Authors: Mike Foster, Andrew VanWylen, Tim Raymer
The power of data analytics is rapidly moving districts towards the analytical orientation necessary to meet today’s challenges, and away from a traditional transactional orientation. Eidex team members reviewed product enhancements that are supporting this analytical orientation.
Enrollment Forecast Module
Mike Foster, Eidex Data Scientist, discussed the Eidex enrollment forecast module he developed. This module utilizes multiple projection methods that allow districts to determine which the best projection method fits best. The module includes a back-test feature showing how the respective models would have performed in prior years and comparing the forecast to historical actual.
Early Warning Forecast Module
Mike Foster explained the basis behind the Early Warning Forecast module recently added to the Eidex tool. The model replicates the Michigan Department of Treasury (MDT) model utilizing current and prior year district data to forecast whether a district will go into deficit within two years based on financial data trends. Key variables included in the forecast model include enrollment, revenues, expenditures, and fund balance.
Andrew VanWylen, Eidex Head of Development, reviewed the recently launched square footage analysis feature. The data was developed using computer models and district data to determine the square footage of each school district building in the state. The project was challenging and labor intensive; however, the process will provide invaluable information for additional analytical comparisons.
Mike Foster reviewed the ROI (Return on Investment) module which measures academic performance and district funding resources against peers. Mike also discussed the recently added Regression Analysis which measures academic performance against free/reduced price lunch %.
Eidex understands that standing on past success is the surest path to falling behind, and ultimately becoming irrelevant. We have this and numerous projects in the planning and early development stage, including:
A Fiscal Stress Model to provide districts with a way to self-analyze based on Early Warning analysis metrics.
Special education is a significant factor in most districts, so we are looking at various ways to collect data that can better measure the impact of special education in a district while looking at comparisons compared with peer districts.
Similar to the ROI feature, you can expect to see more “cross functional” analysis as we correlate various financial, academic, and demographic data in order to provide useful tools for your day-to-day operating decisions.
Finally, a recent national statistic caught our eye. It compared K-12 student enrollment trends with college enrollment in teacher preparation programs. Eidex collected the data and charted it for Michigan (Exhibit A). The result is cause for future concern, as the supply of qualified teachers will be less than the probable demand. What will be the ultimate impact in negotiations, staffing, and ultimately the day-to-day delivery of service to students?
We will keep looking forward and providing districts with relevant data analysis for their consideration, decision-making, and any other purpose they find helpful. We take pride in being a client-driven organization. Let us know how we can help, and let us know subjects you would like us to explore further.