As pointed out by Eric Ries, a minimum viable product is that version of a new product that allows a team to collect the maximum amount of validated learning about customers with the least effort through a cycle of build, measure, learn; that is the foundation of the lean startup methodology.
However, the origin story started in the late 1990s.
Steve Blank, a retired serial entrepreneur had the time to think through what he had missed in terms of business frameworks, during the years as he started several high-tech companies.
He had noticed that the only tool available at the time was the business plan.
However, not only the business plan was a static document that didn’t survive the first contact with the real world.
That document also has plenty of untestable and untested assumptions.
The patterns he noticed would be all gathered into what became a manifesto and the foundation for the lean startup movement.
And the introduction of new tools and frameworks to use as an entrepreneur (Business Model Canvas and all its variations)
A glance at the lean startup methodology
The lean startup methodology aims at creating a scientific, repeatable process for product development that allows the startup to build products and deliver them fast.
In other words, the lean startup moves around three stages:
Build.
Measure.
Learn.
This process of build > measure > learn will need to be repeated over and over, thus creating a feedback loop.
The primary purpose is to initially come up with a minimum viable product (MVP), which is a critical aspect of the lean startup model.
A Minimum Viable Product is that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort.
The MVP will be the foundation to build a successful company.
What is not an MVP?
As Ash Maurya pointed out, the definition of MVP got overtime simplified with “the smallest thing you can build that lets you quickly make it around the build/measure/learn loop.”
This kind of simplification brings flaws and mistakes that can also lead to significant failures.
For instance, Ash Maurya defines the MVP as “the smallest thing you can build that delivers customer value (and as a bonus captures some of that value back).”
When I spoke to Ash Maurya, author of Running Lean and Scaling Lean, we discussed how building a solution before validating it might be the basis of one of the most dangerous biases for entrepreneurs: the innovator’s bias.
As he pointed out, “one of the biases that that that many entrepreneurs fall run into is this premature love of the solution. Like the first principles in science, you almost have to deconstruct an idea. We have to start with the basics. In this case, when we look at our business, we have to break it down into customers and problems.”
And he continued, “If you don’t have the right customers who are trying to get sorted and problem solved, and no matter what solution you build, it doesn’t matter because we know that unless you’re solving a problem, customers are not going to use it.
They’re not going to pay money. Even if you can reach them. Even if you have a patent or an unfair advantage, it doesn’t matter at the end of the day because your customers don’t care. So that is the way we logically break it down, but that innovator’s bias is one of those sneaky things.”
Ash Maurya proposed a slightly different approach:
We might start with the demo. We might first go and find customers, see if we can reach them, even talk to them. Because if you can talk to customers, we can sell them anything. We start with the end in mind and then we deconstruct our way back to the beginning and start validating at a bottom-up level. That generally is how we overcome the innovator’s bias toward a solution.
As Ash Maurya pointed out, “build a demo first, sell that demo, and if you can sell the demo, then don’t even build the product.”
Validating the market with a bottom-up approach to flip upside-down the product-market fit problem
This process helps to validate the market clearly, thus eliminating most of the risks associated with a company’s failure (people do not need or want that product).
This MVP approach flips upside-down the product-market fit problem. Where in a product-market fit scenario, we build a product first, and we iterated times and times again to find this magic moment, called “market fit.”
In this leaner MVP approach, we validate the market first, then build a product.
Of course, that doesn’t mean success is guaranteed. We just moved the market risk away, and now the whole pressure is on the feasibility of the product we demoed.
A great example of this approach is how Tesla pre-sells its cars by demoing them first before going into large-scale production:
While the demoed product already has all the aesthetics and most of the features the final product might have.
For a car company, one thing is to build a single car; another is to produce it at scale.
On a much smaller scale, a demo might be a simple landing page with a mock-up of the product you want to build.
Once again, this process will help us validate the market first.
From there, it will be more of a problem of feasibility.
Of course, the more a product is technically challenging, the more the feasibility risk will be high later on.
However, that also means we saved massive financial resources.
To produce that product and make it go to market, we would have spent time, money, and other people’s capital and built something people do not want.
The leaner MVP approach is about finding whether the “commercial time window” is right
We might argue that the whole concept of leaner MVP is entirely new.
However, companies innovated in their fields have used this approach (or at least the innovative units within those companies).
When I interviewed Alberto Savoia (he was among the engineering team of Google in the early years and before its IPO), he explained how back in the 1980s, IBM thought, “we want everyone to have personal computers.”
IBM thought there was no way that most people would use computers as they would not be predisposed to learn how to use a keyboard (an assumption proved wrong).
How to test this assumption?
IBM thought to tackle the market with a speech-to-text technology that enabled people to talk to computers and get that translated into text.
They figured a mechanism to convert speech into text would make a computer a potential mass-market product.
In short, people would dictate to computers instead of typing on a keyboard.
Yet, instead of focusing on building the product first (it would have taken years and many billion dollars), IBM devised an intelligent experiment.
The IBM team brought people into a room, they gave them a microphone, and there was a screen in front of that microphone and told them, “Look, this a new way of running a computer, there’s no keyboard, you just speak to it, and give it a shot and tell us what you think.”
Therefore, people talk, and the computer translates that into text.
However, it wasn’t the final product, not even close. In the room next door, a human being got the input through the headphone and typed it on a keyboard.
The effect was that the users in the experiment thought the IBM speech-to-text was a working prototype, but it wasn’t.
With this simple experiment, IBM collected valuable data that told them a few things they were completely wrong about.
First, people would not talk to computers for long, as they got a sore throat.
Also, in an office environment, everyone talking loudly will not be viable (especially if you need to input into the computer confidential information).
Those data points alone made IBM stop prioritizing the speech-to-text experiment.
And this would save them years of R&D, lost focus, and financial resources.
A third assumption would be proved wrong after a few years.
Indeed, keyboards would eventually become mass-adopted and efficient to use computers at scale! (and it still is today).
Voice-enabled devices are going into mass-production only now (Alexa, Google Home, Cortana, Siri).
However, this is a much different technological environment compared to the 1980s.
Thus, if at all, this leaner MVP approach can tell us an extremely valuable piece of information on whether the commercial use case timing is right! (that for sure represents a good chunk of the product’s success in the first place).
It’s important to clarify that this approach will not tell us whether a product or technology will ever be successful in the future.
Neither whether this technology will be successful with another commercial use case.
In short, IBM thought the speech-to-text would be an alternative to the keyboard, and this assumption was wrong for the time being.
Would that be proved right if they thought of another commercial use case? Maybe.
But for what they needed back then (make PCs scale and become a mass product), text-to-speech wasn’t the right project to prioritize.
When does an MVP become too risky?
If you are just starting up, you don’t have an established brand, and your reach is limited, the MVP might be the way to go.
That’s because the risk of failure and the cost of branding are very, very limited.
Thus the value captured from the iterations and the feedback gained is high. All that changes if you have an established brand and a broad reach.
That is where the Exceptional Viable Product definition given by Rand Fishkin (founder of Moz and SparkToro) comes in handy.
I believe it’s often the right choice to bias to the EVP, the “exceptional viable product,” for your initial, public release.
Fishkin suggests creating an MVP but not releasing it until that is exceptional. At that point, you do release it to the public.
Thus, the exceptional viable product (EVP) methodology requires an iteration of the product “in-house,” tested with your team and maybe a few selected customers.
Companies like Apple have been following this approach all along. Apple has been building its hardware products by testing them internally as much as possible.
There are two main reasons to opt for this approach:
Brand risk: if you have an established brand, a new product released to your audience is way too risky. As this might compromise the whole brand equity gained over the years.
Competitive risk: when you release a product to the market, even to a smaller subset, you’re enabling competitors to gain access to the new product you’re launching, thus giving away valuable information that will give them a competitive edge, to quickly improve on what you’re doing.
As Fishkin suggests, only when you’re sure the product is exceptional can you launch to a broader audience.
The EVP methodology allows more established brands to avoid failures that can lead to an irrecoverable loss of reputation.
My proposal is that we embrace the reality that MVPs are ideal for some circumstances but harmful in others, and that organizations of all sizes should consider their market, their competition, and their reach before deciding what is “viable” to launch. I believe it’s often the right choice to bias to the EVP, the “exceptional viable product,” for your initial, public release.
Depending on your brand’s size and reach, and on the customers and potential customers you’ll influence with a launch, I’d urge you to consider whether a private launch of that MVP, with lots of testing, learning, and iteration to a smaller audience that knows they’re beta testing, could be the best path.
In other words, he takes into account two main variables. On the one hand, you have the attention, customers, and evangelism.
On the other hand, you have the product quality.
The greater the attention, customer base, and ability to evangelize, the more you’ll need to have a solid product before its launch.
In Rand Fishkin’s vision, an EVP has to have two minimum features:
Have decent exposure.
And be truly impressive, at least at one must-have – identified – feature customers are looking for.
He learned that lesson at Moz when trying to build a new tool to identify spammy links. As Rand Fishkin recounted:
Our research had already revealed what customers wanted. They wanted a web index that included all the sites Google crawled and indexed, so it would be comprehensive enough to spot all the potential risky links. They wanted a score that would definitively say whether a site had been penalized by Google. And they wanted an easy way of knowing which of those spammy sites linked to them (or any other site on the web) so they could easily take that list and either avoid links from it or export and upload it to Google Search Console through a disavow file to prevent Google from penalizing them.
That would be anexceptionalproduct.
But we didn’t have the focus or the bandwidth to build the exceptional product, so we launched an MVP, hoping to learn and iterate. We figured that something to help our customers and community was better than nothing.
I think that’s my biggest lesson from the many times I’ve launched MVPs over my career. Sometimes, something is better than nothing. Surprisingly often, it’s not.
Connecting the dots between MVP, Leaner MVP, and EVP
The lean startup movement and the lean startup methodology made an important contribution to the startup ecosystem.
A core part of the lean startup methodology is the MVP.
As we’ve seen throughout the article, an MVP is the classic mode of experimentation for startups.
It has been a very powerful shift as it enabled companies to gain customers’ feedback early in the product development cycle.
Yet, as we move toward the leaner MVP approach has taught us that we can use an even more bottom-up approach by demoing the product even before we’ve built it to see if people want it.
This approach moves from build > measure > learn to demo > sell > build.
The leaner MVP approach will work well to remove market risk away while putting more pressure on the feasibility risk.
And yet, it will help us save valuable time and resources.
Both an MVP and leaner MVP approach become risky when it comes to an established brand with a wide audience and reach, where a new product release, also if circumscribed to a small audience, can spread quickly.
In that case, an EVP approach will help, as it will focus on iterating the new product with specific units within the company and with only a few selected customers.
Microniches and Minimum Viable Audiences
Another couple pieces of the puzzle to be added to build a valuable product from scratch are microniche and minimum viable audience.
In other words, on a very crowded web with an app for anything, the best way to create options to scale is by targeting a microniche.
A microniche is a subset of potential customers within a niche. In the era of dominating digital super-platforms, identifying a microniche can kick off the strategy of digital businesses to prevent competition against large platforms. As the microniche becomes a niche, then a market, scale becomes an option.
A microniche is such a small sub-segment of a market, which, though, can be extremely valuable as you can gain:
Honest feedback: as a small audience (sometimes comprising also a few dozen of people), they will be so motivated to deal with someone who takes the time to talk to them (compared to existing prominent players that, due to scale, have mostly automated interactions with their customer base) that you’ll get a lot of honest feedback. Having this kind of feedback is extremely valuable.
The minimum viable audience (MVA) represents the smallest possible audience that can sustain your business as you get it started from a microniche (the smallest subset of a market). The main aspect of the MVA is to zoom into existing markets to find those people which needs are unmet by existing players.
This is the essence of what I like to call the Blue Sea Strategy, which, contrary to the Blue Ocean, makes sure to develop a new market by drilling down to tiny niches within that market.
As in those microniches, you’ll discover truths that have the potential (over time) also to help you develop a whole new market!
That’s what makes the Blue Sea Strategy so counterintuitive.
By narrowing down (substantially) the market today, you create options to scale tomorrow!
Today’s microniche might be tomorrow’s huge industry, potentially eating up existing/significant industries!
A Blockchain Business Model according to the FourWeekMBA framework is made of four main components: Value Model (Core Philosophy, Core Values and Value Propositions for the key stakeholders), Blockchain Model (Protocol Rules, Network Shape and Applications Layer/Ecosystem), Distribution Model (the key channels amplifying the protocol and its communities), and the Economic Model (the dynamics/incentives through which protocol players make money). Those elements coming together can serve as the basis to build and analyze a solid Blockchain Business Model.
In an asymmetric business model, the organization doesn’t monetize the user directly, but it leverages the data users provide coupled with technology, thus have a key customer pay to sustain the core asset. For example, Google makes money by leveraging users’ data, combined with its algorithms sold to advertisers for visibility.
In a business world driven by technology and digitalization, competition is much more fluid, as innovation becomes a bottom-up approach that can come from anywhere. Thus, making it much harder to define the boundaries of existing markets. Therefore, a proper business competition analysis looks at customer, technology, distribution, and financial model overlaps. While at the same time looking at future potential intersections among industries that in the short-term seem unrelated.
Technological modeling is a discipline to provide the basis for companies to sustain innovation, thus developing incremental products. While also looking at breakthrough innovative products that can pave the way for long-term success. In a sort of Barbell Strategy, technological modeling suggests having a two-sided approach, on the one hand, to keep sustaining continuous innovation as a core part of the business model. On the other hand, it places bets on future developments that have the potential to break through and take a leap forward.
A transitional business model is used by companies to enter a market (usually a niche) to gain initial traction and prove the idea is sound. The transitional business model helps the company secure the needed capital while having a reality check. It helps shape the long-term vision and a scalable business model.
The minimum viable audience (MVA) represents the smallest possible audience that can sustain your business as you get it started from a microniche (the smallest subset of a market). The main aspect of the MVA is to zoom into existing markets to find those people which needs are unmet by existing players.
Business scaling is the process of transformation of a business as the product is validated by wider and wider market segments. Business scaling is about creating traction for a product that fits a small market segment. As the product is validated it becomes critical to build a viable business model. And as the product is offered at wider and wider market segments, it’s important to align product, business model, and organizational design, to enable wider and wider scale.
The market expansion consists in providing a product or service to a broader portion of an existing market or perhaps expanding that market. Or yet, market expansions can be about creating a whole new market. At each step, as a result, a company scales together with the market covered.
In the FourWeekMBA growth matrix, you can apply growth for existing customers by tackling the same problems (gain mode). Or by tackling existing problems, for new customers (expand mode). Or by tackling new problems for existing customers (extend mode). Or perhaps by tackling whole new problems for new customers (reinvent mode).
In the FourWeekMBA Revenue Streams Matrix, revenue streams are classified according to the kind of interactions the business has with its key customers. The first dimension is the “Frequency” of interaction with the key customer. As the second dimension, there is the “Ownership” of the interaction with the key customer.
Revenue model patterns are a way for companies to monetize their business models. A revenue model pattern is a crucial building block of a business model because it informs how the company will generate short-term financial resources to invest back into the business. Thus, the way a company makes money will also influence its overall business model.
A pricing strategy or model helps companies find the pricing formula in fit with their business models. Thus aligning the customer needs with the product type while trying to enable profitability for the company. A good pricing strategy aligns the customer with the company’s long term financial sustainability to build a solid business model.
Business modelinnovation is about increasing the success of an organization with existing products and technologies by crafting a compelling value proposition able to propel a new business model to scale up customers and create a lasting competitive advantage. And it all starts by mastering the key customers.
The innovation loop is a methodology/framework derived from the Bell Labs, which produced innovation at scale throughout the 20th century. They learned how to leverage a hybrid innovation management model based on science, invention, engineering, and manufacturing at scale. By leveraging individual genius, creativity, and small/large groups.
According to how well defined is the problem and how well defined the domain, we have four main types of innovations: basic research (problem and domain or not well defined); breakthrough innovation (domain is not well defined, the problem is well defined); sustaining innovation (both problem and domain are well defined); and disruptive innovation (domain is well defined, the problem is not well defined).
That is a process that requires a continuous feedback loop to develop a valuable product and build a viable business model. Continuous innovation is a mindset where products and services are designed and delivered to tune them around the customers’ problem and not the technical solution of its founders.
Disruptive innovation as a term was first described by Clayton M. Christensen, an American academic and business consultant whom The Economist called “the most influential management thinker of his time.” Disruptive innovation describes the process by which a product or service takes hold at the bottom of a market and eventually displaces established competitors, products, firms, or alliances.
Sociologist E.M Rogers developed the Diffusion of Innovation Theory in 1962 with the premise that with enough time, tech products are adopted by wider society as a whole. People adopting those technologies are divided according to their psychologic profiles in five groups: innovators, early adopters, early majority, late majority, and laggards.
In the TED talk entitled “creative problem-solving in the face of extreme limits” Navi Radjou defined frugal innovation as “the ability to create more economic and social value using fewer resources. Frugal innovation is not about making do; it’s about making things better.” Indian people call it Jugaad, a Hindi word that means finding inexpensive solutions based on existing scarce resources to solve problems smartly.
A consumer brand company like Procter & Gamble (P&G) defines “Constructive Disruption” as: a willingness to change, adapt, and create new trends and technologies that will shape our industry for the future. According to P&G, it moves around four pillars: lean innovation, brand building, supply chain, and digitalization & data analytics.
An innovation funnel is a tool or process ensuring only the best ideas are executed. In a metaphorical sense, the funnel screens innovative ideas for viability so that only the best products, processes, or business models are launched to the market. An innovation funnel provides a framework for the screening and testing of innovative ideas for viability.
Tim Brown, Executive Chair of IDEO, defined design thinking as “a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.” Therefore, desirability, feasibility, and viability are balanced to solve critical problems.
As pointed out by Eric Ries, a minimum viable product is that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort through a cycle of build, measure, learn; that is the foundation of the lean startup methodology.
What makes a good MVP?
A great MVP is something that delivers enough value to potential customers, thus ready to be launched and as result gather feedbacks from those potential customers to improve it fast.
What is an EVP?
As Rand Fishkin pointed out: “MVPs are ideal for some circumstances but harmful in others, and that organizations of all sizes should consider their market, their competition, and their reach before deciding what is “viable” to launch.” Thus EVP, or “exceptional viable product,” might be the most suited choice for an initial, public release.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
2 thoughts on “What Is the Minimum Viable Product And Why It Matters”
Interesting and concise.
Thank you Laszlo!