Aline Lerner (blog.alinelerner.com) recently published a post on shockingly low efficacy of resume processing chain; the major culprit being the lack of clarity in describing the current work values and achievements. As a result the probability of sorting out the best match approaches that of an uneducated guess - 50%. This result seems incongruous with what we know about artificial intelligence (AI) and the great advances it makes in banking, health care, education, etc.
Low efficacy of engineers filtering has its heavy toll – more working hours are wasted on training and educating at best; more project delays and costs overruns, at worst.
Is there an alternative to human-crafted and human-interpreted resume?
In fact, this work – to make it less biased and more content-rich - is underway and gains momentum.
Some companies already shifted its focus to the applicant latest activities on-spot ranking and totally disregard resumes. Others stage an interview show to select the best actor. LinkedIn, the biggest professional forum, tries to rank the users by a number of connections, followers, posts, and projects. What about keyword-driven algorithms of Applicant Tracking Systems, you ask? Of little help, as every job-seeker has figured out how to stuff his or her resume with keywords they’ve plucked from the job ad. (By Society of Human Resource Managers about 53 percent of resumes and job applications contain falsifications.)
So far, no one really knows how to write resumes particularly well, on the one side, and how to fix top-of-the-funnel filtering, on the other side. In most cases it is staffed with people not technical enough to understand the resume details.
Another problem that surfaced in LinkedIn is the job relocation requirement, which drastically narrows the search for the right person. If this limitation is lifted, the applicants' number will surge dramatically and slow down job search to a crawl.
What, I think, will happen next may be illustrated within the context of business specific cloud platform – nearest target for any company under disruptive transformation.
At present Crenger (crenger.com) is the only working prototype of such a platform for water treatment and desalination. It covers all the business stages from the project bidding, engineering and management to the plant operation and maintenance. Ideally, with time such a platform may turn into ecosystem for all company activities. The user may plug into this platform from any location, learn, get certified, start working on her/his project, place and track orders, share data, get advice, etc.
As Crenger records, tracks and analyzes each and every move and touch of the user, it is reasonable to ask it to compile the user resume with ratings, strong points and projections. Crenger generates the user business digital signature (UDS), part of it is summarized in the human understandable resume. Currently it has the following entries.
- Expertise ratings for each specific area and Global Expertise Rank
- Global Contribution & Participation Ranks for the projects executed in the past
- Global Certification Ranks for business areas (engineering disciplines, project management, etc.)
- Lead Level assessment (ability to produce and implement non-typical solutions, under development)
- Peers & Reviewers Contacts
As UDS is a collection of quantitative ratings and scores, the selection of the best candidates performing above some minimum threshold is straightforward. Of course, figuring out if someone is great will require more sophisticated algorithms. Google already beat this path in the text-driven world.