Trying to identify, understand and match future leaders using the traditional recruitment process was proving prohibitive due to time, resource and costs.
As this type of talent is in high demand and in short supply, the hiring process needed to be positive – regardless of whether the participant was successful or not. And given tight deadlines in the service industry, opportunity costs and time had to be minimized.
Using Cognisess’ video technology – Computer Vision and Deep LearnTM, the tool formed a central part of the client’s future leaders programme whereby candidates recorded three 45 second video profiles answering set questions as well as completing Cognisess’ baseline assessments.
Deep LearnTM instantly analysed each video for Positivity and Expressiveness by reading facial expressions across thousands of data points, 100 times more accurately than any human assessment and in a fraction of the time.
This technology opens up huge opportunities for the client to become more robust in recruitment and assessment of all customer facing employees where Positivity and Expressiveness are predictors of success.
Computer vision technology formed a central part of the management fast-track recruitment programme for which a high number of applicants needed to be screened and assessed accurately and efficiently.
Whilst close to 100 different attributes and several machine learning models were used to inform the overall hiring decisions for the fasttrack programme, the computer vision aspect that focussed on the emotion detection was particularly powerful. It showed clear, statistically significant differences between those candidates that were ultimately presented with a work contract, and those who were not. This difference even held up across two separate cohorts with slightly different entry requirements.
Cognisess Pro provided a very comprehensive suite of assessments spanning all relevant areas of performance that give HR professionals and hiring managers a competitive edge in finding the right talent. At the same time, the use of AI and objective measures of performance allowed candidates to highlight what makes them great and highly suited to their roles, whilst preventing any human bias affecting the data purity.
MATCH Between Human Rating & AI
ACCURACY IN SUCCESS PREDICTION
Estimated Assessment centre saving