India is a rich country with diversity in culture, customs, environment and natural resources. Various types of natural resources are available in different geographical parts of India. The way of living, traditions, cultural ritual changes many times if you travel from east to west and north to south. This in principal provides a sustainable ecosystem to the survival of economic and social activities. India as an emerging economy, fastest developing country is facing some challenges due to diversity based on religion, rituals, tradition and natural resources distribution. After independence, some level of uniformity in the policies was adopted which more or less gave fruitful results but time is changing fast. This clearly says that completely uniform policies for economic development and Human development are not relevant and conducive for empowering different regions of the country. Time of the customization based policy formation utilizing scientific and technological analysis is need of the hour. Hence our policy makers, economist, and expert from diverse fields need the target, region based effective and efficient decentralized policies in the economic, social and human development of the nation.
Science and Technology have changed everything and pushing more changes in pipeline fast. We are in a technology-driven world, especially information and communication technology. With the emergence of the information technology coming on the front and information generation and exchange is taking place instantly. ICT, its tools, and approaches are changing our personal interactions as well as public intersection particularly with government and public institutions. This challenges us to utilize the potential of technology in policy implementation and formation domain too. With the emergence of Good governance inspired by information and communication technology is collection large amount of data right now and will continue to do it in future. This gives us the opportunity to harness the knowledge and information available in collected data to develop effective and efficient decentralized policy and monitor their implementation. Big data analytics is new emerging domain which is placing its feet in most of the domains because of its applicability and potential to solve practical problems. Earlier our experts and policy makers were not able to take a different view of the data, knowledge, and information available to them because of constraints of time, speed and lack of tools and were also not able to process large information pool for knowledge discovery as technological tools and expertise were not available at that time. But now those problems should not become hurdles for our experts. With Big Data analytics, Information collection and processing can be very easy which further can be used for formation of effective and efficient policy formulation and implementation if applied in the governance system.
Big data is a term used to define any collection of data sets so large and complex that it becomes difficult to process them using manual or traditional data processing applications. It might be any fields like Computer science, Medical science, Economics, Public Policy and Social sciences where we collect a large pool of data. In the age of internet and information technology, we are generating more data than even before. It may be wrong to say that we are generating data everywhere whatever activity we perform beginning with calling on the phone, going to school, going to workplaces, sharing our locations which create the huge amount of data containing useful information about us. So to extract information from this large pool of data can be useful in public policy formation. Government and experts’ objective is to provide good governance to its citizens. Big data analytics is the process of examining large data sets containing a variety of data types to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful and relevant information. The analytical findings can lead to more effective policymaking for citizens taking all constraints into consideration, new revenue opportunities, better citizen-centric service, improved operational efficiency, competitive advantages and effective implementation of continuous improvement process.
Implications
The environment in which public policy is made has entered into a new period of rapid changes. Widespread use of digital technologies, the Internet, and social media means both citizens and governments leave digital traces that can be harvested to generate big data and then use that to provide good governance for knowledge discovery. Policy-making must take place in an increasingly rich data environment, which poses both promises and threats to policy-makers.
Positive of Big Data and Policy Formation:
Union, State, and local governments can use analytics to relieve traffic congestion, monitor public utilities, evaluate and predict crime, follow education trends, and keep tabs on public resources. Amazon’s patented algorithms, for example, allege to predict shopping habits before orders are placed. Other private companies are also using analytics to create statistical treasure maps in market trends. On the promise side, such data offers a chance for policy-making and implementation to be more citizen-focused, taking account of citizens’ needs, preferences and actual experience of public services, as recorded on social media platforms and institution-centric applications. They generate a whole range of data that government agencies might harvest to good use. Policy-makers also have access to a huge range of data on citizen’s actual behavior as recorded digitally whenever citizens interact with government administration or undertake some act of civic engagement, such as signing a petition. Data mined from social media or administrative operations in this way also provide a range of new data which can enable government agencies to monitor – and improve – their own performance, for example through log usage data of their own electronic presence or transactions recorded on internal information systems, which are increasingly interlinked. And they can use data from social media for self-improvement, by understanding what people are saying about government, and which policies, services or providers are attracting negative opinions and complaints, enabling identification of a failing school, hospital or contractor, for example. They can solicit such data via their own sites, or those of social enterprises. And they can find out what people are concerned about or look for, from the Google Search API or Google trends, which record the search patterns of a huge proportion of internet users.
Negative of Big data in Public Policy:
Big data is technologically challenging for the government, particularly for those governments which have always struggled with large-scale information systems and technology projects because of the diversity and more volume. The Indian government will not face skill shortages and the complex skill sets required for big data analytics which poses a particularly acute challenge for some countries. There are particular cultural barriers to the government in using such approaches with the informal style and blurring of organizational and public-private boundaries which they engender. And gathering data from social media or intuitional systems presents legal challenges. Lack of information technology infrastructure is able posing challenges.
Big data analytics uses in public policy in important for India as it is growing on rapid pace with and need a robust solution in terms of the problem faced due to diversity and other regional imbalances. This convergence of the domain gives potential scope for effective and efficient implementation of the policy. Public policy problems can be solved easily with this concept especially where the government is collecting some data in a structured form which can be utilized for knowledge discovery and to determine the variable which can form the basis of the policy formation. Government of India
Big Data http://en.wikipedia.org/wiki/Big_data
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