“Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns — the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones.” – United States Secretary of Defense Donald Rumsfeld

How do you possibly plan for something you don’t know will happen? I have spent over 20 years working in the military both in Australia and the United States, firstly in uniform with the Royal Australian Navy and then as a consultant. Our specialty in the consulting world is modelling, including cost and predictive modelling. We also spent over seven years working with the US Navy Training and Readiness organization building a training readiness system, basically measuring how ready the US Navy is to enter into operations.  The US Navy embarks on extensive training, including classroom, simulation and live training to cover a wide range of possible scenarios in a wide range of environmental conditions.  As extensive as the training is, they can’t cover everything in the live environment and there are some things they just don’t know could occur. This is where modeling and simulation play a major role in the military, this allows training in a synthetic environment which is safe as well as providing a much wider range of possible scenarios and conditions to operate in.  It also means that new, previously unknown, scenarios can be generated relatively quickly, as long as the entire environment and appropriate systems are sufficiently modeled well in advance. Compare this with the time and expense of coordinating a bunch of ships, aircraft, training ranges etc. for a live training exercise.

But how relevant is this to Higher Education?  Many institutes of Higher Education, if hit with a crisis, will have analysts pull out spreadsheets and start working from a blank piece of paper – this could take weeks or months to build up an accurate picture.  Then comes the analysis, conducted under stress, which can easily lead to errors.  If the event changes then all of this analysis is thrown away and the analysts have to start all over again. Even worse, if there is no time to perform detailed analysis, then senior management have to make quick decisions based on gut instinct alone.

A better option is to pre-build a “model” of the university that can be used for future simulations.  The model needs to accurately represent the way the university operates, and should be tested and verified by faculty and administrators.  This can all be implemented during non-crisis periods, so that it is carefully built and verified. Once it is built though, it becomes a very powerful simulation engine.  When the university hits an unexpected crisis, the analyst can simply manipulate the variables in the model and determine the impact within a few hours, not weeks or months.  If the event changes or executive management want to test other issues that might occur but haven’t yet, then it’s a simple matter of using the exact same model, manipulating the variables again and comparing multiple scenarios and picking the best options to execute.  We have two models that we use – the Historic Model and the Predictive Model.

The Historic Model is a representation of how the university has operated previously and how it operates today.

The Predictive Model is a representation of how the university could operate in the future, either one year or multiple years into the future.

Now you are probably thinking to yourself that these models could be very expensive and take a long time to build and who is going to maintain them?  This is a major benefit of our experience and the software we use. Initial models can take as little as six-eight weeks to build and the update process can be as short as three weeks. Once it is built, for only three weeks of maintenance, you have a model ready to go at a moments notice for simulations at any time over the next 12 months. You can easily have multiple answers within hours, not weeks or months. It means that analysts can spend a lot more time analyzing rather than building and maintaining spreadsheets. This is particularly important during high stress, turbulent periods.

Obviously if the model is built and maintained so quickly, it has to be a high level summary model. Not at all! The models we build are very detailed, we include, and reconcile to the financials (general ledger). We also include detailed data from student management systems, facilities databases, human resource and timetabling systems. We can also employ a lot of data from these various systems to construct the actual business rules that represent the complex relationships between the various administrative/support departments and faculty. By using as much source data as we do, and automating the model as much as possible, we are able to provide a powerful solution that is quick to build and maintain, represents the way the university actually operates, and is ready to use at a moments notice.

By definition it is impossible to identify the unknown unknowns until after the fact.  But we can help by providing you with a set of tools that make the unknowns easier to cope with once they become known.  As an added benefit the tools also help with management of the knowns! These are currently turbulent times, and just like in a war-time environment, you need the advantage of being well prepared in-advance and confident that if anything new crops up unexpectedly you can quickly assess the impact and formulate and execute a plan to address it.

“Give me six hours to chop down a tree and I will spend the first four sharpening the axe.”  – Abraham Lincoln