Why do leaders need their teams to master lean experiments? It's one of the core skill sets necessary to innovate at scale and accelerate their ability to discover and deliver customer and business value.
It is the fastest way to expose and reduce risk when solving critical customer problems. Half of the original ideas will fail, and teams need the skills and tools to iterate and reach the fastest path to value.
Lean Experiments are one of the primary tools used throughout the discovery process of ideating, creating, and delivering a valuable product or service.
It reduces the time and resources wasted on building something no one wants and increases the speed at which a team learns and finds a validated path that achieves customer and business outcomes.
The output of each experiment produces data, observed customer behavior, and insights to make evidence-based decisions.
It's not enough that teams know how to experiment.
Leaders need the knowledge and skill to support teams running them. It enables leaders to understand when and how to challenge the teams to think critically and ask the right questions so they can produce the most learning and find the fastest path to value.
What are the high-level steps for running experiments?
Understand the customer and their problem, and validate it's a high-value opportunity to go after.
The team must understand and articulate the customer and the problem. Validate it's a high-value opportunity to be solved. If solved, it achieves the desired outcomes. Various research methods can aid teams in developing a deeper understanding of the customer's pain points, desires, and needs.
Expose and prioritize assumptions to quickly identify risks.
Once there is a deep understanding of the customer and problem, the team can start to expose and prioritize assumptions around the problem to validate it first and then possible solutions they believe solve it. The team should always select the riskiest that, if invalidated, will pause or stop the work.
Assumptions introduce different types of risk. They should always start with customer risks. If they prove first a customer problem to solve doesn't exist, the other types of risk are irrelevant as there will be no value from the solution.
The hypothesis restates the riskiest assumption to show what customer behavior they are testing for and how they will measure whether it is validated.
The hypothesis helps them clearly define the goals for the experiment and determine whether it is successful.
Design the experiment, a test, to validate their riskiest assumption.
The hypothesis guides the design. The experiment design is to provide the answers the team needs. There are different types of experiments, and they need to design the one that tests customer behavior.
Provide value to the customer.
These are current or potential customers. The team must ensure positive customer interaction. The customer must experience receiving value when the experiment is complete.
Establish start and end dates to run the experiment.
The length of time the experiment runs should produce the necessary learnings.
What type of evidence should the team gather?
- When running a lean experiment, teams gather evidence of customers investing in your product/service.
- Data collection beyond email, a commitment of funds or letter of intent/agreement, investing their time, and promotion to their networks are all signs of customer engagement.
- Teams must strive to produce evidence driven by a prospect or customer needing to do an activity and take some action requiring them to invest something of value.
Key Questions Leaders and Teams should be asking before running a lean experiment:
- Is the team clear on the riskiest assumption, and does the experiment test it? If not, the time and effort are not testing their hypothesis and won't produce the learnings needed.
- Is the team involving the right group of target customers for this experiment? If it doesn't target customers or proxy customers, the team runs a test with inclusive results.
- Is the team testing a specific customer behavior? If not, it's questionable if it will produce learnings and insights that lead to evidence that validates the assumption.
- Is it clear how the results of this experiment are measured? If the team can't measure results, how do they know if it was successful?
- Is the experiment designed to test multiple variables? If it does, it can lead to unclear results and cause the team to make potentially wrong decisions.
- Can they run the experiment in a way that's faster and still produces the learnings needed? Is it over-designed? The team focuses on perfection versus speed of learning and quick feedback loops that generate evidence.
After the team runs the experiment, they will:
Gather and analyze the evidence.
- Record the results. Did they validate the assumption based on the hypothesis?
- Document what the team observed. What happened?
- Identify critical insights gained. Do they understand what happened and why? It's beyond observation. Understanding insights can help the team think about how to solve the problem.
Make an evidence-based decision.
- Persevere if the experiment validated the assumption. The team tests another riskiest assumption.
- Iterate if the experiment invalidates the assumption and observations determine they should test the same riskiest one with a different experiment.
- Pivot if the experiment invalidates the assumption. The team produced sufficient evidence to change the customer, problem, solution, or combination. Or they may need to stop pursuing the idea altogether.
Running Experiments takes both teams and leaders.
The method of running experiments teams can master for those who embrace it, stay disciplined, remain curious and open to learning, and follow the evidence where it leads. They will iterate and pivot as needed. They know the desired outcome to achieve and have success metrics in place to assess and track their progress.
For teams to work in this way, leaders must:
🔸 Embrace a culture of innovation, experimentation, and a learning mindset.
🔸 Empower teams to experiment and trust them to make data-driven decisions for their work based on the evidence.
🔸 Create a safe environment for experimentation where failure and learning are acceptable and essential to innovation.
🔸 Give teams the freedom to explore new ideas and test solutions they believe to solve critical customer problems.
🔸 Let teams show they can take the lead on solving customer problems.
🔸 Support them when they need cover.
🔸 Help them with connections and encourage collaboration with others they need.
🔸 Break down barriers that impede their progress.
As a leader, if you want to see your organizations innovate at scale and accelerate their ability to discover and deliver customer and business value, have teams master running lean experiments to unlock innovation and learn to understand how best to support them.
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