Case Study: McChrystal Group achieves faster, more accurate survey insights with Rackspace Technology (Onica)

McChrystal Group uses machine learning to drive client outcomes

McChrystal Group, a leadership-development and advisory firm, relied on stakeholder surveys—including many open‑ended responses—to diagnose organizational issues, sometimes receiving up to 20,000 answers per survey. Their manual review process was time‑consuming and inconsistent, so they needed an automated natural language processing solution to analyze large, variable‑length responses quickly and accurately.

Onica built a machine‑learning pipeline on AWS (S3, Glue, Athena, SageMaker, Translate) and optimized LDA topic modeling and visualizations for shorter text and diverse client datasets. The solution delivers results in minutes instead of days, scales to very large accounts, uncovers subtle themes missed by manual review, reduces analyst effort, and produces more consistent, actionable insights for McChrystal’s clients.

McChrystal Group

Victor Bilgen

Partner