Steamboat Springs School District 5 Year Forecast 10/23/16 Provided by Jim Looney Square Cube Consulting, Ltd. Jim_looney@msn.com
Table of Contents Historic Enrollment Birth to Kinder New School Impacts Forecasting Methods Regression Method Growth Rate Method Cohort Comparison Rate 5 Year Forecast Recommendation Scatter Plots
SSSD K12 Historical Enrollment 3000 2500 2000 1500 1000 1,947 1,911 1,933 1,912 1,930 1,979 2,021 2,077 2,142 2,152 2,233 2,282 2,320 2,401 2,468 2,516 2,526 500 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Between 2000 and 2005, the K12 enrollment for SSSD added a total of 32 students. However, in 2001 and 2003 overall enrollment declined for those specific years. Then between 2006 and 2010, the K12 enrollment saw a dramatic uptick adding 254 students. The increase in enrollment continued between 2011 and 2015, when another 283 students were added. For 2016, the K12 enrollment grew by only 10 students from 2015.
Historic Enrollment by Grade 250 2010 250 2016 200 200 150 150 100 100 50 50 0 Kin 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th 0 Kin 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th In 2010, there is a bubble centered on the 2 nd grade with enrollment at 201. By 2016, the bubble has reached the 8 th grade and has grown to 230. By 2021, the bubble will have graduated and exited SSSD.
Historic K12 Enrollment Growth Rate 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% 1.2% 0.9% 2.5% 2.1% 2.8% 3.1% 0.5% 3.8% 2.2% 1.7% 3.5% 2.8% 1.9% 0.4% -1.0% -2.0% -1.8% -1.1% -3.0% 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 The growth rate for SSSD K-12 enrollment has been very erratic. It is unlikely that SSSD will decline in enrollment in any given year. While growing at 3.5% in 2013, the growth rate for SSSD has been on a steady decline (i.e., the pace of growth has slowed).
Birth-Kinder 200 180 160 140 120 100 80 94 105 94 99 110 150 119 119 132 120 165 146 161 162 157 151 154 135 135 115 147 158 60 40 20 0 Births Kinder There is a strong correlation between births and kinder enrollment five years later. In fact, the correlation is 0.90. What this means is that if birth counts go down, it is best to assume that the kinder enrollment 5 years later will also decline. It does not have to be exactly the same increase or decrease, just that they should generally move in the same direction. Between 2010 and 2016 there have been an average of 157 births within SSSD per year. For the next four years, the average per year is 133. The lower birth rate will need to be taken into consideration. The 2021 birth rates are expected to be similar to the 2020 numbers. The lower birth rates are not unique to SSSD. Births have been declining nationwide. Denver Public Schools had been averaging around 10,250 births. Moving forward the number is in the mid-9,000 s. For more data on national births go here: http://blogs.wsj.com/economics/2016/06/07/behind-the-ongoing-u-s-baby-bust-in-5-charts/
New School Impact SSSD Reside Students Attending Montessori K 1st 2 nd 3 rd 4th 5 th 6 th 7 th 8 th Total 2016 20 20 15 10 2 3 70 2017 20 20 20 15 10 2 3 90 2018 20 20 20 20 15 10 2 3 110 2019 20 20 20 20 20 15 10 2 3 130 2020 20 20 20 20 20 20 15 10 2 147 2021 20 20 20 20 20 20 20 15 10 165 The new Montessori program has a kinder class size of 28, with an estimated 20 residing in SSSD. Another 50 SSSD residing students in grades 1 st through 5 th are enrolled in the new school. These students were more heavily distributed in the lower grades. This make sense due the desire for parents to have a continuity of education for their child. By 2021, there should be 165 SSSD reside students attending the Montessori program.
Five Year Forecast - Methods School Enrollment Forecasting Methods Method Description Pros Cons Regression Use a multi-variant regression to calculate enrollment. Total Population and SAP are the independent variables. This is a standard forecasting method, if the R-squared value is near 1.0. For SSSD the R-squared is 0.95. Is dependent on the accuracy of the dependent variables, which are a forecast themselves. DOLA has a Median Absolute Percent Error (MAPE) of 7-8% for a 10 year total population forecast. The SAP will be off even more. Growth Rate Applies a growth rate percentage based on some historical average. The simplest and most straight forward. Does not take into account changes in other variables such as total population and birth rates. Cohort Comparison Method (CCM) Compares the number of students in a particular grade to the number of students in the previous grade during the previous year. This is the standard method for school enrollment forecasting. Good at capturing peaks and valleys moving through the grades. Cannot use to forecast entry grade (kinder). Must use some other method for kinder. There is an art in deciding what the correct ratio should be for each grade. Missing impacts can quickly throw off the forecast.
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Total Population & Student Age Population (SAP) 4,000 30,000 S A P E n r o l l m e n t 3,900 3,800 3,700 3,600 3,500 3,400 3,300 3,200 3,100 SAP TOTAL Pop 25,000 20,000 15,000 10,000 5,000 0 T o t a l P o p Both the Total Population and SAP are estimates for years 2011-2016. In my experience, the estimates are always over projected. In particular, you can see that the state estimated the SAP to grow significantly from 2010 to 2016. This is unlikely.
Total Population & SAP Revised 3,900 26,750 27,000 S A P E n r o l l m e n t 3,850 3,800 3,750 3,700 3,650 3,600 3,843 24,970 3,684 2016 2017 2018 2019 2020 2021 SAP TOTAL Pop 26,500 26,000 25,500 25,000 24,500 24,000 23,500 23,000 T o t a l P o p The revised forecast flattens out the growth in SAP as the full impact of the baby decline starts to be felt in 2019. The revised 2021 numbers are what are used for the dependent variables in the regression analysis
Multi-Variant Regression 3,000 2,500 2,000 1,500 1,000 500 0 Actual Enrollment Predictor 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Using a multi-variant regression, analysis identifies the R-Square (how well of a predictor) as 0.95. Using both Total population and SAP together are a very good predictor of enrollment. When using the regression method to calculate the 2021 enrollment, the new Montessori school (132 students) will need to be backed out of the final number.
Total Population & Student Age Population (SAP) Forecast Year Total Pop. SAP K12 Forecast 2017 24,871 3,727 2,550 2018 25,376 3,780 2,647 2019 26,018 3,804 2,717 2020 26,518 3,834 2,777 2021 27,026 3,875 2,837 Due to the stated error rates from the state demographer, the Total Population and SAP numbers should be revised downward. The 10 year error rate for Total Population is between 7-8%. There are no published error rates for SAP. However, discussions with the state demographer leads me to believe that the SAP 5 year MAPE should be around 6%. The revised 2021 Total Population adds 2,033 people over five years. The 2015 six year increase was 1,118. The revised SAP adds 180 in the same six year period. The 2015 six year increase was 238. Finally, the above forecasted number do not account for the impact of the Montessori program. The build-out from slide 7 need to be subtracted from the forecast numbers on this slide.
Growth Rate Method Average Growth Rates 2000 to 2016 1.70% 2010 to 2016 2.30% 2012 to 2016 2.10% 2014 to 2016 1.70% Forecast using 1.7% 2017 2,569 2018 2,613 2019 2,657 2020 2,702 2021 2,748 As shown in slide 5, the growth rate for SSSD has been slowing since 2013. This slow down should be accounted for in any forecasted growth rate. Below are the growth rate average for different time frames. Reviewing the growth rates above, a growth rate of 1.7% is the safest rate to use. Obviously, this is a very simple method and does not take into account any nuances that might be taking place within certain grades or impacts from new schools opening.
Cohort Comparison Rate Method (CCR) Year Kin 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th 2011 1.13 1.08 1.07 1.02 1.09 1.04 1.04 1.01 1.02 0.96 1.02 0.95 1.02 2012 1.00 1.12 1.05 0.98 1.00 1.04 1.07 1.02 0.96 0.98 0.99 1.02 1.00 2013 1.07 1.12 0.98 1.03 0.99 1.02 1.05 1.00 1.01 1.08 0.99 1.00 1.05 2014 1.21 1.12 1.04 1.05 0.98 0.99 1.01 0.98 1.05 0.99 1.06 0.99 1.06 2015 1.17 1.09 1.03 1.02 1.03 1.05 1.01 1.04 1.06 1.02 0.97 0.94 0.99 2016 1.08 0.92 0.98 0.96 1.05 0.97 1.03 1.05 1.04 1.01 0.99 1.02 1.08 Used 1.08 1.12 1.04 1.03 1.04 1.04 1.03 1.02 1.05 1.01 1.01 1.00 1.04 Square Cubed uses the birth counts gathered by the Colorado Department of Health as a proxy for the kinder cohort. To identify what CCR to use, Square Cubed Consulting identified the six-year average (All Year), the three-year average, and the two-year average. The CCR s take into account any normal development activity related to the construction of new residential units. For any given year, there are a certain number of new units constructed and closed, which will then possibly add students to the SSSD enrollment.
Cohort Comparison Rate Method (CCR) Year Birth K 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th Total 2017 135 146 186 168 209 201 208 198 201 214 232 205 192 198 2,558 2018 135 146 163 193 174 217 208 214 202 211 216 235 205 200 2,584 2019 115 124 163 170 199 180 225 214 219 212 216 219 235 213 2,589 2020 147 159 139 170 175 207 187 232 218 229 216 218 219 244 2,613 2021 150 162 178 145 175 182 214 192 236 229 242 218 218 227 2,618 Birth data is included as a reference point for anyone that would like to recreate the forecast. The only grade were an adjustment was made was in the 9 th grade. Once the Montessori program is built out, the 8 th students will reenter SSSD the following 9 th grade year. The expected impacts can be seen in Chart 4.1
Five Year Forecast - Recommendation Growth Rate: 2,748 MV Regression: 2,703 Minimum: 2,600 CCR: 2,619 Square Cubed Consulting suggests that SSSD uses the forecast produced from the CCR on slide 15. This method accounts for all of the major factors related to enrollment forecasting. Those factors are: birth rates, historic enrollment trends, cohort bubbles, new school impact, and natural residential development. The regression forecast is a quick mathematical way to forecast enrollment. However, even though the regression model used has a very high r-squared value, it relies on future Total Population and SAP forecast to be accurate. The Growth Rate method should also be discounted. It happens to be the quickest way to produce a forecast but also ignores major impacts such as lower birth rates and new school impacts.
Comparison with Previous Forecast Elementary School Year WD SC Difference 2017 1,276 1,118-158 2018 1,336 1,101-235 2019 1,393 1,061-215 Observations The major difference is due to the lower birth rates that are taken into account in the Square Cubed forecast. In addition, The opening of the Montessori program has also caused the Square Cubed forecast to be lower. The new program accounts for 87 of the difference in 2017 and 115 of the difference in 2019. Middle School Year WD SC Difference 2017 598 613 15 2018 598 627 29 2019 615 645 30 The difference has to do with the CCR s used. The WD average rate for Middle School is 1.016. The Square Cubed average CCR is 1.03. In particular, the 8 th grades are very different. WD s 8 th grade was 1.01. For 8 th grade Square Cubed used a rate of 1.05. The SSSD 2014-16 average CCR is 1.05. The three year average when WD provided a forecast was 1.006 High School Year WD SC Difference 2017 813 827 14 2018 826 856 30 2019 831 883 52 The CCR s are not much different for both of the forecasts. The difference has to do with the size of the 9 th grade class in 2017. WD forecasted the class size to be 218. Square Cubed has it forecasted at 230. The 9 th grade CCR s used by both forecast is 1.01. In addition, the 2018 and 2019 Square Cubed numbers are higher because of the higher CCR used in the 8 th grade.
Conclusion Forecast Purpose The purpose of a forecast is not to nail a number on the head. It is great if it happens, but it is more important to identify the major risk to the organization. Success 1. The forecast provided clearly defines the major risks to SSSD enrollment. The risks are: A shrinking demand at elementary due to fewer children being born. The impact of the new school program on SSSD enrollment. The growth at the middle and high school levels over the next 5 years 2. SSSD has the tools to tweak the forecast if necessary. It is likely that at some point over the next few years that one or more of the assumptions used to create this forecast will change. If an impact changes enough, SSSD should not have to hire another consultant to produce a forecast.
Soda Creek Elementary School Scatter Plot Current Students by Region Region Count North 37 Downtown 257 Resort 210 South 46 Non-District 16
Strawberry Park Elementary School Scatter Plot Current Students by Region Region Count North 115 Downtown 178 Resort 82 South 48 Non-District 60
Steamboat Springs Middle School Scatter Plot Current Students by Region Region Count North 104 Downtown 267 Resort 139 South 61 Non-District 30
Steamboat Springs High School Scatter Plot Current Students by Region Region Count North 134 Downtown 308 Resort 177 South 85 Non-District 47
North Routt Charter School Scatter Plot Current Students by Region Region Count North 70 Downtown 17 Resort 6 South 2 Non-District 4
Yampa Valley High School Scatter Plot Current Students by Region Region Count North 1 Downtown 7 Resort 11 South 1 Non-District 3