Leading experimental culture

The ability to design your own experiments is fundamental to running an innovation initiative, and involves continually engaging in participatory action research.

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Why Experimentation

Peer Academy has developed a rigorous process for designing, activating and scaling out a peer learning academy based on experimentation culture. This process makes the development of an academy more likely to succeed within the VPS organisational context.

This process is based on:

  • Behavioural insights from academy participant stakeholders
  • Leading edge design practice in the context of emergent systems (1,2,3,4)
  • Latest evidence about developing human capital from leading thinkers (5,6)   

Experiment cycles are an action research method, which enable real time communication of progress to stakeholders, collect valuable evidence for evaluation of the initiative’s outcomes, and feed behavioural insights into the evolution of the Academy over time.

An experiment cycle
  1. Mintzberg, H., & Waters, J. A. (1985). Of strategies, deliberate and emergent. Strategic management journal, 6(3), 257-272.
  2. Hassan, Z. et al (2015) The rise of the prototyping paradigm. Social Kritik, 142/2015.
  3. Klein, L. (2013) UX For Lean Startups. O’Reilly Media.
  4. Cicero, S. (2017) Platform Design Toolkit.
  5. Hagel, J & Seely-Brown J. (2017) Help Employees Create Knowledge — Not Just Share It. Harvard Business Review 09/2017.
  6. Kulasooriya, D. & Wooll, M. (2017) Unlocking Human Potential. Deloitte Insights 02/2017.

Building Experiments

The experiments outlined below are not an exhaustive array of enquiry-based tactics for activating, sustaining and evolving an Academy. The ability to design your own experiments is fundamental to running an innovation initiative, and involves continually engaging in participatory action research that moves with the current state and culture of VPS. Consider this a crash course guide to writing your own experiments, to help you on that journey.

Each step relates to the Experiment Cycle diagram (below), and each action is linked to specific sections on our Experiment Sheet.

Step 1: Build

Good experiments actually begin with reflecting on what we know, what we think we know, and where we want to get to.

The Build section of the experiment sheet is dedicated to building the context for your experiment. It invites you to set out the assumption(s) you’re testing, your vision for where you’re heading, and any evidence you’re basing your experiment on.
Action: Fill in Purpose & Hypothesis sections
Hint: testing multiple assumptions in one experiment will make it much harder to draw out clear insights and actions, so we suggest breaking down the ideas into a number of smaller experiments.
Hint: try to write your hypothesis in a way that you are able to disprove your ideas if they are wrong. Using numbers, time frames and other falsifiable methods can help with this.

Step 2: Test

The value of experiments is not just in the ‘action’ of doing, but it’s in the way we learn from that action.

The Measure section of the experiment sheet is dedicated to supporting you to work out what you should be listening out for and measuring. It invites you to set out the activities you will undertake, any tools you will rely on, and how you will know whether the experiment has (dis)proved your hypothesis.
Action: Fill in Overview, Tools, Metrics & Criteria sections
Hint: this provides an opportunity to think of multiple different ways you could explore your assumptions and hypotheses. Try to look beyond your first idea and ask how else you could get different results.

Step 3: Learn

Reflective practice is at the core of experiment design. This is your opportunity to make sense of the insights from your experiment.

The Learn section of the experiment sheet is dedicated to documenting the outcome of your experiment and creating momentum for the future. It invites you to record your raw data, draw insight from the data, and make recommendations for the next cycle.
Action: Fill in Observations, Insights, Decisions/Actions sections.
Hint: there’s a variety of ways you can do sensemaking and synthesis well, and most of them rely on getting away from a screen and getting your data all out onto a wall or table to create patterns and themes. Explore different ways in which you can do this over time.

Step 4: Reflect

Designing experiments creates a reliable cycle of action and reflection on top of which you can build, test and evolve the VPS Academy over time.

If you would like to explore this in more detail, we can arrange for more in depth training and development to hone your skills.

Suggested Experiments

The platform is activated through a series of experiment cycles which allow us to have alignment around action, observe and measure behaviour, reflect to gain insights, and then tailor the design of the next cycle to maximise the likelihood of its success.

This section details each of the experiment cycles, what they’re intended to achieve, and the evidence they’re based on.

We have completed an Experiment Sheet for the first two experiments that can be completed once the experiments have been run.
  1. Experiment 1: Onboarding

    This experiment is focused on the development of a platform which supports recruitment, engagement and activity of participants of the VPS Academy.

    It is built on the evidence that for learning platforms to be effective, we need to craft the right invitation and establish the infrastructure to enable interactions.

    Download Experiment Sheet
  2. Experiment 2: Social Capital Building

    The second experiment is focused on the nurturing of interactions between participants to grow trust, engagement and valuable interactions.

    It is built on the evidence that for learning platforms to be effective, we need to build social capital between the participants

    Download Experiment Sheet
  3. Experiment 3: Collaborative Capability

    This experiment is focused on the development of collaborative capacity individually and collectively to enable participants to collaboratively develop new knowledge and solutions in new contexts.

    It is built on the evidence that for collaborative culture to grow, we need to build participants’ hard and soft collaboration capability.
  4. Experiment 4: Enhanced Discovery

    This experiment is focused on best and next practice being developed in technology sector in user experience, artificial intelligence, and platform design.

    It is built on the evidence that new technologies are enabling alternative ways of interacting with content and new interfaces are evolving the possibilities and expectations of society.