The first 90 days of your new startup will be completely chaotic.
You have an idea, a clean slate, and no empirical evidence that anyone will want what you are producing. The instinct of most new founders is to go into hiding.
They go into stealth mode, spend about six months creating a product and/or writing the code necessary for that product, and then show up and say, "Here I am."
This is the path that is almost guaranteed to result in failure.
The other option is to use an Operating System (OS) that was specifically designed for dealing with extreme levels of uncertainty.
That means treating your startup not as a mini version of a big, established company but instead as an experiment in search of a repeatable and scalable business model.
You need to have a framework to follow.
This guide is designed to provide you with a clear step-by-step process for implementing the OS methodology.
It goes beyond just a bunch of definitions and instead provides you with real-life examples of how to successfully implement this OS methodology.
If your goal is to stop guessing and start validating, then the following rules of engagement should help you be successful.
Summary: Founder cheat sheet
For the time strapped entrepreneur, here's a quick breakdown of the core OS methodology:
- Value Hypothesis: Before you build, you must prove that someone wants it, so get that proof first!
- Business Model Hypothesis: After you have your value hypothesis validated, you must prove that people will pay for it in a way that allows you to keep the company alive!
- MVP (Minimum Viable Product): Only build the very smallest amount of product you need in order to validate your assumptions.
- Build-Measure-Learn: You will use this reverse loop. Decide what you need to learn. Figure out how you will measure that learning. Build the item you are trying to validate.
- For an effective Lean Startup approach, define 'Value Hypothesis' - The value your product or service provides, through a process to validate that the customer will actually use/ value your product/service. Customers will not hear about it unless you market it successfully!
- Define your Growth Hypothesis: how new customers will learn about your product. Research and document, for example, how other customers of the same business model have successfully found and become customers.
- As you progress through the Lean Startup methodology, you will begin to eliminate failed assumptions/background work and start to use real 'data', gathered and tracked, as a basis for making business decisions on a 'real' basis rather than continuing to run a company on just 'gut instinct'.
Principles for successful implementation of lean startups
In this section: Principles for Successful Implementation of Lean Startups for New Entrepreneurs, and Why You Should Follow These Principles.
New entrepreneurs often confuse the term "lean" as it relates to their business as simply being a low-cost option, i.e. lean manufacturing or lean logistics.
This is an extremely dangerous misconception about "Lean". Lean, as it relates to your business, is primarily about the "speed of the learning cycle".
The Lean StartUp methodology provides a systematic means for reducing risks to your business (whether developing products, sourcing products, determining/achieving your target customer, etc).
The end goal of Lean StartUp is to design and build a product/service that has a high likelihood of being successful if you invest your time and resources into it, thereby saving yourself many years and thousands of dollars developing and marketing a product that nobody wants.
Lean StartUps enable entrepreneurs to establish business models based on actual 'scientific experimentation' as opposed to making their 'gut' based assumptions on the product or service design/market validation.
This is done by systematically identifying the Product/Service Value (does this solve a customer problem?) through the Value Hypothesis, and Growth (how will customers find out about the product/service?), through the Growth Hypothesis, and utilizing the data collected to determine if they should 'Pivot' (change direction) or 'Persevere' (stay on track).
Principle 1: The value hypothesis
You must first identify your target audience. Once you have done this, the next step is to conduct discovery interviews.
Listen to what your customers have to say.
If they are not complaining about the problem you are trying to solve, or if they haven’t created their own solution, then you know their pain doesn't exist.
To create a strong value hypothesis, you need to gather evidence that friction exists.
For instance, if you are creating a tool to automate the accounting process for freelance workers, you need to hear freelancers explicitly complain about how much of a nightmare tax season is and how many billable hours they lose.
Cross-industry applications
There are different ways to verify the value hypothesis across different industries:
- SaaS Software: Create a landing page that converts like crazy and explains the core benefits. Add a pricing tier and a “Buy Now” button. Once someone clicks on the button, redirect them to a “Currently in Beta” message that asks for their email address. The goal is to measure intent.
- Physical Goods: Use high-quality 3D renderings to create high-quality images of your product, then advertise it using targeted Facebook and Instagram ads that link to your pre-order page. If you can’t get people to put down a $5 deposit, you won’t get them to buy your finished product at a price point of $50.
- Service-Based Companies: Begin by offering the specific service to individuals in a highly targeted local area. For example, if you want to create an Uber-like app for laundry services, go to homes, pick up their laundry, and take it to a laundry service.
The biggest pitfall
Founders often confuse people saying they are nice or encouraging versus validating that they are interested in purchasing your product or service.
When seeking validation for an idea from people, the assumption is that the person will give the most positive answer. People always want to be supportive and put positive spin on something else.
Validation is anything that someone gives you that indicates that they find enough value in whatever it is that you are offering.
At the point that you receive an email address, a block of their time, or money from someone, you have created a valid assumption about the value of your idea or product.
Principle 2: Business model hypothesis (Can it survive?)
While the fact that there are people that want what it is that you have created represents part of the equation, there is an equal, if not greater, part representing how you will monetize that value and turn it into a profitable business.
It is entirely possible that you have created the best productivity tool on earth.
However, if you are spending $10 to acquire a customer and that customer will only bring you $5 in total lifetime revenue, then your company is going to bleed to death.
The business model hypothesis forces you to think about how you will stay alive.
Designing for survival economics
The reason that startups fail (the majority of startups) is that their unit economics are upside down.
In order to be successful and create a viable startup, you need to illustrate that your cost of acquiring customers is less than the revenue generated by those customers.
Establish early on what your Customer Acquisition Cost (CAC) will be versus the Lifetime Value (LTV) of a customer.
You should already have assumptions about how you are going to monetize your company even in the pre-seed stage.
Is it a subscription? Is it going to be a one-time purchase? Is it going to be a marketplace that takes a percentage fee for every transaction?
Testing the mechanics
To test your Business Model, you are going to test users to see if they will complete a transaction.
Therefore, don't wait until Version 1.0 is polished to try to charge them. As soon as possible, introduce pricing.
An effective tactic is providing significant discounting to early adopters who agree to a lifetime price before the product is completely developed. This helps you evaluate the price elasticity and individual's real willingness to pay.
If you are building a B2B SaaS platform, you should not provide an unlimited free trial period. You should ask for a credit card upfront, even if you offer a 30-day money-back guarantee.
This creates some friction between those who are truly interested in using your software versus those who are not.
The most common reason for failing
Founders delay pricing out of fear of being rejected.
Most founders believe they will figure out how to monetize their website once they have enough free users.
This tactic works for companies engaging in large amounts of venture capital to support the development of their consumer social networks.
However, for a founder building a business from scratch, offering free users will result in their ultimate death.
Assuming that free users will magically convert to a paid subscription later on, is a huge leap in assumptions that have not been proven.
Principle 3: Minimum Viable Product (MVP)
Entrepreneurs most commonly abuse the idea of a minimum viable product (MVP).
Developing an MVP is not developing a crummy, buggy version of what you believe the finished product will ultimately look like.
An MVP is the absolute minimum amount of development and effort needed to test a fully complete BML cycle.
An MVP does not ensure a scalable product; therefore, MVPs should be regarded solely as tools for learning—not tools for scaling.
Changing the mindset of the MVP
Rather than thinking of an MVP as a product, think of an MVP as an experiment.
If your objective is to discover whether or not a customer would purchase a pair of custom-fit running shoes, you should not develop a fully automated factory as your MVP.
The Minimum Viable Product (MVP) for our product consists of taking custom measurements with a tape measure, taking existing footwear apart and reassembling them to see if the consumer perceives a difference in performance compared to other shoes.
Time-to-market is essential; however, time-to-learn is the key metric to be aware of because ultimately we want the fastest route to obtain credible evidence of the solution.
High-signal MVP frameworks
There are multiple ways for entrepreneurs to utilize MVP frameworks without writing code.
- The Concierge MVP: Provide the service manually for a very limited number of users; you do everything that the software will be doing, so you learn what the software must deliver.
- The Wizard of Oz MVP: The appearance of a completed product; its back end reflects you, the entrepreneur, operating the levers behind the curtain. A typical example of a Wizard of Oz MVP was Zappos. The founder took photos of shoes that were currently on the shelves of local stores, uploaded them to the internet, and when one of those shoes sold, he physically went to that local store, bought the product, and shipped it to the consumer.
- The Single-Feature MVP: It is removing all features, except the feature that provides the differentiation. For example, when creating a social media platform for musicians, our MVP could simply be a forum for uploading and sharing 10-second sound clips.
Most common cause of failure
The primary reason startups do not succeed is due to overbuilding. Founders are misguided by their egos when creating their MVPs.
They don't want to present their "baby" as being something that is substandard, so they spend the first six months before launch working on adding "just one more feature."
When they finally do go live with their product, they have spent upwards of half of their runway on reallocating features into a much larger, unwieldy product.
If you’re not even a little bit embarrassed by your MVP, then you probably launched it too late.
Principle 4: The build-measure-learn feedback loop
This is the fundamental operating principle of the Lean Startup Method.
The core of this principle is the continuous process of developing products by building something, measuring how customers respond to it and ascertaining whether you should pivot or persevere with that product.
Many founders operate on a completely backward approach to this process.
Founders generally build large products first and then attempt to determine what they should measure. They will analyze the data collected and see if it is useful. This process tends to waste time.
Reverse the loop for improved efficiency
You must start at the end.
Start by determining what you want to Learn about your product. For instance, do you want to determine whether users will log in every day?
Do you want to determine whether they will pay $20 a month? Specify exactly what you need to know.
Next, determine how you will Measure the information you want to acquire.
For example, if you want to learn about daily engagement, you will need to use Daily Active Users (DAU) as your metric, not total signups.
After you establish your Measure, you will need to determine what to Build. You should create the smallest possible thing that you can use to collect the specific measurements you want to collect.
For example, an email campaign, a landing page or a mockup of the product you want to launch.
Define workflow constraints
Lean Startups operate under strict constraints.
Set limits for time spent on each Build-Measure-Learn cycle. If you are a solo founder, a good goal is to have a one-week cycle to validate your idea.
Write down your hypothesis on Monday; by Wednesday, create the test; by Friday, look at the data collected and make a decision.
When an experiment takes more than 30 days to build, it is not an experiment; it has become a full-fledged project. Instead of building a full project, break your project into smaller pieces.
The build trap
The leading cause of a startup failing today ultimately stems from many teams getting caught in the "build trap."
These teams have successfully delivered an MVP; however, upon delivering the MVP, they jump immediately to the next item on their roadmap instead of responding to the data and learning from their MVP.
By treating the build-measure-learn loop as a "checklist" instead of a "strategic compass," these companies are operating in the dark by building without measuring.
Principle 5: New venture accounting (the kill of vanity metrics)
In order to show progress in your startup, you will use a new form of accounting that is different than traditional financial accounting measures, such as ROI or Profit and Loss.
These are completely meaningless for a startup that has yet to generate revenue (and for at least the next several months).
New venture accounting shows you how to define, measure, and communicate your progress in a world where there is a high degree of uncertainty.
Signal vs. noise: The hierarchy of metrics
You need to be aggressive in defining what constitutes a vanity metric compared to an actionable metric.
Vanity metrics are those that can always be counted, but do not provide any useful information about the health of your business.
Vanities consist of "Total Registered Users", "Cumulative Page Views", and "Social Media Followers".
These metrics may present themselves well in a pitch deck; however, they are not guiding metrics based on actual actions taken by your customers.
If your startup has 10,000 signups but has 0 active users, your startup is failing.
Actionable metrics show you how actual customers have behaved and how your business is performing.
For example, actionable metrics are Retention Rate, Cohort Analysis, Conversion Rate, and Customer Acquisition Cost.
Actionable metrics will provide a clear cause-and-effect relationship on how you will move forward from there.
Innovation accounting: 3 stages of tracking progress
The first step for any founder is to understand where their company stands today, that is to say, to define a starting point.
Once you have launched your product (minimum viable product or MVP) and measured your current rate of activity, you have established your baseline.
For example, if you discover that your base line conversion rate is somewhere between 0% and 1% at best, you own that figure no matter how bad it may appear.
Next, it is important to refine your operations and processes. To do this, you will run several "micro-experiments" to identify opportunities to improve your baseline conversion rate.
Micro-experiments may include changing your messaging and pricing, and/or streamlining your customers' first impressions of your service (for example, through an online onboarding process).
The final stage of innovation accounting is to evaluate how your experiments have impacted your conversion rate, as well as whether or not your accomplishments are in line with your ideal business model.
If you see that the active cohort of your customers has increased between January and December from 300 to 1,200 and the conversion rates have increased from 1% to either 10% or 20%, those metrics indicate that you achieved success.
If, however, you see that your efforts to improve your conversion rate have remained stagnant over the last 6-12 months despite your best efforts, then you may have a problem.
Common failure mode in startups
The most common form of self-deception in startups is through the use of cumulative metrics.
For example, a founder who has achieved a milestone of 50,000 total downloads may overlook that only 300 of individuals opened the app in the last week and completely disregard the value of that cumulative figure.
You should never use a cumulative number to measure success; rather, always measure activity based on a recurring cohort.
Principle 6: Establish a growth hypothesis
The next step after you have validated your value proposition and your business model is to conduct the same process in determining how you will scale your startup.
You can no longer afford to make the same mistake of assuming that "if we build it, they will come". You need to be able to design customer acquisition into the product you have developed.
By defining a growth hypothesis, you will be able to create a specific mechanism for achieving exponential adoption of your product.
Growth engines
A start-up should preferably focus on developing a single growth engine at the earliest stages of its operation.
Mixing the three types of growth engines together will likely dilute the focus of your efforts.
- The Sticky Growth Engine: You will maximize growth through your retention. For instance, if you are acquiring 100 new customers a month and retaining all of them, you will continuously grow; high retention represents the sticky engine of growth. Sticky growth engines are primarily used by SaaS companies, hosted databases or enterprise software, so the primary metric you should be measuring is the churn rate because if your churn rate is high, your sticky growth engine is broken.
- The Viral Growth Engine: The growth engine is driven by your current users being able to invite others to use the product simply as a result of using the product themselves. A good illustration would be PayPal, Zoom and Slack, you can't fully use the product without inviting another user to join you and therefore the primary metric you should track is the viral coefficient (how many new users does an existing user invite).
- The Paid Growth Engine: The paid growth engine allows you to buy users for less than what you make from those users over time. For example, if you know that a user generates $100 in lifetime value for your business and you can buy a click that gets that user to convert for $30, you can create a huge amount of volume through your paid growth engine. E-commerce and direct to consumer brands use paid growth engines to grow their businesses.
Start testing growth early
Don't wait until your product is in the right product-market fit before you start testing acquisition channels.
With very small budgets, consider running paid ads to test out how effective your ads are, even when your product isn't ready.
Write content that utilizes SEO techniques to see if there's any organic search intent around your product.
Investigate who your first users were and directly ask them how they found out about your product.
Only rely completely on whichever channel proves to be working and eliminate all other channels until that channel has been completely utilized.
Most common failure point
Startup founders will try to force a viral mechanism onto a product that, by nature, cannot be virally distributed in a collaborative fashion.
Placing a "tweet" (button) at the end of a sales funnel does not magically convert a product into a viral product.
The product is only capable of being virally distributed when the utility of the product is derived from a collaborative or shared manner of using it.
Otherwise, the founder will have to rely on either sticky value or the paid distribution.
Principle 7: Pivots and perseverance (Key decision)
All start-ups will reach a point at which the original direction will be changing. The strategy will fail.
This is simply a fact of mathematical probability.
The most important decision for the founder to make is to know when a new concept is a lost cause and when to give it time to prove its worth.
A pivot is a systematic change in direction and is used to test new core beliefs about either the product's utility or the distribution strategy and growth mechanism.
Establishing a threshold for making decisions
You must set your failure criteria before performing any experimentation.
When you are testing a new landing page, decide ahead of time what your failure criteria will be: "If we do not convert five percent of our audience with this message after 1,000 visits then we will drop this messaging."
This is critical because if you do not have any pre-determined thresholds, your own psychology will lead you in a different direction than where you want to go.
What does it mean if you have a conversion rate of 1.5% and you tell yourself you are "almost there"?
You do not have clarity; you have confusion!
Data will provide clarity because when you have tuned your engine several times and all your actionable metrics are flat lining, you need to pivot.
Anatomy of a successful pivot
When a startup pivots, they will usually make a guidance change from one area to another.
A pivot is not a whim or random act of flailing about; it is a calculation of the knowledge gained from experience.
- Zoom In Pivot: A specific feature of a product becomes the entire product.
- Zoom Out Pivot: The entire product is too constricted and becomes one feature of a much larger platform.
- Customer Segment Pivot: The product is correct but the audience is incorrect. A shift from a specific audience like college students to a much larger audience like Enterprise HR departments.
- Platform Pivot: An application can become a platform that others can build on.
The most common reason for failure
The "Zombie Startup" tragedy results from the failure of a startup founder to pivot.
Startup founders develop an emotional attachment to their initial vision. They deny their horrendous metrics. They also deplete their runway paying server costs and salaries.
Ultimately through all of these activities, founders end up denying they were incorrect in their original hypothesis.
A pivot does not equate to failure; it represents a successful approach stemming from validated learning.
A practical framework for founders to enable decision making
Theoretical knowledge will do your startup no good unless it is executed.
Below is a concrete and observable decision-making process that a new founder can observe starting from day one of establishing a startup.
Example week 1: Discovery
Identify your customer demographics. Conduct 15 unstructured interviews with your identified customer demographics you plan to serve.
During these interviews, do not share your solution; instead, ask your interviewees about their current workflow, biggest frustrations, and what they are currently spending regularly to address these frustrations.
Example week 2: Design/testing and metrics development
Utilizing information learned through the customer discovery interviews, identify your core value hypothesis. Identify what would be the MVP.
For example, will your MVP include a landing page test? Concierge service?
Define your single metric that must be satisfied for it to be considered a success, i.e., 20 people paying $10 deposits.
Example week 3: Build phase
Build out the MVP using no-code tools as instructed. The only time you should spend over three days building the MVP test artifact is if you are building more than you should.
After completion of the MVP, test your Minimum Viable Product with the target customer demographic identified in Week 1 interview process.
Example week 4 - Measurement and the pivot decision
Collect the data... Did you meet your threshold?
- Yes: Press on - Complete the next iteration, which will be a little more robust, and validate the business model hypothesis.
- No: Analyze the qualitative feedback... Did they dislike the price? Did they not see the value? Either pivot the offer, move to another market segment, or go back to week 1.
This framework demands brutal honesty from you.
It holds you accountable for your code, and makes you immediately face the market and act accordingly based on its response.
Final verdict
No matter how bright the initial idea may be, the survival of a brand new startup depends on the ability of the founder(s) to develop iterations faster than cash burns.
By aggressively applying this approach, you will rid yourself of all the fantasy associated with entrepreneurship. You will stop thinking like a visionary and start thinking like a scientist.
You will validate the value proposition, prove out the economics, build the minimum necessary, continuously measure your results, and pivot without regard to your ego.
That's how you transform an idea into a sustainable company.
FAQs
What is the difference between a prototype and an MVP?
A prototype is used to answer the question, "Can we build this?" An MVP is used to answer the question, "Will anyone pay for this?"
You may have built a large or complicated prototype in a laboratory setting to see if a certain material can withstand a specific amount of stress, whereas your MVP is built to discover whether an actual customer will swipe their credit card in exchange for the anticipated outcome or result.
MVPs most often utilize manual labor to provide services for potential customers and prototypes typically answer the question of whether it is technically feasible to create a certain product.
How do the Lean Startup methodologies apply to service businesses?
Service businesses can also leverage these methodologies in a major way.
Rather than sign a five-year lease for an office building and hire employees for a new consulting business, you can run lean tests.
Start with a targeted LinkedIn campaign selling something based on the outcome.
At that point in time, operate as an individual consultant and measure the cost of acquiring a customer versus what you can earn from providing services to them.
Only once you receive more demand for your services than you can physically fulfill should you grow your business, sign a commercial lease, and hire employees.
The principles of validated learning apply equally to both technical and physical service businesses.
What is the biggest mistake made by founders when it comes to validated learning?
The largest flaw associated with validated learning is that most founders fall prey to a confirmation bias.
Founders often create validation experiments solely with the intent of proving themselves correct, rather than objectively testing the marketplace. In customer discovery, founders tend to ask leading questions.
For example, "Wouldn't you love to have a tool that does X?" Then they disregard negative data points as outliers and amplify the positive signals they receive.
True validated learning requires that you define an objective threshold before you conduct a test and absolutely stay true to the data you collect from it, regardless of how much it demolishes your original concept.
