Digital Planning Cell – Maharashtra

Town Planning Directorate · Statewide spatial intelligence · 2024–ongoing

E-governance & spatial planning systems

Project overview

The Digital Planning Cell supports the Town Planning Directorate of Maharashtra in building statewide spatial data infrastructure and digital planning workflows. The programme strengthens how planning authorities access, maintain, and use authoritative maps, layers, and development-control information—so that statutory processes move from paper-heavy silos toward traceable, shared intelligence across districts and agencies.

Strategic context

Effective urban and regional planning at state scale requires consistent data standards, clear custodianship, and realistic phasing of technology and reform. This engagement places as much emphasis on institutional roles, training, and change management as on software—aligning digital investments with existing rules, staffing, and oversight so that benefits persist beyond initial deployment.

Statewide spatial planning and digital planning cell

Operating model, data standards & platforms

Workstreams cover geospatial data governance (metadata, versioning, quality rules); enterprise architecture options for hosting, APIs, and integration with line departments; design of service patterns for planning approvals, monitoring, and reporting; security and access control commensurate with government operations; training and SOPs for planners and survey teams; and performance indicators for adoption and data freshness. Where relevant, interfaces to broader digital infrastructure or PPP-led delivery are defined without compromising sovereign control of core spatial records.

Spatial data & services

Authoritative layers, open/closed publication patterns, and integration paths for DP/TPS and development-control use cases.

Institutional & process readiness

Roles, capacity building, and workflows so digital tools match how departments actually decide and audit.

Implementation timeline

Phase 1 — Research & diagnostics: Stakeholder consultations, baseline spatial data review, sector diagnostics, and prioritised use-case set.

Phase 2 — Strategy & architecture: Target operating model, data standards, technology architecture, policy alignment, and implementation sequencing.

Phase 3 — Implementation support: Technical advisory, pilots, monitoring frameworks, handover artefacts, and institutional capacity building.

Outcomes & impact

  • Stronger, more consistent data-driven planning capacity across the state network
  • Integrated spatial intelligence that reduces duplication and speeds informed decisions
  • Scalable digital foundations for monitoring, transparency, and future application layers