Power BI Dashboard for Project Portfolio Management in Energy Sector

Key Challenges

Fragmented Data Landscape — Project data was scattered across multiple disconnected systems, spreadsheets, and departmental tools. Each project team maintained its own tracking mechanisms, making it impossible to aggregate portfolio-level metrics or compare performance across projects consistently.

Delayed Decision-Making — Generating portfolio-level reports required hours to days of manual data collection, consolidation, and formatting. By the time reports reached senior leadership, the data was already stale, preventing timely intervention on projects falling behind schedule or budget.

Lack of Real-Time Visibility — Project managers and leadership had no live view into project status, milestone progress, or resource utilization. Critical metrics like plan vs actual variance, procurement status, and construction progress were only available through periodic manual updates.

Operational Complexity — Each project involved multiple concurrent workstreams — land acquisition, regulatory approvals, procurement, construction, commissioning — with complex interdependencies. Tracking progress across 8+ workstreams per project without a centralized system created visibility gaps and coordination challenges.

Absence of Scalable Data Infrastructure — There was no underlying data platform to collect, store, transform, and serve project data for analytics. Without a scalable data architecture, any reporting solution would be limited by the same manual data aggregation processes that caused existing inefficiencies.

Our Approach

Kansoft partnered with Sterlite Power’s project management and leadership teams to design and deliver an end-to-end analytics platform:

Discovery & Domain Alignment — Conducted discovery workshops with senior leadership, project managers, and domain experts to define KPIs, success metrics, and reporting requirements across all project workstreams. Mapped the complete data landscape to identify sources, gaps, and transformation needs.

Custom Data Architecture — Designed a purpose-built data architecture using Amazon S3 as the data lake for raw project data ingestion and PostgreSQL as the analytical data store for structured, query-optimized data serving Power BI dashboards.

Iterative Prototyping — Built dashboard prototypes in rapid iterations with continuous stakeholder feedback, ensuring visualizations, drill-down paths, and KPI definitions aligned with how leadership and project managers actually make decisions.

Data Pipeline Enablement — Developed ETL (Extract, Transform, Load) pipelines to automate data collection from source systems, transform raw data into analytical models, and load it into PostgreSQL on scheduled intervals — eliminating manual data aggregation entirely.

Visualization Framework — Designed a comprehensive Power BI visualization layer using DAX (Data Analysis Expressions) for complex calculations including plan vs actual vs forecast variance, S-curve generation, cumulative progress tracking, and financial metrics.

Scalable Foundation — Architected the data platform to accommodate additional projects, workstreams, and data sources as Sterlite Power’s portfolio grows, ensuring the analytics investment scales with the business.

Solutions Delivered

Unified Portfolio Dashboard — Delivered a comprehensive Power BI dashboard providing a single-pane-of-glass view across the entire renewable energy portfolio. Leadership can see portfolio-level summaries and drill down into individual project details, workstream status, and granular metrics.

Plan vs Actual vs Forecast Analytics — Built dynamic variance analysis comparing planned timelines and budgets against actual progress and updated forecasts. Automatic highlighting of deviations enables leadership to identify at-risk projects and intervene before delays compound.

S-Curve Progress Monitoring — Implemented automated S-curve generation for each project, providing visual comparison of planned vs actual progress over time. The S-curve view enables quick assessment of whether projects are tracking ahead, on schedule, or falling behind at any point in their lifecycle.

Land Acquisition Intelligence — Created a centralized land acquisition tracking dashboard with geo-tagged parcel data, acquisition status by stage, landowner interaction history, and milestone tracking. This gives project teams and leadership clear visibility into one of the most complex and unpredictable project workstreams.

Workflow & Performance Tracking — Designed ordered workflow views covering 8+ concurrent workstreams per project — including land acquisition, regulatory approvals, procurement cycles, construction milestones, quality inspections, and commissioning activities — with dependency mapping, status indicators, and performance metrics for each.

Why Kansoft

Kansoft’s combination of data engineering expertise, Power BI visualization skills, and domain understanding of infrastructure project management made them the ideal partner for Sterlite Power’s analytics transformation. The team’s ability to design a scalable data architecture — from raw data ingestion through ETL pipelines to executive dashboards — ensured the solution delivers value today while scaling with the portfolio. By deeply understanding how leadership and project managers make decisions, Kansoft built dashboards that drive action rather than just display data.

Business Impact

• 100% portfolio visibility — Every solar and wind project tracked in a single unified dashboard with drill-down to workstream-level detail
• Near-zero manual reporting — Eliminated 8-12 hours per week of manual data aggregation and report preparation through automated ETL pipelines
• Same-day decision-making — Leadership can access real-time project status and intervene on at-risk projects immediately, replacing the previous hours-to-days reporting cycle
• 8+ workstreams tracked per project with dependency mapping and performance indicators across land, procurement, construction, and commissioning
• Significant data reliability improvement — Automated data pipelines replaced error-prone manual data collection, ensuring consistent and trustworthy metrics across the portfolio
• Scalable data platform architecture supporting additional projects and workstreams as the portfolio grows