As part of our on-going commitment to quality and fairness, we undertake continuous assessment of anonymised data from candidates using Sammi.
We evaluate candidates at volume but also undertake detailed analysis of random samples. Our data shows interview outcomes do not show major bias toward or against any identified group including gender, nationality, and disability. We found performance was consistently fair across all groups, with rewarding signals of enhanced fairness and very good/excellent reliability.
User surveys have consistently demonstrated both assessors and candidates rated the platform highly for convenience and usability.
SAMMI® is grounded in the proven scientific interview methodology, Multiple Mini-Interviews (MMIs). Co-created with diverse users, SAMMI® integrates insights on inclusive language and uses an interface that softens the interaction between humans and technology for maximum performance.
Hosted by Darren Topping, Director of Solutions at Lorien Global, Dr Alison Callwood speaks about her experience from starting off as a midwife all the way through to her prestigious Innovate UK award, and what business owners can do to improve their business' diversity.
Evaluating a first fully automated interview grounded in MMI methodology: results from a feasibility study
Callwood, A., Gillam, L., Christidis A., Doulton, J., Harris, J., Coleman, M., Kubacki, A., Tiffin, P., Roberts, P., Tarmey, D., Dalton, D., Valentin, V.
The predictive validity of Multiple Mini Interviews (MMIs) in nursing and midwifery programmes: Year three findings from a cross-discipline cohort study.
Callwood, A., Groothuizen, J., Lemanksa, A., Allan, HT.
The reliability and validity of multiple mini interviews (MMIs) in values-based recruitment to nursing, midwifery and paramedic practice programmes: Findings from an evaluation study.
Callwood, A., Cooke, D., Bolger, S., Lemanska, A., Allan H.