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Streamlining Growth for Franchisors - Case Study

Streamlined Financial Management - A Case Study

Client: Homefront Brands

Client's Goals: Find and implement a more efficient tool for finance processes and consolidate data across different brands and franchisees.

Our Team's Approach: Citrin Cooperman was tasked with implementing Vena, a corporate performance management (CPM) software, to optimize the operations of a franchisor with multiple brands.

Homefront Brands is an organization that encompasses a growing number of emerging residential and light commercial property service franchised brands. With a network of growth partners, advanced support systems, and in-house consumer acquisition and customer care services, the company accelerates growth for founders and their franchisees.

To streamline management and improve franchisee results, the organization needed to enhance its existing processes and establish a unified, authoritative source of information.


  • Client operates eight different brands with independent data source systems.
  • Google sheets became an inefficient tracking system as the company grew.
  • The budgeting and forecasting processes were excessively time-consuming and inaccurate due to the large number of stakeholders.
  • Lack of permission and visibility control throughout the team.  

Citrin Cooperman's Approach

  • Citrin Cooperman implemented Vena, a cloud-based solution, to revamp and improve existing processes, thereby accommodating the company's rapid growth and future software integrations.
  • Our team developed several custom workflows and templates to streamline the report creation process.


  • Established a unified data source  for eight distinct brands and additional entities.
  • Automated templates to measure advertising spending, franchise time-to-open, and other metrics.
  • Enhanced forecasting capabilities, improving support for franchisees.
  • Accelerated budgeting and forecasting cycles.
  • Established more accurate budgeting process through the collection of clean input and assumption data.

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