When an Intelligence agency organization needed to optimize its ability to identify and integrate internal and external data coming from multiple sources in multiple formats, normalize it and ensure this data was readily available for critical decision making, it faced a huge hurdle. The organization is responsible for a critical mission: track strategic investments in infrastructure, assets, collection and analysis; and enable stakeholders to view and analyze the data collected to make critical decisions regarding resource alignment, program justification, and mission decisions. This includes decisions around funding, R&D investments, strategic planning, and appropriate budget cuts and increases. Collecting disparate data from multiple sources cost the agency thousands of man hours, and there was no efficient way to properly view and analyze all the data to identify trends, or similarities in organizations for R&D and other shared needs, or to quantify an asset’s contributions to validated requirements and intelligence priorities and gaps. Stakeholders who needed to make funding decisions based on trends and priorities were frustrated. There was no consistency in timeliness and standard of the data, no clear chain of custody. The challenge was clear: if data cannot be efficiently collected and trusted to produce meaningful and intelligent information, government will waste time, money, and compromise the performance of ongoing programs. The organization needed a solution that would maximize operational efficiency and support its mission.