Careers Service
Careers Service
CaseLab brings structure, measurement, and accountability to case interview preparation — enabling the Careers Service to track student readiness, allocate coaching resources effectively, and raise offer rates across the cohort.
Students invest hundreds of hours in MBB preparation, yet the process remains largely informal, unmeasured, and difficult for the Careers Service to support at scale.
Feedback is verbal, forgotten within days. Neither the student nor the university retains structured data on strengths, weaknesses, or improvement.
The Careers Service cannot identify which students are on track, who needs support, or where to direct limited coaching resources for maximum impact.
Students practise with whoever is available rather than being matched with partners whose complementary profiles would accelerate mutual development.
A complete coaching ecosystem with dedicated experiences for students, coaches, and university administration.
Each student sees live scores across all 19 MBB criteria grouped into 5 clusters, session-over-session trends, development priorities, and recommended drills.
Student viewAfter each session, coaches complete a standardised evaluation across the official MBB framework with criterion-level scores and qualitative comments.
Coach viewRankings, risk flags, and resource allocation insights let the Careers Service identify top candidates, spot students falling behind, and prioritise investment where it matters.
University viewThe platform analyses skill profiles to pair students whose strengths and weaknesses complement each other — maximising the learning value of every practice session.
All usersStructured exercises students complete independently between sessions — market sizing, framework application, chart interpretation — each mapped to specific MBB criteria.
Student viewEvery coaching interaction logged with case type, performance data, and qualitative notes — building a complete, searchable learning history for each student.
All usersEvery coaching session produces a structured evaluation across five clusters and nineteen individual criteria. Click any criterion to see details.
Real-time visibility into individual performance and cohort-wide readiness — all built on the MBB evaluation framework.
The algorithm analyses each student's skill profile to suggest practice partners whose strengths complement their development areas.
Each exercise is mapped to specific MBB criteria, allowing students to practise independently and track their development.
12 progressively harder market sizing prompts with model answers and scoring rubrics.
Build a MECE issue tree in under 90 seconds for each prompt. Timed, self-graded.
Read a case pack, summarise findings in a 60-second top-down recommendation.
Extract the three most important insights from 10 data exhibits under time pressure.
Unconventional prompts that reward creative brainstorming and non-obvious solutions.
Craft and pressure-test personal experience interview stories using the PEI framework.
We would welcome the opportunity to present a full demonstration to the Careers Service and discuss how CaseLab could be tailored to Saïd Business School's specific needs.