Careermaps, Consultation, Screening & Selection, Transformation Case Study
Volume Screening for Belfast Met
Background
Belfast Metropolitan College (BMC) runs an annual ICT Apprenticeship scheme, a collaborative initiative between the government (Department for the Economy) and leading local ICT companies. This scheme aims to recruit and employ successful applicants in various software development and IT infrastructure roles while they undertake training in Level 3, 5, and 6 Apprenticeships NI frameworks for ICT through BMC.
Given the intensive learning required throughout the apprenticeship, it is crucial to attract and select the right talent through a robust screening process. This involves using psychometric blended assessments to evaluate applicants’ natural skills, abilities, and capacity to process information.
Challenge
One of the main challenges faced by the program is the high volume of applications from young people with little to no experience. This makes it difficult to identify the most suitable candidates. To address this, Belfast Met utilises Mindmill’s role-based blended assessments, which are tailored to evaluate the specific skills and potential of each applicant. This approach helps in efficiently selecting candidates who are best suited for the roles they will undertake during their apprenticeship.
Solution
Mindmill developed a cognitive assessment programme to identify candidates capable of learning the required skills for the apprenticeship. This programme serves as the primary screening method to select candidates for interviews with participating ICT companies.
The cognitive assessments test various skills, including Error Detection, Orientation, Number Fluency, and Odd and Evens. These assessments demand attention and the ability to hold information in memory long enough to process it correctly, as working memory is a key indicator of performance. The assessments focus on natural ability to learn new skills rather than learned curriculum, allowing employers to assess candidates’ raw potential.
Output data from the cognitive assessments include a CPI (Capacity for Processing Information) score, which combines speed and accuracy to identify how quickly an individual can process information and learn new skills. Candidates with top CPI scores are invited to retake the assessment in exam conditions to verify their initial results. Successful candidates are then invited to interviews with employers from participating companies. Those who are appointed attend a boot camp at BMC before starting their apprenticeship, which involves four days of employment and one day of college per week.
Implementation
Mindmill’s screening and selection methodology is designed to sift through candidates efficiently, ensuring that only the most suitable individuals progress through the process. The psychometric assessments are predictive in nature, allowing Mindmill to forecast with 97% accuracy which candidates are likely to complete the training successfully. This high level of accuracy ensures that employers invest in candidates who have the greatest potential to thrive in their roles and contribute meaningfully to their organisations.
2023-2024 Recruitment Statistics
- Approximately 600 applicants
- 111 Apprentices successfully recruited
- 41 at Level 3
- 52 at Level 5 HLAs
- 18 at Level 6 HLAs
The ICT Apprenticeship has been running successfully since 2013 and continues to achieve significant success in matching individuals’ skill sets with industry needs. This process has become increasingly critical to the thriving ICT industry. Effective screening and selection based on data indicating natural skills, aptitude, ability, and personality enable employers to place potential talent in the right roles, ensuring up to 97% of apprentices gaining full time employment through the program.
Outcome
Mindmill assessments have effectively and efficiently identified candidates with the most potential to be trained in the necessary skills and qualifications for a career in ICT. Psychometric testing is increasingly recognised as a critical element of screening, particularly within software and product development roles. The predictive nature of these assessments ensures that employers can confidently select candidates who are most likely to complete their training and excel in their careers.
Case Studies
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