what color is your parachute

The 1970’s called and they want the color of their parachute back

From the outset I will note that this is not intended to be a thought-piece about Dick Bolles or his eponymous career discovery book, “What color is your parachute?” [first published in 1975] — it is, however, intended to be a bit of a diatribe against “the resume” and the lack of innovation in general in the field of career advisement and occupational design.

Begin diatribe….

How is it, that we have nearly arrived at two decades past the year 2000 and are closer to landing a person on Mars than we are to smoothly ensuring the civilian career success of a soldier? — or a graduating student? — or a parent returning to work? — or a technician needing to transition out of an industry that is shutting down?

How is it that we are still using a Resume as the primary currency of the business transaction that is “the hire?” Surely … somewhere there is a solution to the insanity that is a job search — but everywhere we look, the trends point further away from career and more toward a gig economy of transient tasks stitched together via dated algorithms of what it means to be human in an occupation.

What is more amazing to me is the near lack of any meaningful change in the last 50 years — not just in how individuals and companies interact, but in the resources supplied to provide those individuals with insight into how to select a career path they will most enjoy and in which they can succeed. Is our path to success rooted in a psychological profile? Is it best determined by a standardized test? Our we better off with a technical skill assessment? Or are we merely destined to wander along until we manage to strike the right chord or die trying….

“Surely … somewhere there is a solution to the insanity that is a job search”

Personally, I’ve been working the issue through my mind for the better part of a decade [which suggests that I may not be the right one to come up with the right answer] — and every once in awhile I find it useful to walk through the process in the hope that some new nugget will reveal itself.

As it happens, this weekend was one of those moments and so I thought I would share my thoughts with a broader audience as either a means of soliciting greater insight than I can muster on my own … or perhaps as some small cry for help…

If you are willing to follow-along on this thought excursion, join me first in the perspective of the hiring manager. In my observation, the greatest challenge in selection and management of human capital lies at the transactional level. Decision-making surrounding a hire, termination, promotion, tasking, reporting, team construction, project assignment, etc. rests on a manager’s or organization’s ability to observe, infer, trust and ultimately make the correct choice. A myriad of options, products and tools exist to assist in a decision process that often comes down to intuition in the face of what is essentially unknowable complexity.

The Hire

Using the “hire” as an example, we will consider the various decision points the typical organization navigates to arrive at a staffing decision. The process generally begins with the recognition of a need for additional staff to perform a variety of functions, some of which are obvious tasks, some of which are not. Let’s say an organization decides to hire additional sales staff. Assuming that the organization has hired sales professionals in the past, they may have a “template” to work from, perhaps in the form of a job description.

The job description typically references a set of requirements and broad achievements that a candidate must have in order to be considered for selection. When boiled down, the list typically includes: x years of experience with x skills, x level of education, and x certifications. Beyond that are varying amounts of narrative designed to narrow the field, but which is typically either a template from a professional association or written by someone in the human resources office that is assisting in the management of the process.

Job Classification

To this point, the job description may be symbolized in a succinct code such as the taxonomy created by the US Department of Labor’s O*Net occupational database and taxonomy. The DOL O*Net SOC taxonomy classifies occupations by major groups, minor groups, broad occupations, detailed occupations. Unclassified lists of “competencies” in a text format are further assigned to each SOC classification to create a codified narrative useful for creating job descriptions and establishing job requirements. Each SOC is defined by Tasks, Tools & Technology, Knowledge, Skills, Abilities, Work Activities and Work Context. As an example, the code for a Sales Manager is 11–2022.00 and a detailed description of these job requirements can be found by clicking here. Anecdotally, few employers use this system to classify and list jobs as it is admittedly slow to keep up with job requirements and titles, they do use it, however, for categorization and compliance reporting. A significant limitation of this system and taxonomy is a lack of classification structure for assigned knowledge skills and abilities that would permit a more detailed gap analysis for workers and jobs.

“A myriad of options, products and tools exist to assist in a decision process that often comes down to intuition in the face of what is essentially unknowable complexity.”

Regardless of how an employer derives their job requirements, the initial job description is generally placed in an online system to which a number of additional screening “questions” may be added to narrow the pool of applicants. Applicants submit a narrative document known as the “resume,” as evidence of their qualifications. Resumes, being narrative in nature, have few standards, but can be “parsed” into discrete data fields (generally aligned to those basic requirements listed above). Additional measures may be added to further filter the pool including electronic and paper forms that require the applicant to rewrite the content of the resume in a format determined by the employer to more easily baseline and compare information presented by the applicant. At this point, the process typically takes a dramatic turn into the realm of the subjective (eg. the “Interview”).

A few pieces of relevant information are rarely sufficient to confirm that an individual both has the capabilities to do the work required, and has mastered certain competencies to a sufficient degree to successfully perform the functions of the job on a regular and satisfactory basis. Thus, any number of additional and invariably more subjective actions come into play ranging from pre-tests, to simulations, to credit checks, drug tests, psychological profiles, peer interviews, background investigations, and the hiring manager interview. If we are honest, the final selection boils down to the gut feel of the selecting official, whose motivations are inscrutable, but ideally backed by enough objective evidence to avoid running afoul of federal and state regulations.

From the perspective of the job seeker, the entire process is not only intimidating and confusing, but devaluing of their own perspective of their capabilities, motivations and capacity to perform the requirements of the job. Worse, a candidate generally has no idea whether they qualify or not for a position.

Undoubtedly, all parties involved would be better served by a cleaner, clearer system that allows candidates to know if they qualify for a position, and managers to have confidence that their final slate of candidates has the capability to perform the required functions.

To extend the analogy a step further, the same level of obfuscation exists within the vast majority of decisions surrounding human capital at the transactional level: how does an employer effectively transition and grow effective workers into new roles (promotion), how does an employer efficiently train, retrain and assess changing skill requirements (development), how does an employer assess and compare effectiveness of employees (termination, motivation and retention).

To begin to address the inefficiencies and high costs associated with worker selection, promotion and development, we have actually developed a more cohesive taxonomy or means of classifying work requirements at the fundamental unit of work, the competency. To do so, we begin with the definition of competency and create a means by which these competencies can be rapidly assigned, measured, articulated and codified, not only as work requirements, but as metrics and learning objects.

Classification of Competencies

To properly classify a set of competencies and thereby create a cohesive taxonomy, it is first necessary to define how the term is being considered and used. The US Department of Labor developed a Competency system that organizes competencies into nine tiers that fall into three broad categories: Occupation Related, Industry Related, and Foundational Competencies. Given the industry adoption and level of work that has gone into defining work according to this framework, it does supply a solid framework. It does not, however, provide a suitable or standard classification system to organize those competencies. Neither does it address the weighting of competencies, how they are measured and levels of mastery. Rather, competency is the general term used for a range of skills, abilities, knowledge, and familiarization of the same.

Such a broad definition deflates the literal sense of the word “competence” which refers to the possession of a required skill knowledge, qualification, or capacity. In addition to “possession” there is a sense of sufficiency associated with the word that relies upon an assumption that a person who has competence in skill not only possesses the skill, but possesses it in sufficient quality and efficacy as to be able to function in a variety of circumstances.

“Undoubtedly, all parties involved would be better served by a cleaner, clearer system that allows candidates to know if they qualify for a position”

It is this sense of competency that interests an employer. They are not merely interested in whether an individual knows how to do a task, or knows certain information … but how well they can perform the task or recall that information under pressure and a variety of circumstances. A taxonomy that organizes skills, abilities and knowledge, but provides no differentiation in mastery cannot adequately be considered a competency taxonomy.

This being said, I recognize the fact that any classification process or system can easily become mired in unnecessary detail, and therefore, it is the purpose of this organization to create a means by which partners can rapidly align occupational needs to the individuals that can best demonstrate the necessary level of competency required. Desiring to create efficiencies rather than further complication, the taxonomy we have begun to embed in our online tools (check out our Candidit platform or visit us online at: RedcellTalent ), while aware of the broader research on the subject of classification of workplace competencies dating back to the early 70’s — we chose to adopt portions of prevalent approaches into a system more amenable to practical application in the workplace.

To do so, I present the concept of the “job model” as a measure of sets of competencies at defined levels of mastery with a definition of competency reflective of the 1797 latin derivation of competere (also derivative of compete) meaning, “sufficiency of qualification.”

The Job Model

As previously discussed, the job description is generally little more than a poor parody of actual job requirements. Not unlike what is found in our education system, a job description describes job qualifications in terms of time rather than mastery. Assumed in this model is the notion that an individual bearing a similar job title from a similar sized employer is the individual optimally suited for a given position. The “qualification by time in grade” concept creates significant barriers for talent development and is more apt to result in underperformance as well as underemployment. [incidentally this is a key point of failure for military in transition] In turn, job candidates are left without a clear means by which they can become qualified.

In the job model framework, time becomes only one means by which mastery can be demonstrated, but co-equal with more definitive and relevant measures such as proof by examination, demonstration, and certification. Employers may still select time utilizing a given skill as a measure of maturity or sufficiency, but would be wise to consider more relevant testing mechanisms as supplemental proof of sufficiency of qualification (and skill relevance).

Classification

One of the greatest challenges in designing a taxonomy is in the creation of a suitable taxonomy that is flexible, scalable, and ultimately something that can be implemented within various data systems and constraints. Additionally, we face the question of adoption versus protection. In a world of open source versus proprietary, both options have their advantages. Leaving a taxonomy open and free increases the likelihood of adoption, but exposes the creator to obscurity and irrelevance. Holding tight proprietary restrictions on a model can lead to income through various methods such as licensing and product development, but adoption may be slow and ultimately lead to the death of the model outside of its few implementations.

Given the complexities involved in the creation of a classification system, and the myriad options available, it makes some sense, even for a proprietary solution, to create linkages from the model to known systems already in wide adoption ie, the U.S. Department of Labor’s O*Net job taxonomy. At first glance, the O*Net taxonomy appears to be, and is for the most part, a comprehensive solution into which millions of dollars and work-hours have been invested. Undoubtedly, it is the logical basis from which a viable taxonomy may arise. The following section outlines the key components of this taxonomy, deficits, and adjustments that need to be made to form the basis of a job model that provides value to the career advisement process.

O*NET®-SOC (the following section contains whole and partial “quoted material”from documents prepared by the National Center for O*Net Development, December 2010)

“The O*NET®-SOC (Occupational Information Network-Standard Occupational Classification) occupational taxonomy is currently operating on revisions instituted in 2010. [ Given the average length of time between revisions, it is expected that a new revision will be released between 2012 and 2016. The database, however is updated on an annual basis.] The O*NET-SOC 2010 taxonomy includes 1110 occupational titles, 974 of which represent O*NET data-level occupations. Data-level occupations are those for which the O*NET program collects data from job incumbents, occupation experts, and occupational analysts. Data are collected on a wide variety of variables and scales, such as occupational characteristics and worker requirements drawn from the O*NET Content Model (http://www.onetcenter.org/content.html).

The O*NET-SOC 2009 taxonomy contained 1102 occupational titles, 965 of which represented O*NET data-level occupations.

The structure of the SOC system includes four levels of aggregation: 23 major groups, 96 minor groups, 449 broad occupations and 821 detailed occupations. All SOC occupations are assigned a six-digit code. The first and second digits represent the major group; the third digit represents the minor group; the fourth and fifth digits represent the broad occupation; and the sixth digit represents the detailed occupation. The 23 major groups of the SOC include:

• 11–0000 Management Occupations
• 13–0000 Business and Financial Operations Occupations
• 15–0000 Computer and Mathematical Occupations
• 17–0000 Architecture and Engineering Occupations
• 19–0000 Life, Physical, and Social Science Occupations
• 21–0000 Community and Social Services Occupations
• 23–0000 Legal Occupations
• 25–0000 Education, Training, and Library Occupations
• 27–0000 Arts, Design, Entertainment, Sports, and Media Occupations
• 29–0000 Healthcare Practitioners and Technical Occupations
• 31–0000 Healthcare Support Occupations
• 33–0000 Protective Service Occupations
• 35–0000 Food Preparation and Serving Related Occupations
• 37–0000 Building and Grounds Cleaning and Maintenance Occupations
• 39–0000 Personal Care and Service Occupations
• 41–0000 Sales and Related Occupations
• 43–0000 Office and Administrative Support Occupations
• 45–0000 Farming, Fishing, and Forestry Occupations
• 47–0000 Construction and Extraction Occupations
• 49–0000 Installation, Maintenance, and Repair Occupations
• 51–0000 Production Occupations
• 53–0000 Transportation and Material Moving Occupations
• 55–0000 Military Specific Occupations

SOC minor groups, broad occupations, and detailed occupations are assigned codes related to the corresponding major groups. For example:

19–0000 Life, Physical, and Social Science Occupations (SOC major group)

19–4000 Life, Physical and Social Science Technicians (SOC minor group)

19–4050 Nuclear Technicians (SOC broad occupation) 19–4051 Nuclear Technicians (SOC detailed occupation)

In the O*NET-SOC taxonomy, an occupation that is directly adopted from the SOC system is assigned the six-digit SOC code, along with a .00 extension. If directly adopted from the SOC, the SOC title and definition are also used. Hereafter, these are referred to as SOC-level occupations.

If the O*NET-SOC occupation is more detailed than the original SOC detailed occupation, it is assigned the six-digit SOC code from which it originated, along with a two-digit extension starting with .01, then .02, .03 and so on, depending on the number of detailed O*NET-SOC occupations linked to the particular SOC detailed occupation.

For example, Nuclear Technicians is a SOC detailed occupation to which two detailed O*NET-SOC occupations are linked. See the occupational codes and titles for this example below.

19–4051.00 Nuclear Technicians (SOC-level)

19–4051.01 Nuclear Equipment Operation Technicians

(detailed O*NET-SOC occupation)

19–4051.02 Nuclear Monitoring Technicians

(detailed O*NET-SOC occupation)

Both 19–4051.01 Nuclear Equipment Operation Technicians and 19–4051.02 Nuclear Monitoring Technicians are data-level occupations in the taxonomy. Data-level occupations are those for which the O*NET program collects data from job incumbents, occupational experts, and occupational analysts on a wide variety of variables and scales, such as occupational characteristics and worker requirements drawn from the O*NET Content Model (http://www.onetcenter.org/content.html).

In the example above, the two detailed O*NET-SOC occupations, 19–4051.01 Nuclear Equipment Operation Technicians and 19–4051.02 Nuclear Monitoring Technicians, are data- level occupations, whereas the SOC detailed occupation, 19–4051.00 Nuclear Technicians, is not an O*NET data-level occupation. “

Use of the O*Net SOC

As a taxonomy of occupation titles and groupings, the O*Net SOC provides a solid framework that is not only supported and used within the government (for recruiting and classification), but mandated to some extent as the reporting structure for compliance initiatives within the Department of Labor. Given the number of federal contractors and scope of compliance and regulatory authority, any model system will at some point require a cross-walk as a minimum when used in practice. As a practical tool for job seekers, this taxonomy leaves much to be desired. For instance, of the 1110 detailed job classification titles, 136 have no data associated with them being either too specific, marginal or “residual” in nature. Functionally, having 136 titles unrelated to data causes issues within a system of operation. Additionally, the numbering system lacks sufficient scalability to address job changes and increasing specificity that continues to creep into the marketplace.

Fundamentally, the O*Net SOC provides a sound foundation upon which a taxonomy may be constructed for defining and organizing job categories and to some extent job titles. Additional layers of complexity arise, however as the full O*Net Content Model is unveiled.

O*Net Content Model

The Content Model is both the conceptual foundation of O*Net, and the framework by which detail is associated with job titles. The Content Model is divided along a central axis that splits data sets between worker orientation and job-orientation. Worker orientation characteristics and requirements include generalized abilities, interests, values, styles, skills, knowledge, education, experience, training, licensing and entry requirements. This content recognizes the vast majority of information that comes into play in the typical hiring and selection process. The flip-side of the model, “job-oriented” characteristics and requirements focuses on occupational, workforce and occupation-specific tasks, tools, technology, trends, and projections coupled with statements of work activities, work and organizational context.

By dividing classification between worker-oriented and job-oriented, the O*Net system identifies tacitly the key challenge in HR transactions: the gap between worker needs, attributes and interests, and actual job requirements. The challenge in HR transactions (especially hire and promotion) is to match optimal “worker-characteristics” with occupational requirements. A useful job model must be capable of creating associations between these two tensions. The second “division” of characteristics in the O*Net Content Model rests between what is termed as “Cross-Occupation” requirements and “Occupation-Specific” requirements. Worker Characteristics and Occupational Requirements align with the Cross-Occupation threshold, while “Experience Requirements” and “Occupation-Specific” information balance the Occupation Specific orientation. In the visual model, O*Net adds “Worker Requirements” and “Workforce Characteristics” to create a central axis.

Demystifying the O*Net Content Model

The greatest barrier to wide commercial adoption of the O*Net model is its complexity, and the lack of ability to appropriately align the measurable worker characteristics with identifiable occupational requirements. The issue in creating efficiencies within the transactional process is finding an effective balance between detail and simplicity. Job descriptions or definitions that are too simple attract too many applicants and create administrative and regulatory nightmares for the business, while frustrating job seekers who become lost in a pile of resumes. Too much detail leads to few candidates and the possibility of no qualified candidates, creating vacancies in critical business functions.

This model also provides limited insight into how competencies combine to facilitate the translation of competencies across job types and industries. At its core, the O*Net model is mechanistic in its approach to defining occupational requirements.

Reviewing the detailed taxonomy created for the O*Net Content Model, it becomes apparent that the content is structured in the form of a simple outline: [ #.A.#.a.# ]. Each of the six categories is described as an Element and assigned an Element ID, with the heading element given a single Numeric to begin numbering from 1–6 as follows: 1 Worker Characteristics; 2 Worker Requirements; 3 Experience Requirements; 4 Occupational Requirements; Occupation-Specific Information; and 6 Workforce Characteristics. The final two have little specificity at all suggesting that either the available content is incomplete, or someone just got tired and decided to stop creating classification titles and descriptions after 4.

At its core, the O*Net model is mechanistic in its approach to defining occupational requirements.

Only one of the six Elements has additional associated content formatted with an ID code: Element 4 associates each Element ID with “General Work Activities (GWA)” and “Detailed Work Activities (DWA).” Interestingly, the logical relationships created through the mapped classifications provide a useful foundation for addressing the critical gaps in the system, and a rudimentary structure for a simple but usable competency taxonomy. Unfortunately, the numbering system utilized is rife with issues due to its paper-based nomenclature. When adjusted, however, the possibilities for a viable decision framework become apparent.

Understanding Fit

So how do we effectively create a structure that opens the doors of possibility for a functional taxonomy to address the inherent complexities and inefficiencies of HR transactions, most notably the Hire? And how do we link such a structure to requisite training content to establish a pathway by which an individual can move from any present state to any future state? The Department of Education developed a classification system in 1980 to address the variance between degree and academic program offerings. This structure is known as the Classification of Instructional Programs (CIP). According to DoE, the CIP is described as follows, “The Classification of Instructional Programs (CIP) provides a taxonomic scheme that supports the accurate tracking and reporting of fields of study and program completions activity. CIP was originally developed by the U.S. Department of Education’s National Center for Education Statistics (NCES) in 1980, with revisions occurring in 1985, 1990, and 2000. For information about these early revisions to the CIP, click here or access specific links to historical versions from the resourcespage. For information about versions after CIP 2000, click the ‘change year’ link on this site to see the available versions.”

A cross walk between the O*NET database and CIP database is readily available, though linkages occur only at the SOC level and not deeper within the competency framework. In order to develop a system that would link to both of these national standards, while allowing for near infinite expansion, a new code — one beyond the existing structure must be developed — and I would submit must be open-source. At the heart of the Candidit model lies the basis of this newly envisioned taxonomy structure along with an interactive framework that allows for complete customization of the linkages to permit continuous improvement in the quality of the matching algorithm and competency linkages as the system is used over time.

For those of you interested in partnering in this journey — a journey I hope will lead to the birth of a new understanding of career opportunities I, as always, invite thoughts, insights and comments!