Leidos

Leidos Holdings, a US-based defense, intelligence, and civil services company with approximately $14.4 billion in revenue (2022) and over 44,000 employees, manages hundreds of concurrent government programs and contracts. Program performance was historically tracked through manual processes — project managers compiled monthly status reports using spreadsheets, earned value management (EVM) metrics were calculated manually, and risk assessments relied on individual judgment rather than data-driven analysis. Late-stage program overruns and schedule slips cost the company significant margin erosion and affected CPARS ratings (Contractor Performance Assessment Reporting System) that influenced future contract wins.

Between 2021 and 2023, Leidos implemented a comprehensive measurement and analytics framework for program delivery:

• Enterprise program analytics dashboard: Deployed a real-time analytics platform that aggregated earned value metrics, schedule performance indices, cost performance indices, and risk indicators across all active programs. Executive leadership gained portfolio-level visibility into program health rather than relying on individual project manager reports.
• Predictive risk scoring: Built machine learning models trained on historical program data to predict cost and schedule overruns before they materialized. Programs were automatically scored for risk level based on patterns in labor burn rates, subcontractor performance, requirements volatility, and milestone completion rates.
• Automated EVM reporting: Automated the calculation and reporting of earned value management metrics that previously required hours of manual spreadsheet work per program per month, improving data accuracy and freeing project managers for proactive management.
• Subcontractor performance analytics: Created analytics tools that tracked subcontractor delivery against commitments across multiple programs, identifying underperforming vendors before they caused program-level impacts.
• Win rate analytics: Analyzed historical bid/proposal data to identify characteristics of winning proposals, enabling more targeted pursuit decisions and improved win rates on competitive procurements.

• Program margin improvement: Early identification of cost and schedule risks through predictive analytics enabled proactive corrective actions, reducing margin erosion from late-stage program overruns.
• Revenue growth: Revenue grew from $13.7 billion (2021) to $14.4 billion (2022), with strong contract win rates contributing to portfolio growth.
• CPARS improvement: Improved program execution consistency led to better CPARS ratings, strengthening Leidos's competitive position for contract recompetes and new awards.
• Project manager productivity: Automated EVM reporting freed an estimated 15-20% of project manager time from manual reporting, redirecting effort to proactive risk management.
• Adjusted operating margin: Operating margins improved as program execution discipline reduced cost overruns and rework across the portfolio.
• Timeframe: Analytics framework deployed over 2021-2023.

• Leidos's scale (hundreds of concurrent programs) provided sufficient data to train predictive models and benchmark program performance
• Government contracting's standardized EVM requirements provided a common measurement framework that enabled cross-program analytics
• 2016 acquisition of IS&GS from Lockheed Martin provided the program management infrastructure and talent base to support analytics deployment
• Cloud-based analytics platforms enabled secure processing of government program data within required security boundaries