Turf Wars – Who has the most accurate data?

July 08 2014


Author: Chad Cosper

Ask any three department heads in your enterprise “Where can I find the most accurate information about our products and customers?” and chances are good that you will get three different answers. Getting a consistent answer to this question is imperative when taking your business to the next level.

Common business practices, such as mergers and acquisitions or implementing strategic initiatives, like omni-channel or customer-centricity, expose weaknesses in enterprise–wide data governance strategies. One department or brand group may manage critical data assets using a collaborative process to ensure accuracy while another may use strict workflows for approvals from key team members. Each approach has advantages, but the data each produces is still inconsistent. Why?

Think about what motivates those department heads? What keeps them up at night? Your e-commerce team doesn’t care about product details specific to your stores. One brand is not concerned with providing product information using the same format as another brand. Each department relies on different source systems to create and manage information about your customers and products. All of these things create data inconsistencies.

Implementing a data governance strategy using a master data management (MDM) system helps address data quality issues and can lead to greater confidence in the data used by critical business units. However, if not carried out on an enterprise level, you can guarantee that these turf wars will continue. And, more importantly, you won’t be any closer to achieving that single view of your products or customers across all facets of your enterprise.

Putting an end to turf wars and establishing a single view requires an MDM system that allows your teams to institute workflows that enhance data governance but also still encourages collaboration. Most importantly, in order to address all of the needs of your enterprise, it is wise to choose a system that has been built from the ground up to manage the data requirements of each of your data domains without having to build custom integrations between the point systems that many vendors have purchased to address different domains.


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