I’m going to take a different approach with this post today. Many of my posts have focused on the negative things occurring in the Higher Education sector, things like reduction in state and federal funding, more competition for students, reduction in endowments, the end of traditional education as we know it. All doom and gloom, but this time I’m going to be focused on the positive aspects – how to empower the university to take charge and not be victims to an ever changing political and economic landscape.

Step 1 – Cooperation

For the betterment of the entire university, it is imperative that academics and administrators work more closely together and collectively develop solutions. This was discussed in a previous blog post “Balancing Academic Values and Market Forces”  where Professor Massy (Professor Emeritus and Former Vice President for Business and Finance, Stanford University) discusses the major benefits of a close collaboration between CFOs and CAOs to balance costs and missions.

Step 2 – Know where you are now

Do you really know how your university operates? Do you really understand all of the complex relationships going on inside your organization? Like every organization a university consumes a wide range of resources to produce an output. This output could be teaching or it could be research or it could be some type of sporting program or community support project. Whatever the output, there are a large number of players involved in creating that output, a university is a large complex enterprise that can’t be summarized in a simple spreadsheet. To completely understand where you are now, you need to understand how your university currently works. Don’t worry (yet) about whether it’s not operating in the most efficient way, it doesn’t matter if it’s making or losing money, what’s important is understanding HOW it works. Improvements can come later, but not knowing where you are now makes it impossible to work out how to get to where you want to go.  So how do you do this? You model your organization, you build a representation of how your university works, including all of the detailed and intricate relationships that occur between schools, faculty, administration, support services etc. If this sounds like it’s a difficult task then you are correct, well WERE correct. This type of modelling has been exceptionally hard in the past, but with the vast amount of data systems now available inside the university coupled with a standard methodology and powerful modelling software it is now a whole lot quicker and easier. This is the University Management Model and has been used by numerous universities for nearly 10 years now.

Step 3 – Know where you want to go

Now you have a full understanding of how your university operates, you need to work out where you want to go to.  What types of things do you anticipate (or can already see) occurring?  What “questions” do you want to ask? Working out the proper questions is part of the problem, how do you know you are asking the right questions. In short, particularly for complex problems, you don’t really know until you ask. So the trick is to be able to ask a lot of different questions and see what the answers are, it’s experimentation, you are on a path of discovery. Since none of this has happened yet, you can’t be sure if it will happen, the crystal ball isn’t operating, gut feel and intuition are the best you can do as well as harassing your poor analysts to keep producing spreadsheet analysis after analysis. If it’s the wrong question, then a huge amount of work is essentially wasted as the analysis is dumped and a new question / direction is accepted and a whole new analysis started. What you really need is a way of asking these questions of a model that represents the entire university. It’s based on the model above but rather than looking at where you have come from and how you operate now, it is predictive in nature: that is, it can make predictions based on the complex interrelationships embodied in the model. If you ask the wrong question, there is no need to throw the model away and start again because the exact same model can be asked a myriad of questions. The real trick is to ask a wide range of questions and compare all the answers in the one place and to be able to do this consistently, quickly and confidently.  This is the University Predictive Model and has been used by a number of universities for about five years now. Once you have asked all the questions, analyzed all the answers, developed an appropriate plan of attack and have agreement from senior executives then you progress to the next stage.

Step 4 – Execute the plan

This is a vitally important step, all the analysis in the world is pointless if the derived plan can’t be executed. Depending on the plan this could be a simple or very complex task. It is a combination of project management, change management and personnel management. There are numerous books dedicated to just this step alone and far too much to discuss in this blog post.

Step 5 – Collaborate and benchmark

This step is similar to Step 1, but where Step 1 is focused internally, Step 5 looks at a bigger picture, that is, Higher Education as a whole.  There needs to be more collaboration and less competition to ensure that the sector as a whole, both nationally and internationally, succeeds. This means better learning outcomes for students, better artistic outcomes, and better research outcomes to drive advances in science, technology, medicine, business, law, engineering, the arts etc.  You need to not only focus on academics but also on administrators sharing best practice, sharing common services, and sharing benchmarks. I’m not suggesting that there is complete transparency; what I am suggesting is that there is a certain amount of information that can be shared without giving away any competitive advantage. Competition confers many benefits, but a certain degree of collaboration can be better, “Coopertition” as it has been coined. A great starting place for coopertition is blind benchmarking, this is a process of consolidating detailed data sets from the various models described above, making the data anonymous, and producing a set of benchmarks that are common to the group including maximums, means and minimums. Each individual institution will see exactly where they sit with respect to each benchmark, which can then feed into a plan created out of Step 3.

Final Thoughts

An important point to make is that each of these steps is not a one-time exercise, it’s an enduring process and iterative process.  This is why it’s very important to have models that are easily maintained and updated, so that they can evolve as the university evolves. As the university becomes more efficient and this new way of operating is reflected in the models, the benchmarks are likewise updated based on the collective improvements across all universities.  This in turn will be fed back to the originating institutions who can see there are still better ways of improving, thus working towards even more improvement – thus providing a virtuous circle feedback system for the overall benefit of Higher Education.