Community colleges and Michigan Works! agencies (MWAs) in Michigan put great effort into determining which courses and training programs they will offer, and with good reason: A successful program can help employers find the talent they need for success and help individuals obtain and succeed in jobs. Such outcomes also help the delivering institutions’ bottom line; when supply and demand for education are in alignment, everyone wins.
Today, however, the term “skills gap” has become a household phrase, and it is clear that not everyone is getting what they want or need for today’s education and training system. Where is the breakdown?
Certainly, there are factors involved such as lack of information about in-demand jobs, lack of interest in those jobs, insufficient wages or working environments to attract the best workers, and more. However, lack of data related to the delivery of education and training programs is also a major issue.
Education and training providers make decisions regarding the delivery of their programs — including whether a program should even be offered and what the content should be as part of the program — based on an array of inputs. For example, employment and unemployment numbers, real-time job demand data (such as the data produced by the Workforce Intelligence Network for Southeast Michigan), and direct discussions with employers to gauge industry growth or decline and the general need for talent. But these are very top-level inputs that could be influenced by external factors, ranging from changes in technology, to demographic shift or economic-market shifts.
None of these factors can tell the institutions what the outcome was for the individual education or training participants. For example: Did students in a particular program get jobs in a related field? Did their wages increase because of training? Did they get promoted? Did the value of their salaries offset the cost of the education? In short, did the education and training meet the needs of the individual and the employer as reflected in employment data?
Unemployment insurance (UI) wage data can answer the above questions and much more, but it is not readily available to community colleges. This data is held at the state level and restricted from use by colleges and job training providers due an array of state laws and practices. The goal is privacy protection, but according to national benchmarks, the methods are far more restrictive than most other states and make it hard to acquire data that could prove useful to those trying to make good decisions about public (and private) investments in education and training.
UI wage record data is far more reliable than surveys, on which many education and training providers rely now. Unfortunately, response rates to these surveys are very low, people have difficulty remembering the details of their employment history, research tends to be limited to more recent graduates and surveys are expensive to administer. Further, UI data supports longitudinal tracking and research, program evaluation, process improvement and related analyses. Researchers can use the data to determine the size, class and industry of the establishments that have hired certain workers, how many workers there are in particular industries, which industries are more likely to employ certain types of workers (e.g., the long-term unemployed), whether companies that have hired certain workers are growing or shrinking over time, and much more.
While access to UI wage record data unlocks the potential for greater data-driven decision making, this objective must be pursued while maintaining necessary confidentiality and privacy of data. Federal and state laws and regulations prohibit certain usages of data and set boundaries on what kind of information can be published. These safeguards protect participating businesses and workers from having their identities and individual wage data inappropriately disclosed.
In spring/summer 2015, WIN formed a working group to review options for improving Michigan’s UI wage record laws. The committee worked with national data experts that helped facilitatePew Center conversations around data quality and access. Based on a detailed analysis of three “exemplary practice” states’ UI wage record laws and administrative practices, WIN — on behalf of its member community colleges and MWAs — proposes a legislative and regulatory agenda for improving Michigan’s wage and employment data sharing policies.
Adopting these policies could help education and training partners, employers and individuals better understand whether public investments in education and training are being optimized, with workers and employers being well-served. Such good investment could prove one more important asset in eliminating Michigan’s skills gap.
This blog post was developed with data and research compiled by Tricia Walding, senior program manager at WIN.