Developing, Evaluating and Commercialising Scalable Automated Multiple Mini Interviews

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Large multinational companies spend, on average, £4k hiring each new employee; with over 4000 vacancies to fill a year, the costs can exceed £16m. Interviewer bias is widespread across sectors; according to UK government figures, at the most senior level of corporate leadership, 96.7% of individuals are white and 71% male.This 18-month, project, funded by Innovate UK, will enable the refinement, testing and launch to market of a state-of-the-art automated candidate selection system, SAMMI (scalable automated multiple mini interview) designed to get the right people into the right job while increasing cost-efficiency and diversity hiring.SAMMI is currently a prototype designed to offer a scalable, automated version of the face-to-face 'Multiple Mini Interview' (MMI) technique endorsed by Health Education England and widely used in healthcare student selection. MMIs involve candidates sitting a series of 'stations' which present bias-free, 'real life scenarios' designed to assess soft skills. SAMMI builds on over ten years of MMI research and text analytics with a custom built online system. Conversational analysis techniques evaluate applicants' interview responses (text/speech) and artificial intelligence enables scoring of candidate answers/interactions against pre-defined soft-skills. The analytics extracted of candidates' soft skills are applicable to: pre-screening, selection and comparison against CVs/personal statements/cover letters.The SAMMI prototype was developed at the University of Surrey in 2018. It has been tested at Manchester Medical School and The University of Surrey demonstrating good functionality and test re-test reliability. The Innovate UK funded market validation journey revealed extensive international interest in SAMMI across 100+ companies/organisations (private, public and charity) undertaking large scale candidate selection.This project will leverage SAMMI to enable quicker market entry thereby capitalising on prior investment and established customer contact. Core SAMMI components will be developed, refined, tested (to ensure bias-free) and case study evaluation of the effectiveness (reliability, validity, functionality, acceptability and cost-benefit compared to a face-to-face comparator) of SAMMI is planned. Discussion are ongoing with potential pilot sites for example: UK and US Medical Schools; international non-governmental organisations and multinational companies. Time and resources will be used to enhance SAMMI with complementary 'add-ons' including a novel applicant tracking system comparing CV/personal statement content with interview performance.SAMMI offers a unique system designed to be cost-efficient as well as avoid unintentional interview bias.