The Impact of Data Governance on RIM Readiness & Success
Implementing a Regulatory Information Management System (RIMS) is a complex effort that requires thoughtful planning and consideration of the data that goes into the system. These types of projects can be time-consuming, resource-intensive, and expensive. Therefore, it is important to address the various dimensions of quality data early in the planning stage of a RIM project.
RIM Data Readiness
Through project work, IDMP assessments, and several data readiness studies, the NNIT team has identified common issues that can impact the success and timeliness of a RIM project. Data governance is one of the foundational components of data readiness. A review of potential RIM data often signals likely data readiness issues that are directly related to data governance gaps.
RIM systems typically bring together data from different systems. This data may include legacy data in different formats. Quite often, the data is of poor quality, duplicate data, or may even conflict with similar data from a different system. This misalignment of essential data impacts its use and reliability throughout the organization.
RIM Data Quality
As companies prepare for a RIM project, it is essential to understand data lineage and how the data is controlled and maintained. You must understand how data has been and will be governed and managed to address five critical aspects of data quality:
- Accuracy
- Completeness
- Reliability
- Relevance
- Timeliness
A complex data migration might be deemed successful when it finishes on time, but if the data being migrated is of poor quality, it is a wasted effort that can potentially add more problems. When poor quality data is combined with good data, it taints the good data and reduces its value to the organization. If RIM data isn’t accurate and reliable, users will naturally create duplicate processes to gain needed insights, resulting in wasted time, money, and resources. Worse yet, if users unknowingly rely on poor-quality data for regulatory interactions, they can put the company’s relationship with the agency and its reputation in jeopardy.
Whether you have an informal RIMS, are planning a formal project, or have implemented and are using a RIMS, data governance must be an ongoing priority. The RIM data lifecycle is complex but requires constant attention, regardless of the lifecycle stage.
The RIM Building Analogy
Data Governance for RIM is like the critical heating and air conditioning system that supports a new office building. When designing the building, the team must be aware of practical constraints such as ventilation, airflow, air quality, and temperatures. These considerations impact the design of the heating, ventilation, and air conditioning system (HVAC). If the team doesn’t plan correctly, some offices may be too cold or too warm. If ventilation isn’t designed correctly, indoor air pollutants can cause health problems for workers resulting in absenteeism and reduced productivity.
The planning of the HVAC system directly affects how the building is used. The façade may be beautiful, but if the HVAC isn’t working, no one wants to use it. If the data in a RIMS isn’t accurate, complete, reliable, relevant and timely, no one will use it. A RIM system can be an expensive proposition. However, with appropriate data governance planning and design, it will offer reliable insights that the organization will value.
Please contact us to learn more about NNIT’s RIMS experiences and how to incorporate data governance strategies into your RIM project.
