Business Impact

  • Optimized the supply chain for the best price and delivery

  • Improved vendor management, credit, and cost controls

  • Faster and better data-driven decision making

Customer Key Facts

  • Location : India
  • Industry : Pharmaceutical
  • Core Product : Covid-19 Medicines

Problem Context 

The client is a pharmaceutical company headquartered in Bangalore, India. They wanted to discover alternate vendors who could offer the best deal and track procure-to-pay matrices.

In a Pandemic that impacted the world, they wanted to ensure the supply chain optimization for the best price and best delivery while evaluating the best alternative vendors among the existing, with Best-buy Attributes.

The client had an existing SAP ERP & BW. Through desired new age insights and decision making, they aimed at moving towards advanced analytics and visualizations.


  • The client’s existing process to gain insights from data was cumbersome
  • The existing reports in SAP and BW were historical in nature, and could not give predictive analyses
  • Lack of expertise in-house to develop an advanced analytics solution for evaluation and prioritization of the vendors

Technologies Used

Google BigQuery
Google Data Studio
Google Data QnA
SAP Data Services, ERP, BW


Quantiphi developed a set of visually enriched Procure-to-Pay Analytical Dashboards, evaluating Best Buy Attributes for Primary and Alternate Vendors using Google Cloud’s BigQuery and Data Studio.

We leveraged high-value SAP data through the pipelines by integrating the data across the SAP Logistics modules, specifically P2P tables.

This enabled clients to shortlist vendors who could offer the best deal and track all Purchase Orders.


  • High-fidelity dashboards rendered to the client’s pharma-specific visualization themes.
  • Motivation to repeat the success of the Procure-to-Pay process for other business processes.

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