How do you manage ERP data quality and governance conflicts?

1 Assess your data needs and sources

Before implementing or upgrading your ERP system, you need to assess your data needs and sources. What are the business goals and requirements for data? What are the data sources and formats? How are they integrated and transformed? How are they validated and verified? You need to map out your data flows and dependencies, identify potential gaps and errors, and define data standards and rules.

2 Establish a data governance framework

A data governance framework is a set of policies, processes, and roles that guide and monitor data quality and usage across the organization. You need to establish a data governance framework that aligns with your ERP system and business objectives. This includes defining data ownership, stewardship, and accountability, setting data quality metrics and targets, creating data quality reports and dashboards, and enforcing data quality rules and controls.

3 Resolve data conflicts and issues

Data conflicts and issues are inevitable in any ERP system, especially when dealing with multiple data sources, formats, and systems. You need to resolve data conflicts and issues quickly and effectively, using a collaborative and transparent approach. This involves identifying the root causes and impacts of data problems, prioritizing and assigning data issues, communicating and escalating data issues, and documenting and tracking data resolutions.

4 Train and educate your data users

Data users are the people who access, analyze, and act on data in your ERP system. You need to train and educate your data users on how to use the ERP system and the data governance framework. This includes providing data quality awareness and guidance, explaining data definitions and standards, demonstrating data quality tools and reports, and encouraging data quality feedback and improvement.

5 Monitor and improve your data quality and governance

Data quality and governance are not one-time activities, but ongoing processes that require constant monitoring and improvement. You need to monitor and improve your data quality and governance using a data quality cycle that consists of four steps: plan, do, check, act. You need to plan your data quality goals and actions, do your data quality tasks and activities, check your data quality results and performance, and act on your data quality findings and recommendations.

6 Leverage best practices and tools

Managing ERP data quality and governance can be complex and challenging, but you can leverage best practices and tools to help you. You can use best practices such as data profiling, cleansing, matching, enrichment, and auditing to improve your data quality. You can also use tools such as data quality software, ERP modules, or third-party solutions to automate and simplify your data quality and governance processes.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?