From the Archive

Why Is Collaboration Hard? How Can Data Help?!

umbrellas - collaborating in the rain at Seoul city HallOf course, bumping into something counterintuitive in your work (particularly in the realm of what seems mundane), expands the range of solutions, if only by clearing new paths of thought. A welcome serendipity. But, in confronting systemic or intractable problems, active awareness for unexpected or neglected ways to solve them is part of the job. In this post, Jon Hugget takes that approach to the topic  of collaboration – with 6 Simple Rules. [Image: Umbrellas, painted by children, “collaborating” at Seoul city hall, ejh 2013]

We all want to collaborate for good: the world is facing bigger and more complex problems; organizations are becoming smaller and more varied; and innovations happen out there as well as in the lab. But collaborating for the common good can feel harder than in regular business, even among competitors.  We all have war stories, and frustrations to share, which is why this blog is here, and probably why you are reading it. From what I’ve seen as Chair of the Social Innovation Exchange, successful collaborators act on six simple rules. At first, these struck me as counterintuitive. But I’ve learned that each tightens collaboration with facts and data.

1) Share hard goals, not values!

Working together for a shared concrete goal can attract a diverse coalition with the range of skills needed to win. Consider how ACT UP and AIDS activists collaborated with GSK and big pharma to change how new drugs were approved. People with HIV were told that they had a year or two to live. Drug companies had life-saving medicines in a five to ten years approval queue. Together they persuaded the FDA to change its rules. A flood of new treatments arrived. Many lives were saved. The collaboration worked because of a shared goal, not shared values. At the start, and even at the end, the two groups disagreed on different values: progressive vs. conservative. Discussing “shared values” can push us apart and sow discord. Nobody likes their integrity to be questioned. Vague discussions of “responsibility” and “sustainability” can hide real issues. Collaborating across sectors means working with people with different values. Collaborators often often bring different time, talent and treasure. Hard goals help find common cause as we look at the facts and the data.

2) Measure for improving, not proving!

Measures for improving are simple and useful for front-line workers or “beneficiaries.” Innovation needs trial and error, feedback, and learning from the errors. Sharing measures can build trust. Facts are friendly. Opinions are strong when facts are scarce. However, we often we see the “gold standard” of “evidence” as a robust, controlled, academic, longitudinal research study. There is a place for “proving”: Sesame Workshop, Big Brothers Big Sisters and Nurse Family Partnership have each won support for scaling by proving how effective they are. But humanitarian NGOs have often found simple measures to improve disaster response can also tighten trust. Simple measures are easy to share transparently, for example through Project Oracle in London or Strive in Cincinnati. Consider the network Habitat For Humanity which counted “houses built”, a concrete measure. It switched to “families housed”, a lighter metric, which helped share renovation innovations between Bombay (with little space to build new homes) and the US (with a surplus of houses). The network shared more through a new way of looking at the data.

3) Choose the change, not who is in charge!

Collaborating for good attracts leaders. Great collaborations are leader-rich. Collaborations of great leaders looks more like a jazz band than a symphony orchestra. In a jazz band, the lead can shift from piece to piece. The great “band leaders” like Duke Ellington brought together great musicians who improvised and improved on the run. Symphony requires a conductor, a score, and loyalty to both from the orchestra. Jazz, with improvisation, elicits much more from immediate feedback from live audiences – the data of their appreciation, or not. Data feeds leader-rich collaboration.

4) Share credit for successful ideas, not put the “genius” on a pedestal!

Swarm intelligence drives the best collaborations I’ve seen. All people and all parties help improve. Everyone shares credit for the big idea, because their ideas are embedded in the big idea. The data can be about the smart things (done by good people) rather than smart people (doing good things). Wikipedia is written by hundreds of thousands of volunteers, each making a unique contribution, each owning the idea. Success has many fathers; its failure that’s the bastard.

5) Spread ideas, not organizations!

Sometimes scaling impact needs a global organization, like Wikipedia. Sometimes its better to scale with local organizations, like the YMCA. Dan Berelowitz has created the International Centre for Social Franchising; franchising helps local enterprises when some functions needs economies of scale, such as in  branding or purchasing. The School for Social Entrepreneurs is a social franchise which has spread itself  from London to Australia, and its ideas all over. ICSF helping social franchising by sharing the stories,  wisdom, and data.

6) Embrace competition, not stop it!

Great competitors are usually great collaborators. Both focus on results, keep trying to improve, and  embrace change. Both eat data for breakfast. Goodstart is a collaboration of competitive business and social sector types in Australia. It bought a failing for-profit chain of child-care centers to turn it a nonprofit network of early-learning centres helping disadvantaged kids. Collaboration without hard data can be unpleasantly political. Competitiveness can turn to power struggles, and “holier than thou” judgments, which corrode trust. Better to pick a hard goal that brings everyone together, and stick with the data.

I’ve learnt all of this the hard way. I’ve had lots of discussions about “values,”hard  evidence,”governance,”IP,”scaling” and being “non-competitive.” I’ve had more luck when we’ve agreed a goal and got on with it.