Given the published data shown above, the Association has analyzed where each candidate’s stand on solving  US student loan Debt. Translating from what each candidate has said into different scores, we hope to rank them and share the information to the American public.  Before we go further let us critically think what a public policy can and cannot do to solve any particular problem.  Understanding logically on the problems will help to avoid making unnecessary discussions or debate.  It does not mean that the American public cannot discuss this big issue.  Rather, to do it efficiently and purposely.

As the Association has published many articles on this issue, then it will be easier for the American public to understand the root of the problems.  Basically there are 2 culprits that cause all this crisis: (1). Skyrocketed college cost and (2). Systematic errors purposely induced into the system.  No one can solve the US student loans issue until these two elements are understood and then eliminated.

In the applied econometrics or statistical world, the sources of standard deviation or variance can be classified into 2 groups: random and systematic.  Because the opportunities to make money are widely opened in this $1.5 trillion industry, then everyone is trying to get a piece out-of it.  From lending institutions to loan servicing organizations and others.  Because the interests of each institutions may not be the same, except to make as much money as possible, then each one of them is trying to induce or twick the system for they own benefits.  If there are 10 entities involving in the system then potentially there will be 10 sources of systematic errors.  Because these errors are unique to the institution that brought it in, then there is a small opportunity for other entities or outsider to change that.  For example, the  DOE is hardly check if the loan servicing company is operating under DOE’s guidelines.

Will continue to part II.

The answer may be “yes with a note”.  Many colleges in the past may have relied heavily on what has been known as “Best Practices” or BP to report institutional metrics.  One may notice that almost every US higher learning institution follow the same path on reporting their institutional metrics.  Focus heavily on reporting is what was in the past, which may be less relevant given the current changes and dynamics in the industry.  For example, majority factbook or factsheet are provided and make available on the institution’s website.  There is a clear justification of doing so which is partly to fulfill their accountability as public institutions or to show their responsibility to the donors.

While applying BP is a great way to manage an organization, one may ask how has such a policy helped them to cope with the dynamics and changes that have affected the environments where they are operating?  If the best practices represent the best of best strategies that ever invented, found or practice in the industry, then below are the critical questions to think about:

1. Why the second order for optimal condition on the institutional metrics function such as retention and graduation is greater than zero?  If this is the case, then an institution is in need to find a breakthrough to survive in the future.
2. Why there are so many higher ed institutions listed on the DoE’s HCM list? May be the logical answer is clear in that, they did not adopt the so-called BP. However, the troubled institutions may have adopted the BP, but fail to adapt to the new reality which may have caused the BPs are no longer relevant.

There is a clear flaw if organizations hold tight on the BP without looking at (1). the new reality and (2). the institution’s core competencies as discussed in Harvard Business Review written by C.K. Prahalad and Gary Hamel in1990.  The question is how a higher ed entity is able to recognize its core?  Will the core ever change because of new public policies and industry dynamics?  IRI will help finding the answers.

One of the reasons why the Association was established many years ago is to bring the awareness to the American public on potential challenges facing by Uncle Sam because of the national student loan debt.  In fact, the first article written and posted in the BLOG was written on March 13, 2013.  At that time, no one even believe what we have hypothesized.  However, today, six years later, everyone confirmed what AAEA has predicted.  Below are the recent examples of what the players have said:

1. Current administrators.
2. Wall Street.
3. Politicians.
4. Lawmakers.
5. Reporters.
6. Wealth Consultants.
7. State agencies.
8. Money managers.

There are many others that can be added to the above list.  It took 6 years for everyone to realize that student loan debt accumulations are not a good thing.  There are several things that one might be able to observe from the student loan debts: (1). common theme shown by the provided list above is nothing, but a reaction.  They all reacted on something that has happened.  But, we at AAEA applied data analytics can see what is coming; and (2). perhaps, the public rarely heard comments from the US higher ed institutions on loan debts, even the most respective School of Economics i n the country classified as the Fresh and Saltwater institutions seem to avoid talking about it, even though their institutions are one of the most important source of ideas and many of their faculty have won the Nobel Laureate award.  One may ask, why are they so quite?; (3). the American public will hear less from student loans servicing companies, such as NAVI and NNI.

One needs to be proactive instead of reactive.  However, bounded rationality, moral virtue and wisdom of which the Association has shared to the American public may have blinded players’ mind and soul such that a short-run maximizing model of Neo-classical paradigm is adopted, instead.

Back in 2013 the predecessor of the current administration has introduced the so-called CAR. It has been on the news recently that finally the White House is trying to cope with the US higher education related to the student loan debt.  The American public eager to know what public policies on higher ed are being cooked in the kitchen.  If the Congress votes for them, then there will be huge impacts on higher learning institutions, students, their family and the society.  Apparently, the policy has shifted and perhaps it has made a U-turn from ignoring the American public interests to something in supporting them.  This shift in Higher Ed policy occurs because the student loan debt has been a hot topic in the campaign trails.

Basically HEA is ≅ with CAR with a little, but very important twist to limit the amount of taken student loans which previously is not one of the elements in CAR.  However, this little tweak has huge impacts on some higher learning institutions in that it will affect their enrollment significantly.

Please click=======>HERE<=========

to access your institution’s rating, first click on the provided link (in red above), then click on the drop down menu to find the State where your institution is located, then scroll down to find out the score

Based on publicly available NCES data, in 2013 AAEA has calculated and shared to the American public a proxy of the college rating under CAR.  This rating will be updated with the new component in HEA policy.  The results will be shared soon to the American public through AAEA’s website.  Because of the new component (limit on student loan) will be added, then under HEA, the college rating will produce a College Stressed Test Score (CSTS) as a proxy of an institution’s survival probability under the new proposed HEA policy.  For now, the CAR still relevant, and it can be accessed by clicking this link.

The Association of American Education Analytics is persistent in its missions, prove that its research are honest, unbiased, current, trustworthy, relevant, independent, and helpful.  We, at AAEA can see what is coming, based on what has happened in the past.  We accomplish our research by applying IRI mindset, analytical tools, rigorous and totality in its research approaches on institutional data.

Herbert’s hypothesis is yet significant to understand the need of strategic information in the decision making process.  In the past five years, the data analytics and data scientists profession have bloomed and demand for these professionals across different industries are skyrocketed.  However, the speed of companies’ adoption on this new exciting development differs.  Rapid adjustments found in the industries characterized by ultra-competition, such as manufacturing, or retail.  However, others such as education satisfies with best-practices and data visualization approaches, instead of deploying data analytics.

Needless to say that bounded rationality (BR) has prevented any industry, or any company to max-out their opportunities, investments or resources for some may apply less-than-optimal strategies.  Making this honest mistake is natural because of BR.  It prevents any organization to make optimal choice because human beings are constrained to apply their rationality fully because lack of wisdom (LW) or add (gut) feeling, rumors and owned biases in the process.  Therefore, whatever the decisions that have been made in the past suffered from this natural constraint.  The example has been discussed by Ricardo’s–the Law of Diminishing Return.  The current example can be learned from Facebook $120 billion in 24 hours loss in market capitalization because the combination of LW and BR.

Supposed the optimal output/revenue/sales/enrollment or ROI is Π, an organization will never be able to reach Π, but (Π-ε), because of LW & BR.  The gap measured by ε can be reduced by the application of data analytics where strategic decisions are made and based upon.  One can call ε as the waste of resources, or the loss of chances or opportunities because the institutions fail to make important decision based on processed data.  Some decision makers realize this constraint, and welcome the application of data analytics.  However, many may still stick with the Neo-classical theory of profit maximization or simple rule dictated by the Wall Street.

Higher learning organizations are more comfortable with the concept of best-practices. Needless to say that these best practices are unwritten consensus among the institutions in the industry which are communicated to members through different seminars and Associations.  Should it be time to think about these best practices mindset?  The reason is simple for the best practices paradigm fails to recognize special or unique characteristic or core competence of an individual organization.  For example, if one strategy works for Harvard, it does not automatically work for Universities in North Carolina.  Or if it works for 4-year institution then it will work for 2-year colleges.  Or if it works for state-owned institutions, then it will automatically work for non-profit private entities.

Having discussed the role of process data and BR, one may conclude:

1. Strategic decisions need to made based on data analytics and not data visualization alone.
2. Companies or higher learning organizations that have relied more heavily on data analytics will perform better in the long-run and will be able to outsmart their competitors.
3. Demand for data scientists will keep increasing in the future.  Please check out the following current open position.  If interested, please click this link to apply.
4. Decision makers will rely more on information processed by data analytics.
5. Applying data visualization instead of data analytics will not produce the optimal results.
6. Return or profit cannot be maxed out indefinitely.  Therefore, a new paradigm need to be explored, adopted and applied in order to survive in the world of ultra competition.  This new paradigm will be discussed in the up-coming BLOG article.

Following our discussions on moral virtues, it is pretty obvious that any decision made without wisdom will not produce optimal results.  As shown below quoted from Encyclopedia Britannica on Aristotle’s hypothesis about moral virtue and wisdom.

“Wisdom, the intellectual virtue that is proper to practical reason, is inseparably linked with the moral virtues of the affective part of the soul. Only if an agent possesses moral virtue will he endorse an appropriate recipe for a good life. Only if he is gifted with intelligence will he make an accurate assessment of the circumstances in which his decision is to be made. It is impossible, Aristotle says, to be really good without wisdom or to be really wise without moral virtue. Only when correct reasoning and right desire come together does truly virtuous action result”

That having said, we are now understand more about Ricardo’s theory of diminishing return to scale in that no entity will ever experience positive revenue or sales growth forever.  Recent example from FEDEX shows the proof.  Even though, the Wall Street thinks otherwise.  There are all non-linear, and only positively slope in certain range.  The question is why many institutions trying to push higher?  Maybe, some of the companies are living in hallucination?

One can see the parallel with Ricardo’s hypothesis.  The land in the classical Ricardo example is parallel as the business environment at time t. The innovator, enter the market (fertile land) as the market leader (Apple in smart phone industry), then other players such as Samsung and Huawei came at time (t+i) and make the business environment more crowded or saturated (less fertile land).  These laggards, however, entered the market with better technology.  Therefore, their products perceived by the customers have higher value.  It can be observed that success will create more demand for leisure.  Since time is finite, i.e., there are only 24 hours available a day, the effect of increasing demand for leisure on the market leader is obvious.

The same thing occurs in higher ed.  Harvard as the innovator enters the market decades ago, then followed by others.  Now, that in the higher ed industry, the business environments are way too saturated with all kind of noises, especially when the administrators let all kind of for-profit organizations to join the crowd.  For those who already in the market, they are trying to expand their programs, instead of finding their “sweet spot”.  This strategy finally leads to disastrous outcomes. There are two reasons why this happens. (1). The industry has reached it steady-state, i.e., after the first and second order conditions for maximum were met and (2) Because of bounded rationality as it has been explained by Herbert’s.  Certainly, the captain of those institutions may not have the wisdom and perhaps they are leaving in the state of hallucination that makes them to be unwise and irrational in making choices.   In order to compensate their failures or to prove that they have made the rational decision, then they start to cheat or to cover-up?  In other words, any lack of wisdom leads institutions to make disastrous decisions, policy choice or strategies.  It surely will negatively affect the stake holders and the society as a whole.

The answer is yes, because outcomes produced based on rationality has the upper bound (say X), while results produced based on moral virtues equal to upper bound plus., i.e., X+ε. In other words human beings will never be able to use their rationality fully in the decision making process, but partially.  Herbert A. Simon (1947) called this phenomenon as bounded rationality.  If this is the case, then any entity managed based on Neo-classical or Rational Expectation will no longer possible to advance further after it hits the upper bound.  This is not a new concept, but has been discussed by Ricardo with his famous diminishing return to scale hypothesis.  Let us take an example of the Apple company.  It starts as a market leader in the smart phone industry until Samsung, and now potentially Huawei entered the market.  The classical example can also be taken from automobile industry.  The US companies dominated supply of cars in the world, until the Japanese car manufactures took over as the global players.  Market leaders discussed above may have applied the Neo-classical profit-maximizing mindset as the center of their operations.  But newer competitors focusing more toward customers satisfaction and customer perceived value as their competitive weapons.  Therefore, profit is seen as the results, and not the choice variable as seen by the Neo-classical concept adopters.

In the higher education industry, students and employees level of satisfaction are the choice variables.  Therefore, higher ed entities should focus on maximizing their utility function, instead of someone’s else.  This hypothesis has huge implications, and may require significant paradigm shift in the process to manage a higher ed institution.  The transformation in attitude and conduct from different players in the system are required, and this is not an easy task.

The exemplar evidences of practicing moral virtues need to come first from the upper level management.  Sadly, like in any others, education industry has been known to its strong buddy-buddy and a close-knit system.  In such a system, each element will protect each other’s interest.  This reality may cause biases which push the main focus further away to the buddy-buddy group’s interests.  Under such a condition, maximizing group’s interest (example: increase group members’  pay check) will be the focus, instead of students’ utility function. But students’ focus will be used as a rhetoric jargon to camouflage the hidden agenda.  Others, outside the group will be used as the working bees to support the group’s interests.  The pay gap from these two groups is going to be wider. If the institutional budget is finite, and because of the big chucks of it go to the select group, then only a small amount remained to pay the outsiders.  However, their workload go to the other way around.  In contrast to the group members’, the peons will do most of the laundry lists.  Those who go against the group’s interest will be wiped out and this will create further fear in the work place.  This kind of system will only produce yes-man employees while creativity and innovation will be (near) null.  This is the reason why a system operates based on moral virtue produces fruits far more superior than those of bounded rationality.

The paranoid behavior phenomenon is found at higher ed organization and pratically in any industry, big or small are consistent with Herbert’s bounded rationality hypothesis. The close-knit paranoid group behaviors occur because of they in-capabilities to formulate and solve complex problems.  Therefore, the only way they can protect their individual objective is by sticking together.  They are also fear of retaliation or dismay of losing their position and money associated with it, once their lose their power grips.  Sadly on the expense of everyone else in the system, students’ and outsiders’.