McKinsey Representatives Visit Master of Commerce Students
This article documents a campus visit by McKinsey & Company representatives to postgraduate business students at the University of Virginia. While the discussion is specific to a single institution and cohort, the themes raised are commonly cited in consulting recruitment, particularly for analytics-oriented roles.
In 2021, Master of Commerce students from the University of Virginia’s McIntire School of Commerce met with McKinsey & Company Solution Manager Janet Gessner Alford and Client Service Senior Manager Doug McElhaney. The visit focused on analytics careers and included a mock analytics case completed with students in the Marketing & Management concentration.
The questions below reflect what McKinsey representatives highlighted during that visit. They should be read as a case study rather than a comprehensive or current statement of McKinsey’s global hiring criteria.
Why do you like to hire UVA’s M.S. in Commerce students?
Doug: Janet has been working with Professors Netemeyer, Maxham, and Abbasi since the inception of the McIntire School’s Center for Business Analytics and serves on its Advisory Board. As part of that effort, Janet previously visited the M.S. in Commerce Consumer Analytics class and led McKinsey’s initial recruitment of M.S. in Commerce students for analytics consulting roles. This visit represented our second year recruiting from the program.
Janet: We like to hire M.S. in Commerce students because the program prepares them strongly in two broad areas. We often describe these as an “analytics spike” and a “consulting toolkit.” Candidates need to be able to perform analytically from day one, but they also need client-facing skills such as structured problem solving, business judgment, teamwork, and the ability to translate analytical outputs into practical insights.
What tangible skills do M.S. in Commerce students bring to McKinsey?
Doug and Janet: We consistently look for three capabilities.
The first is problem solving and problem structuring. Consultants must be able to take ambiguous problems and impose structure so teams can make progress efficiently.
The second is business acumen. This means translating quantitative findings into meaningful implications for a client. Identifying a pattern in data is only useful if you can explain why it matters.
The third is analytics capability. Candidates should be comfortable applying different analytical approaches to understand complex data environments. While analytics is emphasised differently across McKinsey practices, it is increasingly central to how the firm delivers client work.
What was your favourite part about your visit?
Doug: Working through the “Big Bank” case with students stood out. The teams were asked to propose approaches to a complex problem with limited information, and several groups demonstrated a willingness to take informed risks by outlining structured analyses and work plans despite the lack of data.
What insights did you gain from the analytics case exercise?
Doug: The students showed a strong mix of technical aptitude and curiosity. Effective analytics requires both. In consulting, analytics sits at the intersection of technical skill and a willingness to explore unfamiliar data and test new ideas. That combination was evident during the session.
What should students know if they want to enter analytics or consulting?
Doug: Two things matter most. First, build depth in the application of analytics. Knowing many techniques is less valuable than understanding when and why to use them.
Second, learn to structure problems. Analytics can easily lead to overload. A structured approach allows individuals and teams to test hypotheses efficiently and avoid analysis paralysis.
For a broader and more current view of consulting recruitment, students should also consult firm-level guidance such as McKinsey’s public careers material, which outlines skills, pathways, and role expectations across regions (McKinsey & Company Careers).
