CASE STUDY
Company Sale
Industry
— Manufacturing
— Auto
Duration
— 9 months
Team
— 1 Managing Director
— 1 Director
— 1 Vice President
Services
— Sell Side Readiness
— Transaction Due Diligence
Developing a KPI Data Cube For a Company Sale
A private equity-backed auto parts manufacturer preparing for a sale required a consolidated, enterprise-level view of sales, gross margin, and KPIs across customers, SKUs, and other dimensions. The $250M revenue company had acquired five businesses in the past two years, creating challenges in integrating over 2.7 million transaction-level data points from six disparate ERP systems. To support seller due diligence, we developed a KPI data cube while also managing diligence responses and key analyses in collaboration with Management, the Sponsor, and the investment bank
The Execution
Partnered with the Sponsor and key company leadership (CFO, VP of Sales, CIO, and FP&A) to access ERP data, validate it against financial reports, and map previously untracked dimensions.
Conducted interviews with Management to determine critical data fields and structures required to support the sell-side thesis and facilitate quality-of-earnings (QoE) analysis.
Built a KPI data cube using Power Pivot and Power Query to generate essential insights, including:
Customer churn analysis
Price-volume mix by SKU
Sales and profitability by customer, channel, product category, SKU vintage, and replacement vs. performance parts
Managed information requests and diligence responses, ensuring accurate, timely data for QoE analysis and buyer diligence.
Transitioned the KPI data cube to the FP&A team as an ongoing enterprise performance tool and provided guidance on leveraging it as the foundation for a future business intelligence (BI) system.
The Results
Facilitated a competitive sale process with multiple bidders by equipping Management with the necessary insights to respond confidently to diligence inquiries.
Provided the Sponsor and Management team with ongoing transaction-level visibility, enabling future acquisitions to be integrated seamlessly.
Following the sale, the company engaged in further discussions to enhance its BI capabilities using the KPI data cube as the architectural foundation.
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