Data Management Services are focused on increasing the effectiveness of the procurement, inventory and maintenance management functions across the enterprise through the standardization and enhancement of MRO Material, Vendor and Service Masters Data within the ERP, as well as optimizing inventory information relating to Inventory Management information.

     Dirty data is a term used by Information technology (IT) professionals when referring to inaccurate information (data) collected from data capture forms. There are several causes of dirty data. In some cases, the information is deliberately distorted. A person may insert misleading or fictional personal information which appears real. Such dirty data may not be picked up by an administrator or a validation routine because it appears legitimate. Duplicate data can be caused by repeat submissions, user error or incorrect data joining. There can also be formatting issues or typographical errors. A common formatting issue is caused by variations in a user's preference for entering phone numbers.

     Gartner research shows that poor-quality customer data leads to significant costs, such as higher customer turnover, excessive expenses from customer contact processes like mail-outs and missed sales opportunities. But companies are now discovering that data quality has a significant impact on their most strategic business initiatives, not only sales and marketing. Other back-office functions like budgeting, manufacturing and distribution are also affected. Compliance and transparency are now at the top of the list of most companies’ data concerns, according to Gartner.*



What is Dirty Data?

  • Not structured / Free Text
  • Not complete
  • No Use of Nomenclature (Name Conventions)
  • Garbage / fictitious / ambiguous data
  • Many duplications
  • Many data elements Represent “Old / Non Moving” materials


The Effects of Dirty Data On Industry


  • Free Text = Maverick Spend
  • Poor/No Spend Visibility
  • Cost Increases
  • Limited Compliance management
  • Poor Service Levels
  • Plant Down Time
  • Incorrect Products
  • Stock-outs & Expedited Orders
  • Limited Search Functionality
  • Procurement with Uncertainty
  • Poor Contract Management
  • Poor Spend Visibility
  • Limited Sourcing & Auctions
  • High Inventory Holding Costs
  • Reconciliation of order to goods
  • High QTY of materials on-hand
  • High QTY returns to vendor


How Bad Is The Problem?

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Next: Dirty Data Pt.2 - What Customers are Trying to Solve and How Ariba Helps


Beverly Dunn is a Client Engagement Executive with Ariba. All customers are invited to join the private Customer Success group on Ariba Exchange, where you can access the Customer Success Spotlights, Lunch 'n Learn Webinar calendar and replays, and the Ariba Knowledge Nuggets.