Our Origin Story

A product of necessity

The origins of SkillsEngine were born out of a confluence of global workplace transformations, improvements in technology, and collegial partnerships that allied disparate research efforts into a unified movement to improve the way education, workforce, and individuals interact in the labor market.

As work activities become more complex, standard occupational titles are increasingly inadequate to describe the breadth and variety of work performed in a given job. Moreover, there are far more work situations with nuanced skill and hiring requirements than can be accommodated by static occupational information.

This reality surfaced in many environments throughout the education, training, and workforce development world. The Texas Workforce Commission, which provides intermediary services matching unemployed job seekers and job postings, found significant incongruities between job posting language and how jobseekers described their skills and work history. This resulted in poor job referrals and declining satisfaction from the business community who did not get the skilled talent they wanted. Not to mention workers who were sent to jobs for which they were not qualified. The lack of a commonly understood skill language to mediate these inconsistencies impeded appropriate referrals.

Similarly, as more Baby Boom generation workers fell on the cusp of retirement, the business community found themselves in need of better transferable skills information to facilitate succession planning, identify areas for internal staff training, streamline promotional ladders, and recruit the next generation of workforce talent. The necessary detailed job analysis was either too expensive for most companies or relied on the same limited, occupational constructs already vexing the job posting and recruiting process. Many companies lamented the lack of tools to appropriately build, cross-train, and allocate talent and connect their internal job descriptions with outputs from the education system.

Finally, the education community found themselves under increased pressure from regulators, taxpayers, employers, and students to improve the alignment between what is taught within various course and program offerings and the skills demanded in the workplace. This misalignment is perhaps the most challenging because it requires business, education, and the occupational labor market at large—each with their own vernacular and organizing taxonomies—to communicate at a detailed level. Missing from this conformation was a common and shared transferable skills language around which each constituency could commune.

At the same time these stakeholder pressures were building, the world of technology opened some new data opportunities. Specifically, electronic data parsing engines facilitated the collection and decomposition of online job postings. The ability to scrape and deconstruct job posting data from the Internet provided a path to look at the labor market from a more granular ‘skills’ level and transcend generic occupational coding structures. But while natural language algorithms facilitated the decomposition of job postings, resume, or education program text, there arose a need for a new organizing concept around which to rebuild the raw text into meaningful constructs that could be embraced by all participating stakeholders.

It should be mentioned that job analysis around the concept of skills is hardly a new discipline. The federal government through an operation known as ONET or the Occupational Skills Network routinely collects job task and work context information for a group of standard occupational titles. This often highly detailed and rigorously collected occupational database provides most job analysts with a rich body of information around which one can build a comprehensive understanding of job requirements and the work values, education, and context for workers in those occupations. However, despite the richness of the ONET database it still suffers the challenges of providing data only for standard, generic occupational titles, and operating under an irregular update schedule.

It was under these circumstances that a partnership formed in Texas of groups attempting to remedy these frictions for their respective constituencies.

A Shared Skills Language

The concept of creating and applying a ‘shared skills language’ to describe the interactions among labor market stakeholders was born at the Texas Workforce Commission (TWC) under the leadership of labor market economist Richard Froeschle. This new language borrowed from the detailed work activity domain of ONET in hopes of leveraging federal investments in that database, while improving the quality of skill statements and creating new applications of the data – all facilitated by emerging natural language processing technologies. To assist in this endeavor, the TWC contracted with a private company called SkillsNET under the leadership of Michael Brown. SkillsNET was already engaged in developing a transferable skill library and had contracted with the U.S. Navy to use ‘skill objects’ as a common language to facilitate talent classification and assignment.

While TWC and SkillsNET undertook the task of building an improved common skills language using a combination of job analysis and direct employer contact and validation, Texas State Technical College (TSTC) came to the table as a partner representing the education community. Vice chancellor Michael Bettersworth was tasked with forecasting the skill requirements of Texas industries so that colleges could better align their offerings with market needs. To accomplish this task, TSTC conducted primary research and utilized available labor market data to forecast and inform recommendations for colleges. The resulting reports were rich with information and valuable for educators and workforce professionals alike but were also time and resource intensive. Vice chancellor Bettersworth saw the emerging skill statement data base initiative as a means of helping educators align curricula and develop course materials more relevant and responsive to employers’ needs. By depicting the shared language across all occupations to which they apply, the new skills library could facilitate more granular skill analysis than could be achieved using the traditional job title or keyword approaches.

Under the aegis of the Center for Employability Outcomes (C4EO), TSTC began testing the theory and application of the skills library by prototyping an early version of what is today the Calibrate application. More than 1,300 courses at 26 colleges were translated into the shared skill language and gap analyses provided to educators showed the degree of skill alignment with target occupations. More than 50 percent of participants made curriculum changes based on the resulting analysis. These early successes, encouraging user feedback, and influence from external interests set the stage for making larger investments into what is today SkillsEngine.

While the initial investments and energies from the TWC and SkillsNET partnership laid a foundation for the work at TSTC, the C4EO team carried forward the development mantle by assembling a team with expertise in industrial and organizational psychology, labor market economics, user experience design, machine learning, natural language processing, data architecture, educational administration, policy, and instructional design. Under the strong intellectual and resource commitment from TSTC, the original philosophy of a common and shared skills language model moved from foundational guiding principle to practical application.

Today, SkillsEngine boasts an extensive skill statement library that can be leveraged to address all of the original challenges faced by the founders of the DWA Common Language initiative. The flagship Calibrate application provides an interactive vehicle for anybody interested in creating detailed skill profiles for resumes, job postings or educational coursework.

In addition, the original commitment to assisting and engaging the business community has never wavered. Calibrate can be used for various employer organizational tasks including staff-to-job alignment and identifying whether an applicant or employee constitutes a skill match with existing or emerging job descriptions.

Additional research indicated that the industry advisory processes upon which so many educational programs depend were essentially broken. Although some of these groups had high engagement, efficient processes, and demonstrable efficacy, many suffered from atrophy and even apathy. From the perspective of educational alignment, one could argue that this disconnect is ground zero for the skills gap dilemma facing much of the nation. Calibrate further engages the business community by facilitating an online validation process, allowing educators to involve employers of specific occupations or job titles to confirm the importance of various skills in the hiring process.

From the early recognition that skills needed to be the common currency to lubricate the wheels of labor market interaction, SkillsEngine has evolved into a driving force behind improving labor market alignment and workforce preparation for a nation facing talent deficits and skill shortages. Teaching what matters, communicating skills that are valued, connecting workers with job opportunities. For SkillsEngine and Calibrate, these are more than dictums or slogans. They are the critical challenges for informed and interconnected labor market engagement. It is a matter of necessity.