Data analytics professionals are trained to observe what are happening in the competitive environments where they are working.  If anyone notices the recent AAPL’s stock price movement in recent weeks, then she or he noticed something significance has occurred.

Bazos is correct when he said, one day the AMZN brand will fail.  He is realistic when seeing the world.  GE, one of the beloved US company has experienced a tremendous drop in its stock price, recently.  On November 16, 2000 it was traded around $51.00-52.00, exactly 18 years later it is traded around $8 (today it hits less than $8)  There is around 84 to 85 percent drop.

So, what this has anything to do with analytics and higher education.  Well, let us try to make some inferences, based on the stories above.

1. The non-education industry is usually pretty fast when adapting themselves with changes.  But some big names still fail.  Higher ed institutions usually need a longer time to adjust to any changes.  Think what will happen…
2. Like GE, some institutions will become a history, usually for those that have limited resources.   While others who can make rapid adjustments will survive.  These organizations include non-state-owned organizations with tremendous leadership talents and financial resources.  Including in these groups are selected few state universities and colleges.
3. When the publicly served administrators at the federal or state level struggle to allocate the “pie”, less funding may be available to support higher ed, such that less people will be able to afford attending a higher ed.  Therefore, most likely students and their families have to take more loans from the commercial financial institutions or completely scrap the idea to attend a college.  Those, who decide to go on, but majoring in soft-science will carry tremendous debts, which they will not be able to repay it, ever.  So, borrowers think it over before you sign the paper.

Here is one example of the change that the IRI professional can do.  Focus on analyzing the internal data to support the management to operate more effectively.  Cut all the reporting burdens unless there are mandated by the state/federal laws such as IPEDS.  Old school has made so big of a deal for putting their information online–either fact book or fact sheet, make them colorful without further analyzing them.  In other words, majority of folks are still make a big deal of data visualization (DV) instead of data analytics (DA).  If one needs to make a parallel, stressing on DV will copy what has happened to GE, maybe!