Enabling Data-Driven Real-Time Governance
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The document outlines the capabilities of SocialCops' data-driven platform for real-time governance, focusing on data collection, visualization, and analytics to address challenges faced by various sectors such as education, healthcare, and rural development. It discusses multiple case studies where the platform has been successfully implemented across 150+ organizations and in 7+ countries, showcasing its central role in improving decision-making and tracking progress in diverse initiatives. The platform integrates various data sources and employs machine learning to facilitate effective data analysis and reporting.
Enabling Data-Driven Real-Time Governance
- 2. Outline 1. The problem we are solving 2. Our platform 3. Data visualization capabilities 4. Data cleaning, preparation, and analytics capabilities 5. Data collection capabilities 6. Case studies
- 3. It’s difficult to find answers today… How are villages changing over time? Where is the money being spent? What is the progress across sectors? How are different outcomes affected? DEPARTMENTS ARE NOT SYNCED DATA STORED IN HARD COPIES DATA STORED IN MULTIPLE FORMATS TOO MANY DATABASES DATA IS NOT SEARCHABLE DATA IS DIFFICULT TO CONSUME How is data changing over time?
- 4. MIS Softwares Department reports Online Portals NIC Apps Department Officers Beneficiaries Organizations One Centralized Platform Information is in silos. Can it be joined? ?
- 5. The only data platform that can do it all. SocialCops’ platform puts all data in one central platform and lets you use this data in different ways.
- 6. An end-to-end decision-making platform CENTRAL DATABASE MIS, department databases, and other relevant databases Real-time cleaning and processing engine Machine learning algorithms generating insights Action tracking mechanisms Multi-structured big data analysis Field inspectors Web data entry MIS database PDFs, Excel SMS, IVRS, USSD Real-time querying In-depth searching Web dashboard Mobile dashboard Regular reports 1. Raw data and data sources 2. Data transformation, analysis, and management 3. Data visualization
- 9. Categories of visualizations Multi-parameter dynamic querying1 Village level multi-indicator mapping 2 Dynamic index generation3 Hyper local geo-clustering4 Natural language enabled querying5 Household level GPS mapping6 Instant filter- enabled reports7 Real-time data aggregation8 Progress monitoring and tracking 9
- 10. Village level multi-indicator mapping1 Select parameters1 Colored geo- clusters2
- 11. Multi-parameter geo-querying The villages matching the query are coloured green. 2 Select multiple queries1Change queries2 Instantly see results3
- 12. Real-time dashboard aggregation Select GP, block, district, etc.1 Change tabs to see more details2 Download data or graph3 3
- 13. Household-level GPS mapping Select required indicator3 Choose a household2 Zoom into the households1 4
- 14. Progress monitoring and tracking Select a village name1 Search for any specific indicator2Download custom reports3 5
- 15. Hyper local geo-clustering Select indicators1Zoom into areas2 Click to get more information3 6
- 16. Natural language querying Type out a query1 Filter your data2 Generate relevant graphs3 7
- 17. Instant filter-enabled reports Select an indicator1 Select datasets2 Generate graphs and reports3 8
- 18. Dynamic index generation Select a district1 Click to see in- depth indicators2Hover over to get quick insights3 9
- 19. DATA CLEANING, PREPARATION, & ANALYTICS CAPABILITIES 2
- 21. Load datasets and highlight changes in the columns 1 Select operation from automatic suggestions 2 Record required operations and clean similar datasets 3
- 22. Categories of analytics Multi-polar cloud- based analytics1 Machine learning algorithms2 Trajectory data mining & pattern recognition 3 Predictive analytics4 Cognitive computing5 Fluid analytics6
- 23. DATA COLLECTION CAPABILITIES ▪ Mobile app ▪ Citizen crowdsourcing ▪ Web form ▪ SMS, USSD, IVRS 3
- 25. 1. Create questionnaire on Web Dashboard 2. Apply skip logic, validations, and conditionality 3. Renders Android app in seconds 4. Enter accurate data offline
- 26. Citizen-based crowdsourcing app deployed for Swachh Bharat Mission
- 27. CASE STUDIES We are proud to have deployed our platform for over 150+ organizations in 7+ countries.
- 28. PROBLEM STATEMENT Developing budgets and aligning village development plans to create a model constituency for 264 villages Government of AP (Krishna district) and Tata Trusts leveraged our platform to conduct census data collection and analyze the data in real time. Spread 1 million people, 264 villages Granularity Household level Step 1 Data Collection Via our mobile-based data collection platform Step 2 Data Quality Checks and Analysis Happening in real time Step 3 Data Visualization Map-based dashboard (village level) Map-based querying Village profile dashboard Household level geo-dashboard 1
- 29. A dashboard showing schemes eligibility for households in a village in Vijayawada
- 30. PROBLEM STATEMENT Tracking progress of the Sansad Adarsh Gram Yojana in real time from 700 villages Ministry of Rural Development is leveraging our platform to track the progress of and monitor impact for SAGY villages Spread 700 villages Granularity Village level Step 1 Data Collection Via our mobile and web-based data collection platform Step 2 Data Quality Checks & Analysis Happening in real time Step 3 Data Visualization Real-time dashboard for tracking and progress indicators 2
- 31. A dashboard showing real-time village progress using data filled by nodal officers.
- 32. PROBLEM STATEMENT Comparing Right To Education parameters across India to understand which districts need more funds and attention Oxfam India leveraged our platform to visualize secondary education data across 150+ indicators Spread 14 lakh schools Granularity District level Step 1 Data Aggregation 150+ variables Step 2 Data Indexing, Cleaning, and Preparation Happening in real time Step 3 Data Visualization Map-based dashboard (district level) Map-based comparison 3
- 33. A dashboard comparing districts across India with RTE indicators
- 34. PROBLEM STATEMENT Knowing which districts to invest in to improve quality of life for small and marginal farmers in India The Bill and Melinda Gates Foundation leveraged our platform to visualize secondary agriculture data across 233 indicators States Bihar, Odisha, and Uttar Pradesh Granularity District level Step 1 Data Aggregation 2000+ variables Step 2 Data Indexing, Cleaning & Preparation Happening in real time Step 3 Data Visualization Map-based dashboard (district level) Map-based comparison 4
- 35. A dashboard comparing districts on agriculture parameters
- 36. PROBLEM STATEMENT Increase efficiency and effectiveness of delivery of key RMNCH +A services to improve healthcare facilities in UP Acting as BMGF’s Technical Support Unit, IHAT set out to improve primary care services. This required continuous assessment of the current state of facilities and competency of staff. Spread 1113 healthcare facilities across 150 blocks in Uttar Pradesh Step 1 Preliminary Data Collection Via our mobile-based data collection platform Step 2 Monitoring of Facilities Facilities monitored over 4 cycles with a time period of about 6 months per cycle Step 3 Assessment 5
- 37. Helping Indian Health Action Trust to collect labor monitoring data to curtail maternal mortality Collect captures more than 400 delivery-related data points in real-time in Uttar Pradesh. One survey can last even 28 hours.
- 38. PROBLEM STATEMENT Using mobile technology to optimize disaster relief efforts during the Nepal Earthquake6 Step 1 Registering donors Via our mobile-based data collection platform Step 2 Generating e-receipts Based on the information entered, Goonj donors receive an e-receipt via SMS or email. Step 3 Tracking of relief material Goonj, an NGO, focuses on providing relief material to disaster-stricken areas by mobilizing inventory at large scale. Spread Operations supported over 3 months
- 39. GOONJ uses Collect to manage internal logistics and disaster relief operations for the Nepal Earthquake. GOONJ turns over 5,00,000 kg of throwaway waste into traditional mattresses/quilts across 21 Indian states.
- 40. Featured on Fortune’s 2015 and 2016 lists of 40 under 40. RECOGNITION Featured on Forbes India’s 2015 list of 30 under 30. One of the top 10 emerging companies of 2015.
- 41. Including: United Nations World Youth Summit Award Microsoft Global Social Entrepreneurship Competition IBM Smarter Planet Challenge & some more from IITs, IIMs & NUS. The work we’ve done at the intersection of technology, data and people to have a positive influence on society have won us awards at the global level.
- 42. Rajan Anandan Managing Director, Google India Investor & Advisor “In terms of scale, from his portfolio, Rajan Anandan (MD, Google India) is particularly bullish on SocialCops. SocialCops sees its five-year goal as being able to power products like Google Maps with social data” – Economic Times Dr. Hema Divakar Former President, Federation of Gynecological Societies of India Anurag Banerjee General Manager, Mobilewalla APAC (Previously MD, Jana) Naman Pugalia Previously Policy Advisor, Google India OUR ADVISORS
- 43. Bernise Ang Singapore Woman of the Year 2011, Founder, SYINC Carol Sanford Innovation Advisor Google; Award Winning Author Pankaj Jain Venture Partner, 500 Startups OUR ADVISORS Manoj Menon Managing Director, Frost and Sullivan APAC Investor & Advisor “We are limited only by our imagination in terms of how technology can address the challenges facing humanity. SocialCops is well poised to play an important role in helping shape a better future”
- 44. “IT’S CREATING A VOICE FOR THE PEOPLE” - Fast Company “TRACKING DATA THAT SOLVES PROBLEMS IS THEIR MISSION” - Economic Times “DATA SOURCED FROM THE GRASSROOTS AND INSIGHTS FROM IT CAN YIELD FOCUSED AND SPEEDY PUBLIC INTEREST DECISION MAKING” - LiveMint PRESS & MEDIA
- 45. 150+ Organizations 7+ Countries 40 Million Primary data points 1 Billion Secondary data points