How Will Amplifi 2.0 Help Navigate Data Challenges In The World's Largest Democracy?

Apart from aiding policy-making, evidence and data are also insightful in complementing political perspectives and verifying the credibility of facts.

Notably, the establishment of Amplifi 2.0 (Assessment and Monitoring Platform for Liveable, Inclusive and Future-Ready Urban India) last year by the Ministry of Housing and Urban Affairs comes as India’s bid to adopt an Evidence-Based approach. However, to be able to put it to good use, we need to understand where the nation is placed currently and what its shortcomings are, inhibiting it from relying on it.

What is the data landscape in India?

India already has a national data policy in place, but its execution falls short of the policy's expectations. We did manage to put in place an open platform (https://data.gov.in/) however it is not easily understandable, well-visualized, consistent or accessible and provides data in the form of APIs which need other statistical support softwares to run.

Aside from that, the government has not only failed but has purposefully avoided conducting remuneration exercises (Census 2021), most recently objecting to Bihar's SECC. However, they haven't failed to put out the best-sounding initiatives.

Previously, the Ministry ranked cities using data provided by ULBs on four indices: the Ease of Living Index, Municipal Performance Index, Climate Smart Cities Assessment Framework, and Data Maturity Assessment Framework. The government also intends to release different reports on subsets of the four indices. The government then decided to move from indices to raw data sets.

In December 2023, in light of the Urban Outcomes Framework 2022 report drafted by the National Institute of Urban Affairs and Ernst and Young, the Ministry of Housing and Urban Affairs established Amplifi 2.0 (Assessment and Monitoring Platform for Liveable, Inclusive and Future-Ready Urban India), which is a data aggregation platform that brings together data sets from 14 sectors.

The data sets are collated from areas of Demography, Economy, Education, Energy, Finance, Environment, Governance & ICT, Health, Housing, Mobility, Planning, Safety and Security, Solid Waste Management, Water and Sanitation.

The platform holds massive potential and could help in solving all of India's urban policy problems. However, first, some obstacles need to be addressed.

What could be the challenges?

The first question is how a state agency would use physical or social infrastructure data in the absence of a Census survey. How odd is it to know how many schools or jobs exist but have no idea who will occupy them?

Let's go one level up. How can one construct a national-level data portal without first assessing capacity? Capacity for collecting, cleansing, and creating data. The second stage consists of standardization, followed by visualization. All three levels appear significantly different from town to town, let alone at the state level. Thinking at various scales about this seems to be absent in the current context.

India is already on the verge of reaching 8000 towns. Amplifi 2.0 planned to list 4000 cities on the portal. However, they were only able to include approximately 257 towns out of which data for only about 150 is currently on the platform. Anomalies in terms of category coverage, missing data, incomplete timeframes, and so on exist. Furthermore, in most cases, it only covers fiscal years 2018-19, although a comparable analysis should encompass years prior and subsequent to that.

Aside from the complexities of data quality and completeness, a variety of considerations come into play, with data governance taking the lead. Despite the fact that a policy exists, it is critical to ensure adequate access and usage requirements, particularly when dealing with third-party agencies.

The dynamics of data security and periodic regulatory modifications will have a big impact on the whole scenario. Finally, workforce proficiency gained through sufficient training appears as a critical pillar for the portal's long-term success.

The Way Forward

The European Union has commissioned a visionary project called the ‘open data portals’. Open data portals are an important element of most open data initiatives and are mainly used by public administrations at European, national, and local levels in EU countries. Notable examples of Open Data portals maintained by public administrations in Europe are opendata.paris.fr; www.data.gouv.fr and www.dati.gov.it.

One of the biggest advantages of the Western economies is their seamless collection, availability and use of data systems that developing countries lack; however, that is not a lost hope. Evidence-Based policy can have an even greater influence in developing countries because it is less well established there than in wealthy countries, allowing for more flexibility. Better evidence-based policy and practice can help save lives, decrease poverty, and improve development performance in developing nations.

For example, the Tanzanian government undertook health service improvements based on household disease survey results, which resulted in nearly 40% reductions in newborn mortality between 2000 and 2003 in two trial areas.

On the other side, the HIV/AIDS pandemic has worsened in several countries as governments have ignored evidence on what causes the disease and how to prevent it from spreading.

What India Could Do?

What India could prioritize is to concentrate on improving statistics on not only large urban regions, but also relatively smaller urban areas and backward areas, to examine health, housing, and economic indicators on a regular basis. Only then can we put this portal to good use. The pandemic already highlighted our failing health, housing, and labor markets, which should have been cause for worry, particularly for low-income migrants seeking better lives in cities. This in itself should be alarming enough.

A top-down national data portal is a myth. It is just not possible under the lower levels of collection, consistency, and standardisation put in place. Data needs to be verifiable as well as comparable and can't be thrown around in such a banal fashion that looks grand but does no good to our policies.