AMD Consulting

A leading Pharmaceutical company significantly improved its spend visibility through Data Quality Enhancement Initiative.

Overview
The company was launching an ERP (SAP-Ariba) upgrade program and was looking for item master data cleansing and categorization services in order to have a clean start with the new system. A significant portion of the spend was on indirect material and services, spread over multiple plant locations, which made this exercise critical to the success of the project.
Challenges
  • Inadequate & inconsistent item description, hidden duplications, and inaccurate classification.
  • A key driver of poor data quality was an inefficient Data Governance Process and System.
Solutions

Our rigorous process on Data Quality Enhancement has not only improved the spend visibility & analytics but also enabled effective use of features such as Guided-Buying on the SAP-Ariba platform.

Various work streams included –

  • Data Cleansing
    Initial level cleansing to segregate data by quality & nature of issues.
  • Specification Enrichment
    Item specification enrichment as per standard data taxonomy & Structure
  • Item Categorization
    Granular categorization up to 3 levels.
  • UNSPSC Mapping
    Line item level UNSPSC codification & mapping to level 3 category.
  • Data Governance Structure
    Define and implement a robust data governance policy that included a structured approval process
  • Spend Analysis
    High-level spend analysis to identify cost saving opportunities.
Results

A clean and structured Material Master enabled higher spend visibility, the opportunity to effectively reduce costs as well as manage optimal inventory, and above all a data driven decision making.

Key outcome of this exercise included –

  • Over 90% reduction in number of active item codes.
  • Accurate and usable spend analytics reports.
  • Efficient procurement through standardization & catalog buying.
  • Clear roadmap to optimize indirect spend sustainably across all plant locations.
  • Opportunity to reduce overall procurement costs by 10 to 15% in the first wave.
Improve your data quality to ensure effective decision making

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