Case Study: Makena Capital cuts analyst reporting time 50% and builds a firm-wide data culture on Sigma
Key results
The challenge
Makena Capital, a private endowment managing roughly $20 billion in assets in a fund-of-funds structure, had analysts spending 10 to 20 hours per week downloading CSVs, manually assembling Excel files, and dragging formulas to produce quarterly reports. Its core private-assets dashboard was a single Excel file with a 50% failure rate on open, and four analysts performing the same join independently produced four different outputs. With 20 years of data across vendors and no single source of truth, the firm could not reliably validate that client-facing numbers matched the underlying model.
The solution
Makena selected Sigma for its native Databricks integration and its ability to bring non-technical users into the analytics layer without engineering support. The data engineering team built governed data models as a shared foundation, and analysts built workbooks on top without re-deriving joins. Sigma's Input Tables and controls powered a forward-looking portfolio modeling tool, while conditional formatting and lineage tracking replaced manual audit processes and flagged anomalies at the transaction level.
“We want analysts to do analysis. We don't want them spending their time building reports. We want them using those reports to make their job better, to deliver more sophisticated insights.”
KKKunal KoppulaHead of Data Engineering, Makena Capital
The results, in context
Analysts who previously spent 10 to 20 hours per week on report assembly reclaimed that time for analysis and client engagement, a roughly 50% reduction in weekly reporting hours. Investment analysts became builders, creating self-service tools for portfolio projections, client-specific reporting, and interactive exploration. Penny-level data fidelity is now enforced systematically rather than manually across the firm's approximately $20 billion AUM book.