The Challenge
A not-for-profit organization recognized the critical need to improve the quality and consistency of data across five key systems: HR, case management, finance, donor management, and learning management. The existing data infrastructure was fragmented and lacked the necessary frameworks and processes to ensure data accuracy and consistency. This gap led to operational inefficiencies, such as duplicated records and manual data handling, which increased the risk of errors. These challenges hindered effective decision-making, compliance reporting, and the organization’s ability to scale its services efficiently, ultimately impacting its mission to serve the community.
Driving data quality improvements through automated validation rules that continuously monitor, score, and enhance data quality across all data sources
The Solution
Our dedicated data team executed a focused 10-week project plan, starting with stakeholder alignment and discovery sessions to clearly understand the scope of the challenges experienced and establish the project schedule. We conducted a thorough analysis of the existing infrastructure and data, profiling data to develop a baseline understanding of quality, identifying gaps, and resolving issues related to system access and connectivity. Our team then developed a comprehensive data quality framework, along with scoring protocols and a targeted remediation plan to address the identified challenges. The project culminated in the operationalization phase, where we automated data flows and implemented measures to ensure the long-term sustainability of data quality improvements.
The Results
The project led to significant, outcome-driven improvements for the organization. Data accuracy and consistency were markedly enhanced across all five core systems, reducing errors and increasing trust in the data. This improvement in data quality, combined with streamlined data management processes, eliminated manual interventions, resulting in faster data processing and reduced operational costs. With reliable, high-quality data now readily available, the organization is empowered to make better-informed strategic decisions and manage day-to-day operations more effectively. The implementation of a robust remediation plan and automation of data flows has ensured long-term sustainability of data integrity, enabling the organization to scale and adapt to future needs with confidence.
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