Jokowi seems to believe that big data is key to improve government’s effectiveness and efficiency. Some of his ministers have experimented, to some extent, with the use of big data such as the Finance Ministry in tax intensification and the Education and Culture Ministry in school registry management. His recent presidential campaign was also colored with the story of how big data helped him win the election.

Beyond the magic and myth, what actually is big data? Big data is commonly accepted as a data set so large, that it forces us to look beyond traditional means of processing and storing data. Moreover, the term big data encompasses not only data volume, but also its speed (velocity), diversity (variety), and quality (veracity). The advent of big data enables humans as the user to look beyond static data and the use of big data has started to be integrated into various walks of life.

Although of high relevance, big data remains an under-addressed topic in politics. Currently the use of technology is limited to complementing existing organizational or administrative practices such as digitizing analog data or to allow remote registration of public services, rather than creating an entirely new value stream from the availability of the new technology. The use of big data as a core component in public policy process remains at large.

Traditionally, the policy cycle would consist of several consequential steps required to create, assess, and implement policies. The cycle begins with agenda setting, policy discussion, formulating policy, followed by budgetary preparations. It then moves to the implementations and provision evaluations; to see whether the means are enough to deliver the performance expected. Only after the policy has been implemented, an outcome evaluation will be conducted to assess the policy success. This last step is usually unresponsive to public opinion or outside expertise.

Previously, there was no means to accurately calculate the possibilities of breakout or failures in the policy actions. But it doesn’t have to be that way. The government as an entity has traditionally managed large amounts of data such as civil administrative data or tax data. With the recent availability of new types of data and analytical techniques, the government can process real-time data and allow the feedback cycle to be integrated into each step of the policy-making cycle.

To make this happen, government entities need to build on their existing large data-sets as well as finding access to new datasets. Moreover, they are also required to improve their institutional capabilities in providing the talent as well as the legal umbrella necessary. After all, the success of a big data initiative is determined by how much insights are gained from the data and not just the big size of the data. To build that meaningful prescriptive analysis requires a deep talent pool, which government agencies are struggling to hire most of the time.

This is where there is a big room to create a partnership for technology transfer between the public and private sector. A solid partnership could help the public sector tap into private companies’ professional talent and pace, as well as a complementary huge dataset that comes from these companies.

One of the successful study cases of this public-private-partnership is the case of Jakarta Smart City and Qlue, a private company that provides citizen reporting apps in Jakarta, in collecting urban problem data to help better budgetary planning. In the past, the Public Discussion for Budgetary Planning forums (Musrenbang) were quite an inefficient process. This is because the meeting was conducted on a set timeline in which citizens were required to be present, barring many working citizens from access to voice out their concerns. The process was heavily skewed  to those who had a major interest, and since the data parameter is very limited, the sum of the budget allocated is heavily correlated with the size of a district. This is problematic as some districts in Jakarta, while small in size, hold more  problems such as regular flooding, unsafe urban slums, and poor waste management.

Qlue is collecting reports on problem in the neighborhood to become a new dataset that complements the existing data of demographic, geographic, existing budgetary requests, and past disbursement. By having a map of problems reported by citizens, the budget allocation in the Musrenbang could be seen from a clearer snapshot of the problem’s root cause in the district. As a result, the budget allocated for neighborhood development in Jakarta has now become more efficient and helps to solve citizen’s concern more accurately.

The aforementioned regulation on one data is the first milestone towards better utilization of big data. However, information on itself is not power. Information could only become power under the rigorous actions to execute by all stakeholders involved and to ensure proper implementation, a strong and data literate leadership with a clear vision is needed within the government body.

The public sectors need leaders that are brave enough to push data-literacy agenda at the helm. Big data implementation could only work if it’s integrated into government performance metrics. Without real stakes in place, information derived from big data will not result in better policy decision.

At the end of the day, utilizing big data is about how to improve efficiency and effectiveness of policy by empowering the government to produce an informed policy which is beneficial for the citizen and can be analyzed in a real-time basis. It can equip the government to make quick decisions without compromising the decisions’ quality.

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The writer is a corporate strategist at Qlue Indonesia. His interests include public affairs, impact investing, big data, and sustainable development initiatives. Check out his portfolio (http://gjdavy.weebly.com/blog) or connect with him on LinkedIn (https://www.linkedin.com/in/gjdavy) for partnership or consultancy opportunities. 

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