Governance, Data, And Technology
In the last few decades, we have seen how different fields of knowledge can be integrated for the betterment of the human kind. Financed has fused in with psychology to form Behavioural Finance, economics has integrated with mathematics to form Econometrics and so on. Till now these fusions has helped us to resolve the problems of the world which were previously considered as unresolvable.
Similarly, another combination is on the rise these days, which potentially can change the way in which the world operates. This is the fusion of Governance, Data, And Technology.
The primary objective of any government is the betterment of its people.
In order to do that, the government comes up with different schemes and programs.
But the major drawback of these schemes and programs is that they are not able to reach the people who are really in need of the benefits of these schemes.
India is such a diversified country that the needs and requirements of the people differ from block to block. The concept which was used till now was that the government used to observe the needs of the people via field officials, who used to input the data of a relatively large geographical area to the government, the government formulated programs in accordance with the data provided and then implemented it uniformly in all places. But the major drawback of this technique is that the intensity of the needs of different places is not uniform, which cannot be observed from the traditional method via which field officials record the data. This results in the false implementation of the schemes at different places.
So, a good intentional scheme goes vain just because of the failure of the allocation of the scheme.
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This indicates that there is clearly an immediate need for a system which provides data inclusive of the granule level to the government to work upon.
So, How could this be achieved?
The answer to the question lies in a single word “DATA”
A simplified and classified data, driven by technology is the need of the hour.
The data-driven program making is not limited only to the formulation of a scheme, it also plays an important role in the implementation of the scheme. Since this data-driven governance works in real time, the flaws and the problems in the implementation of the schemes can be identified in real time, and instant attention could be given to them. Digitizing data is basically one step closer to minimize data duplication and redundancy for a better decision-making.
With digitalization on the rise, data-driven governance has also got a boost, now all the process, from the identification of needs of the people, to the allocation of the beneficiaries, to structuring the plan, to the implementation of the plan can be done with the help of a mobile phone or a computer and the most amazing part is that the schemes which would take 1–2 years just to formulate can now be planned and implemented within few weeks or months and that too with almost 100% accuracy. Now schemes can be formed and implemented by keeping each and every household in mind.
Nowadays, the Government of India is collaborating with private organizations like Social Cops and Tata Trust to collect and analyze data, eventually leading to the formulation of effective schemes and programs, which can be implemented and tracked in systematic and justified manner.
The biggest example of it is the Pradhan Mantri Ujjwala Yojna, where the Government of India collaborated with Social Cops to provide LPG gas connections to about 50 million below poverty line women using the data and technology in a systematic and effective way. In the last 11 months, about 20 million women have been provided with the LPG connections under this scheme and 10,000 LPG centers has been set up in accordance with the data collected and analyzed.
Data was present earlier also but was either incomplete, biased or based on a small sample. But now, with the intervention of technology with Data, it is now possible to collect, Access, transform and visualize data from a granule level to a large scale and with almost 100% of accuracy and reliability.
