The process of cleaning your business data is not a one-time task. The goal of data cleansing is to resolve data issues before they cause business interruptions, compliance risks or other issues. This becomes particularly apparent when organizations go through Mergers, Acquisitions or Divestitures. In cases of M&A, it is important to understand that implementing a data quality business process takes time and refinement over the course of its implementation.
Not getting your data house in order before an M&A event can add millions to the bottom-line costs, not just in the short term but for years to come. In one scenario, a $10B+ chemical manufacturing organization acquired a competitor’s division. The technology acquisition team recognized that both companies utilized the same SAP ERP system and expected the data migration process to be efficient and relatively economical over a short six-month period. However, once the acquisition occurred, the project team quickly discovered that the data processes and practices were inconsistent. They both lacked mature, standardized data standards across systems and functional areas, resulting in significant data quality and interoperability issues. Ultimately, the company spent more than a year beyond the completed go-live date and more than $40 million to harmonize the data and establish cohesive data standards.
Share this Marketoon or use it to generate a conversation around data quality at your organization.