We Reduced Maverick Spending By 75% And Increased Savings By 10%

Global large pharma company, California, USA 

Our client is raising the bar for the next generation of digital procurement and payment systems, process compliance, and vendor risk management.  We developed a series of machine learning-based algorithms and workflows to use in their source-to-pay (S2P) system and Procurement help desk, which streamlines finding for the approved vendor and approved rates, increases transparency across teams, and ensures nothing falls through the cracks.

60%

Increase in accuracy of Procurement bots effectiveness in correctly answering user queries.

10X

Faster time to analyze free text and unstructured purchase requisition and order data.

75 %

Reduction in cycle time from purchase request to purchase order.

With the help of Buying Simplified, we could leverage our S2P system better and increase its adoption across all business units for better user experience in the finance and procurement workflow –  Head of Procurement, North America and Global Shared Services 

Goals

Increase spend through pre-existing and contracted supplier contracts and catalogs.

Reduce time to source.

Convert pr to po faster and enhance requester experience.

Our Solution

Cohesive data cleansing, and enrichment strategy, including data standardization, taxonomy correction, desktop research, and following up with vendors for missing catalog information.

Design, implementation, integration, and automation of analyzing a million free text purchase requisition data using machine learning.

Comprehensive documentation and customized team training for all users internally and externally (client, manufacturing partners, and suppliers).

Results

Client users and internal stakeholders could find the goods and services they are looking for from the pre-existing catalogs and rate cards with vendors for most frequently bought goods and services.

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