Customer Story

Moved PE Deal Analysis Beyond Excel with Databricks

What we did

  • Unified four disparate ERP environments into a centralized Databricks data platform.
  • Automated reporting and standardized business metrics to give teams trusted, cross-organizational visibility.
  • Built a scalable foundation for growth and AI, including advanced pricing optimization.

Industry

  • Manufacturing
  • ·
  • Private Equity

Tech Stack

  • Databricks

Databricks Solution Components

  • Lakebase
  • Genie
  • Unity Gateway
  • Lakehouse
  • Agent Bricks
  • Unity Catalog
  • Lakeflow
  • Databricks Apps

Automated LBO Calculations

Reducing spreadsheet work.

Standardized Investment Data

Across aquisition targets.

Scalable Investment Analysis

Supporting all new scenarios

The Problem

A private equity firm focused on mid-sized manufacturing companies, evaluates dozens of potential acquisitions each year. Financial information from target companies arrived in inconsistent Excel files and PDFs, requiring analysts to manually standardize data and enter it into leveraged buyout (LBO) models.

Each new scenario required analysts to adjust assumptions in Excel, with results spread across multiple versions of workbooks. The manual process made it difficult to efficiently compare scenarios, maintain consistent data and assumptions, and scale investment analysis as deal volume increased.

The Solution

Analytics8 partnered with the PE firm to develop a solution that moved its spreadsheet-based LBO analysis into an interactive, automated analysis application. Components include:

  • Standardized Investment Data: Developed a common workbook structure for financial statements, company information, and transaction assumptions across acquisition targets.
  • Centralized Data on Databricks: Ingested target-company data into a Databricks Lakehouse and transformed it through a Medallion architecture into standardized, analysis-ready tables.
  • Automated LBO Calculations: Translated core LBO logic into Databricks to dynamically calculate IRR and MOIC based on financial data and transaction assumptions.
  • Built an Interactive Investment Application: Developed a Streamlit application within Databricks Apps that allows analysts to view results, modify assumptions, and quickly generate new investment scenarios.

The Results

The PE firm moved from a highly manual, spreadsheet-driven deal evaluation process into a standardized, scalable investment analysis capability on Databricks- allowing analysts to spend less time managing models and more time evaluating potential investments.

  • Faster Scenario Analysis: Created a repeatable process for evaluating multiple financing and economic scenarios without duplicating or manually rebuilding LBO workbooks.
  • Standardized Investment Analysis: Centralized financial data, assumptions, and LBO logic to create a more consistent approach for evaluating acquisition targets.
  • Scalable Deal Evaluation on Databricks: Established a modern analytics foundation designed to reduce manual Excel work and enable the firm to evaluate more potential investments as deal volume grows

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