State governments are conducting data analysis to move forward
Take for example salary records.
All states collect them except Maryland, Colorado and Hawaii, in partnership with Research improves people’s livesor RIPL — have created secure, cloud-based digital tools to analyze salary records, national employment data and resumes of the unemployed using scientific methods. powered by artificial intelligence (AI) and M.L. Insights from these tools can provide personalized career recommendations in growing industries, guide workers to data-driven recommendations regarding training opportunities and job postings, and help job seekers understand which careers lead to higher salaries.
More directly, Maryland, Colorado and Hawaii have leveraged data, science and the cloud. to analyze huge amounts of data and inform the creation of tailored workforce development tools that empower job seekers.
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Evidence-based tools give managers rapid insights
Of course, the effectiveness of the latest technologies depends on a government’s ability to use them and integrate them with its existing systems. This means that RIPL can help design evidence-based tools to help government solve challenges, but outdated processes and non-interoperable systems will slow progress.
Forward-thinkers in Maryland, Colorado and Hawaii have turned to the cloud to unlock their data and put it at the service of their job seekers.
First, labor and union leaders partnered with RIPL as a technical assistance partner to create Cloud-powered research data lakes to securely host, optimize and transform key administrative data for rapid insights. RDLs enable policymakers to quickly standardize their data, develop metrics, put them into practice, and then disseminate them to the public via web and mobile applications. This increases the ability of governments to implement data-driven policies, collaborate with researchers to measure what works, and continually iterate and improve.
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Objective data analysis helps agencies move forward
With an RDL in place, each state could then expedite the provision of applications to identify and provide the best recommendations to job seekers. AI and ML algorithms combine all available government data on the work experiences of all workers, including anonymized wage records and national employment data of the National Labor Exchange.
States then built tools that determine for each job seeker what new careers people with their skills have moved into. For example, a machinist might see careers that other machinists opted for, stayed and earned more later in their careers.
By expanding the research infrastructure to power data-driven “recommendation engines” for new jobs, these states have put citizen 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 encourages evidence-based policy development with the real end user in mind.
RIPL’s approach combines high-level research, policy expertise and technical know-how to transform facts into results that provide governments with the tools they need to better serve their communities. This means helping our partners develop a culture of asking the right questions, unlocking then using available data to answer them objectively, then translate the desired outcome into concrete steps and applications that improve lives.
