Imagine a commercial tech provider giving a demo of its platform to a government team. It pulls up a crisp image of an object, layers in a few analytics, and presents the result through a polished dashboard. In the room, the data and the platform feel like the same product.
That is where the problem begins. To access the imagery and analytics, the government often buys licenses to the entire platform. The next data requirement brings another provider, another platform, and another set of licenses. Each purchase makes sense on its own, but together they leave analysts stitching information across disaggregated tools.
This is the origin of platform fatigue. Government teams don’t need a new destination for every new dataset. They need the data to reach the systems where they already work.
A new dataset shouldn’t mean a new dashboard
Platform fatigue rarely begins with one bad purchase. It accumulates one perfectly reasonable purchase at a time. I spent much of my career working in government operations and intelligence, and today I match government requirements with commercial data capabilities. From both sides, I have watched that accumulation turn analysts’ ever expanding toolkit into a burden.
An early-career government analyst is already learning military operations, a new region, several intelligence disciplines, and the tradecraft required to turn raw information into an actionable assessment for a commander. Then we add several platforms, each with its own interface, permissions, and workflows. Before long, disjointed workflows become a scavenger hunt across browser tabs. Analysts have to remember which data lives where, how it fits together, which systems communicate, and where the output goes next.
The application workflows quickly consume the analyst’s focus at the expense of both their tradecraft and their attention to the evolving operational context. Intelligence is supposed to exist to support operations and decisions. A tool that creates more activity without helping someone act is not serving the mission, no matter how good it looked in the demo.
Pay for the foundation once
A better acquisition model separates foundational data from the platform used to view it. Certain commercial datasets support a wide range of missions and operating environments. Maritime teams depend on Automatic Identification System (AIS) data. Air-domain teams use Automatic Dependent Surveillance Broadcast (ADS-B) data. Other mission areas rely on point-of-interest information, scraped and contextualized social media feeds, cyber threat intelligence, and other broadly-useful, mission-relevant feeds.
Defense data and acquisition leaders have already identified these foundational layers, but must acquire them more efficiently and make them more broadly available in government end applications. Today, government teams continue to buy duplicative portions of the same foundational data feeds through separate platform seat licenses that allocate the full burden of the data feeds to those license costs.
There’s a better way: pay for the foundational data to hydrate critical government applications and enable individual teams to focus their money and attention on the specialized data that distinguishes one mission from another. A flexible, consumption-based model lets operational users and small teams of analysts add complementary sources when the problem demands it, without purchasing every possible combination in advance.
Move the data, not the analyst
A strong platform can be useful, but access to the underlying data shouldn’t mean you have to adopt it in its entirety. Government customers expect commercial data to work inside systems they have already funded and integrated into their operations. Compatibility is not an extra feature tacked onto the product at additional cost to the government. It should be inherent to the value proposition offered to the government and often is for data-as-a-service offerings.
Mission priorities change overnight, and a platform-by-platform acquisition model struggles to keep up. Each change brings another procurement process, integration challenge, license, and learning curve. A strong data foundation offers a better option because the data mix adapts without forcing the workflow to change with it.
We are headed toward a world where government data will no longer be locked into individual platforms and programs. Working together, government and industry are building a shared foundation that lets trusted data move wherever the mission runs.