State Governments Conduct Data Analysis to Move Forward
Consider, for instance, wage records.
All states collect them, but Maryland, Colorado and Hawaii — in partnership with Research Improving People’s Lives, or RIPL — have created secure, cloud-powered digital tools to analyze wage records, national jobs data and the resumes of unemployed workers using scientific methods powered by artificial intelligence (AI) and ML. The insights from these tools can deliver personalized career recommendations in growing industries, guide workers to data-backed recommendations for training opportunities and job openings, and help job seekers understand which careers are proven to lead to higher wages.
More directly, Maryland, Colorado and Hawaii leveraged data, science and the cloud to analyze huge quantities of data and inform the creation of tailored workforce development tools that empower those seeking employment.
Evidence-Based Tools Empower Officials with Rapid Insights
Of course, the latest technology is only as good as a government’s capacity to use it and integrate it with its existing systems. This means that RIPL can help design targeted, evidence-backed tools to assist the government in solving challenges, but antiquated processes and noninteroperable systems will slow progress.
Forward-thinkers in Maryland, Colorado and Hawaii turned to the cloud to unlock their data and put it to work for their job seekers.
First, workforce and labor leaders worked with RIPL as a technical assistance partner to create cloud-powered research data lakes to securely house key administrative data and optimize and transform it for rapid insights. RDLs empower policymakers to quickly standardize their data, develop metrics, put them into practice, and then deliver them to the public through web and mobile apps. This increases governments’ capacity to implement data-driven policy, partner with researchers to measure what works and continually iterate and improve.
Objective Data Analysis Enables Agencies to Press Forward
With an RDL in place, each state could then accelerate delivering applications to identify and deliver best-in-class recommendations to job seekers. AI and ML algorithms combine all available government data on job experiences for all workers, including anonymized wage records and national jobs data from the National Labor Exchange.
The states then built tools that determine for each job seeker which new careers people with their skills have moved into. For example, a machinist could view careers that other machinists have switched to, stuck with and earned more in later in their careers.
By developing the research infrastructure to power data-driven “recommendation engines” for new jobs, these states have put the people’s data to work for everyone to accelerate transitions to resilient careers.
From helping more households keep the lights on to creating more reliable pathways to in-demand careers for displaced or underemployed workers, RIPL drives evidence-based policymaking with the real end user in mind.
RIPL’s approach combines high-powered research, policy expertise and technical know-how to turn facts into results that provide governments the tools that they need to serve their communities better. This means helping our partners develop a culture of asking the right questions, unlocking and then using the data available to answer them objectively, and then translating the desired outcome into actionable steps and applications that improve lives.