Forecasting Methods for International Enrollment Management

Individual Economic Summary:  Forecasting Methods for　International Enrollment Management

Daniel J. Stone

Ohio Dominican University　　　　

Forcasting Methods for International Enrollment Management- ELS Language Centers and Ohio Dominican University from Daniel J. Stone, MBA

　　　　　In June 2010, I relocated from my home state of South Carolina to Columbus, Ohio to open an Intensive English Program (IEP) on the campus of Ohio Dominican University (ODU).  Typically, institutions of higher education will facilitate an IEP in-house such as English as Second Language (ESL) programs located on the campuses of Capital, Otterbein, Columbus State and Ohio State for example.  In the case of ODU, management of an ESL Program is outsourced by my former employer, ELS Educational Services (ELS).  A third-party vendor, ELS is based out of Princeton, New Jersey and touts itself as the largest recruiter of international students for universities and postgraduate programs in the US, Canada, and Australia  (ELS Educational Services, Inc., 2012).  At the local level, ELS Language Centers is a private entity that provides English language training on college campuses throughout the US. 

　　　　　Forecasting methods were employed to analyze data to carry out ELS's mission which was to make a profit.  In general, ELS has the belief that the more industrious a Language Center (LC), and doing so with as little of possible manpower, the more profitable it will be.  This trait comes from the ELS’s parent companies of Benesse Corporation and Berliz  Language School based in Tokyo, Japan.  With a Japanese belief system coupled by a corporate office in New Jersey and in the case of ELS/Columbus, a district office in Seattle, Washington, not only were there communication and logistical gaps but there were also culture gaps.  This goes without saying the different cultures that the LCs are expected to manage while trying to navigate ODU's politics and being understaffed by design.  The margin for success under these conditions are small since in order to deliver satisfactory results in circumstances that required a major undertaking and a high level of labor intensiveness is determined on all parties involved to buy in and being able to execute.  While the challenges were great from 2010 to 2012 at ELS/Columbus, the LC was accredited by the US Department of Education and became the first International English Language Testing System (IELTS) Testing Center in Central Ohio.  However, a direct correlation that demonstrates that this ELS's mission needs to be broadened to more than just making a profit is the high turnover of quality staff leaving to work at the other ESL programs in Columbus coupled by the resistance received by "ODU Working Group".  The "ODU Working Group" comprised of direct hires of ODU and in theory were to bridge any gaps in services between ELS and ODU. 

　　　　　Looking back, resources were scarce as I moved forward at Center Director at ELS/Columbus in the Summer of 2010.  For example, the time allowed to prepare the forecast for upcoming enrollment periods was only six weeks.  Alone, much of those first six weeks were spent advertising, interviewing, hiring, and training new staff.  As a result, forecasting was conducted simultaneously the first year of operations until ELS/Columbus had enough data from a local standpoint to even consider employing qualitative forecasting.  Therefore naive forecasting was employed that first year since the future trends of enrollment could not be explained at ELS/Columbus until more data (time) was gained.  Nevertheless, qualitative and quantitative forecasting techniques were employed in order for ELS to operate as a proprietary on college campuses such as ODU.  Having a solid understanding of ELS's mission which is to optimize profit, I was well aware that ELS valued what ODU had to offer because it fit perfectly within ELS's model.  ELS would be operating by using the least expensive method while achieving desire results:  profit maximization. 

Quantitative Forecasting-  Causal Forecasting

　　　　　ELS squeezes out inefficiencies and streamlines resources by using the Full-Time Enrollment (FTE) technique.  This technique is essential to ELS since it ensures that the organization remains profitable by managing a LC's hiring needs (Appendix A).  By taking the item to be forecasted, enrollment, teacher's work schedules, classroom space, textbooks, and other inventory are allocated based on the number of students enrolled at the LC.  In short, the more students enrolled at a LC, the more teaching and administrative hours are available.  For example, a student enrolled in a full-time program (120 hours per session) gets a count of "1".  A student enrolled in a part-time program which is enough hours to maintain student visa requirements (80 hours per session) gets a count of "0.67".  Lastly, a student that is enrolled in a part-time program which does not need to maintain student visa requirements (60 hours per session) gets a count of "0.50".  The formula used to determine the hours per day that are allowed is calculated by the formula =IF(Total Full Time Enrollment Count<41,( Total Full Time Enrollment Count multiplied by 7.76+155.2),( Total Full Time Enrollment Count multiplied by 7.76+164.9))/(Number of days of instruction per session which is 20).  Without the FTE technique, a LC is unable to consistently operate within financial standards while verifying that the students enrolled are in the correct program for the accurate length of time.  While managing the present FTE, the future FTE is managed by controlling levels such as forecasting future students' enrollments. 

　　　　　Next, FTE is tracked by hours allowed with holidays factored in versus the hours scheduled that session.  Known as the Cumulative Standard Tracker, the hours unused which are rolled over to the following sessions are banked for when the schedule can't be kept within the financial standards.  For example, a schedule can't be kept within financial standards due to too many students per a class's academic standards.  The maximum number of students for core classes are 15 students and 20 students for elective classes.  At the end of the year, any banked hours that are unused are taken away and the new year starts at zero banked hours (Appendix B).

　　　　　The Future Student Forecasting Enrollment (FSFE) technique allows tracking and forecasting to be kept in order (Appendix C).  Due to the seemingly endless possibilities of a student's status coupled by tight units of enrollment measurements (four 4-week sessions equate to one semester at ODU).  For example, in any given session, the following events can take place:  A student will depart and return to their home country, a student will transfer to another school, a student will return to their home country with the intention to come back to ELS/Columbus school within the next five months (or have to get a new immigration document thru their nearest US Embassy), a student will take the next session off and stay in the US to apply at other universities or take prep exams for entrance into another university, or a student will take the next session off due to a medical condition such as pregnancy.  Then there are the students that are coming to ELS/Columbus school for classes and will have to the following events take place:  new incoming for the first time, transferring from another school to ELS/Columbus school, returning to ELS/Columbus school after being out of the country temporarily, returning to ELS/Columbus school after taking the previous session off, returning to ELS/Columbus school after taking time off due to a medical condition such as pregnancy.  With so many students coming and going every four weeks, and the importance that ELS/Columbus have enough staff to meet the needs and over staffing is not an option due to ELS's mission of making a profit. 

Qualitative Forecasting-  Contractual Shortfalls, Overgrowth, and Ramadan

　　　　　I learned very quickly that the "one size fits all" approach from the corporate and district levels did not work more times than it did work.  Heartburn experienced that first year was later corrected with both qualitative and quantitative forecasting.  Some examples of the how qualitative forecasting was employed the second year was by ensuring that ELS/Columbus had enough classroom space.  In May 2010, I came to Columbus for the very first time for the final interview and offer.  In meeting some of the "ODU Working Group", members of the ELS senior management, aka "Jury and Executive opinion" explained to the ODU employees that in the first year they should expect approximately 45 ELS students comprising of 15 students staying in the dorms on campus, 15 students staying with host families, and 15 students from the outside.  When classes commenced at the start of the Fall 2010 semester, ELS had four students.  By the end of the semester, ELS's enrollment grew to about 25.  It had appeared that ELS's senior management would be correct in their estimate of 45 students the first year.  ELS operates 13 four-week sessions meaning that during the Winter Break, ELS classes were in session.  Between the semesters, ELS took on 40 students, mainly transfer students.  Despite the horrid conditions that first Winter Break, ELS's enrollment had blown past ELS senior management's expectations.  At the end of the Spring 2011 semester, ELS was forced to have classes on the main campus in the allocated spaces as well as empty spaces usually used by ODU.  Between the semesters in July 2011, ELS/Columbus's enrollment ballooned to 140 students, nearly 100 more than ELS senior management forecasted a year prior.  Since ODU's enrollment was next to nonexistent on the main campus between the semesters, ELS was able to used empty classrooms.  From the start of the Fall 2011 semester, ELS fleshed out its oversized enrollment by using the empty classrooms at the LEAD building on Airport Road.  To bridge the logistical gap, ELS and ODU entered into a joint venture for the next 12 months which comprised of the use of an ODU vans and drivers.  In order to sell the point that this joint venture was sustainable, I was able to use data from the past year.  By employing causal forecasting, ELS was able to carry out its mission of profit maximization by utilizing unused classrooms since LEAD students don't have classes during the day.  ODU supplied the resources and ELS supplied the schedule and split the operational costs 50-50. 

            During the first Winter Break,  ELS students did not have adequate food service since ODU failed miserably by not carry out contractual obligations.  ELS/Columbus protected enrollment by moving completely off the main campus the second Winter Break and did not charge ELS students for meals.  The only thing that was on the main campus over the Winter Break were dorm students.  Since ELS/Columbus had the ODU Shuttle, ELS/Columbus dispatched the shuttle on a regular basis to the Easton Town Center where students picked up meals and shopped at Wal-Mart. 

            Ramadan, the main holiday for Muslims and 80% of ELS/Columbus's FTE proved disastrous the Summer of 2011.  Fortunately, due to the newness of the ELS/Columbus student body, they were not able to return home at their scholarship's expense.  Because of this, ELS/Columbus had enough FTE so that ELS/Columbus teachers' schedules were not affected.  New students at ELS took it upon themselves to not attend class which was in violation of the student visa and terminated their studies on the campus of ODU.  They were told that they had to transfer to another school or return to their home country which didn't fit their agenda. 

            In the Summer of 2012, qualitative forecasting had to be employed effectively to ensure that there were no misunderstandings coupled by the fact that FTE would be substantially lower than in previous sessions.  Students effected by Ramadan were given options and signed an agreement and based on the outcome of the options selected determined how many senior teachers could take off the session that was effected by Ramadan and get paid due to the amount of vacation hours accumulated.  

　　　　　To conclude, the importance of both qualitative and quantitative forecasting techniques allowed me as Center Director to manage the scarce resources at my disposal as well as the heartburn of rolling out a new program.  Despite the obstacles, I was able to carry out ELS's mission by hiring staff on a just-in-time basis, utilize unused classrooms, maintain a manageable amount of inventory such as text books, predict the number of beds needed for the dorms and homestay pools.  These forecasting techniques weren't just  one-way for ELS's benefit.  These techniques were used to provide information to ODU's top management for the their forecasting of upcoming fiscal schedules due to the significance of the income that ELS was generating on the campus of ODU. 

 References

ELS Educational Services, Inc. (2012). About ELS.  Retrieved from ELS Language

Centers official website:  http://www.els.edu/en/AboutELS