The problem every university leader now shares

For Provosts and Deans: this is about making academic effort visible and protecting it from blunt cuts.
For CFOs and COOs: this is about replacing spreadsheet sprawl with one auditable, GL-reconciled model.

The pressure on university budgets has moved from a background concern to the defining challenge of the sector. In KordaMentha’s 2026 Higher Education annual report, a survey of Deputy Vice-Chancellors and Chief Operating Officers found that 68% named cost, budget and funding constraints as their number one challenge. When asked what they would actually do to reduce cost, the same leaders pointed to a number of levers, and two caught my attention: 68% would “Improve academic productivity through better workload management, strengthening performance and productivity frameworks,” and 47% would “Rationalise program/degree offerings.” (Readers Note: I know what you’re thinking, this is about staff reductions, doing more with less and cutting academic programs to improve the financial performance of the institution, however, you’ll see below how the model could be used to argue a different case.)

Unfortunately, traditional financials can’t help them pull either of those levers. They tell you what was spent, but not where it was spent by program, course, campus, mode of delivery or who delivered them.

The statutory accounts are designed to be accurate, audited, compliant and comparable over time. They satisfy ministers, parliaments, auditors and lenders. They are the authoritative record of the institution’s financial position. But notice what they can’t answer – of that total expenditure, how much is consumed by Nursing vs Business vs Performing Arts and does the revenue each discipline attracts actually cover its cost? Where does academic and professional staff effort actually go – teaching, research, community support? Which programs sit below break-even once fully-costed with all overhead costs?

Standard financial accounting was not designed to answers these questions, this is the domain of management accounting, to provide that detailed internal model of the institution to help support academic workload analysis and program/degree financial performance reviews.

The current reality: management accounting by spreadsheet sprawl

Management accounting inside universities today lives inside hundreds of disconnected Excel workbooks scattered across faculties, schools and central finance.

Each faculty builds its own cost model, on its own assumptions, updated on its own timetable. Overhead is allocated one way in the Business School’s spreadsheet and a different way in Nursing’s. Space, workload and enrolment data are keyed in by hand. Nobody can trace a number back to the source, and no two versions reconcile to each other or to the general ledger. When a senior leader asks a portfolio question, weeks are lost reconciling or updating spreadsheets before anyone can even begin to answer it.  When they ask a different type of question, not previously modeled, then the whole process could take significantly longer, starting from scratch with a new model and new data.

This is not a failure of finance or analysts, who work tirelessly to keep these spreadsheets and models alive. It’s a failure of architecture. Spreadsheet sprawl produces analysis that is inconsistent, unauditable, un-scaleable and impossible to trust at the executive table. The very decisions the sector says are most urgent are being made on the shakiest possible information base.

The alternative: one Enterprise model – Everything Everywhere All at Once.

Enterprise Management Accounting replaces the spreadsheet sprawl with a single, integrated model of the whole institution, that every faculty, school and central finance shares. The Enterprise model is a causal model of the entire institution, tracing detailed financials from the general ledger through to subject instances (when, where and how they are taught) and rolling up to programs, schools, campuses and the entire institution. This is what is known as a “bottom up” model. The model requires a range of data sources including the aforementioned general ledger as well as HR, payroll, facility management, student management and timetabling data, all prepared, cleaned and loaded into the model of the entire institution.

The outputs of these models can easily have 100’s millions of rows of data, hence is virtually impossible to model in a spreadsheet, so spreadsheet models are frequently simplified, missing out on that detailed nuance inside institutions.

Crucially the Enterprise model doesn’t relace financial accounting, it complements it. In fact, the Enterprise model is reconciled to the statutory financials to ensure it is true and correct.

How the Enterprise Model delivers on the sector’s priorities

Because it is one integrated model, rather than a patchwork, it can answer a wide-range of different questions, consistently and defensibly, now let’s look at the two levers again “improve academic productivity” and “rationalise program degree offerings” from an Enterprise model perspective.

Making academic effort visible, fair and sustainable – not “doing more with less”

The sector’s cost pressure is real, but the answer is not to ask a shrinking academic workforce to simply do more. Used well, an Enterprise model does the opposite of a headcount exercise: it makes the investment of academic effort visible so that leaders can protect it, distribute it fairly, and reinvest it where it creates the most value.

Because the model integrates workload and staffing data with student load, consistently across the whole institution rather than in competing spreadsheets, it can answer questions that genuinely help academics:

• Where is workload distributed unevenly or invisibly? A single, transparent model surfaces hidden overload, so effort can be rebalanced fairly rather than left to fall on the same people year after year.
• Are there duplicate subject instances delivered at different times or different locations that could be consolidated?
• Which disciplines are genuinely under-resourced for the load they carry, so the case for investment can be made with evidence?
• Where does the real cost pressure sit, in staffing, or in structure, overhead, space and portfolio design? More often than not, the biggest levers are structural, not human, a point we return to when we look at overhead below.

The measures the model produces such as EFTSL per academic FTE and delivery hours per EFTSL are best read not as targets to squeeze, but as a fairness and sustainability lens: they show where teaching models are stretched, where they are sustainable, and where a smarter delivery design (rather than more hours from the same staff) is the answer.

The strategic point for university leaders is this: with a clear, shared evidence base, an institution can find capacity, structural savings and smarter design first  and treat workforce reduction as a genuine last resort rather than a first reflex. That is a far more defensible, and far more sustainable, path than blunt across-the-board cuts that fall hardest on people and quality alike.

Turning the spotlight on overhead — often the larger, less-scrutinised lever

There is an uncomfortable pattern in university cost debates: scrutiny falls first on academic staff and program viability, while the institution’s overhead (central, corporate and support costs) often escapes the same rigour. Yet overhead typically represents a substantial share of total expenditure, and it is the part of the cost base that whole-of-institution accounts leave most opaque. If the goal is to protect teaching, research and the people who deliver them, overhead deserves at least as much attention as the front line.

The reason it escapes scrutiny is structural: in the statutory accounts overhead sits in aggregated blocks disconnected from the activities it serves, and in spreadsheet-based costing every faculty guesses at a different overhead loading. An Enterprise model changes this by allocating overhead transparently down to the products that drive it, using consistent rules across the institution. That makes it possible to:

• Size it honestly – see the true scale of central and support costs as a share of the whole.
• Separate value-adding support from duplication – distinguish essential capability from legacy layering, rather than treating overhead as one untouchable block.
• Test the fairness of the loading – check whether the overhead a program carries is reasonable.
• Find structural savings – cutting genuine duplication frees funds without touching academic capacity.

Framed this way, reviewing overhead isn’t an attack on professional or support staff, it ensures the whole cost structure is examined with equal discipline, so the burden of adjustment doesn’t fall disproportionately on academics and the programs they teach.

Shaping the academic portfolio deliberately – not cutting blindly

The second lever leaders point to, reshaping the program and course portfolio, carries the same risk of being heard as “cutting.” But the purpose of a fully-costed enterprise model is precisely to make portfolio decisions deliberate and evidence-based rather than blunt.

Reshaping a portfolio without full, consistent costing is genuinely dangerous. You can withdraw a program that looks expensive but actually subsidises the rest of the institution, or keep one that quietly erodes the funds available for everything else, because a spreadsheet in one faculty allocated overhead differently from a spreadsheet in another. The enterprise model removes that guesswork.

Because it measures revenue and cost at the program and subject instance level, on a fully-allocated cost basis, the model lets leaders:

• See the true contribution of each offering including the cross-subsidies and strategic dependencies that a whole-of-institution spreadsheet view completely hides.
• Distinguish “genuinely unviable” from “strategically valuable but under-supported” some programs matter for mission, access, community or research pipeline even if they aren’t fully financially viable, and the model lets you choose to invest in them with eyes open.
• Find the design fix before the cut – often the answer is a change to delivery mode, class structure, cross-listing or scheduling that improves a program’s economics without removing it.
• Reinvest deliberately – capacity and funds released from genuine duplication or low-value activity can be redirected into the programs and disciplines the institution most wants to grow.

Framed this way, portfolio work is not about shrinking what a university offers, it’s about shaping the offering intentionally, protecting what matters, fixing what can be fixed, and investing where the institution’s strategy points. That is a conversation deans and academic boards can engage with constructively, because it is built on one shared, transparent set of numbers rather than a contest between competing spreadsheets.

If I can share one final thought on this, when you cut an Academic Program, you lose 100% of the revenue, but only a portion of the cost. Overhead remains exactly the same and is simply redistributed over the remaining institution, which could make things financially worse overall. You need the detail in the model to determine the full financial impact of making these types of rationalisation decisions.

The next step: one model, then peer benchmarks

Once an institution has a single enterprise model, the next thing to explore is credible comparisons with peers. Pilbara’s benchmarking combines anonymised model outputs from participating universities into a sector-wide view. The benchmarks include 22 core financial and non-financial measures with maximum, minimum, median and mean figures for two- and four-digit Fields of Education. The goal is to compare patterns, ratios and relative cost structures – not to reproduce audited statements. Governance is strict: no institution is visible to any other, and Pilbara acts as the independent steward of the data.

This answers the question every executive eventually asks “Are we actually stretched, or is this just what this discipline costs?” Benchmarks reveal whether a discipline that looks expensive internally reflects a sector-wide cost pattern (a discipline reality) or a genuine local opportunity to design differently, a distinction that spreadsheet sprawl, and the statutory accounts, can never make. Used this way, benchmarks support fair, informed decisions rather than arbitrary targets.

One more thing…AI

We’ve been building these types of large complex cost models for 27 years now, covering military, government, gaming, financial services, oil/gas and for the last 20 years higher education. Never have we been more excited than now with the introduction of AI and the power it can deliver to the end user to support these exact types of analysis. The Enterprise model is a causal model, that is, it uses cause and effect methods of allocating cost to the final outputs of the institution. This is a perfect enabler of Enterprise AI for Financial Decision Management. If you simply point your AI tool (agent or chat) at all of your enterprise data, and your published financials, strategic plans etc. and ask it to help “Improve academic productivity” or “rationalise program/degree offerings” it won’t hold back, it will give you, what looks like, a well thought out analysis and recommendations. Unfortunately, it could all be completely wrong, because it doesn’t understand how your institution actually works, this is where the causal model is vital, it explains, using cause and effect logic, how the costs flow, where the workload effort is, where the source of costs come from, all essential for undertaking nuanced analysis of the institution. If you are interested in reading more, we’ve written a whitepaper on how you can prepare your institution for Enterprise AI for University Financial Decision Management. Although written for the CFO, the AI model described in the paper can be used by both academic leaders and financial leaders.

The bottom line

Financial accounting keeps the institution compliant; it will always be essential. But it was never designed to run the institution. The decisions the sector now says are most urgent, sustainability and portfolio, are management-accounting decisions, and today they are too often made on a foundation of scattered, inconsistent, unauditable spreadsheets.

Enterprise Management Accounting replaces that sprawl with one enterprise model of the institution: consistent allocation rules, full traceability, and a single agreed picture that reconciles to the general ledger and holds up at the executive table. Used well, it lets leaders understand where effort and cost really go, so they can rebalance workload fairly, review the true size and make-up of overhead, remove low-value duplication, reinvest freed capacity into teaching and research, and shape the academic portfolio deliberately.

Financial accounting tells you where you have been. One Enterprise model helps you work out what to do next and lets the whole institution trust, and stand behind, the answer.