News & Analysis

The Perils of Poor Data Collection Processes for Business

By: Ashwani Rawat

Crucial for government and institutions, data helps in the accurate planning, funding and evaluation of developmental activities. Factually speaking, basic development indicators are important for painting an accurate picture of a country’s developmental status – this could include a country’s progress towards a specific development goal or even improving the socio-economic conditions of its citizens. The need for good quality data is so pressing that solutions to social and economic problems are often inseparable from the statistics.

The many challenges of data collection

Data collection in India has always had its challenges, issues like conducting pen and paper service with no time stamping, no spatial context or no media files collection means that the quality of data that is collected is not at par. For example, one cannot be building schools without understanding how many children need to be enrolled there.

When we talk about developmental programs that affect the common man, we are talking about measurable results. Decisions regarding development need to be informed by data, and what is even more important is that the collected data should be turned into information that is easily understandable and also useful for the end-users. Poor data collection means that you do not have access to a smart, objective analysis that can study the data and be able to derive informative results out of it. Only if you have access to good quality data, then can you expect decision-makers of all levels to look at relevant information and be able to lay the foundation for policy-making and budgeting that can help the nation.

One can take a look at data on health and demographics in India that is marred by incomplete information, overestimation and even instances of under or over-reporting that can lead to problems in policy planning. Lack of compatibility and poor usability of national-level data sources, disparities between system and service level estimates, increasing length of questionnaires and even questions that are included on socially restricted conversation topics end of resulting in poor data quality. If you look at the sector, incomplete and unavailable disaggregated data on cause of mortality, affects the generation of any sort of estimates that means that there is a lack of evidence which ends up hampering the setting up of any priorities in the healthcare sector, which ultimately affects the common man adversely.

Technology to improve data collection

Technologies such as mobile, AI and analytics can be leveraged in order to improve data collection systems. Data collection agencies are already making great headway in the use of apps and tools to conduct surveys electronically. One major concern that needs to be addressed is how data collection technology needs to be made simpler along with appropriate training being conducted so that anyone can use it. For example, smartphones can be used to conduct surveys that can give instant answers, allowing for smarter data collection at a large scale. Designed to make it easier for people to adopt technology, with the help of smartphones agencies can download and check surveys in real-time and even perform on-the-fly analysis.

Given that there are risks of developing misguided policy responses due to poor data collection, focusing on higher investment in technological support that is regularly monitored during data collection along with more functional clarity during training can help in addressing some of the anthropometric data quality issues that arise when conducting survey sat a large scale.

Time for a change

Data is invaluable since it possesses the power of being able to bring about a transformation in the economic, political as well as social processes of a nation. It is an undeniable fact that inadequate data collection will directly result in poor planning and maintenance of public infrastructure as well as the provision of public services, especially to the common man.

Since all policies rely on official statistics when it comes to design and implementation, it is imperative that the statistics are regularly updated in order to account for the changes that occur in the society and economy periodically. If government agencies are unable to collect data in the right manner, irrespective of whatever the reason might be – policymakers will end up having to work without any source of credible information. Any sort of data sharing practices that are sub-optimal, end up reinforcing fragmentation in governance which ultimately raises challenges for public service provision due to lack of transparency and accountability.

Ultimately along with improving the quality of data, it is really important that there exists collaboration and clear communication between users, government as well as residence in order to improve methods of data collection as well as day sharing, storage and organisation. With the help of technology, and intermediaries we can bring about a change in data standards, formats, technology, tools and methodologies that would ultimately help in better data collection processes.

(The author is Co-Founder & Director, Transerve Technologies Pvt. Ltd. and the views expressed in the article are his own)

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