Edith Cowan University looks into the future

Edith Cowan University (ECU) is one of four public universities in Western Australia, with two metropolitan campuses in Mount Lawley and Joondalup, and a regional campus in Bunbury. Since it gained university status in 1991, ECU has grown to become one of the largest educational institutions in the state, with more than 27,000 students. Approximately 5,500 of these are international students, originating from more than 90 countries worldwide.

Need for standardised reporting
ECU recognised that to continue to succeed in the increasingly competitive Australian higher education sector, it needed to understand and manage its operations efficiently, just like any other large business. In particular, it needed to keep tight control of costs and to maximise income from key funding sources. Student revenue is based on a metric known as Equivalent Full-Time Student Load, or EFTSL. This is a measure of the total study load of students. The ability to calculate EFTSL accurately is vital to ensuring that ECU estimates revenue accurately, and is critical to the budgeting and resource planning process.

“Predicting our future EFTSL was a significant challenge: it took about 12 hours to run all the data through our planning model, and we were not always confident in the results,” explains Rick Gallagher, Business Analytics Administrator at ECU. “It was just one example of a wider issue with data governance: our data was previously held in multiple, disparate data sources, such as cubes, spreadsheets and desktop databases, and we had six different sets of reporting tools. The absence of a single reliable source of data or a standard methodology for analysing it meant we could not be sure that we were getting the correct answers.”

Creating a business analytics competence group
ECU decided to rethink its approach to reporting, and developed an enterprise information management (EIM) vision and strategy to deliver a more coherent architecture for data management and analysis. The project was initially delivered jointly by Deloitte and IBM, and following transition from project to operational status, IBM became the university’s main partner for support and future enhancements. IBM provided expert services exclusively focused on the analytics software that ECU was deploying. This complimented ECU’s EIM strategy and helped to ensure that the implementation was optimised to take full advantage of the capabilities of the IBM products.

Having completed the initial project, the university then formed a business intelligence competency centre (BICC) with assistance from IBM. This enabled ECU to continue the journey and maintain the successes achieved in the project.

“We initially saw IBM as being primarily a technical resource, but as the engagement went on, they increasingly became a strategic partner,” says Rick Gallagher. “IBM Business Analytics software has always enjoyed a significant market share in Western Australia and it’s used by some of the largest companies and government organisations. We were confident that the software was the right choice, and we knew it would be relatively easy to find people with good Cognos and SPSS skills.

“On top of that, we were impressed by the guidance and expertise we received from the IBM Business Analytics Software Services team – not only in terms of technical things like upgrades, but also with training and information transfer to help our power-users get up to speed with all the new capabilities.”

Building a centralised platform
The first step was to deploy an analytics platform based on a single central data warehouse that would collect and standardise data from the university’s major systems: Oracle for finance, Callista for student management, and Alesco for HR and payroll. External sources – such as the Tertiary Institutions Service Centre (TISC), which provides centralised management of applicants to all Western Australian public universities – were integrated too. The complex extract, transform and load (ETL) processes that feed the warehouse are managed by IBM InfoSphere® DataStage®, and the university plans to introduce InfoSphere QualityStage® in the near future to improve data governance even further.

Establishing a single point of control for analysis
To analyse the data, ECU selected a suite of IBM Business Analytics software. The IBM Business Analytics Software Services team helped to deploy IBM Cognos® Business Intelligence and IBM SPSS® Modeler, while IBM Business Partners supported the implementation of IBM Cognos TM1®.

“The team from IBM provided a pair of Guardian Services offerings – one for installing and configuring Cognos Business Intelligence, and one for tuning its performance – that helped us get up and running quickly. Within nine months, we started to see the first reports come through from the Cognos software, and our users quickly began to appreciate the fact that they had a single portal that they could use to access data from across the whole university,” comments Rick Gallagher.

“Instead of having to learn six different reporting tools to look at multiple systems, they now have a single, reliable platform for analysis. Even better, with Cognos 10, they can access their reports on iPads and mobile devices, and even use them offline via the Active Report capability.”

Access to analytics
“Easier access to data is a big win for us, but an even bigger benefit is the new insight that IBM Cognos Business Intelligence provides,” says Rick Gallagher. “We can analyse staffing data in ways we never could before. For instance, previously we could only report on contracted hours, whereas now we can report on and analyse the hours actually worked. We are also enhancing this to include comparison between budget and actual, again something that is currently a very time consuming and manual process. These developments are really important for budgeting and cost controlling – because if our budgets assume that people are working their contractual hours, but they’re actually working more, our projected staffing costs will be incorrect. So this reporting gives us a really easy way to highlight variances and make sure our budgets are accurate.”

Proactive operational planning
The deployment of IBM Cognos TM1 has transformed ECU’s operational planning capabilities, especially around the forecasting of student load over the next academic year. EFTSL calculations can be completed within about 30 minutes – accelerating the process by a factor of 24 and enabling analysts to perform a wide range of “what if” analyses by looking at the effects of different inputs.

“This capability to do ‘what if’ analysis is going to be vital in the near future, because of a change made to the age at which children start primary school in Western Australia, which will impact in 2015 in the form of fewer domestic school leavers reaching university age,” notes Rick Gallagher. “This means that the 2015 intake has the potential to have significantly lower enrolments than average. With TM1, we’ll be able to model the effects of this shortfall, not only on the intake year of 2015, but also in the following years when the ‘pipeline’ effect of a lower intake flows through the system as students undertake years two and three of their degree. We will be able to take action to adjust our operations accordingly – helping us respond to the situation in a much more agile and efficient manner than we ever could before.”

Harnessing predictive analytics to help students achieve
ECU is also using predictive analytics technologies to help support students to achieve success.

“One of the biggest challenges facing all tertiary education providers today is retention,” says Rick Gallagher. As part of a broader initiative around student increasing success, the university used IBM SPSS Modeler to analyse historical data and create a sophisticated statistical model that could assist the university in developing strategies to improve retention.

The team from IBM worked closely with ECU over a period of several months to develop and refine the model which was then deployed utilising IBM SPSS Collaboration and Deployment services. The model utilises historical data to help predict what may occur in the future. In this way the university is more effectively utilising information captured in the data warehouse to develop strategies that will have real outcomes for its students.

About IBM Business Analytics
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