Predictive Analytics: Potential Cure for What Ails the American Economy?

The way we hire and manage employees in America is fundamentally broken. Not only are unemployment rates still high in most cities, but approximately 32 percent of the current unemployed population has been unemployed for seven months or longer. Many people believe these long-term unemployed workers no longer fit in today’s workplace, but they are wrong. To combat this issue, the White House recently unveiled new legislation aimed at getting America back to work with the signing of the Workforce Innovation and Employment Act. Key to this initiative is addressing human bias and the perceived “skills gap” that separates unemployed workers from employers who could hire them. As part of the President’s initiative, 300 corporations have pledged to change hiring practices that discriminate against the long-term unemployed.

The key vehicle for making that change? Predictive analytics.

It is now widely recognized that predictive analytics can surface powerful insights from disparate data sources, serving as a catalyst for cultural change, improved hiring and management practices, and expanded employment opportunities. At Evolv, one of the harmful hiring biases we have debunked through predictive analytics is the belief that “people who haven’t worked recently aren’t viable candidates.” By analyzing millions of employee data points across our customer network, our platform demonstrated that the long-term unemployed perform no worse than those with more continuous work histories. These findings have empowered clients—including several companies supporting this legislation—to hire based on predictive scores rather than outdated assumptions.

We hope this research helps that 32 percent of long-term unemployed Americans get the interview, the callback, and the opportunity to demonstrate that they can be strong contributors to a team.

Despite strong evidence, fear and resistance toward big data and predictive analytics persist. Images of “robot recruiters” or dystopian futures often dominate public discourse. While legitimate concerns exist—particularly around surveillance and privacy—the technology and policy sectors have a powerful opportunity to collaborate in solving real human problems.

What is missing from the conversation is practical dialogue around how predictive analytics can foster partnerships between policymakers and businesses—especially how data can dismantle harmful hiring stereotypes. We must move beyond merely “hacking” societal challenges and toward scalable, actionable solutions that modernize outdated employment practices.

Some organizations are already making meaningful progress. Kaggle enables data scientists to address challenges such as decoding the human brain, classifying forest ecosystems, and predicting survival in disasters. Code for America connects technologists with local governments to modernize public services. Academia has also embraced this approach, exemplified by the Data Science for Social Good Fellowship, which trains data scientists to tackle public-sector challenges.

Placing hope in predictive analytics is not blind optimism—it is grounded in measurable business impact. For example, Xerox, one of the companies actively engaged in hiring the long-term unemployed, found that prior work experience in similar roles did not predict success. By revising hiring criteria, Xerox expanded access to candidates who would never have received interviews and reduced attrition by 20 percent, improving both workforce outcomes and financial performance.

Xerox’s experience is just one illustration of how technology and business can jointly address societal challenges. The question is how business leaders, policymakers, and technologists can work together to solve more human problems at greater scale. Predictive analytics is both the platform and the catalyst.

Leaders should act on this opportunity by using predictive technology to hire candidates with nontraditional backgrounds who can demonstrate—through signals beyond a résumé—that they will succeed, especially those who have been unemployed for extended periods. Used responsibly, predictive analytics can help reshape hiring practices and improve the future of work in America.

Carl Tsukahara is responsible for marketing and product strategy at Evolv.

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