Analytics: Looking for a better return?
Are your institution’s analytics investments paying off? Chances are that you and other campus leaders don’t think so. In 2018, higher education institutions spent $860 million on software as a service applications. In the next five years, that’s predicted to grow to $2.1 billion. Despite the deluge of software that collects and creates data, campus leaders are skeptical that their investments are yielding the improved analytics they expected.
The latest “Campus Computing Survey” results show that while two-thirds of IT leaders rank data analytics for learning and management as a top campus priority, only 20% rate their investment in analytics technologies as “very effective.” And their colleagues in the cabinet agree: 60% of higher education leaders still see data silos as the No. 1 barrier to better data utilization.
Integrating data across campus
Integration is a big part of the issue. While technology purchases are usually made to meet specific, operational business needs, research consistently shows that the most valuable analytics are derived from a cross-campus synthesis of data. Combining data allows leaders to view trends, target initiatives and build more seamless digital experiences.
Synthesis requires an integration architecture strategy. Integration architecture is the connective tissue of code that lets campus systems share data. At most institutions, the IT architecture was not built to optimize for analytics and must be reworked to create a sustainable and effective data environment.
It’s an adage in IT that software is transient, architecture lasts for 15 years and data is yours forever. Despite this hierarchy of value, campus technology systems are often engineered with the priorities in reverse. SIS and ERP systems form the core of most college and university tech environments. Over time, they have been directly connected to hundreds of other systems around campus.
Often, the seemingly cheapest, fastest way to move data between systems is a direct transfer: extracting data from one system, converting it to a new format and loading it into a new system. As the number of systems proliferates, so do the number of integrations. When the time comes to change out large systems, it takes years of planning and mapping to understand and rebuild the integrations around new systems.
Building a centralized data hub
Institutions must invert this pattern. With the present pace of change in the software industry, software products are too transient to rely on for long-term data management. They also tend to isolate data in ways that aren’t optimal for supporting institutions’ broader analytics goals.
The architecture should focus on the item of longest-standing value: data. With a centralized data hub and institutional data model as the centerpiece of the technology ecosystem, each application can be connected to the hub in a single integration, allowing higher ed institutions to disconnect existing systems and transition their data when new, better products come along.
But changing the existing, complex web of hundreds of integrations into a hub-and-spoke integration model is not easy. Most campuses work through dozens of technology implementation projects every year, and each one adds new intricacies. As these projects snowball, it’s hard for IT leaders to find time to think about how to better organize the flow of information around the institution.
But as one IT director at a large public research institution shared: “You need to be aggressive about updating the integration strategy before the need arises; otherwise, you’re constructing your own prison sentence.”
Access to cross-functional insights from analytics can help advance every institutional priority—enrollment growth, student success, operational efficiency and innovation. While finding the time and resources to focus on a campuswide integration strategy can be difficult, it can make the difference in achieving your goals.
Danielle Yardy is a researcher and solutions engineer at EAB. Her work focuses on partnering with institutional leaders to scale effective data governance, integration and analytics solutions across campus.
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