In a move aimed at strengthening transparent and efficient governance, the Delhi government plans to roll out DARPAN 2.0, an advanced unified performance-monitoring dashboard developed by the National Informatics Centre under the Ministry of Electronics and Information Technology, according to an official statement issued on Monday. Designed as a real-time, analytics-driven platform, DARPAN 2.0 will provide decision-makers and government departments with a consolidated view of key schemes and public services, enabling faster and evidence-based decision-making. The platform seeks to address the long-standing issue of siloed and inconsistent data by integrating multiple management information systems into a single, visually intuitive interface.

DARPAN 2.0 will feature department-wise Key Performance Indicators, live progress tracking, early-warning indicators and comparative analytics, aimed at improving accountability and inter-departmental coordination. The existing centralised DARPAN model will be customised for Delhi, with priority schemes integrated through secure application programming interfaces. The rollout is planned in phases over 12–16 weeks, followed by comprehensive training for nodal officers across all departments.

Commenting on the initiative, Delhi IT Minister Pankaj Kumar Singh said DARPAN 2.0 represents a significant step towards accountable and data-driven governance in the national capital. He noted that by breaking down data silos and providing real-time insights into departmental performance, the platform would empower decision-makers to act swiftly and enhance service delivery. Under the guidance of Chief Minister Rekha Gupta, he added, the government will use the tool to ensure that welfare schemes reach citizens in an effective and transparent manner. The key features of DARPAN 2.0 include real-time performance insights to improve governance, faster decision-making through integrated analytics, stronger cross-departmental coordination, and enhanced accountability via KPI-based monitoring and early identification of implementation bottlenecks.