Complexity Isn’t the Barrier – It’s the Context for Action
Universities are complex, but individual tasks don’t need to be.
Take a look at how academic administrators—course coordinators, student advisors, timetablers, and others—manage daily tasks. Their workspaces often resemble air traffic control centres, juggling multiple desktops, dashboards, core information systems, university web pages, and personal Excel files.
This “semi-organised chaos” is the result of trial and error. Individuals create their own bespoke, but unscalable, solutions to achieve their goals.
Some will argue that complex data and information systems have caused this chaos. And of course, every institution dreams of consolidating many disparate software systems into a sleek system that houses all data in one place. But such projects take many years, are extremely costly, and come with substantial risk.
I take a different view. Even without a sweeping digital transformation, universities can start making small, impactful changes. We can achieve this by focusing on two things:
Democratisation and consolidation of in-demand academic planning data for individuals to access; and
Organisational norms and incentives that encourage or discourage effective cooperation between departments and business units.
A Paradigm Shift: Treat Users as Customers and Data Exports as Data Products.
Treating users as customers and data exports as "products" can be a game changer. In higher education, adopting a customer-centric view of data can be difficult. But if data owners—like those managing the curriculum management system—don’t consider both timetabling and student services teams as key “customers,” the institution is likely facing inefficiencies that affect both administrative performance and student experience. For example, a typical curriculum management dashboard might look like this:
Programs – Degree offerings, learning outcomes, credit requirements, etc.
Sub-qualifications – Majors, minors, and specializations.
Subjects – Subject offerings, rules, delivery schedules, etc.
This structure tries to present every possible detail, but it’s a constant challenge to maintain and update. A better approach: Organize data based on the specific needs of the users (customers). Here’s how:
For student advisors – Display active programs, current student enrolments, study plans, and credit requirements.
For timetablers – Show subject combinations needed by students, based on their progress.
For unit coordinators – Present upcoming unit sizes, student cohorts, and progression.
Tailoring data for the actual users makes it more actionable and less overwhelming.
Taking Data and Turning it into Value
Changing how teams think about and collaborate around data is only part of the solution. I see two other low-medium effort, high-benefit interventions: (1) adopt data contracts, and (2) leverage automation.
(1) Data contracts
Data contracts are a powerful tool to simplify data access and usage across departments.
When university teams, such as curriculum managers, student services, and timetablers, are clear on what data they need and how to access it, the entire workflow becomes smoother. Establishing formal data contracts helps define these expectations by codifying the inputs and outputs that each department requires.
These agreements outline who owns which data, how it should be used, and the frequency of updates, ensuring that everyone gets the right information when they need it. Think of a data contract as a service-level agreement (SLA) - ensuring reliability, transparency, and accountability.
(2) Automation
Connecting disparate data sources and using simple algorithms to automate routine processes can save countless hours spent on manual tasks. Rather than manually pulling together data from different systems, and referencing a mishmash of PBI dashboards, simple automations can aggregate, synthesise, and provide the necessary information with minimal manual intervention.
For example, a simple algorithm might automate the generation of student reports, schedule timetables based on student progress, or flag students who may need academic advising. By replacing repetitive tasks with automation, universities can redirect valuable human resources toward tasks that require deeper expertise and creativity, such as mentoring students or designing new programs.
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