March 23, 2023
At a Glance
Our survey identifies opportunities, challenges, and potential solutions for growing data and tech-driven impact.
The rapid advancement of technology shows no signs of slowing down, with AI-driven applications and generative AI programs like ChatGPT at the forefront of innovation. But as these disruptive technologies continue to evolve, the divide between adoption of these emerging technologies and organizational capacities grows wider, creating a more inequitable system. Through our work and partnership with education and workforce organizations, we have gained valuable insights into their challenges and constraints. For example, we’ve learned they have been slower to adopt and effectively utilize data and technology to support their missions. These findings were not unexpected: according to the Salesforce Nonprofit Trends Report, 85% of nonprofits said that technology was the key to the success of their organization in 2019, but by 2020, only 16% of nonprofits ranked as “digitally mature” and only 12% of U.S. nonprofits were at the high maturity level.
To better understand the state of data-driven adoption within our network and ecosystem, Jobs for the Future (JFF), with funding from the Autodesk Foundation, partnered with Engineering for Change (E4C) to conduct a state of data maturity survey. E4C Fellow Arya Sarkar helped assess the data capacity, capability, and culture of education and workforce institutions in key segments of the industry, with hopes of discovering, identifying, defining, and documenting their current state of data maturity. Understanding the state of the data ecosystem is a key first step towards investing, expanding, and scaling the system by adopting new, innovative ways to improve access to equitable economic advancement.
To ensure the widest possible reach, we selected organizations across six categories to serve as voices in their respective fields and areas of work: Workforce development, CBOs, HBCUs, universities, organizations supporting people of color, and organizations supporting people with records.
The survey Sarkar conducted broadly addressed the state of the ecosystem across these three topic areas:
- The ecosystem’s investments in data capacity and infrastructure
- The ecosystem’s data literacy, skills, and capability
- The ecosystem’s culture of data use and application
We discovered that though organizations we surveyed appreciated the need for effective adoption of data and tech-driven ideas, many organizations faced challenges in their ability to fund, deploy, and adopt them.
For many, staffing issues were their biggest road blockers. Roughly 80% of the organizations had between zero and two data- and tech-skilled staff on their teams, partly due to the high demand and competitive nature of data-skilled people. As for good news? Most organizations—around 60%—predicted an increase in investments in capacity and capability in the next five years.
Challenges Faced by Organizations
The surveyed organizations encountered numerous obstacles to the effective utilization and adoption of data and technology in fulfilling their missions. Regrettably, many of these hurdles are not novel and have persisted, awaiting sustainable solutions to address them. The hurdles include deficient skills and tools, insufficient funding for technology and data management, inadequate data sharing and governance, as well as difficulties in productive data collection and utilization, among several other challenges.
The level at which organizations can leverage data analysis and storytelling to measure and showcase outcomes and impact requires specialized data tools and skills—all of which are different and more foreign compared to the compliance reporting needs that organizations have been familiar with for decades. Some organizations have begun creating data-focused positions and building the appropriate teams; others are on a longer timeline.
- Data collection, sharing, management, and use challenges vary by organizational size and budget. Many small organizations have an enormous need for dedicated data and analytics staff and more capable data tools. Some medium and many larger organizations have more resources, but the disparity can make cross-regional collaboration, program impact assessments, and evidence-driven decision-making more difficult. Of the participating organizations, 60% reported plans to increase their “data-driven” investments within the next five years.
- Getting timely access to relevant and quality data can be a problem for organizations at all levels. For example, tracking the long-term impact on learners and workers after exiting the programs is difficult or near impossible. Similarly, a lack of system-to-system integration leads to poor cross-system benefits and tracking of participants leaving one system (like the justice system) and entering another (like workforce development).
Additionally, a subset of the organizations surveyed underscored challenges either exclusive to their domain or inadequately acknowledged that warrant greater attention.
- Tracking the long-term impact for and advancement of job seekers after graduation or completion of training is a major challenge for most organizations. For example, one cited challenge mentioned that most post-exit engagement and tracking through surveys and other means rely on alumni voluntarily providing information to support this effort. Lightcast and the National Student Clearinghouse have collaborated on the development of the Alumni Pathways offering, which has the potential to address this issue.
- Other external factors constrain organizations from building up their data talent and capability. For example, urban areas must deal with the housing challenges for potential staff, whereas rural regions face broadband access, especially in this post-pandemic era of remote work.
- In some cases, organizations reported that much of the data they collected pre-COVID still exists in a physical medium, and they must digitize the data in order to be used effectively.
Recommendations for Data-Missioned Organizations
Although the challenges and opportunities are numerous and have persisted for some time, we have identified several recommendations that can advance organizations’ capacity to leverage the latest data and tech advancements to serve their community.
- Organizations could consider utilizing more cost-effective open-source tools like CKAN and DKAN, available through open-source communities, to meet their needs and budget. For example, CKAN is a powerful data management system for publishing, sharing, and finding open data. DKAN is an open-source data management platform that provides data sharing, publishing, and analysis tools.
- Improving data literacy across the organization is crucial to enhancing data maturity and adopting emerging technologies easier. To achieve this, organizations can leverage the social impact consulting and training services offered by data and technology companies to meet data literacy goals.
- Pooling and sharing the cost of data infrastructure investments can benefit small to medium-sized organizations. Establishing cross-organizational data hubs can centralize data assets, standardize impact metrics, and reduce the cost of data collection and exchange.
Towards a Data-Driven Future
JFF remains dedicated to leveraging our expertise and convening power to address the challenges identified in the learning and work ecosystem. Together with our partners and mission-aligned stakeholders, we are committed to removing challenges and increasing opportunities by deploying all facets of emerging technologies to benefit the ecosystem at large. If we leverage emerging technologies thoughtfully, effectively, and ethically, we can better address existing shortcomings and suboptimal adoptions of emerging technologies currently hindering organizations.
We are actively designing approaches and seeking partnerships to foster and cultivate disruptive technology-driven ideas and solutions. We aim to pilot innovative and effective learner and worker solutions that address their evolving needs over the next decade.