Reflections

Posted 26 May, 2015 by Anneke Victorica

Sparking projects with Matchbox: our learnings from partner selection to matchmaking

Representation of the work of the Research and Advocacy Unit. Credit:   Maya Richman

Representation of the work of the Research and Advocacy Unit. Credit: Maya Richman

Since we launched in October of last year, a lot has happened at the engine room’s Matchbox Program. We’ve provided in-depth support to six organizations and light-touch support to 29 organizations. We don’t want to just do the work: we want to learn and share how (and if) this demand-driven model of support works. In this blog post, we are sharing a few of the things we have tackled since October and what we’ve learned along the way.

The engine room’s Matchbox is a pilot for what is surprisingly a pretty novel concept: providing organizations with strategic and tech support that is based on their unique needs. We meet great transparency and accountability projects, match them with the diverse expertise they need to get their innovative ideas off the ground, and learn critical strategic approaches in the process.

Our work is led by the Matchbox regional coordinators (Lesedi and Ela) and their support goes a bit like this:

  1. assess and discuss strategic and tech needs
  2. propose possible strategic and tech solutions
  3. look for (pro bono) technologists
  4. source the support from within the engine room team, when necessary
  5. help partners find and request funding, when necessary

What we’ve learned so far

Partner selection: We developed criteria for finding projects that we thought would be the best fit for Matchbox. Criteria include clearly defined goals and the ability to talk thoughtfully about successes as well as failures. However, we realized that successful collaboration usually involved partners who:

  • are excited about trying new things
  • truly enjoy collaborating
  • have at least some experience working on projects with a technical or data component.

We continue to go back to our criteria and refine as we learn from each round of partners. The goal is to have objective criteria that we can use to ground any assumptions we make throughout the selection and partnership process.

Finding peer projects: As special as our partners’ projects are, there are usually projects somewhere in the world that can provide insight, guidance, and cautionary tales for newly forming ideas. Existing technology development can also often be customized or evolved to meet the needs of even the most innovative project. To provide our partners with a head-start, we used networks and desk research to find and share similar tools. Connecting these organizations to existing tools and projects sparked new relationships and new ideas. In a couple of cases, we found existing tools that projects could adapt instead of building something from scratch. Whether it was Pybossa for microtasking management or FrontlineSMS for contact management and SMS polling, there are usually tools that fit exact needs. We even discovered brand new (to us) tools, like Artificial Intelligence for Disaster Response (AIDR) and Improving Quality of Urban Water Service by Engaging SMS Technology (IQUEST) that hold a lot of technical possibilities for several partner projects.

Setting expectations: We didn’t want our work with partners to be stuffy or rigid, but we also wanted to set clear expectations. So, we drafted memos of understanding (MOUs) to make sure everyone knew what was expected from them, and more importantly, what they could expect from us. These MOUs also ended up being a useful tool for grounding conversations around what was feasible, and to keep innovations focused on real-world goals rather than innovation for innovation’s sake.

Keepin’ it movin’: A couple of activities have stood out as great opportunities for clarifying strategy and goals. Those activities have been wireframing and data models – which are are also foundations of any great technology project. By developing wireframes, decisions can get made and priorities established in a way that keeps the ball rolling. Developing a data model compels a project to define its scope and reality-check whether an organisation has the resources for a more ambitious project.

Playing matchmaker: We were very lucky to have built relationships with awesome people at Muzinda Hub, HURIDOCS, Frontline SMS, MySociety, Code for Africa, National Resource Governance Institute and School of Data (among many others). It often took some time to find an expert whose objectives and skills aligned with those of a project, but the results really paid off. We had to make a conscious effort to avoid knocking on an engine room team member’s virtual door every time a project required a skillset we had in-house. Resisting this temptation has paid off: our partners’ networks now extend much further into the international technology and data community than they otherwise would, and the expertise we have been able to secure has been extremely specialized.

Sustainability: Sometimes building the perfect tool isn’t an option. We learned that you can never have too frank a discussion about the resources an organization will need to launch a tool and maintain it. We’ve already been successful at getting an organization funding for building a prototype, but we also expect to have more and more conversations with organizations to prevent them from underestimating the time and in-house expertise required for sustaining projects. The launch of a website is never the end of the project, and it is often the beginning.

We’d like to hear from you – do these lessons resonate with you? Or have you learned different lessons in your matchmaking efforts? Please share your experiences in the comment section below.

We’re grateful for all the pro bono support our colleagues have provided through the Matchbox program, and for our passionate and dedicated Matchbox partners – thank you!

1 thought on “Sparking projects with Matchbox: our learnings from partner selection to matchmaking”

[…] Sparking projects with Matchbox: our learnings from partner selection to matchmaking. The engine room reflects on matching tech expertise to the needs of transparency and accountability organisations. […]

Leave a Reply

Your email address will not be published.

Related articles