Universities around the world are investing heavily in Enterprise AI. Yet despite the promise, a large proportion of enterprise AI initiatives fail to deliver meaningful, sustainable value. The reason is rarely the technology itself—it’s the absence of a coherent economic model that explains how the institution actually works. This is where Professor William F. Massy’s […]
READ MOREUnderstanding the Landscape Civil Engineering stands as one of the foundational disciplines in higher education, yet its financial performance reveals fascinating insights when compared to peer engineering programs and non-engineering fields. Using comprehensive Australian sector benchmarks1 from 2024, we can uncover patterns that transcend borders and offer valuable lessons for universities worldwide. The Cost Efficiency […]
READ MOREArtificial intelligence is rapidly reshaping how universities manage data, plan resources, and make financial decisions. But as AI adoption accelerates, so too does the need for strong governance, transparency, and trust. In a recent Pilbara Group webinar, industry leaders from Intelligen, Snowflake, and Pilbara Group came together to explore what responsible, governed AI looks like […]
READ MOREThe recent EDUCAUSE report — “2026 EDUCAUSE Top 10: Making Connections” — identifies ten pressing technology, data and organisational issues for higher education institutions around the world. (EDUCAUSE Review) While many of these issues focus on technology and data, a clear theme is emerging: institutions must build connections — across people, functions, data systems, and […]
READ MOREI was chatting with Gary Cokins on LinkedIn last week about using Activity-Based Costing (ABC) for university financial management and I mentioned that by using traditional financial accounting methods a lot of costs could be missed, specifically cross-subsidization and overhead. Cross-subsidization occurs where the costs of teaching subjects are covered by other schools, think elective […]
READ MOREFollowing on from our post on ‘why’ institutions should be delving into Academic Program Financial Management, and the previous tips on data requirements, project staffing, and model business rules and assumptions, this week’s tip looks at managing expectations relating to timelines. Tip 4 – Timeline (time to build, time to update) Let’s be honest – […]
READ MOREFollowing on from our post on ‘why’ institutions should be delving into Academic Program Financial Management, and the previous tips on data requirements and project staffing, this week’s tip provides advice on Model Business Rules and Assumptions. Tip 3 – Model Business Rules and Assumptions (a list of some of most essential ones) Firstly, the […]
READ MOREFollowing on from our post on ‘why’ institutions should be delving into Academic Program Financial Management, and last week’s post on data requirements, this week’s tip provides advice on the level of project support needed to support these models. Tip 2 – Project Staffing (who is needed and why) These types of models often require […]
READ MOREFollowing on from last week’s blog post on ‘why’ institutions should be delving into Academic Program Financial Management, this post provides advice on the types of data needed to support these models. Tip 1 – Data Data extracts are required from multiple siloed systems. These include Financial Management, HR/Payroll, Student Management Systems, Timetabling and sometimes […]
READ MORECan you estimate the cost of new Programs that your institution is considering adding to your curriculum? New Subjects? What is the cost difference to teach different student types (domestic, international, in-state etc.) in each Program? Or Subject? What is the magic ‘breakeven’ student number for each Program? Subject? And how does this change when […]
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