Building products is an exhilarating journey into the unknown. Every time I sit down with a team to write code, I’m reminded that we’re embarking on a venture that has never been done before. If we weren’t, we wouldn’t be coding; we’d simply be purchasing a ready-made solution. This inherent uncertainty is what gives software engineering its unique character, and it’s also why we experience such a high degree of variance in our projects.
The Entrepreneurial Mindset
In the business realm, this concept mirrors the world of entrepreneurship. When you have an idea that promises value, regardless of how that value is delivered, you need to seek investment to bring that idea to life. This process is akin to what I would do if I were to start a new business. I’d need to approach banks or venture capitalists, convincing them that my idea is worth their time and money.
- Convincing Stakeholders: Whether it’s internal stakeholders or external investors, the challenge remains the same: you must articulate why your idea deserves funding.
- Risk and Reward: New ideas are inherently risky. They don’t come with guarantees of success or a return on investment. In fact, statistics suggest that around 70% of new businesses fail within their first year, and a staggering 30% of those that survive the initial phase will falter within five years.
Understanding this risk profile is crucial when investing in uncharted territories, whether in business or product development.
Funding Products Like a Venture Capitalist
When it comes to funding a product, I advocate for a mindset similar to that of a venture capitalist. You need to assess the potential return on investment and gauge the value you expect to derive from your investment. Here’s how I approach this:
-
Run Small Experiments: Instead of committing large sums upfront, I prefer to conduct numerous small experiments. For instance, if I have an idea for a database of movie stars, I’d seek a modest budget to test its viability.
-
Validate the Idea: Engaging in ideation helps refine the concept. Questions like, “How can we monetise this?” or “What additional features could enhance its value?” are essential. This iterative process can lead to something as impactful as IMDb, which started as a simple database but evolved into a significant player in the film industry.
-
Create a Business Plan: Before I allow any spending, I want to see a well-thought-out business plan or a lean canvas. This ensures that all aspects of the idea have been considered.
-
Proof of Concept: Once funding is secured, I expect to see a proof of concept. This initial version should be tested with real users to gauge its resonance and potential value.
-
Iterate and Experiment: The journey doesn’t stop at the proof of concept. I advocate for continuous experimentation. Each iteration should be a learning opportunity, allowing us to refine our approach based on user feedback and data.
Hypothesis-Driven Engineering Practices
I often refer to this approach as hypothesis-driven engineering. While many use the term MVP (Minimum Viable Product), I find it’s frequently misapplied. An MVP should serve as a proof of concept that may ultimately be discarded before the final product is built.
- Embrace Failure: It’s essential to accept that many experiments will fail. However, the key is to identify the successful ones and invest further in those.
- Stay Within Budget: By running numerous small experiments, we can manage our budget effectively. Each experiment should have a clear hypothesis, expected outcomes, and measurable success criteria.
Balancing Heart and Data
In the end, building products is not just about numbers; it’s about passion and vision. While data is crucial for making informed decisions, there’s also a human element that drives innovation. Balancing these aspects is vital for staying within budget while also fostering creativity and exploration.
As we navigate the complexities of product development, let’s remember that every step into the unknown is an opportunity to learn, adapt, and ultimately succeed. Embrace the journey, and let’s build something remarkable together.
Smart Classifications
Each classification [Concepts, Categories, & Tags] was assigned using AI-powered semantic analysis and scored across relevance, depth, and alignment. Final decisions? Still human. Always traceable. Hover to see how it applies.
What to read next
Maximising Product Value: The Power of Hypothesis-Driven Engineering
Explores how hypothesis-driven engineering helps teams maximise product value by testing ideas, measuring outcomes, and learning from …
Navigating the Unpredictability of Software Development: Embrace Agile for Success
Explores how Agile principles, technical leadership, and engineering excellence help teams manage unpredictability, adapt to change, and …
Mastering Product Development Costs: Empower Your Team for Financial Success
Learn how to track, manage, and optimise product development costs by empowering teams with financial awareness, key metrics, and continuous …
The Importance of Validation in Product Development: A Strategic Approach
Explains why validating product features is essential, highlighting hypothesis-driven development, data collection, and evidence-based …
Harnessing Your Entrepreneurial Spirit: Key Strategies for Product Owners to Drive Team Success
Learn how product owners can boost team success by connecting work to value, making evidence-based decisions, and improving time to market …
The Myth of Knowing Everything Upfront in Software Development
Software development thrives on continuous discovery and adaptation; upfront planning can’t predict everything. Embrace uncertainty, deliver …
Detecting agile theatre with real delivery signals
Why Most Companies Operating Models Fail in Dynamic Markets
A concise comparison of Predictive and Adaptive Operating Models, explaining why traditional structures fail in dynamic markets and how …
Don’t Manage Dependencies, Remove Them
Explains why dependencies are a sign of poor system design and outlines steps to eliminate them by aligning teams, clarifying ownership, and …
The Estimation Trap: How Tracking Accuracy Undermines Trust, Flow, and Value in Software Delivery
Tracking estimation accuracy in software delivery leads to mistrust, fear, and distorted behaviours. Focus on customer value, flow, and …
Flow of Value vs Flow of Work – Misnomer or Useful Shorthand?
Compares “flow of value” and “flow of work” in Kanban, explaining why only validated outcomes count as value and stressing the need for …
Why Outsourcing DevOps Fails, and How Real Engineering Excellence Starts With Your Team
Avoid DevOps vendor lock-in, discover how true engineering excellence starts with partnership, not outsourcing. Ready to transform your …
Why Most Companies Operating Models Fail in Dynamic Markets
A concise comparison of Predictive and Adaptive Operating Models, explaining why traditional structures fail in dynamic markets and how …
Don’t Manage Dependencies, Remove Them
Explains why dependencies are a sign of poor system design and outlines steps to eliminate them by aligning teams, clarifying ownership, and …
The Estimation Trap: How Tracking Accuracy Undermines Trust, Flow, and Value in Software Delivery
Tracking estimation accuracy in software delivery leads to mistrust, fear, and distorted behaviours. Focus on customer value, flow, and …
Kendall Guide - A System of Work for AI Adoption
Flow of Value vs Flow of Work – Misnomer or Useful Shorthand?
Compares “flow of value” and “flow of work” in Kanban, explaining why only validated outcomes count as value and stressing the need for …
Estimating Better in an Overloaded System Is a Poor Man’s Strategy
High work in progress (WIP) causes delays and unpredictability; improving estimates won’t help. Limiting WIP and focusing on flow is key to …
Why Most Companies Operating Models Fail in Dynamic Markets
A concise comparison of Predictive and Adaptive Operating Models, explaining why traditional structures fail in dynamic markets and how …
The Estimation Trap: How Tracking Accuracy Undermines Trust, Flow, and Value in Software Delivery
Tracking estimation accuracy in software delivery leads to mistrust, fear, and distorted behaviours. Focus on customer value, flow, and …
Getting Started with Objectives & Key Results
Learn how to successfully implement OKRs by aligning clear strategy, fostering transparency, empowering teams, focusing on outcomes, and …
OKR Guide - A Social Discipline for Shared Focus, Measurable Contribution, and Strategic Learning
A certification proves you’ve passed a test
Certifications show test-passing ability but don’t prove real-world product skills. Experience, judgement, and stakeholder influence matter …
Most companies still get Product Ownership wrong
Many organisations misunderstand Product Ownership, treating it as simple backlog management instead of a strategic, accountable role …