How does change happen? . . . in local communities, in businesses, in non-governmental organisations or even in global networks the issues are the same. At the heart of them is communication, shared knowledge and shared understanding.
I’ve worked with large and small organisations, in community and corporate situations, and I have a body of experience in how communications can help people work together, and in how new digital media can be a valuable part of this process. The locations and applications are diverse – from global PLCs to disaster-affected villages; but the principles are surprisingly similar.
I work with groups who really want to make a difference. You will find case studies and illustrations on this site - as well as resources which reflect the fact that I am also researching more effective use of communications in communities to achieve change.
Theory into Practice: Building a network and galvanising a global team to reduce the global impact of disasters
I work full time with The Global Network for Disaster Reduction (www.globalnetwork-dr.org). Over 500 participating organisations in 70 countries collaborate in this action network. Our main programme to date has been the 'Views from the Frontline' collaboration to produce a community level perspective and report on the realities of Disaster Reduction at the 'frontline' where billions of people live, work, and contend with natural disasters - many of them climate change driven. Over 20,000 respondents contributed to our last report in a unique community level research programme.
It has made a major impact on the UN's own ten-year programme on disaster reduction. Margareta Wahlstrom, the UN's special adviser for disaster reduction, said:-
“Views from the Frontline shifted the agenda at GP-DRR 2009 (the UN biennial conference on Disaster Reduction) towards a focus on execution of the Hyogo Framework (The UN ten-year programme) at the local level”
On this site you'll find information ranging from papers and reports to my recently completed doctoral thesis based on learning from the network.