The answer to the above question depends on one’s institutional budget, and the organization’s needs.  If the analytics software packages have the same capabilities, then the decision will be based on the price–choose the inexpensive one.

To differentiate itself from the rest of the packs, some of these software companies add a specific feature in their package.  Most software will have data visualization capabilities.  The more capabilities a software package can do, the higher the price that an institution needs to pay.  AAEA will make an open access resources, and we are in the process of developing it.  Members can access these capabilities without paying a penny, but the annual membership fees.

A few may produce some ß estimates. The remaining question will be how these estimates be used to make strategic business decisions?  This can be answered if the institution has competitive/business background.  This required business background can range from Managerial Economics/Accounting to Strategic Management.  Needless to say, that one single person may not have these whole skill sets.  Therefore, the Association will make an open access resources where members can discuss specific companies needs with the subject matters expert by paying minimal fees.

In the long-run, it will be beneficial to have an in-house data analytics group who can develop specific analytics that fit the organization’s needs.  This only can be done, if the institution has enough resources to do it.  Smaller entities will face more challenges than others to keep their data experts not to jump ship.  Folks with this expertise are fluid–they can go to places that offer a better deal.  Make and Keep them happy!!

How many programming languages one needs to know to be an effective analyst in the data science profession? The answers to this question depend on whom that you asked?  However, there is one general rule to be competitive in any profession.  The more languages that one knows, the more competitive she or he will be, right? Learning programming language not only depends on one’s talent, passion, willingness to learn new stuff/programming language, and how much resources that one has, but also to the organization where the analyst is working and the ability to see what is coming, the trends.  Some institutions take the short-cut for deploying canned analytics software, with it unique limitation.

Organizations may have their own legacy system where heavy investments have been done in the past. This situation creates a unique condition where an analyst with only expert in one programming language is the best fit for the position.  The Association thinks that at least one needs to master and being an expert in one language in his work place—knowing it very well and in-depth will make she or he the best asset for the organization.  However, to be able to stay competitive she or he needs to add her or his core competent.  With this in mind, the Association has added several sources such as C++, R or Python and  lists of canned analytics software in its site to help members to be more competitive in the job market.

Nowadays, be able to code and to share the statistical analysis results which may impact the institution’s bottom line are not the only core competent that one needs to have.  It is imperative to understand other aspects such as the industry, the economic condition, the competitors, and output and input markets in the industry where he or she is in.  For example, what will happen to the company when the DOW/stock market dips due to geo-politics?  This interruption may require the analyst to be able capture it and stochastically rerun different scenarios.

Today, the AAEA website hits another important milestone with a quarter of a million site visitors.  This shows the Association’s research results and many posted discussions have helped the researchers, readers, students, faculty, college administrators, both public and private policy makers and American public in making strategic decisions.  Many of the discussions that have been shared to the society solely based on data and analytical analyses where biases, individual or groups’ interests are set aside.  We are independent, not taking any side, self-funded and trust-worthy organization.  Our research findings are based on historical public data and the results of applying various analytical tools then shared.  Some of the institutions which we have predicted to go under many years ago, had actually be merged, closed or were liquidated.

With a humble start in March 2013, the Association has grown as one of the most trusted institutions with more than 7.5K registered members in the education analytics, big data, Institutional Research, the Economics of Education and data science professions.

Thank you for your continuing supports !!

QuarterMillionMilestone

A recent article discussed how important Data Science and Analytics are, especially for the job seekers among the under-represented group.  The Association has brought the shortages issue back in 2012.  These shortages are even more apt in higher education for the application of analytics in the past was considered irrelevant.  The history shows that intensive application of analytics never been known prior to 2012 until after the Association introduced its importance at a SAS Regional Meeting in Houston, Texas.  Prior to that a paper was also presented at 2012 North Carolina Community College Annual Meetings in Raleigh.  Today, Higher Ed institutions have to compete with manufacturing, retail and practically other non-education industries to hire an IRI expert. Consequently, the price for hiring an IRI expert will increase (see below, for examples).  Some people have a vague idea about IRI or Education Analytics.  They think that Data Visualization (completed through the implementation of Tableau or Excel.  Example: traditional IR factsheet and factbook) and data analytics are the same. Or IRI is equivalent to traditional IR + a bit of (statistics + SQL and ERP).  It may take years before the IRI application can be fully implemented in Higher Ed.  In the meantime federal funding, money and resources availability, in general are more limited compared to many years ago. The world does not have enough IRI experts, at the present moment, not until many years to come.

Position: Dean Research, Planning and Institutional Effectiveness. Required Documents: Cover Letter, Resume/CV, Transcript Master’s Degree (Must include Award/Confer Date); Position Status: Full-time; Salary Range: $120,528- $142,833 Annual Salary. Posted: 06/26/2017. Location: CA.

Position: Director, Institutional Research, Analysis, and Planning. Salary benefits: Salary Range $99,748 – $109,940. Federal Government Benefits. Posted & Closing Date: 6/26/2017 & 07/24/2017.  Location: Virginia.

Position: Research Analyst I. Salary benefits: Salary Range $40k – $60k. Posted & Closing Date: 6/26/2017 & Immediate. Location: Pennsylvania.

Note: If you are interested in knowing more about the positions, please email the Association at aaea.us@yahoo.com

Given the multifaceted problems that the US higher education is facing then managing student loans is not a one-person game, at least in the medium-run.  Short-run analyses can only be done, if one knows what agenda is on the table?  Analyzing the dynamic and the motivations of current policy makers and thinking the following factors may help to find proxy answers: (1). Policy will be aimed to reduce student loans default; (2). Collections on past and current student loans are a priority; (3). Reduction of future federal student loans is imminent.  While no one knows exactly, what is in the mind of the decision makers, a forward-thinker knows that the DOE’s budget has been or planned to be cut by $9.2B (negative 14%).  Consequently, future student loans may got impacted in a negative.

Given the above facts, loans unavailability will increase and the impacts can be significant for some players as shown in the following static equilibrium analyses.  So, current $1.3 trillion loans will increase in a slower rate in years to come (later, this can be claimed as a successful policy by the regulator).  Borrowers will rely more on private sources, if they want to get a college degree, unless the State and parents are willing to dig their pocket deeper.  Financial companies will have more business opportunities as it seems the policy benefits them most.  However, the following parties on the demand side, and selected service providers will be impacted negatively:

1. Student borrowers (more profound on lower-income population) and their parents.
2. In general, all private non-profit and non-state owned colleges will suffer due to the reduction on enrollment and a weaker demand for education services.
3. High-operating-cost organizations.
4. More families will relocate to a State that strongly support its public higher education with its reduced or free-college tuition policy for adults or for Associate degree programs.  Example: In the state of TN.

The bottom line is that except for getting back the loaned federal money, other issues in higher ed seem not to be a top priority in the  mind of the decision makers, at least for now.  Uncertainty will increase.  Though challenging, IRI Analytics might be able to lower the risk to go under for certain institutions (non-profit higher learning institutions~1475 pages pdf file), where their total spending exceeds total tuition revenues through various strategic remedies.

Observing on what are happenings in the US Higher Ed, one might notice that the future/current policy is formulated under the assumption that market alone will not be able to increase the efficiency of resource allocations.  Selective interventions need to be done, (1). especially in the supply side;  (2). DOE’s roles need to be reduced to a minimum level, and (3) business/private players will help Adam Smith’s Invisible Hand to work.  This surely a testable hypothesis which can be proved as time passes.  The impacts of these new policy shifts depend on how reactive the market forces are.  Due to the assets fixity, excess supply and technological advancements, supply will not change much from its current condition, despite the policy interventions, at least in the short-run.  However, in the (very) long-run, supply may consolidate i.e., only selective players (state-owned institutions) will survive.  Any policy aims to affect the supply will have minimum impacts. However, reactions in the demand side as results of the supply changes will have more profound effects as shown below.  Future demand, but not the supply will determine the sustainability of US higher education institutions, especially for tuition-dependent organizations.

Exactly about three years ago today the Association started to write many prediction/forecasting articles on the future of higher education in the US.  Despite the bold descriptions, many institutions think the structural & market changes will not have any impacts on them.  Therefore, some of these organizations to this date are operating with the BAU mindset.  The current events that have happened will surely push further the risk factor of institutional failure.  Recently there were many published articles which finally confirm our bold predictions.  Current consolidation in the industry will even be more profound in the years to come.  In particular, when more public money is taken away from the Higher Ed.  Therefore, US colleges’ survival will be determined more by the “Adam Smith’s Invisible Hand“.  Our IRI Analytics book and published articles have discussed such a future trend many years ago.

Perhaps, the next important skills within the IRI component is the ability to write SQL code in SAS. There has been many discussions the plus and minus of SQL and SAS PROC SQL. Knowing both tools will not hurt, but applying SQL for certain task is more difficult and cumbersome than using SAS SQL. SAS has developed certain PROCs to accomplish certain tasks. Therefore, one won’t need to write line of SQL codes to accomplish such tasks. One obvious example is on writing modeling codes equivalent to SAS PROC Arima. One can find several papers below to know and learn more about SAS PROC SQL. To learn more about SAS PROC SQL, please click here.

The news on DOE banned on ITT new students access to federal loans may have surprised many parties.  More than three years ago, the Association has initiated a research on the issue based on published NCES data.  Beginning in 2015, the DOE started publishing the same info to the American public which may have applied different methods compared to AAEA. The following is the list of other institutions which are under the regulator’s microscope.