Our SVP of Marketing and Communications, Kate Heath, weighs in on the messy middle ground between the hardware collecting data and the platforms visualizing it - and how the infrastructure connecting these two ends of the value chain might not be the flashiest but are vital for the success of the entire system.
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I've been a big Kara-and-Scott fan for years ā if you know what that means, then you too are a regular listener of the Pivot podcast. In retrospect, it was probably not the best idea to listen to them so faithfully as I walked down Powell and Market Streets to my job at Meta, but thatās a moot point now.Ā
Anyway, as I moved into the startup world, one observation that Scott Galloway makes repeatedly stayed with me: the businesses that quietly make people rich are usually the boring ones.
His shorthand for it is simple: the sexier the business, the lower the return on investment. Markets that attract the most excitement tend to attract the most competition. Capital floods in, talent floods in, and margins compress. Meanwhile, the companies that quietly become indispensable tend to build infrastructure ā the systems everything else eventually depends on. Think wallets instead of coins, cloud infrastructure instead of SaaS features, rails instead of fintech products.
None of these businesses dominate headlines, but over time they end up owning the ground everyone else has to stand on.
Lately I've been thinking a LOT harder about how that dynamic shows up in the defense industry.
Right now, most of the attention in defense tech lives at the edges of the stack. Drones, sensors, autonomous systems, cool robots, AI copilots, and command center dashboards attract the most excitement and investment. They are the most visible parts of the system and the easiest to demonstrate. A drone buzzing overhead or a sleek command interface makes for a compelling demo, and it's easy to imagine the market opportunity around those technologies.
In other words, they're the sexy parts of the stack.
But when you step back and look at how these systems actually function together in real operational environments, the most consequential layer for whether any of it actually works together often sits somewhere less obvious. It lives in the middle of the value chain ā between the moment data is collected and the moment it is displayed to an operator.
Earlier in my career at Boeing, I had the opportunity to work on advanced aerospace programs and later to lead data analytics strategy supporting the company's first Chief Data and Analytics Officer. Boeing builds some of the most sophisticated platforms in the world ā and they are sexy indeed. (OK, well, not all of them. But I don't care what anyone says, I loved Phantom Eye.) What those experiences taught me, though, is that sophistication at the platform level does not automatically translate to clarity at the data level. The more capable the system, the more data it generatesā¦ and the harder it becomes to turn that information into something operationally useful across a complex environment.
Modern operations are producing enormous volumes of sensor data from increasingly diverse sources. Drones, satellites, ground sensors, autonomous platforms, and existing mission systems all generate streams of information that arrive in different formats, with different levels of fidelity, and often with gaps or duplication.
On the other end of the system sit visualization layers such as dashboards and Common Operating Pictures (COPs) that attempt to present a coherent view of the situation.
In theory, those two ends of the stack should connect cleanly. But in practice, the path between them is often messy.
Data arrives out of order, pipelines break, formats don't align. Signals get buried under noise. Context disappears somewhere along the way, and someone has to reconcile all of that information fast enough for it to matter.
That reconciliation step is where many mission systems quietly struggle. Itās the āmessy middleā of the data value chain. (I should know; I made that slide and used it many times as a young strategy analyst!)
Anyone who has spent time around operational teams has seen what fills the gap when infrastructure is missing. As my Certus Core teammate and CEO Jake Dyal has talked about from personal experience, highly capable analysts do extraordinary work with whatever tools they have available. Spreadsheets become normalization layers. PowerPoint decks turn raw outputs into something that can be briefed. Ad hoc scripts appear to stitch together feeds that were never designed to talk to each other. Occasionally a homegrown database holds the entire environment together in ways that only a handful of people fully understand.
None of this happens because analysts lack skill or creativity. It happens because the infrastructure layer responsible for unifying the data often does not exist, or was never designed for the realities of modern operations. The result is that highly trained personnel spend an enormous amount of time reconciling information before they can act on it.
As sensor environments become denser and operations become more distributed, that problem only grows.
From a business perspective, that is what makes this layer interesting.
The companies building drones, sensors, and visualization tools will continue to evolve and multiply as technology advances. New platforms will appear. New sensors will generate new data. New dashboards will attempt to display it.
But the layer that reconciles their data and allows operators to trust what they are seeing becomes foundational to the system itself. As new sensors appear, formats change, and mission needs evolve (read: like right now), that infrastructure evolves with them, acting as the connective tissue that allows the entire environment to function.
This is the part of the stack where platforms like ours (IBISā¢) operate. The role of that layer is not to collect the data and it is not simply to display it. Instead, it sits between those functions ā fusing data from different sources, governing how that data can be used, and enabling analysts and operators to discover what actually matters within it.
When that layer works well, signals from different systems begin to make sense together. Raw inputs start to form patterns, and those patterns can be turned into decisions. The infrastructure sitting between collection and the COP becomes the place where discovery actually happens.
Traditional data platforms were designed for centralized environments and reliable networks. Modern operations look very different. They are distributed, sensor-dense, and often disconnected. Data is generated everywhere, and the people who need to interpret it are rarely sitting next to a perfectly functioning data center.
That shift changes the role of the infrastructure layer dramatically. It is no longer enough to store data or move it from one place to another. The platform has to help operators figure out what matters. It has to surface relationships across systems and provide confidence in what the data is actually saying. It has to be easy to use and accessible to service members at all levels of the organization, not something that requires years of special training.
Once a platform becomes the place where that discovery happens, and leverages the network effects, it becomes extremely difficult to replace.
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The edges of the stack will keep evolving. They always do. But all of those systems ultimately depend on the same underlying layer. Their data has to make sense together.
The platform that fuses, governs, and operationalizes the information between them becomes foundational infrastructure. And the companies that define that layer end up sitting in one of the most durable positions in the entire ecosystem.
When customers started coming to us, they weren't asking for a prettier dashboard. They were drowning in data from multi-sensor environments that no human team could reasonably reconcile, operating in disconnected environments that made analysis even harder, and watching their best analysts burn hours trying to make sense of information before they could even begin to act on it. The problem wasn't collection, and it wasn't visualization. It was everything in between.
Defense technology understandably gravitates toward what's visible. But the systems that quietly determine whether any of it actually works together tend to live somewhere far less glamorous; rarely on a conference stage, rarely in a press release, but doing the work that makes everything else possible.
In the messy middle.
These days, I've made myself quite at home in this part of the value chain. The middle isn't sexy. But it's where the infrastructure gets built, where the network effects start to form, and where the most durable positions in the market tend to emerge.
Like Scott, I'll take the unsexy business bet every time.
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