<cite id="vzx9x"><noframes id="vzx9x"><menuitem id="vzx9x"></menuitem>
<ins id="vzx9x"><noframes id="vzx9x"><cite id="vzx9x"></cite><ins id="vzx9x"><th id="vzx9x"><ins id="vzx9x"></ins></th></ins>
<ins id="vzx9x"></ins><ins id="vzx9x"></ins>
<ins id="vzx9x"><noframes id="vzx9x"><cite id="vzx9x"></cite>
<ins id="vzx9x"><noframes id="vzx9x">
<var id="vzx9x"><noframes id="vzx9x"><cite id="vzx9x"></cite>
<ins id="vzx9x"></ins>

APPROACH

To solve this problem, we leveraged AI Data Cleanser to –

  • Identify and tag obsolete materials in ERP systems based on transactional/inventory/PO analysis.
  • Identify and tag duplication of materials within each ERP and across ERP systems; assign duplicates to a master record.
  • Match these to existing masters in MDG if they exist or add them to MDG if they don’t exist.

KEY BENEFITS

  • Cleansed and corrected material master data to allow the business stakeholders to rationalize materials and suppliers.
  • Obsolete materials were tagged and made non – available for further use/ordering, thereby improving procurement processes.

RESULTS

  • Out of ~1.5M material records, ~0.5 materials were tagged as obsolete, and ~120-150K master golden material records were created.
  • Around 12% in downstream cost savings were observed due to reduction in material duplication and supplier rationalization.

操逼网站