College and university leaders need adequate access to data to design, execute, and measure the efficacy of strategic initiatives. The ability to source insights quickly is critical to support student success, novel recruitment strategies, and institutional efficiency initiatives. But many schools struggle to gather the data they need in a timely manner, slowing innovation and shaking campus confidence in data-driven decision-making.
Our research has shown there are three key challenges holding back analytics efforts:
1. Campus data is trapped in operational silos and systems
Decades of technology investment means most university campuses run on a complex web of workflow and analysis tools. Each of these systems generates and stores data which in turn represents just one facet of the institution. When the time comes to ask questions across systems, the systems can prove difficult to navigate. Securing data access and extracting the right information across silos can significantly slow decision-making.
2. Turning data into insight requires extensive manual effort
Data analysis in this environment is never simple. The process of retrieving data today is so onerous—and relies so heavily on adding more work for the data experts working with specific systems—that data access can take days or even weeks.
In the meantime, new requests pile up, potentially multiplying the number of data sources to be tapped for a report. Each data source must be obtained, cleansed, and reconciled with other inputs before it is useful for analysis.
Significant money and time spent on one-off requests
per ad hoc report request (fully loaded cost)
week backlog for typical unit-level requests
hours spent on ad hoc reporting over 12 months at one university
3. Analytics teams are overwhelmed with ad-hoc requests
As a result of this labyrinthine technology ecosystem and manual workloads, Institutional Research (IR) and central business intelligence (BI) teams are overwhelmed with basic data requests that crowd out strategic work.
In fact, central decision support teams across higher education estimate that anywhere from 25% to 100% of their capacity is dedicated to responding to ad-hoc data requests, many of which are for basic institutional data such as enrollment figures. While descriptive reporting is crucial for operations, it comes at the expense of dedicating time to more advanced analyses.
To reduce the time needed to find insights—and foster innovation across campus—colleges and universities need a centralized system that makes cross-silo data easier to access, combine, and analyze. That’s why several institutions are considering a Data Management Platform (DMP), an open-purpose solution that aggregates campus data and displays it using common-language definitions, making data easier to access and query at the speed and frequency of campus questions.
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