‘Human Element’ Defines Hyperspace Challenge Model of Collaboration and Iteration

By Gabe Mounce, Director, Space Force Accelerators

If this period of coronavirus quarantine has taught us anything, it’s that there is no substitute for human interaction. It’s how we learn from each other and come to better understand each other’s needs.

According to Amit Mehra, managing partner at Arlington, VA-based NOVI, human interaction is also one of the greatest benefits – and a key differentiator – of Hyperspace Challenge.

“[The Hyperspace Challenge accelerator] has a fairly large element of human interaction that does not normally happen when you’re trying to propose something to the government. Hyperspace Challenge is a two-way connection. You’re directly asking a question, someone is able to respond, and you can follow up with another question. It’s more of a discussion where you can collectively come up with the most applicable solution.”

What Mehra is describing is Hyperspace Challenge’s accelerator model, which is rooted in establishing a direct dialogue between startups and government scientists who present cohort participants with a series of “problem statements,” which outline the issues to which the government is seeking solutions. 

The process is iterative: startups select a problem statement that their technology can address, then get the opportunity to engage with their problem sponsor to find out more about the government’s specific needs and how their technology could potentially be applied to be as effective as possible. Many times, this allows companies to evolve their technology in a more customized way through a process that becomes both collaborative and iterative.

The traditional process has historically offered little of both.

“Typically, the government tells you in a detailed solicitation what it is looking for, what the submission process is and what the proposal should look like,” noted Mehra. “In some cases, you can speak to program managers and get some clarification, but it generally tends to be devoid of any form of personal interaction. The initial exchange is mostly done on paper.”

NOVI, which applies machine-learning algorithms to infrastructure, manufacturing and space / defense verticals, participated in the Hyperspace Challenge’s first cohort in November 2018. It found the early-stage interaction provided by the accelerator to have significant benefits because it offered numerous insights into what problems the customer is trying to solve, versus a one-dimensional request for technology. 

“What typically happens is that the Department of Defense releases small business topics three or four times per year. You get to review those topics and develop your best proposal for what you are going to do to address the ask,” Mehra said. “The typical process is not initially about customer discovery. It’s about just trying to establish some level of feasibility for your tech relative to the ‘ask.’”

The additional layer of discovery enables companies to deliver more, faster.

Mehra reports that when it received a contract in January 2019 through Hyperspace Challenge, hands-on discovery enabled it to go well beyond traditional targets in the first phase of the contract than it would have otherwise.

“Under our Hyperspace Challenge Phase I contract, we were able to collaborate directly with the civil engineering team at Joint Base Lewis-McChord to identify specific applications of our technology on the base,” Mehra explained. One such application: using satellite imagery to monitor base infrastructure and facilities maintenance needs – not an insignificant job for a base comprising over 4,000 buildings on  440,000 acres. 

“This is a large base. And with Hyperspace, we were able to go there, meet the people responsible for infrastructure and facilities maintenance, inspect the buildings and other infrastructural elements they need to monitor, assess their current processes and evaluate the data,” Mehra said. “Being able to identify where the data already exists and what our models can track well really narrowed down how we would structure a next phase use-case.” 

He added: “Because we’ve been working with them closely, the chances of going from the Research & Development stage on to something that makes it to the procurement stage become higher.”

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