In today’s rapidly evolving higher education landscape, data has become a critical tool for driving strategic decisions. Institutions that effectively leverage data have the advantage of making informed choices that directly impact student success, institutional growth, and operational efficiency. However, while data is undeniably important, it’s crucial to remember that data alone isn’t everything. A truly forward-thinking institution knows how to blend data-driven decisions with calculated risks and innovative thinking.
The Importance of Accurate and Accessible Data
In higher education, real-time access to accurate data is essential for making decisions that affect marketing, recruiting, enrollment, and advancement. For example, having up-to-date information on students in the enrollment pipeline allows institutions to tailor communication strategies, minimizing melt and ensuring smooth transitions for incoming students (Anft, 2023). Data, including market analysis, is also invaluable when determining whether to sunset or add new programs. Without reliable data, these decisions would be far more challenging and risk-laden.
However, the effectiveness of data relies heavily on its accessibility and quality. Challenges such as outdated data systems, poorly defined data protocols, and limited staff in institutional research offices can significantly hinder decision-making processes (Hampton, 2023). Additionally, messy datasets, “ghost” data points, and the absence of well-established data glossaries can lead to confusion and misinterpretation. Higher education leaders must address these issues by investing in updated platforms, training staff, and creating standardized data practices (EAB, 2022).
The Role of ERP and SIS Systems
To further enhance data accessibility and accuracy, institutions must ensure that their Enterprise Resource Planning (ERP) and Student Information Systems (SIS) are user-friendly and well-integrated. These systems (and CRM, SIS, LMS, HRMS, IAM, etc) are crucial for collecting, managing, and analyzing data across various functions of the institution. When these platforms are intuitive and easy to navigate, they empower faculty and staff to engage with data more effectively, leading to better-informed decisions.
Moreover, adequate training and resources are essential for maximizing the potential of ERP and SIS systems. Institutions should prioritize continuous professional development and support for faculty and staff to ensure they can fully utilize these systems. This includes offering regular training sessions, providing access to help desks or technical support teams, and fostering a culture of data literacy across the campus. By doing so, institutions can not only improve data collection and management but also enhance the overall effectiveness of their data-driven strategies.
The rise of data-driven cultures in academia highlights the shift toward using data analytics to enhance decision-making across multiple areas, from identifying at-risk students to optimizing resource allocation. Institutions increasingly leverage predictive analytics to pinpoint academic areas needing attention and implement timely interventions (NCES, 2023). Despite this progress, institutions often struggle with ensuring that data is consistent, high-quality, and accessible to decision-makers across all levels (EAB, 2022; Hampton, 2023).
The Roadblocks: Lack of Access and Unreliable Data
While the potential of data to transform decision-making in higher education is widely recognized, the reality is that many institutions face significant roadblocks due to a lack of easy access to key data and the prevalence of unreliable or poor-quality data. These challenges are particularly acute in smaller institutions and those with limited resources, where outdated data systems and insufficient staffing in key roles like Institutional Research (IR) and Information Technology (IT) exacerbate the problem (Hampton, 2023).
Impact on Operations, Growth, and Sustainability
A lack of reliable data access can severely disrupt the day-to-day operations of a college or university. Decisions on resource allocation, program development, and student support services often require timely and accurate data. When this data is not easily accessible or is of questionable quality, decision-making becomes delayed or misinformed, leading to suboptimal outcomes that can hinder institutional effectiveness and student success (Anft, 2023).
Moreover, the absence of reliable data can have long-term implications for institutional growth and sustainability. For instance, institutions that cannot accurately assess their financial health, student retention rates, or market positioning are at a higher risk of making strategic errors that could lead to financial instability or even closure. This is particularly concerning given the ongoing challenges in higher education, including declining enrollment in many regions and increased competition for students (EAB, 2022).
As highlighted in a recent EAB report, nearly 97% of college leaders agree that better data use is essential for making strategic decisions, yet only a fraction of institutions have fully centralized their data sources (EAB, 2022). This fragmentation not only limits the ability to make informed decisions but also hampers efforts to foster cross-departmental collaboration, which is critical for comprehensive institutional planning and growth.
In the current climate, where the higher education sector is facing unprecedented challenges, the ability to access and utilize high-quality data is not just a competitive advantage—it is a necessity for survival. Institutions that fail to address these data challenges risk falling behind, as they are less equipped to adapt to changing conditions, identify opportunities for innovation, or mitigate risks (NCEE, 2023).
Key Insights from Leadership Perspectives on Data Strategy
A recent survey of higher education leaders provided valuable insights into the challenges and opportunities surrounding data strategy (EAB, 2022). Here are some key findings:
- Data’s Role in Enrollment and Retention: Leaders overwhelmingly view data as crucial for improving enrollment, retention, resource allocation, and student success. In fact, 99% of respondents indicated that retention is a top priority, followed closely by enrollment at 97%. These findings emphasize the critical nature of data analytics in sustaining key institutional functions.
- Staffing Shortages and Training Gaps: The report highlights that 77% of institutions cite insufficient staffing as the biggest roadblock to effective data usage. Staffing issues are particularly acute in technical roles like Institutional Research (IR) and Information Technology (IT), where turnover and lack of training hinder progress. 32% of respondents said that institutional knowledge loss as a result of staff turnover is their most concerning data issue.
- Access Disparities: Although executive leadership generally has reliable access to data, nearly half of respondents noted that faculty and staff face significant barriers in accessing reliable data. Smaller institutions are particularly challenged, with only 38% of faculty and 35% of staff at institutions with fewer than 5,000 students having easy access to reliable data. Based on data from IPEDS, in the Fall of 2022, there were 5,978 post-secondary institutions in the US, and of those, 5,006 had total student enrollment with 5,000 or fewer, representing 84% of the institutions. Thus, easy access to reliable institutional data is a major barrier and no doubt will be a contributing factor to the predicted ongoing school closure crisis.
- Centralizing Data for Strategic Use: Only 9% of institutions have fully centralized their data in a warehouse, with the majority reporting that some systems remain siloed. This lack of integration limits comprehensive decision-making and hinders cross-departmental collaboration.
- The Importance of Data Warehousing: While many institutions are actively building data warehouses, 25% of respondents have yet to fully integrate all campus data sources into a single repository. Institutions often underestimate the time and resources required to maintain a fully functional warehouse, resulting in incomplete data integration.
- Investing in Technology: Investments in technology and software are a priority for many institutions, with 35% planning to increase their spending in this area over the next year. Upgrades are focused on student success platforms, learning management systems, and data warehouses.
- The Impact of Failed Technology Implementations: One in three institutions reported that a recent technology implementation failed to impact key metrics, largely due to poor implementation or inadequate staff training. Leaders emphasized the importance of choosing the right vendors and ensuring sufficient buy-in across departments.
- The Need for Data Governance: Nearly two-thirds of institutions indicated that improving data governance and access protocols is a high priority. Establishing clear data definitions and governance practices is seen as critical for enabling more effective data usage and decision-making.
- Engaging Institutional Research: Despite the critical role of Institutional Research (IR), many institutions approach IR and Institutional Effectiveness (IE) departments transactionally, primarily for compliance reporting. Only 31% of leaders see IR as integral to strategic decision-making, missing an opportunity for deeper engagement with data professionals.
- Choosing the Right Partners: Selecting the right vendor is crucial for successful technology implementation. Institutions benefit most when working with partners who understand the unique challenges of higher education. This includes prioritizing vendors with a track record of successful deployments in similar institutions.
Balancing Data with Entrepreneurial Risk-Taking
While data provides a strong foundation, it isn’t always sufficient when exploring new opportunities or differentiating your institution from others. Sometimes, especially in uncharted territory, direct data might be limited or nonexistent. In these cases, institutions may need to rely on indirect data or informed intuition to make bold, strategic moves. For example, when launching a unique program that hasn’t been tested in your market, the absence of direct supporting data doesn’t automatically mean the decision isn’t worth pursuing. Instead, entrepreneurial leaders use calculated risks, guided by whatever relevant data is available, to drive innovation (Anft, 2023).
As institutions strive to strike a balance between data-driven decisions and visionary leadership, it’s important to recognize that while data can reduce risk, it cannot entirely eliminate it. Data is a powerful tool for addressing persistent issues and driving digital transformation, but leaders must also consider the potential for innovation that lies beyond the numbers (Hampton, 2023). Collaborations with experts like AWS and institutions such as the University of Maryland–Baltimore County and Illinois Institute of Technology demonstrate how data can be harnessed to manage challenges across an institution’s lifecycle—from collection and analysis to strategic planning (EAB, 2022).
Making Sense of the Mess: Leveraging Trusted Data Sources
While data is powerful, the landscape of higher education is messy and constantly changing. The ability to sift through this complexity requires access to robust data sources that can offer clarity, even if momentarily. Below is a list of reliable data sources that can help provide insights into the current landscape and aid in navigating the challenges higher education institutions face. These sources range from government databases like NCES and IPEDS to specialized tools like the College Viability App and Higher Ed Data Stories. This data can only take staff, faculty, and administrators so far as the Achilles heel in all of this is clean, reliable, and accessible institutional data.
References
Anft, M. (2023). Becoming a data-driven institution: College leaders assess the value and challenges of using data to make strategic decisions. The Chronicle of Higher Education. https://aws.amazon.com/education/higher-ed/
EAB. (2022). Leadership perspectives on higher education data strategy: Survey report. https://www.eab.com
Hampton, M. C. (2023). Data-driven decision-making in higher education: How REL work makes a difference. National Center for Education Statistics. https://nces.ed.gov
National Center for Education Statistics. (2023). Data-driven strategies in higher education. https://nces.ed.gov