Ask any successful startup founder to narrate a story of their journey to success, and you are most likely to hear about the decision to pivot at a particular point. Tales about startup success are incomplete without reference to the founders undergoing a pivot one time or another. From Honda to Twitter, every successful startup had to pivot or implement multiple pivots to be where they are now.

Interestingly enough, this realization about the ubiquitous nature of pivots in the life of a startup does not deter notions about them being considered last-ditch options employed to transform a struggling startup. Pivots are synonymous with startups and happen all the time. All startup founders are aware that they will have to pivot at some point; however, they are unsure when and how to do so.

What is a Pivot and why is it necessary?

According to Eric Ries, a pivot is ‘a structured course correction designed to test a new fundamental hypothesis about a product, strategy or engine of growth’. From this, we can deduce that it is an activity steeped in experimentation and learning. It is triggered when founders recognize from experimentation feedback that their findings differ from the earlier assumptions that they created at the beginning of the startup process.

All startups must expect to pivot more than once before finally achieving success. For most, pivoting will occur at every stage as the founders realize that their assumptions about customer segment, problem, solution, channels, or technology are not valid.

Startups that cannot bring themselves to pivot to a new direction based on feedback from the marketplace can get stuck, neither growing enough nor dying. If left unchecked, such startups end up failing.

If Pivots are so important, why don’t more startups implement them?

Despite widespread knowledge of its importance to ensuring success in startups, pivoting is still not a common occurrence for many startups.

This is because recognizing that there is a need to course correct for most founders who are emotionally attached to their product is a challenging undertaking. Such recognition goes against the typical human behaviour to admit that the initial course of action was wrong. Doing this takes putting egos and convictions aside to accept that a certain action plan was incorrect.

Other reasons why pivots are not implemented by founders include:

• The use of vanity metrics by startups can allow founders to reach false conclusions about their performance.

This is most common during the product-market fit stage when founders rely on metrics that do not provide a critical reflection of their performance, and as such, do not see the need for course correction.

• Arrogance on the part of the founders.

Most founders tend to have an absolute belief in the viability of their ideas that they become very resistant and hesitant about the need to change their business model. This commonly leads to a situation where products/solutions are created for problems that prospective customers have not validated yet.

• A refusal to approach the startup process as a learning activity.

While there are examples of startups that have been successfully founded with little input from anyone else apart from the founders, most founders tend to approach the startup process and create a product based on their ideas and conjectures.

Thus, there is very little room for them to learn anything as they do not believe the customers know what they want, and it is their job to tell the customer what they want. They see no need to test assumptions about customers, problems, solutions, etc.

When do startups decide that it is time to Pivot?

Executing a pivot is a strenuous activity. It is difficult for founders to recognize their need to implement a course correction and even more challenging to achieve one when they have decided to go for it. There is also no guarantee that the course correction to be taken will be successful or change the direction of the startup.

This notwithstanding, founders must understand that implementing a pivot/multiple pivots is inevitable and must be prepared to do so if the need arises. However, to do this successfully, founders must know when it is the right time to pivot.

The decision to pivot represents a combination of both art and science. Often, most startup founders decide to pivot on the back of a gut feeling or intuition they have that their current course is no longer the right one. This gut feeling can come from prior experience gained from running an earlier startup or from feedback gotten from other stakeholders (e.g., partners, advisors, customers).

In addition to this, founders may also decide to pivot on the back of the metrics/numbers generated from testing their ideas, problems, and solutions with their customers. Key questions to ask when considering this include:

• Are the numbers (e.g., acquisition rate, activation rate, retention, and revenue rates) coming from customers’ interaction with the solution, thus validating the original hypothesis?
• Are the experiments being run (e.g., tuning product features, interviews with customers) yielding outcomes that increasingly deviate from the initial expectation?

If the answer to any of these questions is YES, it is time to pivot!!

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How do you successfully execute a Pivot?

As previously argued, executing a pivot is an arduous activity. A key reason for this difficulty is the indecisiveness or refusal by the founders to accept the need to implement one. Thus, to successfully execute a pivot, the first thing required from the founders is decisiveness.

Startup founders must be aware, recognize and accept the need for a correction in their current course. One recommended approach is for startups to schedule periodic pivot meetings. During these meetings, the startup team reviews the numbers, discusses their perceptions about performance and their current direction, identifies the need to pivot, and obtains all stakeholders’ buy-in regarding the need to pivot.

Once you’ve achieved this and founders have accepted the need to execute a pivot, they must begin experimenting. Since pivots can occur at different stages in the life of a startup, running experiments can help founders identify where the issues exist and how to correct them. A framework based around the principles of experimentation, which will guide the pivot activity, such as the Pivot Pyramid, can be of great use here.

The pivot pyramid is a visual guideline to help founders make changes and run experiments in different business areas to drive growth. The pyramid looks at all the elements of a startup business model (customers, problem, solution, technology, engine of growth, channel, revenue, unique value proposition). It then tests assumptions that founders have made about a particular element with data from either interviews or running usability tests.

By running such experiments, founders can quickly realize whether the problems they have identified are a must-have for their targeted customer segments and, if not the case, recognize the need to adjust it. They can also determine whether the solution they have designed addresses the customers’ problems and, if not so, recognize the need to adjust it or redesign a new solution.

Types of Pivots

When most founders hear about pivots, the first thing that comes to their minds is fundamentally changing the solution/product they are creating. This is, however, not always the case. While a good number of product pivots exist (e.g., Airbnb, Starbucks, Nintendo), there are other types of pivots that can lead to success. These include the following:

1. Zoom-in Pivot: a zoom-in pivot is a type of product pivot that takes a single feature in an earlier iteration of a product and makes it the centerpiece of the new product.

This pivot typically happens when early adopters use a product because of a particular feature rather than the whole set of features accompanying the product. An excellent example of this type of pivot is the photo-sharing startup Flickr.

Flickr started as a massively multiplayer online role-playing game called ‘Neverending’. Back in the days of ‘Neverending’, there was a feature in the game that allowed users to share photos and save them on a web page. This feature turned out to be the most fun part of the entire game’s experience and later became the company’s centerpiece.

2. Zoom-out Pivot: In a zoom-out pivot, the startup realizes that a single feature is insufficient to support a complete product and decides to make the feature part of a larger product or ecosystem.

This typically occurs when the earlier development is not gaining enough traction and customers have requested additional features that enable them to use the product more.

3. Customer segment Pivot: Under this type of pivot, a startup realizes that its product addresses a must-have problem for a specific group of customers (its early adopters) but may not be a must-have problem for its originally-intended or mainstream customers.

This type of pivot is typically associated with startups trying to scale their activities into their proposed mainstream market.

4. Customer need Pivot: This type of pivot occurs when founders realize from their interactions with customers that the problem earlier identified is not crucial to its customers.

However, from its interaction, the startup can identify issues that are actually relevant.

5. Engine of Growth Pivot: In an engine of growth pivot, a startup realizes that its assumed growth engine (viral, paid, or sticky) may not allow it to achieve rapid growth and decides to change this for a new strategy to seek faster or more profitable growth.

6. Channel Pivot: In a channel pivot, a platform realizes that its earlier assumed path to reaching customers may not be the most effective and decides to change this to a different channel with greater effectiveness.

Other types of pivots include the Business Architecture Pivot, Technology Pivot, Platform Pivot, and Value Capture Pivot.

Final thoughts

Pivots are a permanent facet of any startup. It is the rule, not the exception. As such, all startup founders must expect to pivot multiple times throughout their startup process.

For startups to become successful, founders must be willing to learn and experiment. They must go into the startup exercise with humility and the knowledge that their initial assumptions will most certainly change.

They must be decisive in their attempt to execute such change and try to separate themselves emotionally from their startups. Only when they achieve these things will they have a good chance for success.

The Case for the Minimum Viable Product

Conventional wisdom says the startups should first build a Minimum Viable Product (MVP) to test customers’ reactions.

The MVP is a barebones version of the actual product the startup intends to sell. Unlike the genuine product on the shelves (or in the app store), the MVP would provide only the key functionalities – those that make it worthwhile for the clients.

The startup would analyze the feedback from the clients and then refine the MVP into the final product. The process usually takes several phases. Each phase addresses the issues identified by the client as well as new ideas the startup team comes up with. Eventually, the product is polished and ready to sell.

Starting with an MVP allows the startup to save money and time by avoiding developing features the customers won’t need. It also helps the startup find out early on if customers care about such a product.

People often say they would like something, yet when they get it, it turns out they don’t need it badly enough to generate a profitable business around it. Therefore, using an MVP and collecting their feedback goes a long way towards avoiding a costly failure.

The Trouble with the Minimum Viable Product

Sometimes, it takes many months just to develop the MVP. Even worse, it might require some expensive parts. For example, building the MVP for a flying car would hardly come cheap.

In these cases, entrepreneurs sometimes build mock-ups or models instead and use them to extract as much helpful feedback as possible before moving on.

Such models are OK for getting feedback on the product’s looks, but since the models cannot perform the job the client is interested in, there is no way to gather usability data. If the feedback on the looks is positive, the team enthusiastically starts working on the MVP, pouring resources into it.

Juicero, a startup that burned through USD $120 million venture capital, did precisely that: worked for 3 years on a device that was squeezing juice bags. The product ended up having an initial retail price of USD $700, soon slashed down to USD $400, only to go belly up when the clients realized the obvious: that they could squeeze the juice bags manually. So why pay for the expensive bag squeezer?

In practice, Juicero’s business plan relied on selling juice bags at USD $8 per piece.

In theory, the thought process was that people could have continued buying the bags and squeezing them manually. That would have allowed the company to break even and then become profitable. The problem was that once you removed the high-tech bag squeezer from the mix, all that was left was an expensive bag of juice with no justification for the price. That killed the business very quickly.

Was there any way to test the viability of the business without building a Minimum Viable Product?

The answer is yes. There is a way to test if a business can be built around it for any product or app, even without investing in the MVP, and we call it the Butler Criterion.

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The Butler Criterion

Clients don’t buy cars. They buy a means of getting from here to there. A taxi, a bus, a train, or a bicycle can and do replace the need to own a car. Before cars existed, people used horses or porters to carry them in rickshaws.

The fundamental idea is people have needs, and just like in the case of the rickshaw, they are willing to hire other people to fulfill their needs. A butler was such a hire. The butler directly served his master, and in addition to that, he was managing the other servants, each of them providing a particular service like cleaning, cooking, gardening, etc. Therefore, the butler was the most important servant of the household and, as such, received the best pay and enjoyed a lot of other perks (better lodgings, nicer clothes, etc.)

All the modern appliances around the house perform duties that used to be assigned to hired help, which laboured manually, under the supervision of the butler. If the person who owns the appliances is well off, they usually hire someone to operate them, even nowadays. The reasoning is simple: the time spent vacuuming a large mansion has a higher hourly cost if performed by the estate owner than if the maid performs it. The owner could afford the building precisely because they earned more by the hour than the maid.

That brings us to the Butler Criterion: is there a human who gets paid to do the work our product or app would do for the client?

If the answer is yes, then it makes sense to build the MVP, which would replace or improve that specific human activity.

Applying the Butler Criterion to Juicero would have quickly revealed that people willing to pay for somebody to squeeze juice bags for them would rather pay a cook or a maid to prepare fresh juice directly from fruits and vegetables. That meant there was no real market for an expensive bag of juice and even less for a high-tech bag squeezer.

There is always a market of premium juices, but they come in packages that suggest their premium status, not in plain-looking bags. Therefore, since the business was about selling premium juices, there were other ways to do it properly, and none included building an expensive high-tech squeezer.

Let’s apply the Butler Criterion to Facebook. The paper variant of Facebook, the yearbook, existed for 200 years before its Internet version. Students hired photographers and printing shop workers to make them, and local businesses hired copywriters to create ads for these yearbooks, which appeared on certain pages.

So, when Mark Zuckerberg went to build an online version of the yearbook, he was confident the yearbook was something humans were willing to pay other humans to make. Even though he chose to monetize only the advertising part of the yearbook, he knew for sure Facebook passed the Butler Criterion.

The beauty of the Butler Criterion is it helps more than just evaluating the viability of the business built around the app or product. It also helps detect the right market segments.

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Imagine we know how to make a robot which can put clothes on us. At first glance, the robot would replace a 19th-century valet. The thing is, nowadays, people who can afford to hire a valet would find it strange to have somebody dress them.

Yet, even today, people are paid to dress other people, such as those who care for the elderly or differently-abled people. This point relates to our supposed startup because it can identify interested parties by seeing who is willing to pay a person for dressing another person. As a result, they might discover that were a robot to work with the elderly or those suffering from disabilities, some additional features might be needed, which could not have been imagined otherwise. All of that can be achieved before even buying the first screw for the MVP.

The Butler Criterion can be performed through observation or practice as part of an experiment.

For instance, before attempting to build a high-tech-based business platform, it is worth checking if a low-tech version of it can work. Don’t build the high-tech one first. Use manual work to test if there is any need for the platform’s service. If customers keep coming, then build the high-tech platform to replace the “butler” (the manual work). Amazon started that way. So did zappos.com and diapers.com, both later acquired by Amazon.

These examples prove that the method works time & time again and, therefore, every startup should use it before starting to work on the MVP.

If the butler did it, we can (and should) make it using technology.