I often describe the tertiary education system in Australia as one of the sector’s global success stories. It is home to some of the largest institutions that have developed through mergers and collaborations to become internationally recognised, with strong research outputs and a vital role to play in developing the region’s workforce.
These institutions operate at a scale that enables them to absorb many of the market forces that can affect the sector, including shifts in international student demand, changing workforce needs, tighter public funding, and the rapid advancement of technologies such as AI. In the United States and parts of the United Kingdom, collaborative models such as shared services and mergers are increasingly being seen as solutions to these pressures, particularly where institutions are under financial strain or student numbers have declined. Collaboration in this context is about institutional viability.
But many institutions across Australia are already operating at significant scale. The question here is therefore not how to build scale, but how to make existing scale more productive. Many of the pressures now facing the sector — funding constraint, workforce demand, and AI-enabled expectations — expose a gap between what individual institutions can do at scale and what the system as a whole needs to deliver.
Collaboration here is therefore more about how institutions can work more closely together to improve efficiency, make better use of existing resources, and deliver more for students.
It is important to distinguish between two kinds of collaboration. Back-office collaboration focuses on shared administrative services such as HR, finance, and procurement. Front-office collaboration focuses on how institutions align programs, pathways, advising, and student progression. Back-office collaboration improves cost structure. Front-office collaboration determines whether scale improves student outcomes and system performance. Back-office collaboration is where most partnerships start. Front-office collaboration is where they need to go.
A Sliding Scale of Collaboration
In my 30 years of working with universities across the United States and around the world, I’ve been involved in collaborations of every shape and size. As Chancellor of the Pennsylvania State System of Higher Education (PASSHE) I was at the forefront of a full institutional merger which combined six smaller campuses into two larger entities, a major project that took many years to plan and deliver.
The most successful collaborations I’ve seen were approached thoughtfully and deliberately, whether they were years in the making or a more urgent response to external pressures. At the larger end of the spectrum, options need careful consideration, and time to explore ‘what if’ scenarios to anticipate problems in advance and design solutions that achieve long-term impact.
At the other end of the spectrum, collaborations can begin more modestly and develop over time. Two universities might come together to jointly deliver a computer science programme or student support service, often the low hanging fruit for a budding partnership. The efficiency gains achievable from initiatives like these build trust and confidence that institutions and people can work together in an effective way towards more ambitious goals, without fundamentally changing how they operate.
These early collaborations are often effective because they are low-risk. But they also have limits. Without extending collaboration into how programs are delivered and how students move across institutions, the impact remains incremental. Deeper collaborative models require more change but could have a greater positive impact. Joint research facilities or a shared service for back-office HR or procurement might help stretch limited resources further across a group of institutions, reduce duplicated effort, and generate cost savings from economies of scale as relationships grow stronger.
Whether small, medium or large-scale, the foundations for successful collaboration don’t tend to change.
The Principles for a Successful Collaborative Model in Tertiary Education
What every project I’ve been involved in across higher and tertiary education has shown time and time again is that the principles for a successful collaboration are consistent, regardless of the size or shape of the collaboration.
1. A Clear Governance Framework
A lack of governance can be a significant threat to any partnership. In practice, this means being explicit about who has authority over key decisions — including admissions standards, shared services, and how resources are allocated across institutions. Uncertainty over who is responsible for decision-making or how to measure progress makes it much harder for the institutions involved to move forward or resolve disagreements. Multiple institutions often have different priorities, and without a structured governance framework, projects will likely stall or lose focus.
I’ve seen joint steering committees of representatives from each partner institution become a real driving force for change. These are the people who create clearly documented roles and responsibilities for both operational and strategic decisions, a defined schedule for reviewing progress, and an agreed framework for resolving conflict that might otherwise put the brakes on a project.
Collective governance is particularly important in collaborations where institutions operate under different funding or regulatory frameworks, as in Australia’s tertiary education sector.
2. Make an Evidence-Based Case for Change
Agreeing the priorities of a partnership and what action is needed to address the issues can be challenging, particularly if the union is happening because the individual institutions involved are no longer viable alone.
Even when a collaboration is purely about growth and innovation, there are typically trade-offs in terms of maintaining institutional identity, autonomy, and long-established ways of working. Data can help a fledgeling partnership to keep discussions and decision-making evidence based and focused on facts, not assumptions.
I’ve had access to huge amounts of operational, financial and student success data from across thousands of US institutions in my work over the last 15 years. Historical data like this can be used to assess risk, identify opportunities and shape strategies to address the challenges institutions face.
In my experience, people don’t automatically buy into a collaboration unless they can see the concrete benefits of doing so. If an institution needs to convince their faculty that delivering a Business Analytics course across three campuses will cut costs and increase access for students from low socioeconomic status (SES) backgrounds, showing them the data will go a long way towards this.
Institutions need to demonstrate clearly why collaboration is necessary, what risks they face if they do nothing, and what outcomes can be achieved by working together.
3. Align Early on a Shared Purpose
Another common reason collaborations struggle is a lack of clarity about what the partnership is actually trying to achieve.
It sounds obvious, but I’ve seen many institutions come together with broadly similar ambitions of improving efficiency or growth without ever properly aligning on what success in each area looks like in practice.
There needs to be a clear goal so that progress towards it can be measured. An objective to reduce costs will be very different to the goal of improving students’ grades or expanding into new markets. Each goal requires its own strategy and governance structure.
If leadership teams are not aligned from the outset, ambiguity quickly filters through the organisation. Each institution interprets the collaboration differently, priorities drift, and decision-making becomes slower and more contested.
The most effective partnerships take the time to define their objectives clearly, upfront. That clarity then becomes the foundation for everything else, from where investment is needed most to how success is measured over time.
4. Be Consistent and Relevant in Communication
One of the hardest parts of collaboration may not be making the decisions at all, but how those decisions are communicated across partner institutions.
Consistency of language is key. If one institution describes the collaboration as a merger and another calls it a partnership or shared service, this can cause confusion. People may even come to their own conclusions, which is not always helpful.
This consistency also needs to extend to the decisions made within the collaboration. If AI is being introduced to improve efficiency and reduce reporting errors, that core rationale should remain constant across all partner institutions. That said, communications do need to be tailored to address the specific concerns of different audiences. Faculty will want to know what the expansion of AI means in terms of academic control, programme design or how courses are taught. Students will be more concerned about how much easier it would be to find information or make career choices.
5. Play to Institutional Strengths
Working together means some decisions are no longer made independently. That can be uncomfortable in a sector where autonomy and identity are deeply embedded.
But the value of collaboration lies in what institutions can achieve together that they cannot achieve alone. By working across a group, institutions can specialise in what they do best and share that capability.
No single institution can realistically provide specialist careers guidance across every industry and market. As a collective, institutions can pool expertise so students have access to more targeted, higher-quality advice than would otherwise be available within a single institution.
The Technical Foundations for Effective Collaboration
Technology does not create collaboration. It enables it. The value of shared systems lies in making it possible for institutions to operate against shared definitions, consistent data, and common processes — not just to consolidate, but to coordinate.
Technology helps institutions operate as a coordinated partnership by making data, processes, and outcomes comparable across institutions. It provides a view of activity across the group, improves efficiency by standardising how information is recorded and shared, and ensures decisions are based on accurate, real-time data across all partners.
An Integrated Student Information System
An integrated student information system like Ellucian Student brings student, course, and staff data from across multiple institutions into a shared and comparable view. This allows partners to manage provision across the group and support students moving between programmes or institutions more easily.
With enrolment, progression, and outcomes visible in one place, institutions can identify students who need extra support and intervene earlier to improve retention. It also becomes much simpler to highlight where similar programmes or modules are running in parallel across the group, which reduces duplication and allows teaching and support services to be more effectively resourced.
AI-Enabled Student Success
The rise of AI in tertiary education has allowed institutions to make more effective use of shared data across a partnership. These tools can analyse large datasets instantly to identify patterns in student behaviour, such as declining engagement across a cohort or programme.
This makes it easier to act earlier and coordinate targeted interventions across institutions, rather than responding in isolation. AI can also automate many of the routine processes staff undertake to reduce workload pressure and allow staff to focus more time on supporting students.
In a system like Australia’s, where institutions operate at scale but largely independently, AI will only be as effective as the consistency of the data and rules it operates on. Fragmented systems will produce fragmented outcomes.
Analytics and Reporting
Systems that ensure data is presented in a consistent format allow institutions to compare outcomes on a like-for-like basis, track progress against shared goals, and see where performance differs across the group. Where one institution is achieving stronger results in a shared programme or built a successful pipeline of students returning to continually update their skills, insights into how this was achieved can be clearly identified and replicated across the partnership.
A Collaborative Ecosystem
Solutions built on Software as a Service (SaaS) allow institutions to operate on the same systems and processes across a partnership, rather than maintaining separate infrastructure. This gives the institutions in a collaboration a common technical environment to deliver services, manage data, and support students.
This reduces the need for complex integrations between institutions and ensures that updates, processes and data structures are applied consistently across the group. As a result, partners can introduce changes more quickly, scale services more easily, and avoid the fragmentation that often slows down collaboration.
Australia’s challenge is not how to grow larger institutions, but how to make existing scale work more effectively across institutional boundaries.
The opportunity for Australia is not to build bigger institutions. It is to make the institutions that already exist work as a system — and to build the governance, the culture, and the technology infrastructure that makes that possible.
Discover how Ellucian Student can support institutions across Australia to collaborate more effectively.
