Where do We Go from Here?
Mellyana Frederika for Data Innovation for Policy Makers Conference 2014
The International Conference on Data Innovation for Policy Makers was held on 26-27 November 2014 in Bali, Indonesia. The questions are: Where do we go from here? What kind of data innovation can policy makers pursue to turn opportunities into real solutions?
1. More data accessible to the public
The Government organizes regular data collection from census, surveys and a database of basic services. The data are often buried in the system, managed by a few people with only limited use. It is not unusual to find an organization or individuals being possessive about their data; these data have the potential to become meaningful and insightful. Unfortunately, they often lie dormant on government desks and in private firms.
We need to take the data silo out and create a platform where other organizations, individuals and entities can pick them up, analyze them and have new insights. Data should not be kept secret, but should be available to the public.
The Government of Indonesia recently launched data.id. The website is intended to promote more open government and improve service delivery. It is the first step towards gathering information related to Indonesia in one place. The information is accessible to the public, however it should not end there. The Government should be able to use this data for dialogue and consultation with citizens when making policies.
2. More citizen involvement
Citizens are now playing greater roles in solving social problems; they are changing from being frustrated to proposing solutions. This proves that citizens want to be involved and their active participation can bring about change.
One example is kawalpemilu.org, a crowd-sourcing project initiated by a group of volunteers to monitor official election counting via scanned forms from Indonesia’s Election Commission. Its success is seen as an example of civil society participation in monitoring vote recapitulation.
Another example comes from Varun Banka, the co-founder of socialcops.org, which based its work on the premise that “citizens are the most powerful sensors”. The channels must be opened and nurtured for citizen involvement to become instrumental sensors and empower key decision makers to make data-driven decisions.
3. The need for data ecosystems
There was a lot of talk at the conference about coordination. John Paterson shared the experience of REDD in developing a new model regarding deforestation and forest degradation. This task required an extensive set of data from three different areas, namely sustainable welfare, reduced emission of increased carbon stock and biodiversity. From this need, the idea of Open Map was born, a portal that integrates all government maps and public service competitions on openness. This initiative has enabled collaboration and agreement throughout the Government.
Currently, there is a “one-way street” model for data processing. Data is being sourced from different systems, organizations and in some cases involving different data definitions. What is needed, in regard to the experience above, is a data consortium - a model that provides a data ecosystem.
4. More safe-to-fail experiments
What kind of innovation should governments pursue? Innovation just for the sake of innovation should be avoided. There is an increasing need for better service quality, better ways of working and avoiding doing business-as-usual.
The conference served as a learning event where various ideas to answer these growing needs were shared. Some of them are led by government, others are privately led, and more initiatives are led by communities. There is fertile ground for safe-to-fail experiments. Governments in Scandinavian countries, the United Kingdom and New Zealand are choosing to set up innovation labs and data forums. They are not necessarily operating within the government system but their work is intended to improve service quality and delivery mechanisms. They can also run small pilots and tests before implementing a system more widely, reducing the risk of failure.
There is no exact formula for how these experiments lead to answers. It is about a change of mindset. It is a continued exercise in finding the best way to manifest an idea, test it and adjust it into something tangible, and therefore provide sufficient evidence for policy makers to act.
Topic : data innovation, policy
