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FORUM ON
17
th
November 2023 | Lucknow
“Leveraging State Data
Ecosystems for State and District
Level Policy and Planning” Disclaimer: The report titled “Forum on Leveraging State Data Ecosystems for State and District Level Policy and Planning” is an outcome
report of the proceedings and discussion held during the workshop on November 17, 2023 in Lucknow. The views expressed in this report
are strictly those of the presenters and do not necessarily reflect the views of NITI Aayog or the World Bank; nor do they guarantee the
accuracy of the information provided. NITI Aayog and the World Bank do not accept responsibility for any consequences of using this data.
NITI Aayog disclaims any legal liability for the accuracy or inferences drawn from the material contained in this document, or for any
consequences arising from the use of this material. Reproducing any part of this report, whether by electronic or mechanical means, is
strictly prohibited without prior permission from or intimation to NITI Aayog. Users are encouraged to seek permission for reproduction
through official channels to avoid any legal implications. Leveraging State Data Ecosystems for State and District Level Policy and Planning Foreword��i
Preface��iii
Acknowledgement��iv
Abbreviation and Acronyms ��v
Executive Summary��viii
Introduction��xiii
INAUGURAL SESSION��1
Keynote Address (Suman Bery, Vice Chairman (VC), NITI Aayog)��3
Inaugural Address (Durga Shanker Mishra, Chief Secretary (CS), Uttar Pradesh (UP))��4
SESSION 1: GETTING THE ENABLING ENVIRONMENT RIGHT��7
Opening Remarks (Rajeeva Laxman Karandikar, Director of Chennai
Mathematical Institute)��8
Building Blocks for Data Governance (Abhishek Singh, Additional Secretary, MeitY)��11
Frontiers of Data-Driven Decision Support Systems (Paul Cheung, Former Chief
Statistician of Singapore and Director of the United Nations Statistics Division)��13
Data Governance Architecture (Pravin Srivastava, Chairman of the Madhya Pradesh
State Statistical Commission)��15
Open Data Telangana (Dayanandam, Director, Government of Telengana)�� 17
SESSION 2: TRANSFORMING DATA INTO KNOWLEDGE
ACHIEVING THE INDIA@2047 VISION��19
Opening Remarks (Thomas Danielewitz, Senior Economist/Statistician for World Bank
Poverty and Equity Global Practice in the South-Asia Region) ��20
Towards District GDP: Leveraging (Regional) Business Statistics for State and District
Level Policy and Planning (Arthur Giesberts, Statistician/Economist at the World Bank’s
Development Data Group)��22
TABLE OF CONTENTS Leveraging State Data Ecosystems for State and District Level Policy and Planning District Domestic Product Estimation (K. V. Raju, Professor Emeritus at
Chanakya University, Bengaluru, India)��24
Harmonization of Data: Integrating Survey and Non-Survey Data Sources for Faster,
More Accurate Insights into District Growth (Pallavi Choudhuri, Senior Fellow at the
NCAER-National Data Innovation Center)��26
Supporting Districts as a Fulcrum of Growth (Surendra Kumar, Joint Secretary,
Department of Commerce, Ministry of Commerce & Industries)��28
SESSION 3: TRANSFORMING DATA INTO KNOWLEDGE:
PRO-ACTIVE AND PRE-EMPTIVE GOVERANCE ��31
Opening remarks (Prof. Avik Sarkar, Professor, Indian School of Business��32
Using GIS Data to Improve Service Delivery (Ashok Kumar Joshi, Director of
Maharashtra Remote Sensing Applications Centre (MRSAC), Nagpur)��34
Data analytics for Localising and Upscaling Implementation of SDGs
(Bhawana Vashishtha, IAS, Andhra Pradesh)��36
Using Data to Improve Targeting of Schemes and Public Services – DBT 2.0
and 3.0 (Saurabh Kumar Tiwari, Joint Secretary, DBT Mission, Cabinet Secretariat)��38
SESSION 4: EXPERIMENTS ON DATA DISSEMINATION & PROMOTING ANALYTICS��41
Opening remarks (D Tripati Rao, Professor of Economics (HAG), IIM Lucknow)��42
Overview of NDAP 2.0: Towards Enabling Data Analytics (Anna Roy, Principal
Economic Adviser, Government of India)��45
City Data Analytics Platform (CDAP) 2.0: City-Level Data (Anand Iyer, Chief Policy
& Insights Officer at Janaagraha)��47
Gender Portal on NDAP 2.0 (Yamini Atmavilas, President, The Udaiti Foundation)��49
International Experience in Data Dissemination (Malarvizhi Veerappan, Program
Manager and Senior Data Scientist at the World Bank�� 51
Importance of Feedback Using Service Delivery Data & CM Dashboard
(Nand Kumaram, Deputy Director, LBSNAA)��53
Data for Development (Deeksha Supyaal Bisht, Deputy Director, Dept. of
Economic Affairs, Government of India)��55
Recommendations And Way Forward��58 Leveraging State Data Ecosystems for State and District Level Policy and Planning i
FOREWORD
In an increasingly interconnected world, data has become the cornerstone of informed decision-
making. It is the fuel that propels effective planning and policy making, which enables policy makers,
investors, researchers, and citizens to navigate complex challenges with precision and foresight.
Whether in the realm of health care, education, economics, or environmental sustainability, the
importance of reliable, comprehensive, and timely data cannot be overstated.
India has been a front-runner in digital transformation over the last decade. Around 1.3 billion
people have been registered on Aadhaar, which has become ubiquitous in government-citizen,
and increasingly in private sector interactions as well. Over 15 million micro, small, and medium
sized enterprises (MSMEs) have been registered on the MSME Portal, UDYAM. A similar number of
firms are registered as GST taxpayers. Hundreds of government services are now offered online
through digital one-stop shops. This has unleashed digital data flows with an enormous potential
for governance.
A key advantage of digitization is its ability to enhance the planning of process efficiency. With
real-time data at their fingertips, policy makers can respond swiftly to emerging trends and
challenges, ensuring that plans remain dynamic and adaptable. This is critical in order for India
to achieve its goal of becoming a $30 trillion economy by 2047. Moreover, data accessibility
empowers policy makers to tailor their strategies to the specific needs of communities, paving
the way for more targeted and impactful interventions at the local level. Districts have rightly
been identified as critical administrative units for accelerating development. More localized data
products and services for subnational and sub-state planning have now become possible as a
result of India’s data revolution.
Integrating digital technologies also enables an inclusive and participatory approach to policy
making. Citizen engagement and feedback, facilitated by digital platforms, creates a more
democratic and transparent decision-making process. Good governance is no longer just about
efficient delivery services to citizens; it is also about actively involving them in the process, and
ensuring that their diverse perspectives can help to shape government solutions. Leveraging State Data Ecosystems for State and District Level Policy and Planning ii
The synergy of data, digitization, and technology unlocks new avenues for innovation and
economic growth. Industries are being revolutionized, and new possibilities are emerging in fields
such as artificial intelligence, machine learning, and predictive analytics. These advancements can
streamline processes and create new opportunities for entrepreneurship and job creation.
On November 17, 2023, NITI Aayog, in partnership with the government of Uttar Pradesh, and with
the support of the World Bank, convened a forum on Leveraging State Data Ecosystems for State
and District-Level Policy and Planning. Around 100 representatives from central ministries and
state governments participated.
The Forum served as a platform for peer-to-peer knowledge exchange between policy makers, data
scientists, statisticians, and technologists at various levels of government. Several presentations
showcased India’s progress on digitization and data-driven governance, including many high-
impact use cases. This report includes all of the presentations shared at the Forum, as well as
an Executive Summary of the discussions. We hope that it will be a useful resource for those
interested in learning more about the current status and future plans for data digitization in India.
Suman BeryAuguste Tano Kouame
Vice Chairman Country Director India
NITI AayogWorld Bank Leveraging State Data Ecosystems for State and District Level Policy and Planning iii Leveraging State Data Ecosystems for State and District Level Policy and Planning iv
ACKNOWLEDGEMENT
The Data Forum on “Leveraging State Data Ecosystems for State and District Level Policy and
Planning” was organized under the overall guidance of Suman K. Bery, Vice Chairperson, NITI Aayog,
and Durga Shanker Mishra, Chief Secretary, Government of Uttar Pradesh. Collaboration with the
World Bank as the knowledge partner has enriched this workshop’s discussion and deliberation. In
developing this report, Thomas Danielewitz, Senior Economist, World Bank, Malarvizhi Veerappan,
World Bank, Program Manager, Development Economics, World Bank; Shreya Dutt Mishra, Data
Systems Specialist, Poverty and Equity Global Practice, World Bank; and Liankhankhup Guite,
Assistant Director, NITI Aayog, made valuable contributions. The drafting of this report by Avik
Sarkar and Sonia Chauhan, from the Indian School of Business, is also acknowledged.
This workshop could not have been organized without funding and valuable support from the State
Support Mission of NITI Aayog. We are also grateful to Durga Shanker Mishra, Chief Secretary, and
Alok Kumar, Principal Secretary of Planning, of the Government of Uttar Pradesh, for their support
in hosting this workshop in Lucknow, Uttar Pradesh.
The presentations by and interaction with the central ministries and state governments, as well as
those with academics, have brought forth interesting insights and stimulated valuable discussions
on the frontier data ecosystem of the country. We acknowledge the participation of the Ministry
of Finance; Department for Promotion of Industry and Internal Trade; Ministry of Electronics and
IT; Direct Benefit Transfer Mission; Maharashtra Remote Sensing Applications Centre; Lal Bahadur
Shastri National Academy of Administration; and the National Statistical Commission.
As states are key in reforming any data system, we acknowledge the participation of the governments
of Uttar Pradesh, Andhra Pradesh, Assam, Karnataka, Arunachal Pradesh, Bihar, Goa, Manipur,
Meghalaya, Odisha, Tamil Nadu, Uttarakhand, Mizoram, Tripura, Telangana, Rajasthan, Gujarat, and
the Madhya Pradesh State Statistical Commission. We also acknowledge the overall coordination
and organization of the workshop, which was carried out by Mohd Zubair Ali Hashmi, Director,
NITI Aayog, and Liankhankhup Guite, Assistant Director, NITI Aayog. Logistics management and
support, including session management, by NDAP PMU and Deloitte, and technical consultation
by Object Technology Solutions Inc (OTSI) are also acknowledged.
(Anna Roy)
Principal Economic Adviser, NITI Aayog Leveraging State Data Ecosystems for State and District Level Policy and Planning v
ABBREVIATIONS AND
ACRONYMS
ACI Asia Competitiveness Institute
ADP Aspirational Districts Program
AP Andhra Pradesh
API Application Programming Interface
AWS Automatic Weather Stations
BIMS Beneficiary Identification and Management System
CDAP City Data Analytics Platform
CEDA Centre for Economic Data and Analysis
CM Chief Minister
CS Chief Secretary
DDH Data Development Hub
DDP District Domestic Product
DEA Department of Economic Affairs
DiCRA Data in Climate Resilient Agriculture
DM District Magistrate
DMU Data Management Unit
DMEO Development, Monitoring & Evaluation Office
DBT Direct Benefit Transfer
EV Electric Vehicle
FICCI Federation of Indian Chambers of Commerce and Industry
GDO Government Data office
GIS Geographic Information System
GSDA Ground Water Supply & Development Agency
GST Goods and Service Tax
GoUP Government of Uttar Pradesh Leveraging State Data Ecosystems for State and District Level Policy and Planning vi
GSWS Grama and Ward Sachivalayam
GDP Gross Domestic Product
GVA Gross Value Added
GSDA Groundwater Survey & Development Agency
HAG Higher Administrative Grade
IAS Indian Administrative Service
IDI Integrated Data Infrastructure
IDMO India Data Management Office
IDP India Datasets Platform
IIM Indian Institute of Management
IMF International Monetary Fund
ISB Indian School of Business
ISRO Indian Space & Research Organisation
JAM Jan Dhan Account, Aadhar Card, Mobile Data
J&K Jammu & Kashmir
KYC Know Your Customer
LBSNAA Lal Bahadur Shastri National Academy of Administration
LGD Local Government Directory
LBD Longitudinal Business Database
MADAT Monitoring and Assessment of Drought using Advanced Technology
MGNREGS Mahatma Gandhi National Rural Employment Guarantee Scheme
MoC Ministry of Corporate Office
MRSAC Maharashtra Remote Sensing Application Centere
MSME Micro, Small & Medium Enterprise
Meity Ministry of Electronics & Information Technology
MoSPI Ministry of Statistics & Program Implementation
NCAER National Council of Applied Economic Research
NDAP National Data Analytics Platform Leveraging State Data Ecosystems for State and District Level Policy and Planning vii
NDGP National Data Governance Policy
NDMO National Data Management Office
NDSAP National Data Sharing and Accessibility Policy
NMP National Master Plan
NSWS National Single Window System
NSO National Statistical Organization
OTSI Object Technology Solutions Inc
PAHUNCH Portal to Assess Habitaions Unserved and Needing College or High school
PPP Public Private Partnership
PMU Project Management Unit
SMM Samruddhi Mahamarg
SBR Statistical Business Register
SDG Sustainable Development Goals
SITs State Institution of Transformations
SMP State Master Plan
SOP Standard operating procedure
SSM State Support Mission
TERI The Energy and Resource Institute
TODP Telangana Open Data Portal
ULIP Unified Logistics Interface Program
UNDP United Nations Development Programme
UP Uttar Pradesh
UPI Unified Payment Interface
UT Union Territory(ies)
UN United Nations
UN-GGIM United Nations Global Geospatial Information Management Leveraging State Data Ecosystems for State and District Level Policy and Planning viii
EXECUTIVE SUMMARY
The Leveraging State Data Ecosystems for State and District- Level Policy and Planning Forum was
held on November 17, 2023 at Lucknow, Uttar Pradesh. The Forum was organized by NITI Aayog
and the government of Uttar Pradesh, in collaboration with the World Bank. It brought together
leading experts, stakeholders, and practitioners from the central and state governments, industries,
leading academic universities, and global institutions to explore the latest innovations, challenges,
and opportunities in establishing vibrant state data ecosystems in support of the India@2047
vision. The Forum served as a dynamic platform for knowledge exchange, collaboration and
innovation, and for fostering dialogue on key themes related to data-driven governance.
The keynote addresses were delivered by the Honorable Vice Chairman of NITI Aayog, Mr. Suman
Bery, and the Honorable Chief Secretary of the Government of Uttar Pradesh, Mr. Durga Shanker
Mishra; they both emphasized the crucial role of data in good governance and in achieving the
goals of the India@2047 vision and associated state efforts.
The agenda was divided into four distinct, but interrelated sessions:
1. Getting the Enabling Environment Right;
2. Transforming Data into Knowledge – Achieving the India@2047 Vision;
3. Transforming Data into Knowledge – Proactive and Preemptive Governance; and
4. Experiments on Data Dissemination and Promoting Analytics.
The first session on Getting the Enabling Environment Right featured presentations by
distinguished speakers who spoke about the technological infrastructure, regulatory frameworks,
data governance architecture, and skills needed for data initiatives that can add value to
governance, service delivery, and planning.
In 2012, the Indian government launched the Open Data Initiative with the aim of promoting
the transparency, accountability, and accessibility of government data. A National Data Sharing
and Accessibility Policy (NDSAP) was adopted; NDSAP introduced the open government data
platform, data.gov.in; standard operating protocols (SOPs) for data standardization; and the
criteria for ensuring the quality of datasets.
Despite early successes, the national data ecosystem is still characterized by silos. Often there is a
lack of uniform, harmonized procedures for collecting, curating, and sharing data. A new National
Data Governance Framework Policy (NDGP) that aims to address the shortcomings of existing
policies has been introduced. Under this new policy, the India Data Management Office (IDMO) will
be created to develop rules, standards, and guidelines for data collection, curation, storage, and
sharing. Several states are contemplating similar initiatives at the state level. The data management
offices, which would be staffed by a Chief Data Officer and teams of data scientists, would have
the overall responsibility for data standards; define rules for data-sharing; and develop use cases Leveraging State Data Ecosystems for State and District Level Policy and Planning ix
to extract value from data. This session also featured international examples of data governance
frameworks in countries like Australia, Denmark, New Zealand, and Singapore.
The second session, Transforming Data into Knowledge, focused on how data can bolster the
India@2047 vision. Presenters gave examples of how administrative data, integrated with surveys
and censuses, can enhance local planning at the district level. A standout example is the Prime
Minister’s Gati Shakti National Master Plan, which was initiated in 2021. This plan utilizes innovative
geospatial information systems to streamline economic and social infrastructure planning and
management at the local level. When combined with local statistical data, this approach has the
potential to significantly enhance information for evidence-based planning and monitoring at the
local level. Many specific use cases were given, from disaster risk management to the building
of schools in underserved areas, and the identification of locations for new charging stations for
electric vehicles.
However, presenters also recognized the ongoing and persistent challenge of obtaining high-
quality statistical information below the state level. Uttar Pradesh and other states are adopting a
bottom-up methodology to assess the local economy, evaluate its growth potential, and pinpoint
critical growth industries and sectors. This methodology involves combining traditional data
sources like surveys and censuses with the growing availability of administrative data sources such
as business registers, and transactional data like the goods and services tax (GST) database. The
integration of survey and administrative data in combination with geospatial data has enormous
potential for revolutionizing the subnational data ecosystem.
The third session focused on using data systems for Proactive and Preemptive Governance.
Presenters gave examples of how data can be used to improve service delivery to citizens and
businesses. One notable example of this is the Direct Benefit Transfer (DBT) system, which
seamlessly links data systems such as Aadhar, the Local Government Directory (LGD), and
social registries. It uses these linked data to precisely target eligible beneficiaries, ensuring the
transparent and efficient delivery of subsidies and other services. It is estimated that the DBT
system has reduced leaks to the tune of 275,000 crore rupees, or 1.1 percent of GDP. Some states
are using geographical information systems to proactively enhance citizen delivery services by
geotagging beneficiaries and social, economic, and environmental assets. For example, in Andhra
Pradesh (AP), the state government has built a network of technology portals combining data
on the Sustainable Development Goals (SDGs) using the AP Seva Portal and the Navasakam
Beneficiary Portal to identify underserved areas in need of improvement.
State remote-sensing agencies play a pivotal role in developing and deploying GIS tools for planning
and service delivery. The Maharashtra Remote Sensing Application Centre (MRSAC) showcased a
range of geospatial use cases for data, including transport, water resource management, soil and
water conservation, crop mapping, and agricultural predictive analysis. Leveraging State Data Ecosystems for State and District Level Policy and Planning x
The concluding session of the Forum was focused on Data Dissemination and Knowledge
Generation. This session emphasized the significance of making high-quality data and information
accessible in machine-readable and user-friendly formats wherever and whenever needed. Meeting
the diverse needs of data users, including government planners, administrators, researchers,
media, and the public, requires tailored delivery mechanisms and formats. This session explored
various methods for data dissemination and analytics, drawing on experiences from several states.
These included “Chief Minister Dashboards” that provide high-level overviews of key statistics
and performance indicators by district. Open-data platforms like data.gov.in and the National
Data Analytics Platform (NDAP), along with initiatives targeting aspirational blocks and districts,
were also highlighted as examples. A key takeaway from these discussions was the importance of
adaptability and user-centric design in developing and sustaining such platforms. Looking ahead,
as India advances its data agenda, there will be a growing need for increasingly specialized data
platforms, such as the City Data Analytics Platform (CDAP), and a dedicated Gender Portal, to
meet the evolving needs and priorities of diverse users.
The Forum provided a unique platform for policy makers, officials, data scientists, statisticians,
researchers, and other experts to convene and take stock of India’s rapidly evolving public sector
data landscape, and to share their experiences and best practices. As the first event of its kind
focusing solely on state data ecosystems, its success was evident through the active engagement
of presenters, organizers, and the audience. Given the immense interest in this topic, NITI Aayog
and the World Bank hope to make the Data Forum a recurring event, so that additional data
success stories can be shared, and knowledge exchange between states and the Center can be
fostered.
Harnessing the momentum gained from this inaugural Data Forum can drive forward the
transformative potential of data-driven governance. Working together, we can continue to
champion innovation, collaboration, and transparency, and ensure that data remains a force for
positive change, prosperity, and equitable development across all sectors and regions. Leveraging State Data Ecosystems for State and District Level Policy and Planning xi Leveraging State Data Ecosystems for State and District Level Policy and Planning xii Leveraging State Data Ecosystems for State and District Level Policy and Planning xiii
INTRODUCTION
To mark the 100th anniversary of India’s independence, the Honorable Prime Minister Narendra
Modi has envisioned reaching Viksit Bharat (Developed India) by 2047. This ambitious vision
aims to complete India’s transformation into a prosperous, equitable, and sustainable nation. Key
aspects of the plan include robust economic development through the achievement of a $30
trillion economy by 2047; making India a global economic powerhouse; promoting innovation and
entrepreneurship; and creating millions of jobs across various sectors.
The vision of India as a Viksit Bharat involves creating an ecosystem that meets the aspirations
of all citizens to achieve a living standard that meets basic socioeconomic parameters. It aims to
ensure universal access to quality education and health care for all citizens; eliminate poverty and
inequality; empower women and girls to reach their full potential; build a world-class infrastructure
in the transportation, energy, and communication sectors; and develop smart cities that are
sustainable and livable, while connecting rural and urban areas in order to promote balanced
social development.
Furthermore, India aims to become a leader in emerging technologies like artificial intelligence,
renewable energy, and biotechnology, and to leverage this technology to solve social and
economic challenges, and to develop a robust digital infrastructure that supports e-governance
and the digital economy. Viksit Bharat also aims for environmental sustainability by transitioning
to clean energy sources to combat climate change; protecting and conserving biodiversity for
future generations; and promoting sustainable practices in agriculture, industry, and other sectors.
The roadmap to achieving Viksit Bharat by 2047 will involve:
• Strong political leadership and commitment from the government;
• Effective implementation of policies and programs;
• The active participation of all stakeholders, including citizens, businesses, and civil society;
• Continuous innovation, and adaptation to changing circumstances.
Evidence-based decision-making for policy makers and governments is crucial in attaining the
goals of Viksit Bharat. India has a rich data ecosystem that generates invaluable data that can be
used for decision-making and research. We have witnessed the increasing role of digitization, and
how data can assist in planning and decision-making during the COVID-19 pandemic; in the success
of unified payment interface (UPI); in the rollout of the Direct Benefit Transfer (DBT) program, and
in the extensive Good and Service Tax Network (GSTN) Network. The efficacy of targeted support
under various government schemes where beneficiaries are identified on specific parameters has
been demonstrated by the steep decline reported in the number of multidimensionally poor, from
29.17 percent to 11.28 percent from 2013-14 to 2022-23, as reported in the discussion paper on
Multidimensional Poverty in India that was released on January 12, 2024. Leveraging State Data Ecosystems for State and District Level Policy and Planning xiv
The Aspirational District Program (ADP) has demonstrated the successful use of data as a crucial
tool for informed decision-making, efficient resource allocation, and targeted interventions aimed
at improving the key development parameters of the chosen districts.
Along with these initiatives, the foundational bedrock of the National Data Governance Framework
Policy by the Ministry of Electronics & Information Technology (MeitY), and the National Policy
on Official Statistics by the Ministry of Statistics & Program Implementation (MoSPI) are under
development; they will streamline and integrate the data ecosystem of the country.
Based on the success of these projects, the Aspirational Blocks Program has recently been
launched by NITI Aayog in order to enable development at the block level. Over the last few
years, the central government has spearheaded several initiatives, but there is a different level of
intensity in activities at the state and district levels. The National Data Analytics Platform (NDAP),
which aims to improve access to and discoverability of published government datasets in an open,
standardized, and coherent manner, was also recently launched by NITI Aayog. Under NDAP,
states like Karnataka and Meghalaya have developed a State Data Analytics Platform along similar
lines.
In order to institute a dialogue on key aspects of the country’s data ecosystem, best practices,
and how to arrive at a common minimum agenda among all constituents at the state and central
levels, NITI Aayog held the Data Forum described in this report under its State Support Mission
in Lucknow, Uttar Pradesh. This forum was organized with the government of Uttar Pradesh and
with support from the World Bank. It aimed to bring relevant actors together at the central and
state levels to discuss common interests relevant to the data agenda, and to share knowledge on
recent experiences and good practices. It is intended to be the first in a series of regular events to
discuss progress toward building an evidence-based decision-making support system for policy
and planning.
The four sessions of this inaugural forum were:
• Session 1: Getting the Enabling Environment Right
• Session 2: Transforming Data into Knowledge – Achieving the India @2047 Vision
• Session 3: Transforming Data into Knowledge: Proactive and Preemptive Governance
• Session 4: Experiments on Data Dissemination and Promoting Analytics
This report summarizes the content covered during these sessions, and presents recommendations
that state governments and their officials can adopt going forward. Leveraging State Data Ecosystems for State and District Level Policy and Planning 1
Hoon Sahib SohAnna Roy
Principal Economic Adviser,
NITI Aayog
Practice Manager,
World Bank
Vice Chairman (VC),
NITI Aayog
Suman Bery
Alok KumarAvinash Awasthy
Advisor to CM,
Uttar Pradesh (UP)
Principal Secretary, Planning,
Uttar Pradesh (UP)
Durga Shanker Mishra
Chief Secretary (CS),
Uttar Pradesh (UP)
INAUGURAL SESSION
INAUGURAL SESSION Leveraging State Data Ecosystems for State and District Level Policy and Planning 2
The purpose of the inaugural session was to introduce participants to the broad landscape of the
use of data for improving policy making and governance at the state and district level. Speakers
in this session included:
• Suman Bery, Vice Chairman (VC), NITI Aayog
• Durga Shanker Mishra, Chief Secretary (CS), Uttar Pradesh (UP)
• Avinash Awasthy, Advisor to the Chief Minister (CM), Uttar Pradesh (UP)
• Alok Kumar, Principal Secretary, Planning Department, Uttar Pradesh (UP)
• Anna Roy, Principal Economic Adviser, NITI Aayog
• Hoon Sahib Soh, Practice Manager, World Bank Leveraging State Data Ecosystems for State and District Level Policy and Planning 3
Suman Bery is currently Vice Chairman, NITI Aayog, with the rank and status of a Cabinet Minister.
An experienced policy economist and research administrator, he took over as NITI Aayog Vice
Chairman on May 1, 2022. At the time of his appointment, he was a Senior Visiting Fellow at
the Centre for Policy Research, New Delhi; a Global Fellow in the Asia Program of the Woodrow
Wilson International Center for Scholars in Washington DC; and a nonresident fellow at Bruegel, an
economic policy research institution in Brussels.
Keynote Address
In line with the Honorable Prime Minister’s Vision for a Viksit Bharat by 2047, this workshop is an
effort to foster cooperative federalism. The important role of data in policy making was witnessed
during the COVID pandemic, as well as across multiple initiatives of NITI, such as the National
Data Analytics Platform (NDAP) and the Aspirational Districts Program, as well as the data-based
monitoring of central sector schemes by the Development Monitoring & Evaluation Office (DMEO)
at NITI, among others. A data-driven paradigm will promote initiatives that aggregate data at
different levels of granularity, by engaging with states.
NITI has launched the NITI for States initiative, an umbrella mechanism through which NITI Aayog
assists states and UTs in developing capabilities in designing, implementing, and monitoring
development strategies for achieving green, resilient, and inclusive growth. Underlining the
importance of dialogue and deliberation, a NITI Task Force on the Indian Statistical System has
provided a platform for bringing together various stakeholders in the data ecosystem. The Working
Group on Business Statistics constituted as part of the Task Force has already made considerable
progress, in collaboration with various central government ministries and the World Bank.
Underscoring the importance of data analysis and dissemination, NDAP has vastly improved
the analytical value of published government data in a user-centric manner. Central and state
governments generate valuable data at every level; however, thus far it largely exists in silos,
creating challenges for its optimal use and dissemination.
States are encouraged to partner with NITI for showcasing and disseminating best practices. The
importance of district-level planning -- a bottom-up approach of data collection and compilation
leading to analytics -- should be undertaken uniformly across states. NITI Aayog will continue to
extend support to all state governments for building a robust data ecosystem, under the aegis of
the State Support Mission.
Suman Bery
Vice Chairman (VC), NITI Aayog Leveraging State Data Ecosystems for State and District Level Policy and Planning 4
Durga Shankar Mishra is the Chief Secretary of Uttar Pradesh. He is a 1984 batch Indian Administrative
Service (IAS) officer of the Uttar Pradesh cadre. He was Housing and Urban Affairs Secretary, and
Chairman of the Delhi Metro Rail Corporation from June 21, 2017 - December 29, 2021.
Inaugural Address
The government of Uttar Pradesh (UP) has an ambitious mission to become a $1 trillion economy by
2027-28, leading to massive development within the state, thereby accelerating India’s economic
growth. “Strengthening Data Systems” is one of the core pillars toward achieving the target of a
$1 trillion economy for the state. To this end, access to reliable, frequent (monthly or quarterly), as
well as granular (district or block-level) data is the cornerstone for creating a robust monitoring and
planning system.
The availability of granular data becomes critical for informing district-specific policies and planning.
For instance, the availability of disaggregated data allows district officials to know how their district
is faring and where they should focus their efforts. If there is a lack of adequate data, or it is available
only at infrequent intervals, it is less helpful in understanding whether a policy is working.
The states face several challenges in accessing reliable data (especially monthly or quarterly data)
at the district or subdistrict level, or data that is disaggregated by sectors. For instance, if the GDP
data comes only every quarter and after a time lag of two months, it isn’t as helpful in measuring
economic activity as it would be if the data were available more frequently. Furthermore, concerns
regarding the quality of data leads to a low level of trust in government data. Finally, states aren’t
able to measure all of their economic activities, specifically those in the informal or digital sectors, if
they aren’t fully captured by traditional economic measurement methods.
The Planning Department has been at the fulcrum of efforts to address some of these challenges,
improve data collection and monitoring, and analyze available data for better insights. The government
of UP (GoUP) has been estimating the District Domestic Product (on the lines of GDP) for 75 districts
of UP. At the state level, GoUP is taking the principle of competitive federalism to the districts; it
wants to empower District Magistrates (DMs) to become district CEOs with tools to monitor their
performance. Monthly review meetings at the district level will further facilitate the ability to do
this. GoUP is also engaging with multiple knowledge partners to achieve our mission of $1 trillion
and effective monitoring - thus highlighting the key role of external partners like NITI Aayog, and
academic institutions, toward state development.
Durga Shanker Mishra
Chief Secretary (CS), Uttar Pradesh (UP) Leveraging State Data Ecosystems for State and District Level Policy and Planning 5
In this regard, GoUP has been undertaking innovative steps to use digital systems and make targeted
interventions. This is visible in the Aspirational Blocks Program, which was started by GoUP, and
scaled nationally by NITI Aayog. GoUP has seen more effective functioning due to data systems,
including tracking files digitally, monitoring flagship schemes and initiatives through dashboards, and
listing all budget data on a portal (Koshvani) for public access.
In this manner, Uttar Pradesh is benefitting from its robust mechanism for data collection. This includes
a dedicated division for data and monitoring and a district-level infrastructure including personnel
deployed in each of the 826 blocks. UP was ranked 2nd in DBT Ranking by the government of India
in 2022. With support from NITI Aayog’s State Support Mission, the Planning Department is in the
mature stages of conceiving a State Transformation Commission for UP that responds to its specific
needs. The government of UP has also transitioned from pen-and-paper-based data collection to
digital tools to smoothen this process and strengthen data quality. To this end, GoUP has procured
electronic tablets for all of the state’s enumerators. Leveraging State Data Ecosystems for State and District Level Policy and Planning 6 Leveraging State Data Ecosystems for State and District Level Policy and Planning 7
Director of Chennai Mathematical Institute
Prof. Rajeeva Laxman Karandikar
PANELISTS
Session Chair
Pravin Srivastava
Paul Cheung
Former Chief Statistician of
Singapore and Director of the United
Nations Statistics Division
Chairman,
Madhya Pradesh
State Statistical Commission
Dayanandam
Director,
Government of Telengana
Abhishek Singh
Additional Secretary,
MeitY
SESSION 1:
Getting The Enabling
Environment Right Leveraging State Data Ecosystems for State and District Level Policy and Planning 8
Professor Rajeeva L. Karandikar is currently the Chairperson of the National Statistics Commission
and Professor Emeritus at Chennai Mathematical Institute. Rajeeva obtained his PhD at the Indian
Statistical Institute, Kolkata in 1981. He spent some years as a visiting professor in the USA and
returned to the Indian Statistical Institute, Delhi, in 1984 as an Associate Professor. He became
a full professor in 1989 and served as Head of the Department of Mathematics and Statistics at
the Institute, and as Head of the Delhi Centre of the Institute. He was the Director of Chennai
Mathematical Institute, Chennai, India, from 2011 until 2021.
Opening Remarks by Prof Rajeeva Laxman Karandikar, Session Chair.
When governments and policy makers make decisions based on data, they can achieve more
effective and holistic results. This makes data a high-value asset throughout the globe. India is on
a mission to become a developed nation by 2047 based on a data-driven economy within the next
few decades. However, certain aspects of the data ecosystem regarding collation, sharing, and
dissemination must be revamped in order to take advantage of the underlying data.
India is the most populated country in the world. This means that there is extensive human capital
generating unmatched quantities of data. At the same time, it urges the creation of public systems
that can harness this data to help govern citizens efficiently and bring them on board with our
dream of a digital economy.
To make use of its full potential, India’s data ecosystem needs some revamping. As a first step,
an organized way must be developed to collate, process, and share data within governmental
set-ups. India does have an open government data portal, data.gov.in, which stores high-level
data shared by different ministries; but it lacks continuity, completeness, and granular data. India
currently lacks the institutional frameworks needed to oversee and manage this data-sharing.
Also, supporting structures for data-sharing, such as metadata standards and citizen privacy
protections must be created during data-sharing. Presently, most data-sharing initiatives are
undertaken in silos within a particular ministry or department, or through a few states sharing data
through a state data portal. There is no real inter governmental data-sharing taking place on a
large scale. Further, there are no appropriate mechanisms for data discovery because there aren’t
any dedicated data departments, or teams within departments or ministries that can cater to the
Rajeeva Laxman Karandikar
Director of Chennai Mathematical Institute
SESSION CHAIR Leveraging State Data Ecosystems for State and District Level Policy and Planning 9
precise data needs of the government. There is, therefore, a definite need for a national-level data
governance policy that covers all the above.
This session provides an overview of best practices in data-sharing and management in several
countries. Singapore, for instance, is one of the most data-forward nations in the world. Several of
their government ministries have data centers. They have a clearly defined data-sharing strategy,
and have drafted legal and regulatory considerations, including technical and organizational
considerations concerning data-sharing. Data-sharing is done with transparency, accountability,
legal compliance, retention, and data disposal in mind. Singapore also has a Government Data
Office that implements data strategy. Data scientists and chief data officers oversee the framework
of data governance. Data custodians and data stewards work under them, performing specific
roles relating to data management.
New Zealand has a unique approach to data management. They have developed an Integrated
Data Infrastructure (IDI) that merges data from various sectors, and a Longitudinal Business
Database (LBD) that contains financial and agricultural data. Australia is also strengthening its
data strategy and building a niche for data specialists.
Learning from the above examples, MeitY have developed a robust digital governance framework
with a defined structure, and precise definitions and work processes.
Creating trust and maintaining citizen privacy are some of the critical challenges in governing data
and developing a data-sharing infrastructure. Other challenging aspects can be ensuring that the
data quality is maintained while sharing, merging, and dissecting datasets; continuously updating
data sets and ensuring that they can adapt to an ecosystem of constant change; and deciding
which data to retain. The supervision of data infrastructure and constant reporting to ensure that
all standards are being met are additional challenges. Leveraging State Data Ecosystems for State and District Level Policy and Planning 10
An integrated data-cum-statistics approach can help in navigating these challenges because the
country’s statistics departments have the most experience holding and managing historical data
across states, sectors, and divisions. MeitY has proposed a simple, straightforward solution in
the form of a National Data Governance Policy (NDGP). First an institutional framework must be
developed to govern data management. There will be sector-specific management units within
ministries and departments, with a definite hierarchy of officers whose sole responsibility will be
to take care of all aspects related to governing data. Some states have adopted an open data
policy with data governance methods for storing data, data- sharing between ministries, and the
development of open data portals, as demonstrated in the state of Telangana.
Telangana is greatly committed to data-driven governance. In 2016 they adopted an Open Data
Policy, and in 2017 they created a portal called Open Data Telangana which contains high-value
datasets on various sectors within the state. Open Data, by definition, means data that can be freely
used, reused, distributed, and redistributed for analysis and innovation. Telangana’s government
has uploaded freely available data and resources onto their portal in a machine-readable format
that citizens, researchers, and organizations can read and use. All datasets are updated monthly
so that the latest information is available. Open Data Telangana furthers transparency, because all
of the data is freely available to the public. It aids collaboration between interested third parties,
including government departments--for example, between Transportation and City Planning--to
achieve cross-perspective and drive successful projects that lead to development in the state. An
interesting example is the AI4AI project, which brought together climate data with agricultural
patterns to further food initiatives.
The talks and presentations in this session will highlight some of the gaps in the current ecosystem,
and international best practices for sharing and managing data, along with a proposed approach
to enabling a robust data ecosystem. Leveraging State Data Ecosystems for State and District Level Policy and Planning 11
Abhishek Singh is a Civil Servant with 27 years of experience in governance and policy formulation.
He specializes in the use of technology for improving governance. In his role as President &
CEO of the National e-Governance Division, and MD&CEO of Digital India Corporation, he leads
major Digital India Initiatives, including projects in the field of artificial intelligence and emerging
technologies, and he oversees India’s artificial intelligence program. He has been involved in
several e-governance initiatives, and has firsthand experience in using data for economic growth
and policy making.
Building Blocks for Data Governance
In line with the vision of the Honorable Prime Minister of India to have a data-driven economy, the
aim is to hold data as a high-value commodity and use the huge volumes of data created by India’s
growing digital population to improve current public systems, develop future policies, and foster
a digital economy. That said, there are definite challenges in our current data ecosystem. The key
challenges noted are lack of institutional frameworks for data-sharing; lack of metadata standards;
siloed data initiatives; poor mechanisms for data discovery and intergovernmental data-sharing;
and lack of dedicated data teams.
MeitY has proposed developing the
National Data Governance Policy (NDGP)
to mitigate these challenges, by enabling
intragovernmental data-sharing for
economic benefit and inclusive growth.
The policy aims to enhance the quality
and use of nonpersonal data so that
governments and researchers can access
high-quality data while ensuring privacy
and trust. The following actions are
suggested to further operationalization of
the policy:
Abhishek Singh
Additional Secretary, MeitY Leveraging State Data Ecosystems for State and District Level Policy and Planning 12
• An institutional framework is needed, to bind and govern data management and processing.
A National Data Management Office (NDMO) that will oversee the availability and quality
of datasets, and how they are accessed, stored, and made available to and used by various
third parties should be set up.
• Sector-specific management units to implement the above governing framework should then
be established. Every ministry must have a Data Management Unit (DMU) headed by a Chief
Data Officer. This unit will curate high-quality, accurate datasets of the ministry, and chalk
out a data strategy in line with the standards prescribed by the National Data Management
Office.
• Once the datasets are in place, there should be programs and platforms to help catalyze
research and innovation. The India Datasets Program should identify and curate datasets by
government ministries and private entities to further AI research and to disrupt the existing
technology ecosystem in India. This could be done by the India Datasets Platform (IDP),
which will provide a real-time interface where these authenticated, anonymized, and meta
standard-complying datasets are uploaded and maintained.
• MeitY also aims to improve public service delivery by integrating the beneficiary database
across multiple central schemes of the government. This would be achieved by accessing
and processing information from citizen and family-level beneficiary databases, where a
360-degree view of the benefits received by each family can be accessed and acted upon.
Already, the Aadhar Card has been linked with various central government schemes, which
allows government departments to access the schemes availed by the beneficiary. This
will enhance the delivery of government benefits, ease of governance and service delivery,
enable proactive delivery services, and enhance citizen-government interaction. Leveraging State Data Ecosystems for State and District Level Policy and Planning 13
Paul Cheung is the Director of the Asia Competitiveness Institute (ACI) and Professor in Practice
at the Lee Kuan Yew School of Public Policy, National University of Singapore. Professor Cheung
served as the Director of the United Nations Statistics Office from 2004 to 2012. As the Chief
Statistician at the UN, he facilitated the development of the global statistical system, and was
responsible for implementing UN mandates on geospatial data and analytics. In 2011, the UN
endorsed Professor Cheung’s initiative of establishing an intergovernmental platform to address
issues on Global Geospatial Information Management (UN-GGIM).
Frontiers of Data-Driven Decision Support Systems
Looking at various data and statistical modernization projects in Singapore and other nations
reveal that there are key factors that are critical for the success of such projects. One is that
governments aim to foster a cohesive data ecosystem by combining multiple data streams. This
approach is reflected by various nations in their data strategies, as can be seen from the following
examples:
Singapore
• The key principles for Singapore’s data ecosystem are viewing data as a service with the
continuous addition of new data sources, secure data exchanges, and knowledge generation.
Currently, data centers exist for several ministries and private entities in Singapore.
• Data-sharing consists of four essential parameters:
• Data-Sharing Strategy: Data models, and the value of data, are properly understood;
• Legal and Regulatory: Data-sharing contracts are developed;
• Technical and Organizational Data-Sharing; Understanding the considerations; and
• Operationalizing Data-Sharing: Transparency, accountability, legal compliance, and the
retention and disposal of data.
• Singapore’s governance system focuses on four key aspects: Leadership and Intent, Technical
Standards, Custodianship, and Sharing.
Paul Cheung
Former Chief Statistician of Singapore,
and Director of the United Nations Statistics Division Leveraging State Data Ecosystems for State and District Level Policy and Planning 14
• The Government Data Office (GDO) implements a data strategy. Civil servants are trained in
data science so they can navigate the ecosystem. A Data Science and Chief Data Officer is
appointed to oversee the competency framework for civil servants.
• To support the data infrastructure,
data custodians perform specific roles
like collecting, managing, storing, and
ensuring data quality. Data stewards
are professionals who oversee the data
production process.
Singapore has developed an integrated data
system called the Singpass myinfo, which is
a digital identity for all Singapore citizens and
residents that allows them to access over 460
government agencies and businesses with
1,700+ digital services, both online and in person.
• With Singpass Myinfo integration, users
can easily access their personal data
and control how it is shared with private and public sectors securely. By giving consent
through Singpass, users can share their information without the need for manual data entry,
leading to better data quality and “instant” approvals. Myinfo retrieves data from various
government sources, streamlining the “Know-Your-Customer” (KYC) process for businesses,
and eliminating the need for customers to provide additional verification documents.
• Businesses can leverage Singpass Myinfo integration API with their own digital services,
enabling more efficient and more instant provision of products; an improved customer
experience; and increased customer satisfaction.
New Zealand
• The government’s principles are: Investment in making the correct data available at the right
time; transparent processes; and intra- and intergovernmental partnerships.
• Integrated Data Infrastructure (IDI) ensures the amalgamation of data from various sectors
(education, housing, etc.); the Longitudinal Business Database (LBD) contains financial,
agricultural, and other data. The IDI and LBD are linked through tax data.
Denmark
• Denmark specifically focuses on making data usable and reusable across authorities and
sectors. The aim is to create digital solutions of strategic importance to society.
• The foundation is transparent and high-quality data sources consisting of digital base
registers on people, businesses, addresses, and buildings, supplemented by a network of
secondary interoperable sectoral registers. Digital infrastructure has been built to facilitate
seamless data exchange and integration for users with varying access levels.
Australia
• In 2020, Australia launched its Data Profession Strategy with the aim of strengthening the
professionalism and talent acquisition of data scientists across government. Leveraging State Data Ecosystems for State and District Level Policy and Planning 15
Pravin Srivastava currently serves as Chairman of the Madhya Pradesh State Statistical Commission.
He superannuated from the Indian Statistical Service as Chief Statistician of India and Secretary,
Government of India in the year 2020 after rendering 37 years in the Indian Statistical System. He
has provided statistical leadership to the country and led teams in subjects of official statistics,
statistical analysis, macroeconomics, information technology systems, web portal systems,
business process restructuring, and so on.
Data Governance Architecture
The data initiatives for improved decision-making
in several states suggest the strong need for data
governance. Data governance enables states to use
data as a true asset that not only supports informed
action, but is also compliant with defined rules aligned
across organizations. For this, a cross-organizational
framework that will be a mechanism for controlling and
trusting data is suggested.
From an organizational perspective, a data governance
framework protects the needs of stakeholders, creates
processes and standards, and reduces operational friction.
A strong data governance program has a defined structure
(Data Governance Board, data stewards, review boards, etc.); definitions (described in handbooks,
mission, and scope); and work processes (communication, culture, and continuous improvement).
The Data Governance Board should contain the heads of all relevant departments. They should
have monthly meetings, and should set guiding principles, and actionable agenda items, with
timelines. In line with this, the Data Steward Workgroup should have the core responsibilities
of managing metadata; ensuring high quality; communicating changed data requirements;
determining the need for the retention of data; overseeing data analysis; and reporting on all of
the above aspects. The Workgroup should report to the Data Governance Board.
Pravin Srivastava
Chairman of the Madhya Pradesh State Statistical Commission Leveraging State Data Ecosystems for State and District Level Policy and Planning 16
Data governance can crystalize many gray areas in the sector. It manages data, controls quality,
audits, and extends to post-secondary data. It also fosters consistent communication among
external stakeholders. Trust is a big factor that links all of this. Five principles of trustworthiness
are suggested that are used for official statistics as well:
• Necessity and proportionality;
• Professional independence;
• Privacy;
• Quality; and
• National and international comparability.
Statistics Approach
• The United National Statistics Division (UNSD) manages its data through built-in processes.
The National Statistics Office acts as Data Steward, based on clear governance principles.
Privacy is upheld and a holistic approach to data and policies is encouraged.
• A simple yet clear hierarchy while defining data governance can be seen in this way:
Executive Leadership (Chief Minister /Chief Secretary level), Governance Board (State
Planning Commission / NITI), Data Owners (Departments), Data Steward Workgroups (Chief
Data Officer / IT Team).
• For example, in Madhya Pradesh, the MP State Statistical Commission was established to
coordinate data flow across departments. After capacity building, they generated their
District Domestic Product using a bottom-up approach. This is how they created a state-
level Statistical Business Register. Leveraging State Data Ecosystems for State and District Level Policy and Planning 17
Open Data Telangana
Open Data Telangana stands out as a pioneering effort by the state government to provide
structured, machine-readable access to government-held data. This initiative, which spans the
health, education, agriculture, energy, industry, and urban development sectors, aims to bolster
transparency, empower citizens, and drive economic growth through data-driven innovation. By
making vast repositories of information publicly available, the government is nurturing trust and
engagement with its citizens.
The Innovation: While the concept itself might not
be new, what sets this portal apart is its monthly
updates for many granular datasets; superior filters for
data discoverability; ease of navigation; Application
Programming Interface (API) interoperability; unique
datasets; and various applications and models that can
be built out of the data from this portal, which features
global standards, policy-backed procedures, and user-
centric norms.
The Open Data portal expanded even further, with over 3,535 resources available, updated up
to the most granular level every month. Start-ups and not-for-profit organizations can actively
use the data for various projects. Collaborations with organizations such as the World Economic
Forum, UNDP, and the Agri AI start-ups have strengthened the use of open data in initiatives
related to agriculture and food systems.
Being an open data portal that ensures transparency and cross-perspective, TODP drives
collaboration between state departments, for example between Transportation and City Planning
(General Transit Feed Specification); health care and tech collaborations; and the use of weather
data to predict emergencies and facilitate the provision of real-time help. TODP regularly
collaborates with international forums to drive innovation and better policies. Some examples are
the Saagu Baagu AI4AI Project to harness agri innovation, and DiCRA (Data in Climate Resilient
Agriculture) with UNDP, to develop a “data for policy” food initiative on food systems.
Presentation by the
Government of Telangana on
Open Data Telangana Leveraging State Data Ecosystems for State and District Level Policy and Planning 18 Leveraging State Data Ecosystems for State and District Level Policy and Planning 19
Senior Economist/Statistician for World Bank
Poverty and Equity Global Practice in the South-Asia Region
Thomas Danielewitz
PANELISTS
Session Chair
Pallavi Choudhuri
K.V.Raju
Professor Emeritus
at Chanakya University,
Bengaluru, India
Senior Fellow at the
NCAER-National Data Innovation
Center
Surendra Kumar
Joint Secretary,
Department of Commerce,
Ministry of Commerce & Industries
Arthur Giesbert
Statistician/Economist
at the World Bank’s Development
Data Group
SESSION 2:
TRANSFORMING DATA INTO
KNOWLEDGE – ACHIEVING THE
INDIA @2047 VISION Leveraging State Data Ecosystems for State and District Level Policy and Planning 20
Thomas Danielewitz is a senior economist/statistician for the World Bank Poverty and Equity
Global Practice in the South-Asia Region posted in Colombo, Sri Lanka. He joined the World Bank
in 2008 and is an economist by training. He has been Task Team Leader for numerous World
Bank lending projects and advisory tasks within data and statistical system development across
several regions in the Bank. Currently, he coleads the World Bank’s Global Solutions Group on
Statistical Modernization, and the StatCap Community of Practice. Before joining the World Bank,
he worked as an economist at Statistics Denmark, where he was responsible for national accounts,
government finance statistics, and technical assistance projects.
Opening Remarks by Thomas Danielewitz, Session Chair
The main value of data is its ability to inform decision-making. Data has the potential to provide
facts and insights about society, the economy, and the environment that decision-makers need to
make informed choices. It helps us to understand trends, patterns, and relationships that may not
be apparent otherwise, and it can help drive resource allocation more efficiently by identifying
areas where resources are being underutilized, or where there is a need for additional resources.
We live in a world with an abundance of data. However, a key challenge is transforming those
raw numbers into information and actionable knowledge. This session highlights some of those
challenges and some potential use cases.
Most public sector data is collected through administrative registration and transactions with
citizens and business, as well as through periodic surveys and censuses. These data sources have
different strengths and weaknesses vis-a-vis decision-making. Surveys can be tailored to respond
to the exact needs of policy makers, but they are collected infrequently, sometimes only annually
or every five years; and they take time and effort to implement. Survey data can also be riddled with
bias due to nonresponses, making the findings inaccurate. Administrative data, on the other hand,
is freely available as a by-product from interactions with citizens and businesses as well as internal
government operations. However, administrative data is often unstructured, and can suffer from a
range of issues including lack of uniform standards, storage, and exchange. Moreover, it does not
always respond to the exact topic of interest to policy makers, and is generally harder to transform
into useful knowledge compared to a well-designed survey. However, the combination of survey
Thomas Danielewitz
Senior Economist/Statistician for World Bank
Poverty and Equity Global Practice in the South-Asia Region
SESSION CHAIR Leveraging State Data Ecosystems for State and District Level Policy and Planning 21
and administrative data has the potential to yield new and faster insights to help decision-making,
especially at the local level.
Districts are recognized as India’s growth engines. Hence, in-depth district-level planning is
needed to accelerate the country’s overall growth. Just as nations measure the value added
by goods and services in a year through GDP, districts can do this by calculating their District
Domestic Product (DDP), which is the total value added of goods and services produced within
the territorial boundaries of a district. To manage economic growth, districts must have a system
to estimate DDP for the district as well as for key industries. To arrive at DDP, states must use
administrative data sources, since few surveys are detailed enough to be representative at that
level; there are a few strategies that can be implemented to estimate DDP through the combined
use of administrative data and surveys.
Another important mechanism that can be used to turn data into insights is the combination of
statistical and geographical information. A prime example is PM Gati Shakti, a digital initiative by
the central government to improve infrastructure planning across various ministries. Gati Shakti
contains a National Master Plan (NMP) and a State Master Plan (SMP), including a geo-referenced
collection of over 300 central, state, and UT government projects. The session also delves upon
the utilization of PM Gati Shakti to drive decision-making through power of data. Leveraging State Data Ecosystems for State and District Level Policy and Planning 22
Arthur Giesbert has been working as a Statistician/Economist at the World Bank’s Development
Data Group since April 2019. His main responsibilities include developing methodologies and
instruments in the field of business statistics, and providing technical assistance, training, and
capacity building. He mostly works with and for national statistical institutes in close cooperation
with other departments in the World Bank. The immediate outputs of his work are new, improved,
or more timely business statistics, and better inputs to national accounts.
Towards District GDP: Leveraging (Regional) Business Statistics for State and
District-Level Policy and Planning
The calculation of annual District
GDP will give a breakdown of each
district’s progress in a state; this can
be calculated by using a Supply and
Use table. Supply includes the output
of all industries and imports, while Use
contains consumption, exports, and
investments. To achieve this, many
variables must first be consolidated
and then used.
Another way to arrive at District GDP
might be a generic work program in
business statistics combined with
national accounts. This is a feasible
best practice, as implementation can be gradual and dynamic due to changing economies and
requirements. All systems can only generate outputs based on data. Several data-rich kinds of
administrative data and survey data can be used for this purpose: for example the data collected
and retained by the Ministry of Statistics and Program Implementation (MOSPI); the Federation of
Indian Chambers of Commerce and Industry (FICCI); and the Ministry of Corporate Affairs (MOC),
among many others.
Arthur Giesbert
Statistician/Economist at the World Bank’s Development Data Group Leveraging State Data Ecosystems for State and District Level Policy and Planning 23
Massive amounts of business statistics data already available at the state and national level must
be better used for this purpose. Some next steps might be using all census, administrative, and
district survey data to create a proof of concept, and form an inventory of best practices.
The content needed for a Statistical Business Register (SBR) comes from singular enterprises, local
units, enterprise groups, and legal units. SBR can also create business demographic publications
by sampling, weighing, and grossing up survey data. In this way, a complete and mature SBR can
be achieved and maintained by using census data, survey data, and administrative data from the
private and public sectors, as well as through profiling within the National Statistical Organization
(NSO). Leveraging State Data Ecosystems for State and District Level Policy and Planning 24
K.V. Raju is Professor Emeritus at Chanakya University, Bengaluru, India. He is currently working as
the Economic Advisor to the Chief Minister, Government of Uttar Pradesh. Earlier, he worked as the
Economic Advisor to the Chief Minister, Government of Karnataka. He was Principal Scientist, Policy
and Impact, Asia Division, for the International Crops Research Institute for Semi-Arid Tropics, in
Hyderabad; Social Scientist, International Water Management Institute, Colombo; Visiting Senior
Research Fellow at the International Food Policy Research Institute, Washington DC; and Professor
and Head at the Center for Ecological Economics and Natural Resources, Institute for Social and
Economic Change, Bengaluru.
District Domestic Product Estimation
The government of Uttar Pradesh has developed an approach for developing the District Domestic
Product (DDP). The DDP methodology was jointly created by the Directorate of Economics and
Statistics, Karnataka and Uttar Pradesh in 1998. Today, DDP is estimated in 19 states of India
across the primary, secondary, and tertiary sectors of the economy.
The district-level estimation process helps state governments arrive at the gross state-added-value
of their state. For this, a district-wise and sector-wise estimation is helpful. Presently, district-wise
Gross Value Added (GVA) is arrived at by apportioning State GVA to districts based on specific
indicators – workforce, wages, railway tracks, electricity units, buildings, etc.
The Directorate has proposed a bottom-up approach for the District Level Estimation Process.
For the primary sector, GVA can be estimated through this approach. For the secondary and
tertiary sectors, district-level indicators for estimating DDP can be used, as this data is not readily
available. The bottom-up approach is proposed for the secondary and tertiary sectors in four
districts of UP – Meerut, Kanpur Nagar, Gorakhpur, and Varanasi. Gross District Value Added will
be calculated based on balance sheets from departmental and non departmental enterprises,
workforce wages, and salaries for the organized sector. For the unorganized sector, it will be
calculated by the Labor Force Survey and the Survey on Unincorporated Sector Enterprises.
K.V.Raju
Professor Emeritus at Chanakya University, Bengaluru, India Leveraging State Data Ecosystems for State and District Level Policy and Planning 25
These estimates are for defined sectors of the economy; and a key cross-cutting sector in Uttar
Pradesh is tourism. This sector indirectly impacts many other sectors, such as hospitality, trade, and
transport. Therefore, tourism’s value addition is vital to calculate so that the sector’s contribution
to the state’s economy can be understood. To arrive at the DDP of tourism in a district of Uttar
Pradesh, the prediction model uses datasets on tourist footfall, average tourist spending, and
average stay duration, and bunches them together. Separately, datasets on the investment-led
tourist contribution are also obtained through reported GST turnover, construction services of
hotels, halls, parking spaces, etc. Leveraging State Data Ecosystems for State and District Level Policy and Planning 26
Pallavi Choudhuri is a Senior Fellow at the NCAER-National Data Innovation Center. Her research
primarily focuses on employment, social protection, and gender. Prior to joining NCAER, Choudhuri
taught courses in Economics at the Grand Valley State University in Michigan as a Visiting Assistant
Professor. She has a PhD in Economics from the University of Wyoming, and has also served on
government committees while working at NCAER.
Harmonization of Data: Integrating Survey and Non-Survey Data Sources for
Faster, More Accurate Insights into District Growth
There is a growing need to use both kinds
of data – non-survey and survey--to support
policy making and planning by the states.
Data must be evaluated over time to
understand its long-term impact, and policies
must be formulated after analyzing costs and
benefits and targeting beneficiaries. Survey
data comes with many advantages – robust,
representative data for various indicators
that cover those at the lower end of the
economic spectrum and contain a thick layer
of information providing socioeconomic
context. However, it also poses certain
challenges – infrequent collection (annual
or five-yearly); nonresponse bias of items;
quality; and issues in harmonizing across
industries.
Non-survey data has its own advantages. Administrative data is usually low-cost, regularly
updated, and consistent across individuals. Geospatial data is known for its accuracy, as it is
collected by technology; the challenges it poses are that it is unstructured, or only semi-structured,
so there’s no heterogeneity. There are also questions of quality and bias.
Pallavi Choudhuri
Senior Fellow at the NCAER-National Data Innovation Center Leveraging State Data Ecosystems for State and District Level Policy and Planning 27
There are several challenges in integrating survey and nonsurvey data, and with both kinds, proper
cautions should be taken. Some of the challenges are:
• The need for research error properties of organic data and possible links to survey data;
• How deanonymized administrative data might intersect with survey data;
• The sample sizes of each subset may not be representative of the underlying population;
• How to document cross-walking across various datasets while comparing economic
indicators. Leveraging State Data Ecosystems for State and District Level Policy and Planning 28
Surendra Kumar Ahirwar is a 1996 batch officer of the Indian Railway Traffic Service. He is currently
posted as Joint Secretary in the Department of Commerce, Ministry of Commerce & Industries,
overseeing Logistics. Before joining the Ministry of Commerce and Industries in 2018, he worked
in the Ministry of Railways in various positions: managing operations, marketing, infrastructure
planning, project implementation, PPP Project planning & implementation, and the Mumbai-
Ahmedabad High-Speed Rail Project. He has been the recipient of many awards, including the
National Award for Improving Efficiency in Railway Operations.
Supporting Districts as a Fulcrum of Growth
PM Gati Shakti, the National Master Plan for Multi-Modal Connectivity, is a $1.2 trillion megaproject
to improve India’s manufacturing competitiveness and is used to identify and build a “growth
corridor” at the subnational level.
India aspires to be a $32 trillion economy by 2047. For this, there is a need to accelerate infrastructure
development at an unprecedented rate. The government is undertaking an integrated, cross-
functional approach to ensure that all stakeholders are simultaneously involved. This can be best
realized through data-driven decision-making.
The government has two core systems to
ensure infrastructure development: efficient
governance of projects, and an efficient
logistics system. These are achieved through
digital initiatives such as PM Gati Shakti NMP,
the National Single Window System (NSWS),
the Unified Logistics Interface Program
(ULIP), and VAHAN and SARTHI, among
others.
Gati Shakti is a GIS-based platform that
contains a National Master Plan (NMP) and a
State Master Plan. It is based on geospatial
technology encompassing over 100 critical
Surendra Kumar
Joint Secretary, Department of Commerce, Ministry of Commerce & Industries Leveraging State Data Ecosystems for State and District Level Policy and Planning 29
transport infrastructure projects that ensure Shapelast-mile connectivity, and over 300 projects of
the central, state, and UT governments that are examined using NMP and SMP at the national and
state levels, respectively. This has led to reduced timelines, digitized approvals, visible GIS-based
layers, accuracy in alignment planning, and holistic social and economic infrastructure planning.
PM Gati Shakti is also operational in social sector planning across 22 social ministries where
health, sports, and school data are integrated in various individual portals and through NMP. This
facilitates better planning for social welfare schemes such as:
• Goa – Disaster management plan for flood-prone areas;
• J&K – Suitable locations for electric vehicle (EV) charging stations;
• UP – PAHUNCH portal identifies sites for high schools in unserved and needy areas;
• Gujarat –
• Finalization of alignment of the Gujarat coastal corridor (300 km)
• Gap Identification Tool for identifying land to construct new Aanganwadi
• Maharashtra – Planning of Samruddhi Mahamarg (SMM)
At the district level, data can be collated on various platforms. Sector-specific applications can
be developed to plan and implement projects, and integrate available digital platforms like Gati
Shakti, the State Remote Sensing Application Centre, the Road Accident Database, etc. Leveraging State Data Ecosystems for State and District Level Policy and Planning 30 Leveraging State Data Ecosystems for State and District Level Policy and Planning 31
SESSION 3:
TRANSFORMING DATA INTO
KNOWLEDGE – PROACTIVE AND
PREEMPTIVE GOVERNANCE
Indian School of Business
Avik Sarkar
Professor,
Session Chair
Saurabh Kumar TiwariBhawana Vashista
IASJoint Secretary, DBT Mission,
Cabinet Secretariat
Ashok Kumar Joshi
Director of Maharashtra Remote
Sensing Applications Centre
(MRSAC), Nagpur
PANELISTS Leveraging State Data Ecosystems for State and District Level Policy and Planning 32
Dr. Avik Sarkar is currently associated with the Indian School of Business (ISB), where he works
and teaches Data Science, Artificial Intelligence, Emerging Technology, and Public Policy. At ISB,
Dr. Sarkar headed the development of the India Data Portal, a one-stop portal for analyzing and
visualizing government data and working on the societal and policy aspects related to emerging
technologies like artificial intelligence trustworthiness, ethics, data privacy, and e-commerce policy.
Dr. Sarkar previously headed the Data Analytics Cell at NITI Aayog, where he helped develop
India’s first AI Strategy and roadmap for the use of data, analytics, and artificial intelligence for
governance and policy making across various sectors for India’s inclusive growth and led efforts
toward setting up the first high-performance computing-based Data Analytics Lab and Energy
Modeling Unit at NITI Aayog.
Opening remarks by Prof. Avik Sarkar, Session Chair
Various projects have already been undertaken to improve state governance based on
administrative data. A few of these projects have included the use of tax collection data to identify
fraud in corporate tax payments for the government of Assam, and the use of medicine delivery
data to reduce medicine shortages in government hospitals across Punjab.
State governments have a massive repository of data that can be used to transform existing
policies and make evidence-based decisions regarding the administration of districts and blocks.
Various states are undertaking different data initiatives to improve governance. This session
analyzes some examples of where data-driven narratives have achieved great results for both
state and central governments.
The central government has launched the Direct Benefit Transfer (DBT) Mission to provide
government subsidies and benefits to needy citizens. The DBT Mission extracted and merged
the necessary data from the JAM Trinity – Jan Dhan Account, Aadhar Card, and Mobile data.
Since the above data points are linked with each other, it becomes easy to eliminate redundant
as well as fraudulent data, and to streamline beneficiaries. DBT is an example of large-scale data
transformation, but because of its gigantic scale, it faces many data-related challenges: for example,
maintaining accurate transaction records; database management; removal of duplication; payment
failures; regular updating; standardized mechanisms for state benefit schemes; infrastructure
Avik Sarkar
Professor, Indian School of Business
SESSION CHAIR Leveraging State Data Ecosystems for State and District Level Policy and Planning 33
flexibility issues; and grievance redressal. Nevertheless, the DBT Mission is an active repository of
over a billion people garnering worldwide praise from various international organizations like the
World Bank and the International Monetary Fund.
Another excellent example of using available data to improve governance is how the Maharashtra
government is using GIS data to implement policies. The government collects geospatial data such
as geographic imagery and mapping technology, and they use this information for e-governance
projects to achieve various objectives, including groundwater mapping in remote villages;
mapping crop cycles and predicting harvest quality; analysis of agricultural market trends; and
mapping hilly areas within the states. Two critical uses of geospatial information are predicting
adverse weather, and natural calamities that can harm crops. The Maharashtra government has
developed a mobile app, MahaMADAT (Monitoring and Assessment of Drought using Advanced
Technology) to distill and predict the weather and inform farmers beforehand so they can prepare
accordingly. This can be helpful when predicting drought-like situations by the e-Panchnama app,
which tracks damage caused by drought; identifies people who need relief; and then keeps track
of the beneficiaries.
Aligned with the aim of data initiatives to improve governance, in 2019 the government of
Andhra Pradesh launched a Grama and Ward Sachivalayam (GSWS). These are local government
facilities set up in villages and wards to decentralize governance and provide policy makers with
access to every resident in each village of the state. These village secretariats cater to all the
requirements of citizens, including welfare benefits such as pension and monthly provisions,
administrative grievance redressal, and so on, through a single window system. o achieve this, the
AP government has set up various tech portals so that all the work at the government’s end can
be done together. ll data collected in silos by targeted portals is collated through a data exchange
platform. In this manner, the AP government has made many successful interventions through
the GSWS program, and the apps and portals designed under it. The government has adopted
the 116 indicators developed by NITI Aayog in line with the 16 Sustainability Development Goals
(SDGs). All portals created under the GSWS program collect and analyze data, which is then used
toward various social welfare objectives, such as eliminating anemia amongst school-going girls,
readmitting children who have dropped out of school, and so on. Leveraging State Data Ecosystems for State and District Level Policy and Planning 34
Ashok Kumar Joshi serves as Director of Maharashtra Remote Sensing Applications Centre
(MRSAC), Nagpur. He is also a Scientist/Engineer at the National Remote Sensing Centre, Indian
Space Research Organization (ISRO), Bengaluru.
Using GIS Data to Improve Service Delivery
The Maharashtra government
uses GIS data to effect
decentralized planning and to
implement policies. MRSAC is
the nodal agency for generating
and disseminating geospatial
information in the state. They
have had a huge repository of
geospatial data since 1988, which
they use it for e-governance
projects with various departments.
Some examples are:
• The MahaBHUMI project (Planning Department): For land use, transport, and water resources;
• SMART village–Groundwater Survey & Development Agency (GSDA): Mapping for soil and
water conservation structures;
• Maha-AgriTech Project (Agriculture Department): For crop mapping, predictive analysis,
and agri-market analysis;
• Hill Area Development Project (Planning Department): List of villages in core and buffer areas.
During the monsoon (Kharif) 2023, about 2,165 circle-wide Automatic Weather Stations (AWS)
were installed in Maharashtra. These services are integrated with the MahaMADAT (Monitoring
and Assessment of Drought using Advanced Technology) mobile app. Using this app, weather
information can be distilled and predicted; this can help farmers by providing them with sufficient
information regarding the Kharif season so that they can make appropriate crop plantation
decisions.
Ashok Kumar Joshi
Director of Maharashtra Remote Sensing Applications Centre (MRSAC), Nagpur Leveraging State Data Ecosystems for State and District Level Policy and Planning 35
This information system is critical during drought. The e-Panchnama app predicts drought-like
situations and periods; does damage assessment during natural calamities; prepares district,
Taluka and village-affected area reports; undertakes crop-mapping reports; identifies approved
beneficiaries for all Talukas; and gives a detailed Calamity Report of each village to the concerned
authorities. Once the relief is distributed, it keeps track of the beneficiaries and the relief amounts.
This approach can be adopted and applied across various sectors to create an evidence-based
relief and payment system for all government activities funded out of the state budget. Mobile
apps can collect field inputs of development; monitor activities; periodically assess department
implementation; correct and coordinate activities; and provide decision support. Leveraging State Data Ecosystems for State and District Level Policy and Planning 36
Bhawana Vashishtha is a member of the Indian Administrative Service.
Data Analytics for Localizing and Upscaling Implementation of the SDGs
The Government of Andhra Pradesh has launched a Gram/Ward Sachivalayam (GSWS), a one-
stop solution to address citizen requirements related to welfare schemes and deliver sustainable
services at doorsteps. Its objectives are to provide welfare benefits to all eligible beneficiaries
through a single window system; act as a supporting arm to Panchayats and local bodies; develop
policies in line with the SDGs; and redress citizen grievances at the secretariat level. To achieve
this, GSWS has a robust network of tech portals such as the Sustainable Goals Development
Portal, AP Seva Portal, and the Navasakam Beneficiary Portal.
Bhawana Vashista
IAS Leveraging State Data Ecosystems for State and District Level Policy and Planning 37
NITI Aayog identified 115 growth indicators covering 16 of the 17 SDGs. The government picked
these SDGs and aligned their health and education-related programs with them. In this project,
the government developed mobile apps and portals as digitized interventions. An integrated
dashboard that monitors and details district-level government interventions was compiled out
of state-level data to reflect all of this. This has allowed many successful interventions to be
executed and monitored by government officials. Here are two examples:
• Eliminating Anemia: Identifying and targeting anemia in girls at educational institutions. All
data points from respective departments (Health Department, GSWS) were collected and
collated.
• Putting Children Back in School: Massive survey data was gathered by volunteers on the
ground, and data was entered into the Volunteer App. A Student Info Portal was also
developed as a single enrollment source for each child.
The Navasakam Beneficiary Portal is a BIMS (Beneficiary Identification and Management System)
that connects government schemes to residents. To this end, it collects resident data on vehicle
ownership, land ownership, electricity consumption, tax status, employment status, and so on.
Disparate data collected by various departments are then collated through a data exchange
platform. Leveraging State Data Ecosystems for State and District Level Policy and Planning 38
Saurabh Kumar Tiwari is Joint Secretary at DBT Mission, Cabinet Secretariat. With a master’s degree
in Political Science, an LLB, and an MBA, he has wide-ranging experience in the government of
India and its state-owned entities. Since 2018, as Joint Secretary in the Cabinet Secretariat, he has
been overseeing the operations of the Direct Benefit Transfer Mission, and dealing with the legal,
technical, and administrative policy framework of DBT schemes across the ministries of the central
government as well as state governments.
Using Data to Improve the Targeting of Schemes and Public Services – DBT 2.0
and 3.0
The Direct Benefit Transfer (DBT) Mission
is a government initiative that provides
efficient, transparent, and targeted delivery
of government subsidies and benefits to
eligible citizens, whether in cash or in kind.
This talk summarizes the journey of DBT and
the generational changes in its evolution.
DBT has been made possible due to the
amalgamation of the JAM trinity, which
consists of the following data sources:
• JAN DHAN (160 million bank accounts,
including 507 million Jan Dhan
accounts)
• AADHAAR (1.38 billion citizens on the
identification system)
• MOBILE (more than 1.2 billion mobile connections)
DBT is constantly improved, and newer versions tackle the issues not addressed by the previous
version, such as improving eligibility verification and developing a social registry. DBT has been
applauded internationally by the World Bank and IMF for stellar work at providing support to
Saurabh Kumar Tiwari
Joint Secretary, DBT Mission, Cabinet Secretariat Leveraging State Data Ecosystems for State and District Level Policy and Planning 39
hundreds of millions of citizens; and as per their estimates by March 2021, it had reduced leakages
to 1.1 percent of GDP. Up to 2022, the cumulative estimated savings/benefits achieved was about
Rs 2,73,093 crores.
 DBT is an outstanding example of using data for efficient social governance. District-level data
is being harnessed in DBT version 2.0 for efficient beneficiary verification. Furthermore, social
registries have been created in states like Haryana, Rajasthan, Madhya Pradesh, and Karnataka.
DBT 3.0 aims to automate the determination of citizen eligibility for various schemes, enabling
suo moto targeting in welfare schemes, and the proactive sharing of information with citizens. The
interlinking of the databases of the Digital Public Infrastructure has created innovative solutions
for an efficient public service delivery ecosystem: Aadhaar Card to Mobile linking, Aadhaar Card to
Bank Account, Mobile to Bank Accounts and vice versa are some core examples. Linking multiple
databases also creates efficient and effective verification systems that can prevent fraud. A Local
Government Directory (LGD) is also used to identify beneficiaries and geographical areas that
need attention. Leveraging State Data Ecosystems for State and District Level Policy and Planning 40 Leveraging State Data Ecosystems for State and District Level Policy and Planning 41
SESSION 4:
EXPERIMENTS ON DATA DISSEMINATION
& PROMOTING ANALYTICS
Principal Economic Adviser
Government of India
Anna Roy
Nand KumarumMalarvizhi Veerappan
Program Manager &
Senior Data Scientist at
the World Bank
Deputy Director,
LBSNAA
Yamini Atmavilas
President,
The Udaiti Foundation
Chief Policy & Insights Ofﬁcer
at Janaagraha
Anand Iyer
Professor of Economics (HAG)
at IIM Lucknow
D Tripati Rao
Deeksha Supyaal Bisht
Deputy Director,
Dept. of Economic Affairs
Session Chair
PANELISTS Leveraging State Data Ecosystems for State and District Level Policy and Planning 42
D. Tripati Rao is currently Professor of Economics in the Business Environment Area at the Indian
Institute of Management, Lucknow. He has his PhD from the Department of Economics, University
of Mumbai under the auspices of RBI Monetary Economics Endowment Research Fellowship and
his M.Phil degree in Applied Economics from CDS, Trivandrum, JNU.
Opening remarks by D Tripati Rao, Session Chair
Given the phenomenal growth of connected devices, enhancing various means of communication
to enable end users is increasingly important. The core challenge in a highly connected environment
is how to design a smart data dissemination strategy for exchanging information between devices
based on the nature and type of events. This is also needed to facilitate public policy delivery
effectively.  Therefore, data usage analytics should aim for accessibility, accuracy, and ease of use
for a scalable aggregation of data. This session will be focused on these issues, drawn from the
experience of the panelists at the international, state, and meso (sectoral) levels.
The Indian government has launched data.gov.in, the Open Government Data Platform India. This
portal offers one-point access to datasets published by various government ministries. Though
it is a great initiative, because of a lack of continuity in uploading data onto the portal by the
ministries, it is not yet very effective. A large amount of data across domains has been made
available by ministries, but this data is shared in ministry websites in non-machine-readable format
(for example, as scanned PDF files); this makes data discovery and use a challenge for both the
government and the public. There are also many private initiatives collecting data across websites
and putting them in a central portal for better data dissemination: for example, – India Data Portal
by the Indian School of Business, Jano India by Swaniti Initiative, Open Budgets India Platform by
Civic Data Labs, Centre for Economic Data and Analysis (CEDA) by Ashoka University, How India
Lives, India Data Hub, etc.
In line with the open data mission, several state governments have launched their own CM
Dashboard, a step toward improving transparency by sharing several data points, which helps to
receive feedback on government officers working on all levels across state government offices.
D Tripati Rao
Professor of Economics (HAG) at IIM Lucknow
SESSION CHAIR Leveraging State Data Ecosystems for State and District Level Policy and Planning 43
Similarly, the CM Helpline is the grievance redressal mechanism combining over 50 Madhya Pradesh
government departments. Another redressal mechanism along the same lines is Samadhan Ek
Din, which recruits designated officers who are only geared towards grievance redressal and
provide disposal of grievances within the same day. State data is collected and uploaded into the
CM Dashboards to enable governments to make informed decisions based on data and engage
citizens in every step of governance.
Governments also use data to navigate unprecedented circumstances such as the COVID-19
pandemic. During this time, India’s government used high-frequency indicators such as fuel
consumption, freight and cargo trade, currency circulation, power consumption, and retail
mobility to monitor India’s macroeconomic situation. These indicators are regularly mapped
by the Monthly Economic Review of the Ministry of Finance’s Department of Economic Affairs
(DEA). The fact that this data was at hand helped shape the nation’s economic atmosphere during
a global resource crunch.
Other disaggregated data collected across sectors is integrated and used by governments to
transform the lives of citizens. The Aspirational Districts Program (ADP), in which data captured
across state dashboards in real time is analyzed to create a baseline ranking, and every district
in India is ranked accordingly, is one example. This gives state governments defined targets and
areas of improvement, to help localize governance efforts in otherwise ignored districts.
There is enormous scope for improving the mechanisms for data-sharing and dissemination by
government ministries, including the aspect related to discoverability and further data analysis.
Presently, most data are still collected in silos because each department or governing body is only
looking at a small data pie. Furthermore, the data collection methodology is riddled with errors
and inaccuracies. Efforts towards resolving this aspect of data governance need to be undertaken.
Standard mechanisms are required for data-sharing by ministries that consider citizen privacy,
and a one-stop data portal that presents data in a consolidated and machine-readable format.
Data in this format will be potentially richer in insights, and will push innovation more than any
other subset of data.
The World Bank is on a data dissemination mission: they believe in open, harmonized standards
for data interoperability. The World Bank Data Development Hub (DDH) has been put in place by
the World Bank to create and maintain a catalog of datasets out of all the data it collects through
its operations, projects, and research activities. The DDH has a team of curated technologists, data
scientists, statisticians, and managers who work toward making all the data collected by the World
Bank into a machine-readable, easy-to-access, easy-to-use, search-enabled, and downloadable
format. There are also guidelines for who can access data, and the licensing of datasets.
NITI Aayog has launched a flagship data portal, the National Data Analytics Platform (NDAP),
to facilitate and improve access to Indian government data. Citizens, organizations, and
researchers can use NDAP to access datasets from India’s extensive administrative landscape. All
the foundational datasets from the central and state governments are available on NDAP in a
machine-readable format. The aim of NDAP is to provide last-mile delivery, and enable access to
government data through an intuitive, user-friendly platform.
NDAP collects all government data in one place. It has a powerful search engine that promotes
ease of access and discovery for the end user. All data is first standardized and cleaned to make
it available in a cohesive, readable format. NDAP’s features are very user-centric, so it increases Leveraging State Data Ecosystems for State and District Level Policy and Planning 44
user interactivity with the portal. All available data is interoperable across ministries and state
departments; that is, it gives out streamlined datasets to end users. Furthermore, these datasets
will have advanced search-query-enabled, and available in downloadable formats. NDAP is already
a powerful data tool that disseminates data in the most enabling and innovation-centric way. Still,
specific improvements can move India’s governance to new heights; and this can only be achieved
through data.
One improvement needed is gaining access to city datasets. Forty percent of Indians are going
to live in cities by 2030. City governments are the closest to the citizens; therefore, city-level
data is crucial for inclusive and equitable governance and development. The City Data Analytics
Platform (CDAP) is a portal modeled as an extension to NITI Aayog’s NDAP; it will focus on
collating urban datasets from across the nation with the support of state governments. Currently,
most data are in silos within sectors: planning, electricity, tourism, hospitality, agriculture, revenue,
and so on. CDAP will interweave all this data to form cohesive datasets containing cross-sectional,
spatialized, and time-series data. All of this information will be presented in clean, state-of-the-
art, visualization-enabled datasets. All this information will be presented in clean, state-of-the-art,
visualization-enabled datasets.
Another area where NDAP can improve is gender-based data. Today, gender data is fragmented
across various administrative landscapes of state governments. The Udaiti Foundation is
collaborating with NITI Aayog to create The Gender Data portal. Their aim is to provide value-rich
women-centric datasets that will be helpful in making decisions related to women’s economic
empowerment. The Gender Data Portal will provide gender-segregated data across eight key
themes, including employment, education, entrepreneurship, health, and ownership of assets.
Workshops are being conducted to brainstorm what the Gender Data Portal should contain, and
how it can help the future of women citizens. Leveraging State Data Ecosystems for State and District Level Policy and Planning 45
Anna Roy is a 1992-batch officer of the Indian Economic Service (IES) serving as Principal Economic
Adviser, Government of India. She received her education from Shri Ram College of Commerce,
Delhi University, and the Delhi School of Economics. She has been a lecturer at Delhi University and
worked at the Energy and Resource Institute (TERI) before joining the IES. She has worked in the
Ministry of Finance, the Ministry of Civil Aviation, and NITI Aayog.
Overview of NDAP 2.0: Toward Enabling Data Analytics
The NDAP National Data Analytics Platform (NDAP) is the flagship data portal launched by NITI
Aayog, which facilitates and improves access to Indian government data. Its vision is to improve
last-mile delivery and enable seamless use of published government data through an intuitive,
user-friendly platform that:
Anna Roy
Principal Economic Adviser, Government of India Leveraging State Data Ecosystems for State and District Level Policy and Planning 46
• Collates data from 3,000+ sources in one place;
• Contains standardized, clean, easily downloadable data;
• Is a powerful yet simple search engine with user-centric features.
The datasets are identified from ministries and sectors and use-case scenarios, and are onboarded
onto NDAP. Granular datasets across states, districts, blocks, and villages are also included, to
ensure last-mile access. NDAP combines datasets from multiple sources into an intuitive, single
dataset where all data is accessible in a machine-readable format and is keyword search enabled.
NDAP provides a rich user experience through interactive visualizations so that users can create
maps, and bar and line charts, using any dataset and indicator. It also aims to provide the highest
spatial and temporal resolution data possible.
Among the numerous use-case scenarios of NDAP, here are a few:
• Jharkhand: Merging healthcare location data with population census data to identify where
new healthcare centers are needed.
• Karnataka: Merging district-wise National Health Survey data with the district information
system for education to calculate the estimated number of anemic girls in schools.
• National Level: Combining district-level climate vulnerability indicators (focusing on per
capita income) and National Family Health Survey data (focusing on overweight or obese
women) to plan state nutrition programs. Leveraging State Data Ecosystems for State and District Level Policy and Planning 47
Anand Iyer is the Chief Policy & Insights Officer at Janaagraha. Over the last 22 years, he has worked
across state and central government in urban development; in the private sector consulting in land,
infrastructure, and building; in academia and in practice, in architecture and design. He now works
with a civil society organization in citizenship and democracy.
City Data Analytics Platform (CDAP) 2.0: City-Level Data
City governments are the closest to the people and have the maximum potential to impact lives.
Analytics on city-level data will aid data-based decision-making for inclusive, sustainable, and
equitable urban development.
Anand Iyer
Chief Policy & Insights Officer at Janaagraha Leveraging State Data Ecosystems for State and District Level Policy and Planning 48
Currently, the data available across various platforms is fragmented, and is specified to central
and state schemes, or development statistics. CDAP (the City Data Analytics Platform) will be
built on the pattern of NITI’s National Data and Analytics Program, and will focus on synthesizing
urban datasets across departments and sectors – streets, polling areas, wards, zones, districts,
states, and unions. All of the data will be presented in a state-of-the-art visualization format to
make it user-friendly and downloadable. Ethical parameters will be kept in mind so that citizen
privacy is upheld.
In this way, CDAP will have a comprehensive account of several types of datasets:
• Cross-sectional data, including that from nonurban departments, that affect quality of life
issues in urban areas (livelihoods, access to services, quality of infrastructure, etc.)
• Spatialized Data across districts, states, and cities
• Time-Series Data across annual quarterly collections and several decades.
CDAP will focus on the needs of different stakeholders, prioritizing urban governance decision-
makers, and will bring our most relevant analytics, while heavy data can limit visibility and access.
Some administrative boundaries may change over time, which must also be considered when
collating time series data
The layered and localized nature of our urban issues makes it imperative to adopt a place-based
approach to urban planning. Initiatives and policies need to be tailored to the specific attributes
and needs of neighborhoods, aiming for inclusivity and sustainability. Inadequate data at the city
level is a challenge, and even what little exists is organized across sectoral silos and distinct spatial
units, rather than along a consistent unit of local governance. This makes it impossible to overlay
the datasets for meaningful analysis.
Local governments need place-based data for holistic urban planning and sustainable, equitable
development. This will benefit many user groups: local governments, urban planners, CSOs/CBOs,
researchers, academicians, businesses, citizens, infrastructure and utility providers, public health
agencies, transportation service providers. Indian cities have only scratched the surface when
it comes to data-driven innovations. As cities expand and evolve, commensurate improvement
in data management practices becomes necessary. CDAP is an early but essential step in that
direction. It will enable informed decision-making, optimization of resources, and address urban
challenges with precision, while promoting transparency, accountability, and evidence-based
policymaking. Leveraging State Data Ecosystems for State and District Level Policy and Planning 49
Yamini Atmavilas is a gender sector leader with a track record of building impactful partnerships
for advancing gender justice in the public, social, and philanthropic areas. She is currently President
of the Udaiti Foundation, which seeks to advance women’s employment, entrepreneurship, and
agency.
Gender Portal on NDAP 2.0
Gender data is currently fragmented across economic, social, and health data. In May 2022, NITI
Aayog launched the National Data Analytics Platform (NDAP) to improve the use of published
government data. The Udaiti Foundation has collaborated with the NITI Aayog-NDAP team and
the World Bank to develop a gender layer within NDAP: The Gender Data Portal. The vision is to
make NDAP the foundation for data-informed conversations and decisions on women’s economic
empowerment. NDAP breaks the siloed view of data that leads to inefficient and piecemeal
decision-making.
The Gender Data Portal has been designed to provide users access to 89 gender indicators
spanning eight key themes:
• Work & Employment
• Education, Training, and Skills
• Entrepreneurship
• Health & Demographics
• Decision-Making
• Ownership of Assets / Access to Services
• Leadership
• Violence
A design thinking workshop was conducted in October 2023 to solicit insights for the Gender Data
Portal. Members from the Ministry of Women & Child Development, UN Women, the Population
Yamini Atmavilas
President, The Udaiti Foundation Leveraging State Data Ecosystems for State and District Level Policy and Planning 50
Council of India, the National Council for Applied Economic Research, and other vital organizations
participated, and suggested specific use cases where the above indicators can be derived to
support policy and programs.
One interesting finding was that the workshop participants tended to look at the performance
of each indicator in correlation to other indicators rather than looking at them independently.
Budget also emerged as an essential theme: participants said they wanted a separate category to
address indicators that fall under budget. It was also noted that gender-segregated data at the
state and district levels would accelerate the achievement of “Goal 5 – Gender Equality” in India. Leveraging State Data Ecosystems for State and District Level Policy and Planning 51
Malar Veerappan specializes in large-scale data governance, management, analytics, and technology
implementations, and brings a wealth of experience gained from collaborating with countries
across Africa, Asia, Latin America, and Europe in various sectors. She has coauthored influential
reports like “Digital-in-Health: Unlocking Value for Everyone” and the 2021 World Development
Report, “Data for Better Lives.” She has also led initiatives to modernize the World Bank’s data
architecture and launch its Open Data Initiative. Her role in establishing the Bank’s Data Council
and Development Data Hub has significantly advanced data-sharing efforts.
International Experience in Data Dissemination
Effective data dissemination practices are crucial for enhancing data use and reuse. Good
dissemination practices not only enhance transparency but also provide valuable insights that are
helpful in government decision-making; foster citizen trust in government data and institutions;
and facilitate a favorable capital market to foster growth.
Malarvizhi Veerappan
Program Manager and Senior Data Scientist at the World Bank Leveraging State Data Ecosystems for State and District Level Policy and Planning 52
Increased data use can lead to improvements in data quality over time. When more people use
data, there are more eyes on the data, which can lead to the identification and correction of
errors or inconsistencies. Additionally, increased use may prompt organizations to invest more
resources in data collection, storage, and maintenance, which can further enhance data quality.
As data becomes more integral to operations and decision-making processes, there’s typically
greater emphasis placed on ensuring its accuracy, completeness, and reliability.
The World Bank has been a strong advocate for the data agenda for many years. The launch
of the flagship World Development Report 2021, “Data for Better Lives,” the first such report
entirely devoted to data, is an example of the Bank’s commitment to this agenda. Since its launch
in 2010, the World Bank’s Open Data Initiative has provided free and open access to the Bank’s
development data. The Bank has continuously updated its data dissemination and visualization
tools, and has supported countries in launching their own data initiatives.
Today, data is the number-one reason people visit the World Bank’s website, accounting for over
30 percent of its overall traffic. The Bank’s data catalog provides a fully searchable central location
for users to access various types of data, including microdata and geospatial data assets.
The World Bank’s commitment to evolving into a data-informed organization is centered on
embracing a digital-first approach by moving away from printed reports to digital dissemination
practices that can reach wider audiences. This transition is coupled with a focus on enhanced data-
sharing, and (re)use of the large volumes of development data it generates. The core principles
guiding our approach include fostering a culture of data-sharing and maximizing dataset use and
reuse; improving interoperability; and promoting data literacy.
A significant milestone was the establishment of the Development Data Hub (DDH), the Bank’s
first integrated data hub. DDH connects datasets across the organization, and is governed by a
data classification policy. This initiative rests on three key pillars: policies, platforms, and people.
It encompasses transparent policies and processes; data and metadata standards and protocols
for dissemination; and clear guidelines on data access and licensing, along with platforms for
data storage, management, and access. Additionally, it relies on a dedicated data management
team comprised of the technologists, statisticians, data scientists, and program managers who are
essential for its success.
All of these enhancements are continuously and consistently pursued with the goal of facilitating
easy access and (re)use of our data; expanding its reach for productive purposes; and fostering
innovation and collaboration, empowering everyone to shape a brighter future together. Leveraging State Data Ecosystems for State and District Level Policy and Planning 53
Nand Kumarum is an IAS Officer of 2008 Batch. He belongs to Madhya Pradesh Cadre. Currently
he serves as Senior Deputy Director at LBSNAA, Mussoorie.
Importance of Feedback Using Service Delivery Data & the CM Dashboard
Feedback is a crucial part of system improvement for governments. Sources of feedback include
the CM Helpline, Samadhan Online, the CM Dashboard, News Media Management, and Settlement
Analysis. Insight gathered from feedback has led to many successful action plans, including the
following:
• CM Helpline: The Madhya Pradesh CM Helpline Program is a centralized grievance redressal
system combining 55 governmental departments. It also integrates all helpline call centers
across all districts.
• Samadhan Online: A digital system that shortlists the complainant’s review and the action
mechanism by the Chief Minister’s office. Departments are graded for their grievance
redressal, and top performers are recognized.
• CM Dashboard: Information from different applications of state citizen services is collected,
integrated, analyzed, and uploaded to the dashboard for the user. The dashboard has
application modules across various departments and districts.
• Service Notification & Process Re-engineering: First, the departments’ services are studied,
and a Service Notification is released, leading to re-engineering of the process, after which a
to-be solution is proposed. A revised service is designed and rolled out after formulation and
testing. Finally, the performance is managed.
• Samadhan Ek Din: Thirty-four services are being provided under this initiative, which are
implemented by designated officers appointed at Lok Seva Kendras. Government Process
Re-engineering has been done for these services. It has a 99.8 percent same-day disposal rate.
• Single Citizen Database (SCD): SCD is a verified demographic information of citizens via
Common API that maps each citizen family and monitors the benefits provided to them.
Citizens can easily discover and access government schemes, while the government can
provide demand-based governance.
Nand Kumarum
Deputy Director, LBSNAA Leveraging State Data Ecosystems for State and District Level Policy and Planning 54 Leveraging State Data Ecosystems for State and District Level Policy and Planning 55
Deeksha Supyaal Bisht is an officer of the Indian Economic Service, 2018 batch. She is currently
posted as Deputy Director in the Department of Economic Affairs, Ministry of Finance, where she
analyzes labor market trends, poverty, inequality, health, and education.
Data for Development
When used well, data can revolutionize the way government functions. The government of
India uses data to monitor and assess every sector, ministry, and industry. During the COVID
pandemic, the government used high-frequency indicators like domestic vehicular sales, UPI and
ATM transactions, crude oil supply, and foreign exchange reserves to monitor the macroeconomic
situation. These datasets enabled efficient decision-making during a period of extreme global
uncertainty.
In the social sector, e-governance initiatives, social initiatives, and central government programs
such as GST e-way bills, the NITI Aayog Multidimensional Poverty Index, MGNREGS data, the
Jal Jeevan Mission, and the Swachh Bharat Mission capture real-time data, analyze datasets,
and present them in an accessible, downloadable format. NDAP is the centralized platform for
government data, capturing data from various sectors, ministries, time, and space. Government
officials and researchers can use NDAP for various purposes, such as tallying industry credit with
industry growth, or predicting climate vulnerability. Disaggregated data is also used to identify
specific pockets of deprivation where aggregate numbers may be concealing the granular picture
at the state, district, or village level. For example, the national poverty rate is around 15 percent,
but there is a wide range around this figure. Governments gather district-wise data (such as the
District MPI Score) to identify and focus their efforts on the areas where they are most needed.
Today, governments make heavy use of local-level data analytics to provide tailor-made solutions
for their citizens. For example, Montgomery, Alabama has introduced new software to identify
urban decay using census, utility, and building data; and Tempe, Arizona has been using water
analytics to collect data on opioid abuse.
Deeksha Supyaal Bisht
Deputy Director, Dept. of Economic Affairs
Government of India Leveraging State Data Ecosystems for State and District Level Policy and Planning 56
Data is at the foundation of the Aspirational Districts Program (ADP), which has transformed the
lives of 25 crore people in 112 districts. Data was a critical input from identification to planning to
real-time monitoring of the steady progress of aspirational districts. Forty-nine sector indicators
were identified, then a baseline ranking was released, and the dashboard captured data in real
time. Inspired by ADP, the Aspirational Blocks Program was launched recently to drill down further
into each district. Leveraging State Data Ecosystems for State and District Level Policy and Planning 57 Leveraging State Data Ecosystems for State and District Level Policy and Planning 58
RECOMMENDATIONS
AND WAY FORWARD
The deliberations throughout the sessions of this Forum have highlighted the vast potential for
accelerating social and economic development by adopting data-based methods. Some states
have already taken significant data-led initiatives toward improving governance; this provides a
blueprint that other states can adopt with the support of NITI Aayog.
The following are some of the key initiatives state governments can adopt to leverage data for
state and district-level planning and policy making.
State Open Data Policy: This policy advocates for interoperability, highlighting its crucial role in
optimizing data collection and minimizing redundancy, and provides clear guidelines for how to
realize it. An Open Data Portal that contains high-value datasets at the most granular level on
various sectors and departments—for example, transport, vehicular, online sales, and weather
data--can be created. This can help financial firms, start-ups, and industry players innovate using
the available data, and can give insight into economic growth at the state level.
State Data Governance: A state data governance policy can enhance the quality and use of non-
personal data so that governments and researchers can access high-quality data while ensuring
privacy and trust. This would lead to better-quality data and improved operational efficiency,
collaboration and communication, policy and decision-making, service delivery, transparency and
accountability, as well as reduced costs, greater efficiency, and citizen engagement.
NITI for States: NITI Aayog has been engaged with some states to improve governance and
citizen welfare. In the future, states will also be able to engage with NITI Aayog in accelerating
development activities, especially those that are evidence-based policy making.
State Data Portal Based on NDAP: The National Data Analytics Platform (NDAP) is a treasure
trove of 2000+ government data sources that consists of data from all states. States can access
data specific to them and create a State NDAP based on the same architecture and technical stack.
State governments can also add other administrative or state-specific data points to enhance and
customize their own data portals.
Identification of Use Cases: State planning departments must continuously engage with their line
ministries in order to identify the critical developmental, policy, and/or governance issues that a
particular ministry is facing. Based on these use cases, the planning or data department must first
identify the availability of suitable data sources to resolve these issues. If specific necessary data
points are missing, the state can start collecting those data, or can explore alternative “Big Data”
sources to act as a proxy for the missing data aspects. Leveraging State Data Ecosystems for State and District Level Policy and Planning 59
Collaboration with Academia or Multilateral bodies: Often the state government doesn’t have
the skilled resources needed to start analyzing the data. It is always a good idea to find a relevant
partner with expertise in data collection and analysis who can help guide the data collection
process, put quality measures in place, and develop the analytical use cases required for planning
and policy making. This will help states jump-start their data-based policy-making journeys;
interpret the initial results; and then scale up their efforts.
Attend Data Forums: The Data Forum will be organized annually by NITI Aayog under its State
Support Mission initiative. State nodal officers will be identified to enable year-long engagement
leading up to the next forum, which will then be designed more collaboratively. Based on interest,
regional forums may also be organized as feeder forums for the national forum.
CONTACT DETAILS
S.No. NameOrganisation Email ID
1 Ms. Anna Roy NITI Aayog annaroy@nic.in
2 Mr. Mohd Zubair Ali HashmiNITI Aayog zubair.hashmi@ias.nic.in
3 Mr. Liankhankhup Guite NITI Aayog khup.guite15@gov.in
4 Mr. Thomas Danielewitz World Banktdanielewitz@worldbank.org
5 Ms. Malarvizhi Veerappan World Bankmveerappan@worldbank.org
6 Ms. Shreya Dutt World Bank sdutt@worldbank.org Notes Notes Designed by: