CaseStudy: P-card analytics for a Real Estate Company.

Industry Real Estate and Construction industry

Public/Private – Private

Annual Revenue $2.5B

Number of Divisions 17 global divisions

Problem

  • P-card spend was not managed and increasingly high, with around 30M spend annually

  • Improper categorization of the P-card data causing firm to miss out on savings and compliance opportunities

  • Lack of aggregation of Accounts Payable and P-card data causing uncontrolled spending

Process

  • Worked with client to outline the data flow of P-card data and accounts payable

  • Assigned logical categories for the P-card base data which included level 2 and 3 categorization.

  • Automated the categorization of future data flows into system by setting business rules with the custom taxonomies for both, P-card data and accounts payable data

  • Developed logical rules to help reporting of savings opportunities in terms of supplier aggregation and maverick spending identification

 

Key Findings/Savings

  • Discovered high amount of spend in travel category with the increased visibility due to categorization. Identified opportunity to save 15% on 20M Travel Spend annually.

  • Identified 1.2M worth of maverick spend

  • Discovered that uncontrolled spend was more than the managed spend. Specifically, certain equipment rental suppliers had large amounts of spend through both P-card and AP. Identified savings of 3M through the opportunity to aggregate the P-card spend with the AP spend.

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