The importance of data quality to business processes cannot be overemphasized. Perfect data quality ensures business-process excellence. Poor data quality results in business-process interruptions and costly delays. Understanding data quality, though, is easier said than done.
When implementing new enterprise software such as SAP®, Oracle® or other ERP, HR, CRM, PLM solutions, a company’s data stewards must decide what data to migrate from their legacy systems and what data to retire. They must determine what data needs to be maintained to satisfy legal requirements and whether the quality of that data is sufficient. In the midst of implementation and ongoing business processes, very few companies have the time and expertise to determine if their migrated data will properly support execution of critical business processes, or what we refer to as having Business-Ready Data™.
Data quality is an ongoing concern whether a company is involved with a migration or not. Once embedded in the system environment, bad data negatively affects business processes and drags down corporate performance. Without understanding the nature of the problem and undertaking comprehensive remediation, companies are setting themselves up for data-induced disasters.
To avoid botched migrations and long-term data quality issues, many companies turn to BackOffice Associates® to help them better understand the quality, volume and complexity of their data. The first step is a BackOffice Associates Data Audit™. With the fact-based and measurable results gained from the Data Audit, companies can mitigate data related business risk and project delays.
A BackOffice Associates Data Audit provides a quick and robust insight into a company’s data. A Data Audit can help jump-start a migration project, identify critical data quality issues and metrics that help drive executive support, or simply as a way for a company to deep dive into data-related business problems.
With a Data Audit you can:
- Quickly understand the impact of data quality on business processes
- Highlight existing data quality, complexity and volume in any source system
- Use actionable reports and fact-based metrics to design and implement near-term remediation plans for mapping, data cleansing and configurations
- Build or support a business case for initiating a data migration or data governance solution