The digitalisation of traditional assessment methods is spawning a wide range of instruments to predict future work performance. What are the implications and where are we headed?
Based on my experience as managing director at Aperio -Assessment & Development, I would like to highlight some opportunities and challenges for HR practitioners interested in exploring and improving these innovations. Some key areas to consider should be:
- Measurement equivalence when using a mobile phone or tablet versus desktop.
- Datification of talent and questions of accuracy and validity, versus price and user experience.
- What does the future of talent identification look like – Hot or Not?
A significant technological push in employment testing has been toward mobile internet testing. Obvious advantages are minimal costs, increased speed, and convenience for both administrators and participants. Indeed, Aperio behavioural and cognitive assessments have been developed to be used for this purpose.
However, we have at times seen more sporadic results coming from candidates who have completed assessments on mobile devices rather than desktop, with clients raising questions such as:
Can dealing with limited screen size, fiddly input methods, and challenges in navigation impact candidate performance on mobile devices?
What is the measurement equivalence of different types of tests when completed using a mobile handheld device versus on a desktop?
Candidates have also shown increased anxiety related to mobile testing and reactions to the tests taken affecting performance. These are most likely linked to increased sound, visual and motion distractions.
At Aperio we recommend that companies considering mobile delivery of assessments might want to ensure that test takers have the opportunity to choose to complete assessments on desktops or notebooks if desired, so as to reduce these negative influences on test scores.
However, the digital revolution of assessment methods is far from limited to online and mobile testing. The datification of talent is upon us, and the prospect of new technologies is exciting as well as daunting. As we continue to innovate and develop new products for market at Aperio we are uncovering some interesting progression as well as obstacles to new technologies.
Many new tools especially that involve scraping publicly available records as found on social media eg. Facebook, LinkedIn etc. do not demonstrate validity comparable with traditional methods, tending to pay less attention to the constructs being measured. This may not worry big data enthusiasts so much as they are primarily interested in finding relationships between variables. We agree that predicting behavior is a key focus in talent identification, but we also believe that understanding behavior is equally important when predicting performance in a future role. Scientifically defensible assessment tools such as Aperio do not just provide accurate data, they also explain how we can expect a candidate to behave in certain situations.
Privacy and anonymity concerns may also limit access to individual data, a point that is being raised repeatedly both in the market place as well as scientific circles. People are living their lives increasingly online. By doing so they make their behavior public, and that behavior leaves more or less perpetual footprints. It has been found that emerging tools leveraging social media profiles are highly likely to identify an individual’s ethnicity, gender, or sexual orientation as well as talent signals. These applications enable employers to know more about potential candidates than they probably should, and ethical and legal issues may represent the ultimate barrier to the long-term application of such technologies.
Finally, when we look to the future of assessment methods I cannot help but draw parallels between the direction we are headed and the popular dating application Tinder. We see increasingly with job and career sites as well as LinkedIn, where people are including their profile reports with their resumes as well as photos and other biodata.
As is the case of Tinder, users agree to have some elements of their social media footprint profiled when they sign up for the service. Potential employers are able to judge these profiles and report whether they are interested in them or not, similar to Tinder’s swiping left or right (…so I have heard). There is actually research supporting that personality traits can be accurately inferred through photographs and that these inferences drive dating and relationship choices. Finally, if the algorithm determines a match, both parties receive instant feedback on their preferences. This model is increasingly being applied to the talent identification process. You could argue that it is easier to predict job performance and career success than relationship compatibility and success.
In summary, our challenge today as organisational psychologists and HR practitioners is to integrate the fragmented services and technology of today with scientifically proven methods to create the most accurate and predictive profiles yet.