Category: Use Cases
Superset district profile Template
factor profile ui state selection testing
Superset
Education
Secondary School Dropouts
Data-driven analysis of factors influencing secondary school dropout outcomes
Agriculture
Agriculture Price Fluctuations
Data-driven analysis of factors influencing agricultural price fluctuations
Use Cases
Secondary School Dropouts(superset)
Secondary School Dropout
Secondary school dropout remains a critical challenge, impacting long-term educational attainment, workforce readiness, and socio-economic development. To address this issue proactively, this use case leverages data-driven modeling techniques to identify patterns, risk factors, and vulnerable student segments associated with dropout at the secondary education level.
Modeling Approaches Used
1. Sensitivity Modeling
The Sensitivity Modeling dashboard is designed as a tool to analyze and reduce school dropout rates across India by identifying high-impact factors at the state and district levels. It enables us to explore dropout trends, understand how different factors influence the dropout rate, and perform what-if scenario analysis for data-driven decision making.
2. Prescriptive Modeling
Prescriptive modeling answers one key question: “What changes are needed to reach a target dropout rate?” The model recommended changes for each factor are called prescribed values. Prescriptive modeling considers all factors together and finds a combination that best supports achieving the target.
We have employed both modeling approaches and developed a sequence of dashboards tailored for two distinct user groups: district-level and state-level officials.
For access to the detailed user manual, click here.
1(a). District View (District Profile)
Under the District View, users can drill down from the All India Dashboard to a district-wise dropout map and access detailed district profile, results in a District Prescription module. This section supports both what-if analysis and what-to-do analysis, enabling users to simulate changes across key factors and assess their relative impact on reducing secondary school dropout rates. The what-if analysis helps identify which factors contribute most significantly to lowering dropout rates within a district, while the what-to-do analysis translates these insights into actionable, data-driven recommendations to guide targeted interventions and policy decisions.
1(b). District Prescriptive
2(a). State View (Factor Profile)
Under the State View, users navigate from the All India Dashboard to a district-wise dropout map, followed by a Factor Profile that enables what-if analysis to assess which factors contribute most significantly to reducing dropout rates across districts within a state. This is complemented by the Intervention Index, which supports what-to-do analysis by quantifying how much each factor needs to change to achieve a targeted reduction in secondary school dropout at the state level. These insights feed into the State Prescription and State Budget modules, helping policymakers prioritize interventions, allocate resources efficiently, and design evidence-based strategies tailored to state-specific needs.
2(b). All India Intervention Index, State Prescriptive and State Budget
The Intervention Index shows how much support or action a state needs, based on the model’s suggestions. Darker colors mean the state needs more intervention, while lighter colors mean less intervention is required. This makes it easy to quickly spot which states need the most attention.
Agriculture Price Fluctuations
Tomato Price Story
The dashboard presents the monthly supply-demand dynamics underlying wholesale tomato price movements in India for FY2019–20 to FY2023–24. It is built around the Supply-Demand Ratio (SDR) derived from the All India Tomato Balance Sheet, which brings together production, market arrivals, post-harvest losses and estimated consumption demand. An SDR above one indicates surplus availability, while a value below one reflects relatively tighter supply conditions. The dashboard compares changes in tomato availability with movements in the Wholesale Price Index (WPI), providing context on how periods of surplus and shortage correspond with price movements. It also places these movements against major market events across the study period. The analysis establishes SDR as the key market indicator and provides the basis for assessing interventions such as cold storage, Operation Greens and processing offtake.
Tomato Policy Simulator
The dashboard translates the tomato price framework into a policy decision-support tool. Using the validated SDR elasticity from the econometric model, it simulates how changes in effective market availability could influence wholesale tomato prices under alternative intervention scenarios. The dashboard focuses on Operation Greens, allowing users to vary the price-crash trigger threshold and examine the resulting frequency and expected price recovery. Lower thresholds represent earlier intervention, potentially providing greater protection against distress sales but requiring more frequent deployment of public resources; higher thresholds delay intervention but reduce the frequency of support. The simulations are intended to illustrate trade-offs rather than prescribe a single optimal threshold. Together with the broader framework, the tool can support assessment of Operation Greens alongside cold storage and processing offtake as different mechanisms for managing seasonal tomato surpluses.
