The U.S. Chamber of Commerce Foundation's Data-Driven Innovation Project explores the rapid advancements happening in the digital economy as well as the inventive use of data for good. The promise of bigger and better data is a future of greater opportunity and growth. The Foundation is conducting research activities and a series of events around the country in order to highlight this potential.
We encourage you to read the blog posts and research reports here to gain a full understanding of the U.S. Chamber of Commerce Foundation's work on data-driven innovation.
Be sure to read our in-depth report, The Future of Data-Driven Innovation.
Economic mobility rests on the opportunities that individuals are granted or seek out. Education plays a big part of that, which is why many professionals are now looking for continuous ways to improve their skillsets. But how do you validate that people have earned what they say they've earned? The reality is that people lie about their credentials. The solution? Use advanced technology to make credentials trackable and unfakeable.
That work is going well and is spurring a more comprehensive transformation of the public schools and greater alignment between higher education programs and business needs. But the payoff is long term. Meanwhile, manufacturers have more immediate skill needs that are not being met. So, ConxusNEO is now focusing on those needs as well. The starting point for meeting those immediate skill needs is reliable and actionable information about which jobs are most difficult to fill and what skills those jobs require. But that information turns out to be in short supply, creating a missing link at a crucial point in the talent supply chain. Enter, the Talent Pipeline Management (TPM) Initiative.
The Chamber Foundation proposes to develop and pilot test an employer-led job registry service that can assist employers and their HR technology partners.
Social Media Analytics Reveal Positive Impact of CSR Communications
The growth of the information economy and the use of data should encourage regulators to develop privacy rules based on empirical evidence, rather than anecdotes and worst-case scenarios.