Lean Startup Methodology
Perfecting a lean startup is not easy. Startups, in general, are not easy. However, this blog will help breakdown the lean startup methodology so that you can understand what your consumer desires in a product or service. I have been entrepreneurial since I was a kid. Lawn mowing service, making and selling candles and candy, bee farming, selling door to door, you name it, as a kid I was all in. Since that time, I have started a number of businesses. Some were successful, some went bust, some I sold and some are still active and growing. As a serial entrepreneur, I am constantly asked, “What does it take to be an entrepreneur?” From my vantage point, it is a combination of passion, instinct, growth-mindset, humility, guts, grit and eternal optimism. You have to be willing to shake up the status quo or fly in the face of convention and you have to be willing to fail.
Most entrepreneurs fail. This is simply a fact. I have had plenty of failures. You haven’t heard of the Vibrapon, the vibrating tampon for menstrual cramps, or Dead TV, the online video obituary or cable channel, or HealthyBid, the reverse auction for high-cost healthcare, have you? These are just some of my failed business ideas. I have failed in some subtle ways and some extraordinary and public ways. Probably like you, I am often told about some “great idea” that will change the world.
Everyone has great ideas, but that is not what makes an entrepreneur. It’s not the idea, it’s the execution. I have had a few great ideas that probably would have worked had I not screwed the execution. Having a mentor can also help you with execution and your idea. Lean does not mean doing something on the cheap. You actually spend more in the early phase to test your hypothesis. This prevents you from building something no one wants and from the “just do it” mantra. The goal with lean is to quickly figure out what the customers want and if your product or service meets it. You need to know how to be efficient in your execution.
What is the lean way?
Lean means efficient – it means having a fast feedback loop that allows you to try, fail, learn and try again – quickly. Here is the important part, entrepreneurs tend to waste a lot of time pursuing ideas and options that do not come to fruition. We find ourselves failing because we:
- pursue ideas that are not well thought out
- pursue too many ideas and overextend ourselves
- pursued ideas for too long and abandon them months after we should have.
The idea during the early stage and really during any growth stage (which is actually every stage) is to fail fast. Learn from the mistake, make the course correction and restart. A famous example of this was a site called BURBN (one of the founders liked to drink expensive whiskey and scotch) and was initially designed as a check-in app that also allowed users to upload photos. However, fairly early in its development, the founders noticed that people were generally only sharing photos. Instead of wasting time and going with their original plan, the founders pivoted to create a minimum viable product that became what is known today as Instagram. The graph to the right is a typical, successful startup company life cycle. The startup begins their search for a scalable, repeatable business model, at some point, the startup begins to earn revenue, achieves break-even cash flow and earns a profit. Before learning lean principle methodology this is how most of my startups looked. At least the ones that actually gained some traction. The lean startup shifts the company life cycle curve up and to the left, resulting in lower cost of innovation, reduced time to innovation, or both. The lean product/market fit accelerates the company life cycle through two value propositions for entrepreneurs’ and enterprises’ customer segments:
- reducing the cost of innovation
- reducing the time to innovation.
Keep in mind a value proposition tells prospects why they should do business with you rather than your competitors and makes the benefits of your products or services crystal clear from the outset. Consequently, the value of a pivot is the area between the original company life cycle projection and the new company life cycle. i.e. the area between the curves.
Starting out, graph A is what I always predicted in my pro forma statements. We all do. It just makes sense. The longer you are involved, the better it does. We think and model that growth is linear – It actually rarely and probably never is. However, despite the facts, when we present it to others or when we lay awake and think of the future, we tend to think that our business will grow in a linear fashion. When I started NextCare (a chain of urgent care centers), I was going to add one clinic every six months and estimated that each clinic’s patient volume would grow linearly. Thus, my growth line was closer to an 80-degree slope as opposed to 45 degree. I was completely wrong in my predictions.
Graph B is what we model if we are out raising capital. A bit of time progresses as we build the product/infrastructure necessary and then, once capital is infused it takes off on a nearly vertical track. This is what venture capitalists like to see. Their capital infusion quickly accelerates the business so that the growth curve gets the proverbial hockey stick shape. Again this rarely happens in real life.
And then there is reality, Graph C. There are a few things that are important there. Notice the small course corrections during the startup phase. Notice that they are getting shorter in duration. Then it takes off and plateaus and you stick it out a while before you realize that the growth you once predicted is not going to happen. You pivot, revenue drops and then you make small, quick course corrections before it starts to work and then you start hitting your stride.
This is what I am talking about when discussing what leans means. This is the lean way in a nutshell. A learn startup has four basic building blocks:
- Create the vision
- Build the MVP (Minimum viable/value product)
- Test the Assumptions
- Pivot or Persevere
Create the vision
Ok, so you have created your vision and it all makes sense to you and to the few people with whom you discussed it. It’s all coming together – at least on paper, except it isn’t.
- What if one of the assumptions that is integral to your thesis turns out to be incorrect?
- What does that do to your model?
- How will this simple failure in identifying what the customer needs impact your business?
This has happened to me a few times. Things that I think would be an obvious no brainer are in fact, not obvious at all. For example, when I started MeMD (a nationwide telehealth service where consumers can connect with a health professional online) in 2010, I had made two assumptions that were integral to the business model.
- Assumption 1: Urgent care centers would want to expand their catchment area by seeing patients virtually all over the state and augment their patient flow during their downtime by seeing patients virtually.
- Assumption 2: Patients with minor complaints would jump at the chance to be seen virtually.
These were no brainers to me! Urgent care centers in Arizona slowed way down in the summer and all urgent care centers suffered times without patients. When this happened, the centers still had to cover their high fixed overhead costs. Second, who would not want to be seen nearly immediately from their own home when they felt sick for a very low cost? As it turned out both of these assumptions were wrong! The urgent care centers believed that they would cannibalize their own business by seeing patients virtually at a lower price point and that the patients who were now coming in for an in-person visit with a price point of $125 would all opt to be seen virtually with a price point of $50. The second critical assumption I missed was that people would jump at the chance to see a provider online. This to me was so obvious that I did not really consider that back in 2010, the thought of seeing a physician virtually would be beyond the imagination of the patients we wanted to attract. So how could I have prevented this? I had done my “homework” and surveyed my markets. I asked people I knew if they would use a virtual medicine portal and they said they would. I also asked some urgent care owners who were ultimately not all that enthusiastic, but said they would use it. What I missed was the reservation they shared with me. I discounted it because I had at that point opened more urgent care centers than anyone in the US so who knew better than me? As it turns out – a lot of people!
What I should have done is create an MVP (Minimum Viable Product)
Techopedia explains Minimum Viable Product (MVP): “A minimum viable product (MVP) is the most pared-down version of a product that can still be released. An MVP has three key characteristics:
- It has enough value that people are willing to use it or buy it initially.
- It demonstrates enough future benefit to retain early adopters.
- It provides a feedback loop to guide future development.”
The catch to this development technique is that it assumes that early adopters can see the vision or promise of the final product and provide the valuable feedback needed to guide developers forward.
MVP to test the assumptions
Test only the features that are mandatory for the most basic version of the product. The learning cycle that I should have used to test my assumptions is below. The goal of a startup is to move this cycle as quickly as possible to save the two most precious resources, which are time and capital. So, MeMD is a virtual medicine platform. Anyone have any ideas how I could have done an MVP to test the assumptions I had made?
Step 1: Vision
I could have used an app like Facetime on the apple phone along with a very simple Electronic Health Record (EHR) system and called in the scripts to the pharmacy. The patients could have filled out a simple form online that was auto-emailed to me. The model may be called “Build-Measure-Learn” but, if you follow that sequence and jump in at the “Build” phase, you’ll be missing the mark. Instead, it’s essential to start with a planning stage. Your first task is to define the idea that you want to test and the information that you need to learn. You do this by developing a hypothesis – your prediction of what will happen during the experiment. Your hypothesis could focus on anything from product features and customer service ideas to finding the best pricing strategies and distribution channels. You might, for example, hypothesize that “increasing the frequency of our newsletters from two to four per month will increase overall revenue.” Next, decide what you’ll need to measure to test your hypothesis, and plan how you’ll collect your data. Interviews, surveys, website analytics and specialized software programs are common methods for gathering data.
Step 2: Build
Your goal here is to create a Minimum Viable Product (MVP) – the smallest possible product that allows you to test your hypothesis. It could be a working prototype or a basic advertisement or landing page. It could be a presentation slideshow, a mock brochure, a sample dataset, a storyboard, or a video that illustrates what you offer. Whatever MVP you choose, it needs to show just enough core features to attract the interest of early adopters – the people who’ll likely want to buy your product as soon as it launches. For example, the first 5,000 people who subscribed to the cloud-based file-sharing company Dropbox™ did so before its service was launched. They’d been convinced by the strength of Dropbox’s MVP – a 90-second video explaining the service that it was about to offer.
Step 3: Measure
Here, you measure the results that you obtained in Step 2.
- How does what actually happened compare with your hypothesis?
- Is there sufficient interest in your idea to continue developing it?
- Does the data show that you’ll be able to build a sustainable business around your product or service?
- Did customers ask for additional services? Changes to the product?
Step 4: Learn
By the time you reach this stage, you’ll be equipped to make sound, evidence-based business decisions about what to do next. There are then two ways forward:
- Persevere: Your hypothesis was correct, so you decide to press on with the same goals. You repeat the feedback loop to continuously improve and refine your idea.
- Even though your idea has achieved sufficient initial success to persevere with it, bear in mind that your next iteration may not do so. Be prepared to pivot in the future.
- Pivot: The experiment has refuted your hypothesis, but you’ve still gained valuable knowledge about what doesn’t work. You can reset, or correct your course and repeat the loop, using what you’ve learned to test new hypotheses and carry out different experiments.
- You can pivot in various ways. For example, you could develop a single feature from your MVP (called “zoom-in pivoting”) or focus on a different type of customer (“customer segment pivoting”). Or, you could try delivering through a new channel (“channel pivoting”) or use a single feature as the basis of a different product (“zoom-out pivoting”).
Eric Ries pioneered the idea of Build-Measure-Learn in his book, “The Lean Startup.” It is a learning and feedback loop for establishing how effective a product, service or idea is, and doing this as quickly and cheaply as possible. Follow these steps to use the Build-Measure-Learn feedback loop:
- Step 1: Plan your experiment: learn, measure and build – including developing a formal hypothesis.
- Step 2: Build a minimum viable product, and test it.
- Step 3: Measure the results against your hypothesis to decide whether you can develop a viable business around your product.
- Step 4: Learn from your results, and decide whether to persevere or pivot. Then, cycle back to the beginning, and keep on going around the loop as you develop your product. It is common to do this loop multiple times before landing on a product that works.
The biggest advantage of this technique is that it minimizes the risk and cost of creating products or services that no one wants, and helps you to “zero in” on something that customers will embrace.
Examples of MVP
Dropbox 5,000-75,000 subscribers overnight. Dropbox did not even exist. Video showed an extremely easy product that allowed for file sharing. Early enthusiasm for Dropbox’s idea persuaded the organization to persevere. However, it made mistakes when attempting to expand its initial user base, so it had to pivot several times during subsequent iterations of the feedback loop.
When you envision your company’s idealized product, you might imagine a powerful web app that gives users a smooth onboarding experience, gives them smart recommendations about what to do, follows up with nice personalized emails, and automates a high level of support. Throw that all out. Replace it with a human. That’s a Concierge MVP.
In the process of delivering the Concierge MVP, you’ll learn a ton about your users and the value you’re offering. Maybe you’ll find that these questions are so weird that they don’t help you make good matches at all. Even more drastically, maybe you’ll find that users don’t actually want a dating app – they want a way to make new friends when they move into a new city, and these questions are a great way to do that. This will move your company in a promising new direction. Use the Concierge MVP when you’re not strongly confident about your understanding of customer problems, and you want deeper customer interaction.
Wizard of OZ MVP:
Pretend that you have a fancy technical solution, however behind the current are humans fulfilling the requests. This is how Zappos started. The Wizard of Oz MVP wraps a technical shell around a human who’s actually powering the back-end. The customer believes she’s interacting with an automated product, but in reality, a human is pulling all the levers and delivering the service.
For example, let’s say you want to build a travel service where users type a complicated request articulating what they want, and your company plans the perfect trip for them. You want to be able to handle a request like: “I want to book a 5-day, 6-night trip to Paris, in June, for two people. We’re leaving from New York. I really like food and live music, and I want a short trip to Versailles. Please minimize my total travel costs.” This is clearly pretty tough for a machine to handle. It has to parse the language to understand what’s being said, then look up possible travel options, then assemble this into a coherent travel plan. But a human could do this very quickly. In fact, humans do this all the time to plan their own vacations. Use the Wizard of Oz MVP when you want to evaluate a faithful representation of your product and hide the human from the customer.
Landing page MVP:
Set up the service or product as if it exists and see what the interest is using a buy button.
This is what Kickstarter or Indiegogo does. You mock up your product on their site and try to raise money for its development.
What do you measure to determine progress?
So, you have your MVP and it is operational, although not yet producing your planned customer response. You realize after talking to your customers that you need to pivot a bit to achieve the response you want. How do you measure and what do you measure after the pivot? Here are some things to consider. There has to be a cause and effect relationship. For example, you decide to change the app from a monthly fee to a free app. Start monitoring download or conversion numbers. All else being unchanged, the increase in these numbers after moving from a monthly fee to free should be a simple cause and effect.
- Accessible: The data has to be easy to obtain. In other words, it has to be line of sight so that it is easy to check on a daily basis. When Google bought YouTube their goal was to have a billion hours per day of viewing. While they were pivoting along the way, these hours viewed per day numbers were easily accessible and everyone monitored them.
- Auditable: If your goal is to raise money, what you do has to be reproducible or auditable in order for anyone who wants to validate your numbers. Investors will demand to see the data that your assumptions are validated. Finally, picking easy to access and understand numbers is integral to understanding if your pivots are producing the necessary results.
Sometimes you need to pivot
I talked about BURBDN earlier, and they are a classic pivot story. The founders had some traction and a bit of capital, they decided that their photo-sharing feature had the most opportunity for success so they re-branded it to Instagram. Within the first ½ day after release, they were the number one photo-sharing app on the web.
When to pivot:
- Establish a baseline of your current MVP.
- Attempt to tune, measure and learn.
- Pivot or persevere.
- Determine, what defines your adequate rate of growth?
- If it is not improving after a few iterations, then pivot.
- Customer segment pivot – initial customer segment was not all that interested so pivot to another group.
- Value capture pivot – give it away and get ad revenue. Viral engine of growth
- Engine of growth pivot: did not spread viral but lifetime value is higher than the cost of acquiring the customer so switch from viral to paid.
- Pivot does not mean failure.
Ok team, here are the main points. If you don’t remember anything about lean startup methodology, remember this: Everyone has ideas, where the rubber meets the road is your ability to execute on that great idea. How you execute is crucial. The steps and the sequence you take are important. Determine your vision and then test your critical assumptions using an MVP. Test and learn quickly so you don’t outrun your capital. Continue to make small changes to your MVP as you continue to test your assumptions. If you get to the point where you still have not found your mark despite the changes made to your MVP then you will likely need to pivot. Once your product meets the basic needs of your target audience it is time to accelerate the cycle of the learning feedback loop. Continue to iterate your product or service as you receive more customer feedback. Lastly, understanding 5s lean principles as your business grows will be beneficial.