Why the Lean Inception Approach Makes Sense For AI Projects
- Posted by GM, Digital Solutions
- On April 22, 2021
AI-powered business applications and products can create tremendous value for modern enterprises. However, executing AI projects effectively is no walk in the park – you need the right team, processes, and buy-in from key stakeholders, as well as tried-and-true strategies, to maximize your chances of success. This is where lean inception can play a role.
Daitan uses the Lean Inception approach as one of their strategies in software development, particularly in the Discovery phase of AI projects. Lean Inception is the brainchild of Paulo Caroli, a thought leader in the world of agile development and lean practices, who recognized that companies often spend too much time pursuing digital product ideas that customers may not even appreciate. Caroli’s methodology solves this challenge by eliminating extraneous activities and forcing teams to focus only on the most essential elements.
Today, Lean Inception is widely used in larger organizations that need to get many different types of people on the same page. The approach draws from several popular software development ideologies and culminates in an efficient playbook for developing digital products and services in a democratic manner.
Daitan has witnessed the benefit of Lean Inception first hand when it comes to aligning various stakeholder groups – business leaders, engineers, and customers – around product development goals. In this post, we’ll share some of our insights, dive deeper into what Lean Inception is, and discuss why the strategy works so well in modern product development, especially when it comes to AI projects.
What Is Lean Inception?
The Lean Inception approach to software development is one of many strategies for organizing collective brainpower around new product ideas. The process takes place before any real development begins (hence the “inception” part of the name). It does not include the actual delivery of a minimum viable product (MVP) – it’s meant solely to organize stakeholders around an MVP to achieve specific goals.
Under Lean Inception, teams take up to one week to pressure-test certain assumptions and hypotheses. This narrow timeframe forces the individuals involved to focus intensely on the key decision-making factors surrounding their projects. At any time, teams are free to stop the Lean Inception process if it no longer makes sense to proceed.
The output of Lean Inception is typically a more refined product roadmap for a potential digital product or service. Leaders can then use this roadmap to determine how much or how little to invest, who should be involved going forward, and whether or not the original hypothesis still holds true.
To be clear, Lean Inception does not replace other essential product development activities, such as conducting user research, surveying the competitive landscape, reviewing IT architecture, etc. Lean Inception leverages existing knowledge across these areas to bring together the best aspects of design thinking and agile development.
What Are The Benefits Of Lean Inception?
Lean Inception offers several important advantages for companies.
One of the primary benefits is that teams align around specific digital products, features, or services that could create value for customers and ultimately the business. The approach is designed to empower stakeholders to thoroughly investigate an idea before committing resources too early.
Lean Inception also promotes rapid iteration, ensuring companies don’t waste time, money, or energy building features or products that customers don’t actually want. Furthermore, teams can adapt Lean Inception according to their unique needs. The methodology includes many helpful tools and exercises, each with their own valuable outputs, that bring clarity to the product development process.
For these reasons, Lean Inception works well for AI projects, which tend to be ambiguous and complex; and requires rapid iterations as a model is developed. Lean Inception encourages groups to think through how development efforts will impact customer experiences and ensures that engineers move forward with the right MVP.
Teams can develop AI prototypes that map to user journeys without getting bogged down in details, such as how architecture needs to change, how to achieve scale, etc. (although these are crucial conversations to have down the road!).
How Is Lean Inception Used Best?
As a user-centered design approach, Lean Inception requires companies to know their customers intimately. Stakeholders should have a firm grasp on their user journeys and an understanding of how customers interact with products and services today.
Companies should also have growth or cost savings targets going into the Lean Inception process. Otherwise, it’s difficult to make go or no-go decisions when it comes to MVP development.
Additionally, teams should revisit the Lean Inception methodology regularly throughout the product development process. It often makes sense to use Lean Inception to help break MVPs up into small units and iterate quickly, all the while seeking constant validation from customers.
The Lean Inception concept incorporates user feedback which drive insights that determine what features remain and evolve.
The Lean Inception Approach In Action
At Daitan, we’ve implemented Lean Inception for both internal and external-facing projects.
Internally, Lean Inception enables our software developers to pursue research initiatives and explore edge technologies efficiently. We use Lean Inception to evaluate new innovations, ideate around proof of concepts, and map early-stage ideas to customer journeys. The methodology allows us to operate in a nimble manner and still arrive at sound conclusions.
Externally, Lean Inception has helped us make smart recommendations to clients around growth opportunities, as well as advise against certain technology pursuits. At a time when many leadership teams are interested in incorporating AI and machine learning into their businesses, we trust that Lean Inception can point us in the right direction.
On the cost savings side, some clients approach us with nascent ideas that they want to deliver to market. When we go through Lean Inception, we occasionally discover that the opportunity the client thought existed isn’t that compelling. In this way, the Lean Inception approach prevents companies from investing resources that will likely not generate attractive returns.
Again, Lean Inception isn’t a silver bullet for AI projects. It’s one of many tools and strategies development teams can use to pursue ideas wisely. We encourage you to learn as much as you can about Lean Inception in case it suits your company’s needs well.
To learn more about why the Lean Inception approach works well for AI projects, download our eBook, Planning Your Next AI Project.
To connect with a Daitan expert about your exciting AI MVP idea, contact us today.