Uncertainty clouds higher education institutions in many ways that never been happened before. For examples, reduction on federal student loans and aids along with treating any scholarships received by students as income have brought multiple forces which will, at least theoretically reduce demand for higher education services. The new administration’s policy in higher ed can be summarized into one sentence which is reducing student loans debt by controlling/affecting buyers’ purchasing power i.e., the ability to acquire higher education services. Controlling the ability to finance one’s education is an effective way to control the student loans debts.

College and universities have to understand that the current new administration policy is caused by their (Higher Eds) actions and past policy which took advantage of cheap Loan (money) policy to the extreme level by increasing college tuition uncontrollably and reckless spending which have caused the national student loans to reach a new high level (reported in Sept, 2017) of $1.45 trillion or higher. Recent changes were just reactions to past colleges’ policy. During the “golden era”, most decision makers’ report card will be based on how many new buildings are built or planned to be built. But, now, instead of tangible assets their performance will be based on something that are more intangible such as retention, completion and student loans default rates.  And now they, the Colleges will be judged on how bad is their waste function, how high their customers’ satisfactions is or/and how low their tuition is and how efficient they are?

In line with this new reality, US higher education organizations cannot just use the old approach to navigate the sea of competition. Even, applying the first generation of IRI–Education Analytics will no longer yield the optimal results. There are many institutions which may not at the second stage of the evolution map yet. Some have tried to move to second stage through data visualization (not data analytics–applying software such as Tableau and other canned softwares). It requires at least five to 8 years to move from one stage to the next.

Given increasing uncertainties, we have suggested institutions to move to the second stage of the IRI. This stage will be championed by applying stochastic simulations on every aspects of institutional’ s metrics such as cost, pricing, HR, promotion, tenure practice, enrollments and others. It required the institutions to change their culture.