Data is your institution’s most powerful resource—but managing it? That’s the tricky part.
A recent report from Experian highlights that up to 25% of institutional data is inaccurate or incomplete. That’s a serious challenge when accurate data is critical to operations like enrollment, alumni contributions, or improving institutional outcomes.
In this blog, we’re diving into the most common data challenges in higher ed—issues that make your data unreliable, misleading, or downright unusable. Even better, we’ll share straightforward, actionable steps to help you cut through the noise and work with data you can trust.
For admins, registrars, and data professionals, clean, dependable data isn’t just nice to have—it’s essential. Reliable data creates seamless student experiences and supports informed decisions that propel your institution forward.
So, what’s blocking your path to better data visibility, and how can higher ed overcome these hurdles? Let’s explore.
Common Data Challenges in Higher Ed
Before diving into solutions, let’s step back and identify the root causes of unreliable data—it’s essential to understand where the breakdown begins.
1. Disconnected Data Systems
Most higher education institutions use multiple platforms for enrollment, CRM, learning management, and more. When these systems don’t communicate, it results in silos and fragmented information. According to EDUCAUSE, 78% of institutions report difficulties integrating data across platforms.
2. Inconsistent Data Definitions
Does “student engagement” mean event attendance, engagement in class, or participation in campus activities? If the definition is not clearly defined, and consistently applied, reporting starts to overlap and become unreliable.
3. Absence of Data Governance
When no one is clearly accountable for maintaining data standards, the result is often inaccurate, outdated, or non-compliant information. Institutions without a governance framework face significant hurdles in enforcing data quality policies.
Do you see yourself in these challenges? Recognizing which of these challenges apply to your institution is step one. Addressing them with actionable solutions is how you can regain control and trust in your data.
Four Strategies to Improve Data Quality
1. Develop a Data Governance Framework
Consider data governance your foundation for success. Define clear policies and assign roles—such as departmental data stewards—to ensure consistency, accuracy, and compliance across the institution. Read this article for a step-by-step guide to get started on creating your governance framework.
Governance provides the structure, but engaging your team’s commitment to data quality is equally crucial.
2. Build a Data-Informed Culture
Shift your institutional mindset to value data-driven decisions over gut feelings. Offer training to staff on best practices for data management and create clear connections between their daily work and broader institutional goals. If your team is not too technical, check out these tips on getting them up to speed.
Equipping staff with a data-centric mindset is critical, but you’ll also need the right tools to streamline data processes.
3. Implement Data Integration Solutions
Automation is key to breaking down silos. Integrations can connect platforms like CRM systems and ERP databases, creating a seamless flow of information. Gartner research shows that automating data processes can increase operational efficiency by 30%.
Integration ensures consistency and visibility across your different tools. Advanced analytics tools can help you take this clean connected data and draw out insights.
4. Leverage Analytics for Deeper Insights
Analytics platforms with AI capabilities can identify data inconsistencies, predict trends, and suggest actionable improvements. These tools turn raw data into insights that drive decision-making and strategic planning.
Why Data Quality Matters More Than Ever
Clean data isn’t just about compliance or convenience. It enables you to look back at historical trends to predict future outcomes and make informed changes accordingly. It also positions you to anticipate and prepare for challenges before they arise. In short, it’s a pathway to transformative results.
- Institutions prioritizing data governance report 20% increases in operational efficiency (McKinsey & Company).
- Accurate engagement metrics can drive alumni donations up by 15% (Council for Advancement and Support of Education).
- Improved data processes reduce manual errors by up to 40%, enhancing student and staff satisfaction (EDUCAUSE).
Improving data quality is not a “nice-to-have”—it’s truly essential for connecting with digitally-savvy Gen Z and effectively running a modern higher education institution in today’s data-driven world.
Begin Your Data Quality Journey
Improving data quality takes commitment, but the rewards—better insights, streamlined operations, and stronger outcomes—are well worth the effort. Start by assessing your current practices and setting clear goals for improvement.
Need a little help? At FormAssembly, we help higher education institutions achieve seamless data collection with automated and integrated workflows and web forms ( see examples here ), so they can get back to raising the bar.
Data shapes the future, be a part of it. Learn More About Data Solutions for Higher Ed