Introduction

The survey of College and University Chief Academic Officers (CAOs) was recently released and is available at http://www.insidehighered.com/audio/2013/02/14/2013-inside-higher-ed-survey-chief-academic-officers. The survey covers a range of issues that CAOs in the United States have concerns about or they believe are in need of attention within their institution. The objective of this paper is not revisit each item but to select a handful of specific concerns around cost management and data analytics and look at likely strategies to resolve this particular group of issues that confront CAOs.

Summary of survey

Costs management is an area that reflects a growing concern amongst CAOs. The survey demonstrates that all is not well within their institutions and resolving these issues is difficult.

Concerns about costs were reflected in the following areas of the survey:

• “seven in 10 CAOs (69%) agree or strongly agree that budget shortfalls are a challenge confronting their institution this year”
• 58% indicated that they are planning to increase their emphasis on “Cutting underperforming academic programs”
• “Controlling rising costs for students and their families” was an area only 22% indicated that they were very effective in achieving.
• On the issue of “Faculty understand the financial challenges confronting our institution” only 8% strongly agreed that this was being achieved.
• “My institution can make additional and significant spending cuts without hurting quality” only 3% strongly agreed indicating that most organisations consider themselves at their financial limits.
• “Financial concerns (revenue, market opportunities, profit, etc.) are prevalent in my institution’s discussions about launching new academic programs” 50% strongly agreed that this was the case.

There is also a problem with using existing data to support the above cost concerns.

• Only 25% of CAOs said they were very effective at “Using data to aid and inform campus decision-making”
• Only 15% of CAOs said they were very effective at “Data Analysis and organizational analytics”

Discussion

Pilbara Group strongly agree with using good data to drive organisational decision making, our analytic models are constructed using as much data as possible from existing corporate systems including HR, payroll, student management, time tabling, asset management etc.

It is interesting to note from the results of the survey that 58% of CAOs want to cut underperforming academic programs but only 15% said they were very effective at using data analysis and organizational analytics and only 25% said they were very effective at using data to aid and inform campus decision-making. This begs the question, how do the other CAOs plan on determining which programs are underperforming and whether cutting these programs could have an impact on other areas of the university.

Unlike businesses which can isolate various aspects of their operations in profit centres, universities and colleges are complex and interwoven organisations with many activities and courses spanning faculties and schools creating a complex financial picture. Changes in one area could have an adverse financial impact in other areas.

Despite the high level of concern demonstrated by the survey results the typical response is to focus on the short term and when “quick wins” are required by senior management, to arrest budget “blow outs”, arbitrary across the board cuts are instituted which could be at the detriment of students, staff and the quality of education.

The short term reactions to budget over runs are disappointing especially when financial modelling practices have been around for more than 40 years and have reached a level of sophistication that several years ago could only be dreamed of.  Universities that have already implemented a range of financial models, not only understand their cost base and how to arrest budget “blow outs” before they occur, but are forecasting 7-10 years into the future examining a range of likely scenarios in their quest to control costs and limit surprises to management that could severely impact the bottom line. Some of these future scenarios are already being predicted by groups like Moody’s , Standard and Poor’s, Bain and Company as well as industry experts, these include:

• Reduction in State and Federal Funding
• Decreasing enrolments as tuition increases
• Increased administrative overhead to support more regulation and accreditation sanctions
• 33% of existing universities are not financially sustainable
• General outlook for Higher Education is “increasingly volatile”

A number of these can be used to create a combination of various scenarios to predict the likely impact on the university and allow management to plan in advance rather than operating under emergency management when a crisis occurs. A rather apt quote from The Economist states “If you think predicting the future is risky, try ignoring it.”

Solution

A growing number of universities outside of the US are starting to understand their costs and margins down to the lowest level of teaching. They know who is making money and who is losing it!

Some readers may recall the recent NACUBO conference in Indianapolis where the University of Sydney presented the way it was tackling the issue of utilising data analytics to aid decision making and examining their cost base so that they could remove underperforming courses as well as more closely examine financially unstable faculties and schools and make cross subsidization transparent.

The University of Sydney embarked on an ambitious, albeit necessary, program of understanding and costing their space and resource utilisation and then charging users for the space and services they received. This combined with data analytics is allowing the university to see and understand what is financially viable, down to individual courses and units, and make informed decisions on the future of these courses and units.

In order to achieve this level of sophistication in their financial modelling, The University of Sydney draws on data from all of its corporate systems and models the entire business of the university using a range of automated business rules to provide a very detailed historic view of the university. The next step will be to use a number of these historic models to build a predictive model to forecast various scenarios and determine the impact on the university.

These types of models can address all of the CAO cost concerns highlighted in the Inside Higher Ed survey. Specifically:

• The models can be used to determine the impact of expected revenue shortfalls
• The historic models will provide very detailed cost and revenue data on all academic programs including all support and overhead costs to determine the true performance of the program to allow for informed decision making.
• By identifying the drivers of cost and what specific costs contribute to various courses, management can make informed decisions on how to control these costs.
• CAOs can use the results of the model to better inform faculty on the financial challenges confronting the institution. Educating Faculty on the methodology and the use of the models is a key to Pilbara Group’s solution.
• Identify ways of “Doing more with less” – how can the institution reduce costs but maintain quality, the model can provide a large amount of data to allow management to make informed decisions.
• Since financial concerns are prevalent in most institutions, then embrace these discussions and use it to inform the development of the model to ensure the model addresses the key concerns upfront.
• All of the above specifically address the issue of using data to better inform campus decision-making as well as increasing the effectiveness of using data and analytics.