Expert-Driven Innovation

Organization invites and facilitates intentional collaboration among carefully chosen group of experts and non-traditional partners who have the deep vertical knowledge on the domain (or parallel domains) to come up with a solution to reframe, imagine, or combine different perspectives in new ways. This model is effective in generating desired solutions at any stage of development through collaboration of relevant experts in a variety of fields, in a relatively short period of time. Experts can play diverse roles throughout the design and implementation of program initiatives to inspire innovative thinking. In this model, funders play a vital role in curating experts from wide ranging fields to collaborate who would not cross paths otherwise to develop a desired outcome, and choosing the right moment to utilize the method.

Tailor-made expert team

In social innovation challenges, there may be no existing experts, or known experts may not be able to provide new perspectives. Carefully curated expert teams can overcome such barriers effectively, with appropriate facilitation.

Funder as: Curator & Partner

You identify and invite the most relevant experts in the process at the right time, providing the right problem to solve, hoping to unlock nontraditional solutions and partnerships that have been proven in other spheres


Methods at a Glance

When it's best to use
When it goes well
When it goes wrong


provide a collaborative platform for invited experts to look into the root causes of a problem and come up with solutions accordingly.

  • Your problem is clearly defined but there are no known solutions yet.
  • You want to raise the awareness of the issue to the broader audience.

  • Incentivizes participation by people whose time and effort has a high opportunity cost.
  • Yields a great number of ideas that are mature enough to be developed

  • Fails to engage the right participants or receive enough number of entries
  • Quality of entries falls short of expectation.


employ various research & analytic techniques to better understand the parameters of the problem space under a set of initial hypotheses.

  • Your challenge has a clearly defined set of hypotheses.
  • You have access to environments for live experiments with control groups.

  • The ability to surface "behavioral bottlenecks" more quickly
  • The design or adaptation of interventions to better respond to realities on the ground.
  • The ability to reveal counter-intuitive insights that traditional qualitative research would fail to uncover
  • Strengthens the sustainability of an intervention because it's based on scientifically / rigorously tested findings about how people will actually respond or behave.

  • When the initial hypotheses are not set on the credible data and assumptions, the method cannot produce desired outcomes.


A system map provides the jumping off point for fresh thinking about relationships, resources and connections that might inspire innovative approaches to system change.

  • Your problem requires specific technical skills to come up with plausible solutions.
  • You want to engage the broad network of people with relevant technical skills to become interested in the issue.

  • You get concrete, feasible solutions that are mature enough in a short time frame to get investment for further refinement.
  • You promote the topic in the community that can contribute to solution development later.

  • No remarkable outcome to take forward
  • Low enthusiasm among participants due to lack of motivation


brings together experts from a wide range of fields to develop a series of stories that describe different but plausible futures that might require innovative approaches.

  • You would benefit from simultaneous input from a large number of users to understand problems they are facing and opportunities to innovate which might not be obvious from the outside
  • You can set up a platform that users can reach independently

  • You get a different perspective on the issue with the vast amount of data that you could not get hands on otherwise, e.g., disaster situation
  • May highlight structures that are invisible to external organizations

  • Derives biased outcomes due to the limited participation
  • Produces controversial outcome but it’s difficult to verify data