deliver measurable differentiation, firms both unlock premiums and shorten their path to VSS compliance — since the hardest part (data discipline and traceability) is built from day one.

References
Blank, S. (2013). Why the lean start-up changes everything. Harvard Business Review.

https://hbr.org/2013/05/why-the-lean-start-up-changes-everything (Harvard Business Review)

Blank, S. (2013). Free reprints of “Why the Lean Startup Changes Everything”. Steve Blank Blog.

https://steveblank.com/2013/05/06/free-reprints-of-why-the-lean-startup-... (Steve Blank)

ISO. (2007). ISO 22005:2007—Traceability in the feed and food chain.

https://www.iso.org/standard/36297.html (ISO)

ISO. (2007). ISO 22005:2007 (online browsing platform) — principles & requirements.

https://www.iso.org/obp/ui/ (ISO)

GS1. (2021). GS1 Global Traceability Standard (GTS).

https://www.gs1.org/standards/gs1-global-traceability-standard/current-s... (GS1)

GS1. (2017). GS1 Global Traceability Standard (PDF).

https://www.gs1.org/sites/default/files/docs/traceability/GS1_Global_Tra... (GS1)

European Commission. (n.d.). Traceability and geolocation of commodities subject to EUDR.

https://green-forum.ec.europa.eu/nature-and-biodiversity/deforestation-r...

Driven Coffee. (2024). What is microlot coffee, and what makes it special?

https://www.drivencoffee.com/blogs/blog/what-is-microlot-coffee (Driven Coffee)

Perfect Daily Grind. (2020). What is a micro lot in specialty coffee?

https://perfectdailygrind.com/2020/04/what-is-a-micro-lot-in-specialty-c... (Perfect Daily Grind)

Coffeelands/CRS. (2013, June 26). The economic impacts of microlots.

https://coffeelands.crs.org/2013/06/367-the-economic-impacts-of-microlots/ (coffeelands.crs.org)

Daily Coffee News. (2013, June 26). Exploring the economic impacts of microlots….

https://dailycoffeenews.com/2013/06/26/exploring-the-economic-impacts-of... (Daily Coffee News by Roast Magazine)

Oilslick Coffee. (2023, June 18). Microlots (Coffee Prices: The Big Fix).

https://oilslickcoffee.com/economics/market/coffee-the-big-fix/ (Oil Slick Coffee)

Smyth, S., & Phillips, P. (2002). Product differentiation alternatives: Identity preservation, segregation, and traceability. AgBioForum, 5(2), 30–42.

https://agbioforum.org/wp-content/uploads/2021/02/AgBioForum_5_2_30.pdf (agbioforum.org)

Google Support. (n.d.). Share & collaborate on a spreadsheet.

https://support.google.com/a/users/answer/13309904

Microsoft Support. (n.d.). Collaborate on Excel workbooks at the same time with co-authoring.

https://support.microsoft.com/office/7152aa8b-b791-414c-a3bb-3024e46fb104 (Harvard Business Review)

(Tài liệu bổ trợ: PECB/ISO 22005 overview; GS1 chain-of-custody & DSCSA để tham chiếu mô hình truy xuất/segregation trong các chuỗi khác). (PECB)

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.

KisStartup was established in 2015 with the mission to accompany entrepreneurs and startups in enhancing their innovation capacity, to support them to innovate more effectively and bring more practical benefits to the community.

Our vision is to become a flourishing community of innovators, rooted in Vietnam and acting globally, that creates long lasting impact.

To realize our vision, we nurture the following values:

(1) Empathetic: Always starting a business, always empathize. We constanly nurture our entrepreneurial experience to have the deepest understanding of innovative people/organizations

(2) Trusted supporter: Always a good support partner for start-up projects, partners and customers

(3) Innovative: Continuously innovate to create new values

(4) Get it done: To us, simplicity is intelligence

(5) Learning: At KisStartup, no one is not learning something. 

(6) Challenge accepted: Setting up your own challenges is how our team matures

 

(7) Constantly curious:  Make us maintain motivation and excitement every day

 

(8) Transparency:  Make us always confident in our activities and values

 

We carry out our mission through a series of activities: 

• Training

Lean Startup for Startups: provide knowledge and tools to validate ideas and business model, complete business model, and market products.

Lean Startup for Enterprises: provide leaders with right mindset and tools to innovate, develop products/services/project in the spirit of Lean Startup.

Training of the trainers (ToT)

Training of Innovation Coach

Training of Ecosystem player >> View details

• Coaching

​We adopt Lean Startup – mindset and tools – to support startups in finding, identifying, discovering customer and working out a sustainable business model.

Duration: Coaching 1:1 once per week for 03 – 06 months (or by request) is advised. >> View details

• Mentoring

SME Mentoring is our not-for-profit activity as a part of SME Mentoring 1on1, first introduced in 2011 in HCMC. SME Mentoring helps to get community members closer and establish a mentoring culture, making it our feature activity. In 2015, KisStartup Cofounder and Manager Nguyen Dang Tuan Minh becam Manager of SME Mentoring & Networking Hanoi.

Find out more about SME Mentoring 1:1 in Vietnam in general and HCMC, Hanoi in particular here: http://www.mentoring1on1.com >> View details

• Research

KisStartup conducts researches related to innovation and entrepreneurship that are practical and useful for businesses, investors, domestic and international support organizations, and other stakeholders. Our research helps enhance the efficiency of the decision-making process.

Learn more about our research capacity >> Click here

Learn more about our research team >> Click here

Learn more about our research case studies  >> Click here

• Content Development

Enabling innovative projects to validate their business models via innovative content development and management. >> View details

• Knowledge-sharing Channels Development

Visit our LinkedIn: https://www.linkedin.com/company/kisstartupvietnam/

Visit our Youtube Channel at: https://kisstartup.com/en/youtube