Cost-Cutting Consulting Case Interview: AI in Healthcare (W/ BCG & EY Consultants)

Why It Matters

If successful, AI-driven workflow changes could meaningfully reduce costly agency spend and improve margins without compromising patient care, offering a repeatable model for other labor-intensive hospital functions. The pilot will signal how healthcare systems balance automation, quality outcomes, and workforce redeployment amid structural nursing shortages.

Summary

Consultants advised Kaiser on a pilot to use AI-enabled workflow redesign in medical imaging to address rising labor costs driven by nursing shortages and expensive agency staffing. They focused on mapping FTEs and fully loaded labor costs, decomposing imaging workflows into pre-procedure, procedure, post-procedure and administrative steps, and identifying repeatable, rule-based tasks with high AI fit. The team proposed quantifying potential savings from targeted automation, evaluating impacts on care quality, and planning redeployment pathways for freed capacity. The approach emphasizes a measured pilot to test sustainable cost reduction before broader staffing changes.

Original Description

🎥 Here’s a consulting case interview focused on reducing healthcare costs through AI-enabled workflow redesign.

Caiser, a large integrated U.S. healthcare system, is facing mounting margin pressure as labor costs - especially nursing and agency staffing - continue to rise. The Board wants to understand whether AI can meaningfully reduce workforce costs without compromising access or quality of care. To test this, leadership has chosen to pilot AI-driven workflow changes in medical imaging, where processes are particularly labor-intensive.

Watch Ben Wilson (Director at Alvarez & Marsal, ex-EY, Darden MBA) run Christopher MacRae Ham (ex-BCG Project Leader, London Business School MBA) through this cost-cutting operations focused consulting case interview.

🎬 Video Sections:

00:00 Start

00:03 About the case

00:39 Case question

01:20 Clarifying questions

04:48 Framework

07:22 Interviewer feedback

07:55 Charts & data I

15:55 Interviewer feedback

16:48 Brainstorm

20:34 Interviewer feedback

21:18 Charts & data II

23:43 Interviewer feedback

24:00 Quantitative

29:16 Interviewer feedback

29:57 Recommendation

31:19 Interviewer feedback

31:37 Conclusion

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