A lightweight visual tool to foster distributed innovation and a culture based on experiments
A cornerstone of Agile and modern ways of working is often the reliance on experimentations, observations, and continuous improvement. This approach can be highly effective for organizations that are looking to stay competitive and adapt to changing market conditions. However, there is a dangerous misconception that this type of work should happen sporadically and without any structures, which can lead to confusion, lack of focus, and ultimately, a failure to extract meaningful learnings from the experimentation process.
One way to avoid this problem is to implement a structured experimentation framework or processes, such as the Demming Cycle (Plan-Do-Check-Act) or regular retrospection, making it easier to extract valuable learnings and apply them to the organization. At XITASO however, we needed something else to really fit our needs, so our Agile Coaches at designed our Experiment Canvas, as the way to offer a minimal structured visual support for running reliable experiments and delivering consistent results.
You can download it here: Experiment Canvas (EN)
Why developing something new?
Similar to how children learn through trial and error, organizations also learn through experimentation and making mistakes. However, in organizations, the consequences of failure can be much greater than a scraped knee or a bumped head. Relying on luck or pain as a decision-making mechanism is not sustainable or advisable, as it can lead to negative consequences and make it difficult to extract meaningful learnings. Instead, organizations should strive to make data-driven decisions and use a systematic approach to experimentation and continuous improvement.
Therefore, it’s important for organizations to structure their experimentation and continuous improvement efforts in a way that minimizes risk and maximizes the chances of success.
A lot of this is baked in agile methodologies such as Scrum or Kanban, which allows you to have regular retrospectives (or any other mechanism for continuous improvement) with your team, where you can discuss what worked, what didn’t, and what needs improvement. However, we needed something else to help us to create transparency, focus and alignment around experimentations on organisation level. The OKR framework could have supported our efforts in this direction, but we were looking for something lighter and streamlined.
How to use our Experiment Canvas
The Experiment Canvas was then developed to help organizations to design, run, and conclude experiments in a more structured and efficient way. The canvas is a visual tool that helps to define a challenge, the main hypothesis, its measurements, and eventually the expected outcome. It is designed to make the experimentation process more systematic, clearer, and more focused, which in turn enables each part of an organisation to steer their continuous improvement more effectively. A key component being the definition of success criteria and learning goals, it is supporting the creation of a shared understanding what is to be achieved, and how success or failure will be measured.
Here is how it looks:
You can download it here: https://baptistegrand.info/dl/Experiment-Canvas-en.pdf
How to fill the Experiment Canvas
First, it’s important to establish clear and transparent information about an experiment, including its Name, Timeframe, and Ownership, to ensure that all stakeholders understand what is being done and by whom. This information can be used to keep track of the progress of the experiment, as well as to identify any potential issues or concerns that may arise.
Here are a few things to consider when naming an experiment:
- The Name should be descriptive and easy to understand, so that anyone can quickly grasp the goal and purpose of the experiment.
- The Name should be unique, so that it’s easily distinguishable from other experiments.
- Consider including the key variables or elements of the experiment in the name, such as the product, feature, or customer segment that’s being tested.
In terms of Timeframe, it’s important to establish a clear duration for the experiment, so that everyone involved knows when the experiment begins and when it’s expected to end. Additionally, you can also define and write down milestones in the Next Steps area, so that everyone understands the context of the experiment.
Finally, it’s important to identify the owner of the experiment, who will be responsible for overseeing its design, execution, and analysis. This person should have the necessary expertise and resources to carry out the experiment, as well as the authority to make decisions and take actions based on the results.
Once the frame of the experiment is set, it is time to design it:
The hope describes what you are aiming at. You don’t need to describe how the experiment will exactly run but the result you are wishing for. It is also important to note that the hope should be realistic, meaning that it should be achievable within the Timeframe of the experiment. It is good to strive for big goals but also keep in mind the constraints and feasibility of achieving it.
The Success Criteria are the specific measures or metrics that will be used to determine whether the experiment was successful in achieving its hoped-for outcome. They help to provide a clear and objective way to evaluate the results of the experiment and determine whether the hoped-for outcome was achieved. They best work when qualitatively defined, as to avoid a black-or-white interpretation that would hinder an incremental and iterative approach. It’s also important to have multiple success criteria so that the experiment can be evaluated from different perspectives. It will help to mitigate the risk of having false positives or negatives by looking at the results through multiple lenses.
Please note that the worst output possible would be the impossibility to observe or measure Success Criteria, as it would mean that the experiment was performed for nothing… 🚫
Here is a real example of an experiment we ran at XITASO:
That’s all folks! I hope this Experiment canvas will help you to foster distributed innovation and a culture based on experiments within your organisations. Encouraging experimentation, giving autonomy and enable teams to test new ideas and new ways of working is a powerful way to drive innovation and find new opportunities.
Baptiste.
