How do you decide, in an afternoon, whether a drone program is worth a government’s time? For Andrew Shipe, that’s a real, recurring question.
As an Innovation Strategist on Sourcewell’s innovation team, Sourcewell Ventures, Shipe helps a government cooperative serving public agencies across the country figure out which ideas are worth pursuing, and which ones need to wait. Sourcewell itself is unusual as a government entity: it can’t tax to raise revenue, so everything it does has to justify itself as a service governments want. Ventures exists specifically to find opportunities beyond Sourcewell’s core cooperative-purchasing business, new ways to serve public agencies that the private market isn’t equipped, or motivated, to solve on its own.
With a small, focused team, Shipe doesn’t have the luxury of researching every idea that comes in. Every idea has to earn its place quickly, on the strength of the evidence behind it.
The problem with comparing the incomparable
The hardest part of that job is finding a shared yardstick. A county fleet services department’s problem doesn’t look anything like a fire department’s wildfire response, even though both are government agencies wrestling with urgent, resource-constrained work. There’s no obvious way to weigh one against the other. Without a consistent way to evaluate opportunities across such different contexts, good ideas were easy to misjudge, or simply lose to timing while something else got prioritized.
Shipe has come to rely on IDC for this kind of cross-context clarity: understanding where technology is going, and how different types of agencies are adopting it, so that a fleet department’s technology curve and a fire department’s technology curve become at least a little more comparable.
A vague pain point, made concrete
Nowhere did that gap between “everyone says this is a problem” and “we understand why” show up more clearly than with drones.
Agencies at the city and state level had been telling Sourcewell the same thing for a while: drone-based first-responder programs were powerful. They changed how a community could be kept safe. But they weren’t affordable, and nobody seemed to have a clear, specific answer for why. Shipe’s team didn’t have a good sense of where the cost was coming from, which meant they couldn’t tell whether it was a problem Sourcewell could realistically help solve.
Working with IDC and IDC Quanta, Shipe put real numbers behind what agencies had only been able to describe anecdotally, turning a vague complaint into a defined, structural problem a government partner could plan around.
The trust problem underneath every other problem
None of that research would have mattered if Shipe couldn’t trust the numbers behind it. Trust was exactly where every other AI tool he’d used had fallen short.
“That’s kind of always been one of my challenges with other AI tools,” he said, “what is real and what is hallucinated.” It’s a familiar frustration for anyone who has asked a chatbot for a statistic and then had to go verify it independently anyway. At that point, the tool hasn’t saved any time. It’s just moved the work later.
IDC Quanta changed that with inline footnotes tied directly to source articles. A list of links at the bottom of a response never told Shipe which claim came from which source, so he’d never been able to trust those either. IDC Quanta showed him exactly which sentence was backed by exactly which footnote. If a number looked interesting or surprising, he could open the source immediately, in context, and check it against the original article before he ever used it in front of a decision-maker.
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The appeal of IDC Quanta, he said, was that it’s backed by specific articles, and I could read them and make sure that the numbers I’m getting are correct.
That capability sounds small, but it changes what you can trust the tool to do. Shipe could finally build a real decision on top of what it told him, instead of just using it to get started.
Faster research means more shots on goal
Drones were one example. The same problem (a real question with no fast, trustworthy way to answer it) comes up constantly for a team fielding ideas from every direction.
The Sourcewell Ventures team doesn’t have a shortage-of-ideas problem. Ideas arrive from so many directions that time to evaluate them is the real constraint.
That’s what made IDC Quanta useful beyond any single research question. Shipe could plug in a new idea and get enough grounded, source-checked information back to make a real call: yes, this has potential, worth spending more team time on. Or no, this isn’t the right fit for the market right now, worth setting aside. Multiply that across every idea competing for a small team’s attention, and the value goes beyond accuracy on any one question. It’s the ability to run through far more ideas than the team could have researched manually, without sacrificing confidence in the answers.
Shipe called it a genuine leap forward from every other AI tool he’d used. The reason had nothing to do with flash. It was the first tool he felt he could build a real decision on top of.
Shipe’s team still gets more ideas than it has hours to research. IDC Quanta just means more of those hours go toward the ideas worth the time.
