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Why companies should implement Lean Startup: the advantages of the method and the AI revolution

The Lean Startup Methodology (or "lean startup") is an approach to creating and managing startups developed by Eric Rice. The main idea is to minimize losses and risks when launching new products by testing hypotheses in the market and getting feedback as quickly as possible. This approach can be effectively used not only by startups, but also by large companies seeking innovation.

The goals of Lean Startup are radically different from the classic business model. If in Lean Startup you check your product immediately and collect feedback, then in the classic business model you take a very long time to build a scheme to attract capital and explain the uniqueness of your product, and instead of instant push to the market, keep secrecy to the maximum ideal state of your service or application. 

The difference between Lean Startup and the classic business model is clear:

  1. Testing hypothesis: Instead of spending months or even years developing a product, companies can quickly bring a minimum fixed product (MVP) to market and collect feedback.
  2. Minimizing losses: if a product or service is not found, the cost of its development will be incurred.
  3. Resource optimization: the method allows you to concentrate efforts and funds only on those solutions that are really in demand on the market.

1. MVP (minimally independent product)

A minimally isolated product (MVP) is a version of a new product that uses only minimal functionality to test the hypotheses contained. Creating an MVP allows you to quickly test an idea on the market, collect feedback and improve or redesign this product based on the data.

2. Continuous learning and training

Lean Startup teaches that the hypothesis of what a product or service should look like should be tested by example. Companies are constantly collecting data from the market, adjusting the product, learning and repeating the cycle.

3. Fast adaptation 

If the collected data shows that the product does not meet the expectations of users, the company should be ready to change course. This may lead to a change in the external, functional product or business model.

4. Making decisions based on data

The Lean Startup methodology is based on data. This allows companies to make informed decisions, avoiding mistakes.

Lean Startup offers many benefits that can be important for both startups and mature companies. Let's look at the main ones.

1. Saving time and resources

Instead of spending years developing a product that might not work, Lean Startup allows companies to start with a minimal set of features, checking their relevance in the market. This approach reduces costs and allows you to focus on the most promising solutions.

2. Quick response to market changes

Technologies using Lean Startup can quickly respond to changes in customer preferences, the competitive environment, or technological development. This is especially important in modern conditions, when the rate of change increases every year.

3. Minimizing the risk of failure

By constantly testing the hypothesis and collecting feedback, the company can avoid costly mistakes at the product scaling stage. Lean Startup takes into account the limitations of the fact that the product turns out to be unclaimed or unsuccessful.

4. Product quality improvement.

Feedback from other users in the early stages of development helps companies identify weaknesses in the product and improve its mass market release. This makes the product more competitive.

1. Dropbox

When Dropbox first appeared on the market, its founders decided not to immediately develop a fully functional product. Instead, they created a video tutorial with a detailed explanation of how the service works. This approach has significantly reduced costs and accelerated the launch of the product to the market.

2. Zappos

The Zappos concept tested its hypothesis that people are willing to buy shoes online rather than create a full-fledged website with millions of products. Founder Nick Swinmurn simply photographed shoes in local stores and posted photos online, receiving orders from customers. This resource tests the idea and determines the demand for creating a full-fledged online store.

3. Buffer

Buffer is a service for scheduling posts on social networks. The founders suggested that users register in the trial version to gain access to the future product. After receiving a positive feedback, they started developing the full version of the application.

4.Grove Collaborative

Grove Collaborative is an environmental company offering products for home and personal care. They used Lean Startup to quickly test environmentally friendly products. The founders of Grove Collaborative started creating MVP, a simple online store where customers could sign a contract for the supply of eco-goods. Only after that they started to expand the range. 

5. Zola

Zola, a wedding gift platform, has used Lean Startup to test its business models. Instead of launching a full-fledged platform right away, they started with a minimal standalone product that offers fast tested hypotheses and adapts to user needs.

Lean Startup is based solely on hypotheses. In simple terms, you check your idea every time — fix the advantages and disadvantages of your idea — refine it based on the data you receive. 

The implementation of Lean Startup requires process restructuring and changes in corporate culture. Below are a few steps that can help implement the methodology in the company.

1. Changing attitudes towards product development

The company needs to move away from traditional methodologies in which a product is produced for a long time before it is put on the market. Instead, you should focus on creating an MVP and collecting data from the market.

2. Creating small cross-functional teams

Lean Startup works best in small teams that can make decisions quickly and adapt to changes. The creation of such teams within the company for the holding of the meeting event.

3. Constant interaction with customers

Collecting feedback from customers should remain the same. This will allow the company to quickly adjust its decisions and remain competitive.

4. Accepting Failure

Lean Startup assumes that not all ideas will be successful, and this is normal. A cultural company should support its employees in experimentation and innovative approaches, even if they sometimes lead to failures.

One of the well-known researchers at Lean Startup is Steve Blank, who suggests using the concept of synthetic humans. 

According to his logic, by creating synthetic people with the help of artificial intelligence, entrepreneurs will have more ideas and more opportunities to generate income. 

The AI implementation model in Lean Startup may look like this: 

The company creates synthetic humans or even entire synthetic cities and asks these respondents within a given range (for example, household goods) to answer questions about the future product. These synthetic humans send feedback to the company much more quickly, and based on this data, there is more space for analyzing hypotheses and ideas. 

Accordingly, two important factors are combined in this scheme at once: quantity and speed. Thanks to this, the company will be able to find new opportunities for scaling and growth without the cost of human labor, since ultimately no team of 10 or even 100 people will be able to process as many hypotheses as AI can process. 

And this is a big step towards optimization for new startups, which will allow them to stay in the race as long as possible, because according to statistics, about 90% of startups fail. 

1. Fast data processing and market analysis

One of the key elements of Lean Startup is constant interaction with the market and customers to receive feedback. AI can significantly speed up this process by providing startups with tools to analyze large amounts of data in the shortest possible time. The use of machine learning and data analysis technology helps automate the information processing process, which allows you to make decisions based on accuracy faster.

Example:

A startup developing a mobile application for personal finance management can use AI to analyze user behavior and identify the most in-demand functions. Instead of relying on manual analysis, AI algorithms can process arousal data in a matter of minutes using applications, cases of manifestation and indicate the direction for improvement.

2. Optimizing MVP with Predictive analytics

Creating a minimal independent product (MVP) is an important step in the field of lean startup, allowing you to quickly test a hypothesis in the market. Artificial intelligence helps to improve this process by applying predictive analytics to assess the probability of success of a product even before its launch. AI can take into account historical data and current market trends to predict whether an MVP can be really successful and suggest adjustments even before it.

Example:

A company that is developing a new food delivery subscription service can use AI to analyze different markets and adjust business models. This avoids significant startup costs by testing hypotheses in advance.

3. Improving the user experience (UX)

Lean Startup actively uses customer feedback to improve the product. Artificial intelligence, in turn, can analyze user behavior and automatically find points that require improvement. With the help of AI, you can automate the process of implementing interfaces by identifying gaps that cause user dissatisfaction.

Example:

An online education startup platform can implement AI to analyze user activity on the service. AI identifies problematic moments when users stop using the service more often, and offers solutions to improve the interface and functionality.

4. Marketing automation and personalization of offers

For startups, it is important not only to create a product, but also to bring it to market effectively. Artificial intelligence can greatly simplify this process to calculate the automation of marketing campaigns. AI systems can automatically segment the audience, personalize advertising messages and adjust budgets. This allows you to quickly and accurately convey a valuable offer to the network connection.

Example:

A startup building a fitness app can use AI to analyze a database and create personalized subscription offers, which increases user workability and increases the accuracy of forecasts and project management.

In conditions of limited resources, it is especially important for startups to properly manage finances, production facilities and human resources. AI can help in predicting business development and optimizing resource use, which reduces risks and increases efficiency.

Example: 

An electronics startup can use AI to manage supply chains, predict and minimize logistics costs. This will help to reduce costs and avoid problems with the availability of products in stock.

Thus, lean Startup is a well—known tool that can help companies of any size minimize risks, increase efficiency and speed up the product development process. In today's world, where change is happening faster than ever, the ability to quickly adapt and respond to such customers is becoming a competitive advantage. The implementation of Lean Startup allows companies not only to bring innovative products to market faster, but also to save resources by minimizing the cost of unsuccessful decisions.

Lean Startup helps companies stay flexible, experiment, and use data to make decisions. This approach has already proven its effectiveness in many examples, both among startups and mature companies seeking innovation. T ut is a link to my tg channel "Cards, money, KPI". The channel has more short posts about strategies for IT and blockchain projects, interesting news and management. Subscribe if such topics are close to you.