Did you realise Leonardo de Vinci is recognised as having created the first known and recorded CV? He did this back in 1482. But while the CV has since been formalised (1950s), personalised (1960s) and templated (1970s), it is surprising that the first guide to writing a CV only appeared in 1984.
Since the launch of the major internet companies like Google (in 1998), we have seen greater sophistication through the offices of LinkedIn (2003) and YouTube (2007)1. Running parallel to these developments has been the growth of businesses finding ways of identifying ‘hidden’ candidates by using data science methods to profile potential recruits in new ways2. But despite better ways of presenting a career, the CV has not changed greatly. Is the CV due for a change now? And, if it is, what might it look like?
Most CVs have a series of key features: no more than two well-balanced A4 pages; effective use of headings; clear layout, concise format; organised into expected (by the employer and recruitment agency) sections; tailored to the job being applied for; etc. Typical headings in a CV are: personal information; education; work experience/career to-date; skills; interests and achievements; plus, a summary profile and listing of awards3. International transferability of qualifications and their recognition has been helped by the Bologna Process4. But what should a CV contain?
At the heart of the recruitment process is one of matching the capability of the individual (and their aspirations) with the entry and near-term future requirements of the role with an eye on the medium-longer term future likely needs. To make this match there is a need to assemble both personal career information and job requirements and so acquire data on:
|Occupation Data Category/Individual Capability Area||
Individual/Job Applicant Contribution
|Abilities||What are your top 6-10 abilities?||What are the top 6-10 abilities required to rapidly enter and succeed in the role?|
|Work activities||What do your abilities allow you to achieve?||What are the major activities of the role?|
|Education (include awards and other qualifications)||What is the range and depth of education and other qualifications and experiences?||What is the minimum education requirement for the role?|
|Interests||How can you best demonstrate your personal and career preferences?||What are job and career interests of your best performing job holders?|
|Job level||How have you demonstrated the ability to compress job entry learning and work at levels above the jobs you have held?||What is usual time period of education, training and experience required to undertake the role successfully?|
|Knowledge||What fields of knowledge have you mastered through your education, training and career?||What are the critical areas and items of knowledge to successfully perform in the role?|
|Skills||What range skills and at what level of proficiency have you demonstrated them?||What are the top 6-10 skills required to be successful in the role?|
|Technology skills and tools||What range of technology (largely computer-based) skills are you competent in?||Which specific set of technology skills are required to enter an operate in the job?|
|Work context||What range of work contexts (types) have you worked within?||What is the predominant work context of the organisation, and does this demand any specific requirement of employees?|
|Work styles||What style (personal characteristics) of work best suits your approach to work?||What is the predominant work style of the organisation?|
|Work values||What set of organisation beliefs, culture and behaviour best suits your style of working?||What are the core values of the organisation, and how do these translate into specific employee behaviours?|
Notes: These 11 data categories are taken from the 15 used by O*NET.
Assembling the data required to complete the matrix shown in Table 1 would allow both potential applicants and employers to undertake a close matching of capabilities with requirements. Now if this is the direction of travel for the future CV, then it would mean that candidates would assemble a structured dataset which captures their capabilities and achievements which can be assembled to meet any and every job application. This would also suggest that employers receiving on-line applications would be able to interrogate5 the CV of all applicants and so allow greater validation of the statements made6. Such interrogation would allow for greater filtering of applications but also shape and structure any further elements of the recruitment process.
All of this makes great sense, and is common to well-run recruitment processes now, but the big departure from current practice is the sharing of itemised CV data across a common platform which is trusted by candidates and employers, as well as those in education, training, staff agencies, and the recruitment industry7. We can see algorithms seeking to achieve this matching and deeper searching of capabilities which are implicit in the experiences of a candidate8. By making candidate data more explicit and structured both allows all candidates to declare their full capabilities to employers. This would also pressure education and training organisation to declare the outcomes gained by their students in a very explicit way. The practice of using an applicant’s portfolio is already well practiced in the performing arts and art more generally.
Will a data-based approach to CVs really happen? Beyond lodging their CV on a website, would candidates easily move to uploading skills, abilities and competence level data? One of the possible by-products of this trend would be for learning outcomes to be more clearly stated and linked to micro-credentials, rather than being wrapped up in whole unit assessments and accreditation9. With this direction of travel comes the value of career mapping and the identification of the gaps between a candidate’s current career (and CV) and their desired target career entry point. And, perhaps, out this will come greater student and candidate engagement and their personal development10.
The CV is dead. Its place will be filled by a database which can be multi-formatted and interrogated by both the owner (the applicant) and employers and their intermediaries. What we need, however, is an agreed framework and a set of metrics for each and every event and achievement statement (and the associated competences, abilities, knowledge and skills).
- 1: See: www.theundercoverrecruiter.com
- See for examples of HR Tech: www.codility.com and www.hrtechintl.com where the big drivers are using big data and using predictive analyses
- See www.imperial.ac.uk/careers – provides the guide for the students of Imperial College London
- European Commission/EACEA/Eurydice (2015) The European Higher Education Area in 2015: Bologna Process Implementation Report. The Bologna Process is a process of co-operation and reform in the field of higher education bringing together 48 countries. It established and seeks to consolidate the European Higher Education Area (EHEA) with comparable and compatible systems of higher education in order to facilitate mobility, increase employability, allow equitable student access and progression and strengthen Europe’s attractiveness and competitiveness worldwide.
- See: www.michaelpage.co.uk contains a series of useful insights as to where the CV of the future might lie
- See: www.analyticsinhr.com – provides a set of useful HR metrics to drive improved performance
- Will this be a commercial platform and be a near natural development of the current job search and matching sites, and/or a centrally driven one run by a Government agency like the Careers and Enterprise Company. This is clearly a space which will be contested over the coming years.
- See  above
- For example, see the micro-credentials work of Future Learn and its multiple higher education partners. It is worth noting the development of micro-credentials opens-up the opportunity for picking and mixing across degree programmes from several higher education organisations.
- A further next step in this process would be the more formal linking of occupation demand by highlighting those jobs which are emerging and have significant job postings, and so prompt individuals of further alternative career paths.