When the current Government took charge in May 2014, there was a rush of policies and reforms to be implemented at the ground level. With the slogan "Acche Din Aa Rahe Hai", and a strategy that is completely different from what other cabinets have tried in the past, there is still a long way to go in terms of policy implementation and social change integration.
Data has always been an integral part of bringing about change. It helps analysts figure out the extent up to which policies are effective in doing what they were meant to. But, with the population in a country like ours and limited resources at the ground level - does the data actually make sense? What is the methodology to capture this data? Do analytics on this data get lost in translation? These questions have been looming for long in our system. Going by the definition, Data Inconsistency arises when there are two copies of the same sample, and only one of them has been updated as per the latest records. This results in ambiguities in conclusions and in return may lead to the sample being rendered useless at the end. Such a waste of time and money!
The thing that makes data inconsistency in government records a critical loophole are the people affected by it. Governments conduct surveys and deploy field teams to collate data. For example, before the Delhi Elections, thousands of people were issued Voter-ID cards so that they can take part in the upcoming event. Media reports from ground zero revealed that a single individual was holding multiple Voter-ID cards - at times with the same name at the same address. As per reports, the count of fake ID's was up to 13 lakh! Delhi, being the center of all the action - has pseudo voters electing the Government. Imagine if all these records are set straight, and every individual has his own unique Voter-ID, 13 lakh votes (provided everyone is participating) can definitely change the course of the new government formation. And with the new government, new policies that benefit the people - or don't, are also impacted largely.
Another Example, Point No. 7.7 - "Generating gender based evidence" of the latest draft of National Policy for women accepts the fact that "Data gaps on women's economic, political and social rights remain very large" and states 9 points to tackle this issue. God Speed.
Data has always been an integral part of bringing about change. It helps analysts figure out the extent up to which policies are effective in doing what they were meant to. But, with the population in a country like ours and limited resources at the ground level - does the data actually make sense? What is the methodology to capture this data? Do analytics on this data get lost in translation? These questions have been looming for long in our system. Going by the definition, Data Inconsistency arises when there are two copies of the same sample, and only one of them has been updated as per the latest records. This results in ambiguities in conclusions and in return may lead to the sample being rendered useless at the end. Such a waste of time and money!
The thing that makes data inconsistency in government records a critical loophole are the people affected by it. Governments conduct surveys and deploy field teams to collate data. For example, before the Delhi Elections, thousands of people were issued Voter-ID cards so that they can take part in the upcoming event. Media reports from ground zero revealed that a single individual was holding multiple Voter-ID cards - at times with the same name at the same address. As per reports, the count of fake ID's was up to 13 lakh! Delhi, being the center of all the action - has pseudo voters electing the Government. Imagine if all these records are set straight, and every individual has his own unique Voter-ID, 13 lakh votes (provided everyone is participating) can definitely change the course of the new government formation. And with the new government, new policies that benefit the people - or don't, are also impacted largely.
Another Example, Point No. 7.7 - "Generating gender based evidence" of the latest draft of National Policy for women accepts the fact that "Data gaps on women's economic, political and social rights remain very large" and states 9 points to tackle this issue. God Speed.
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