Structural Snags $2.5M Investment to Fund Growth and Augment Platform
Structural, an employee-data management startup based in Indianapolis and the Twin Cities, today announced that it has raised $2.5 million in an equity investment round, with backing from High Alpha, Revolution’s Rise of the Rest Seed Fund, Matchstick Ventures, the Syndicate Fund, and Great North Labs. The 15-person company has raised just under $5 million since its inception last year.
Structural applies data science and analytics to a company’s raw human resources information to find insights about employees that pertain to skills, certifications, internal networks, and how employees manage their time. Scott Burns, the company’s co-founder and CEO, says Structural helps employers identify and nurture talent within their organizations while leveraging their current communications systems to drive growth.
Over its first year of operation, Burns says, the company learned an important lesson about its value to customers. “When finding and activating people, all of the value is in the robustness and currency of the data,” he says. “We’ve narrowed our focus to being a people insight platform and augmenting what already exists. We’re using data to target the right people at the right time.”
When Xconomy talked to Burns last year, soon after the company launched, he pointed out that while older workers may be comfortable with hierarchies and doing things the way they’ve always been done, younger workers are not. They want to feel valued and use all of their skills, Burns says. Figuring out whose talents might best be applied to any given project gets exponentially harder in workplaces where employees might be geographically distributed or working different schedules, meaning it’s rare for everyone to be in the same place at the same time. Or even on the same page.
Burns says that when he meets with clients, they often complain of their workplaces being too siloed. (He asked one customer what that meant, and they said that they didn’t know anyone on the east side of their floor.) He also shares an example from his past about the importance of proximity and networks: When he was leading his former company, GovDelivery, an employee came up to him one day and said she was glad he liked peanut butter cups, because otherwise she wouldn’t have been promoted.
When he asked what she meant, she explained that he used to regularly stop by her office to grab a piece of chocolate from her desk’s candy bowl. While there, he would inevitably discuss things like soon-to-open jobs in her division. As a result of being privy to this information, she eventually applied for and won a management position. Burns says that illustrates how inefficiently communication can travel in big office settings.
“How do you personalize the employee experience and use [human resources] data to connect people working from home two days a week to the person who’s in the office every day?” he asks. “The problem was clear, but it hadn’t been solved because we didn’t have data science capabilities like we have today.”
Burns says the Structural platform now has more than 5,000 users from a mix of companies, including three Fortune 500 businesses. Employers can track a wide variety of data points, resulting in employee profiles that encompass “all their projects, skills, and networks and not just what books they’ve read, although we have that too,” he adds. “We’re learning from our users. It’s informing the model for better search functionality and other features to make the platform more useful.”
In the future, Burns would like to add Amazon-like recommendations to Structural’s search capacity. For example, if an employer is looking for someone to lead a particular project, the platform could suggest the employee that best fits along with three additional people with similar profiles.
“Our customers haven’t asked for it, but we can tell they need it by user behavior,” he says. “The way we look for people inside an organization is like the Dark Ages.”