In today's rapidly changing world, organizations need to be able to adapt and innovate at scale to stay ahead of the competition. However, new products and services often fail.
According to the late Harvard Business School professor Clayton Christensen, astonishingly, 95% of new products fail. Marty Cagan of the Silicon Valley Product Group summed it up: "One of the inconvenient truths about product…at least half of our ideas are just not going to work."
Even the tech giants have learned that new products and services can fail. Google Health, IBM Watson Health, Microsoft Health Vault, and Amazon Care are a few examples.
But why do so many products fail?
One of the main reasons why new products fail is that teams often fail to expose, prioritize, and reduce risk before building, during, and through to delivering value.
One way to reduce the risk of product failure is to adopt a continuous discovery approach. It means that teams should constantly test and validate their assumptions, starting with their customer needs, pain points, and desires through all phases of product development.
Teams tend to make assumptions from the early stages of discovery through ideation and creation to execution. Without sufficient proof assumptions are true, it introduces a high risk that could invalidate the entire idea.
There are different types of risks that teams should be aware of:
- Customer Desirability and Usability Risk: Will customers get value from the product or service? Does anyone want it? Will they use it? Will they understand how to use it?
- Feasibility Risk: Can we build it? Will our legal or security teams allow it? Will our salespeople sell it? Can finance support the model? Do we have customer service support? Does it comply with regulations?
- Business Viability Risk: Should we build it? Will it drive value for the business? Is there potential harm if we were to develop the solution?
A team must identify and expose all risks but start by brainstorming assumptions, beginning with customer risks. If a validated customer problem to solve doesn't exist, the other types of risk are irrelevant as there will be no value from the solution.
That's why teams need to start validating these assumptions by experimenting in the early discovery stages when they uncover what they believe is a problem to solve.
Here are some tips for brainstorming assumptions:
- If you are validating the customer's problem, determine what behaviors and actions they would need to take if this was a problem they wanted to solve.
- If you validated the problem and have an idea of the solutions, walk through all the steps on how you expect the customer to interact with the product or service from when they first receive value. What assumptions are you making about the actions they will take?
- All assumptions should be phrased in a positive statement because the team believes the customer will take some action.
Once you have your list of assumptions, prioritize them based on those believed to be high risk to your work and for which there is insufficient evidence or proof that they are true.
The team then selects the riskiest assumption, if not validated, which would mean pivoting, pausing, or stopping the work. Now that the high risk is exposed, the team can reduce it by quickly testing the most critical assumptions to (in)validate by running lean experiments and generating evidence.
The process repeats, running experiments and testing those high-risk assumptions, gathering evidence to find the validated path that delivers customer and business value.
There are several benefits to this approach. Below are a few:
- Reduces the risk of product failure
- Increases the likelihood teams discover a high-value problem worth solving
- Maximizes a team's speed of learning
- Reinforces the team's ability to make evidence-based decisions
- Minimizes waste of a team spending time, resources, and energy going too far down the wrong path
- Provides critical skills and tools to use whenever teams face uncertainty and risk
There are many approaches to continuous discovery. I covered one. You have to right-size discovery based on what decision you need to make next and what you need to learn to get the answers.
If you want to transform your organization to innovate at scale, accelerating discovering and delivering customer and business value, teams need to work and think in a new way.
It is one core practice and crucial skill set teams' must learn for the organization to adapt and stay ahead of the competition, innovate at scale, and reduce the number of products and services that fail.
How to Run Effective Experiments
In a future blog post, I will discuss how to run experiments that gain the most learning to validate your critical assumptions. It will include tips on how to avoid falling into pitfalls that can cause false results.