1

David Stevens, Manager of Web Services,

Lehman College, City University of New York

Joe Medved, Manager of Database &

Applications, Lehman College, City University

of New York

Aarti Deshmukh, Senior Applications System

Developer, Lehman College, City University of

New York

Beyond Recruitment & Retention:

Success Via a Data-Centric Ecosystem

2

What?: The suite of tools & applications that comprise

Lehman’s enterprise publishing & communication systems.

Why?:

To align the College’s messaging, brand identity, and delivery of

personalized content.

To expose critical information and create calls-to-action re

recruitment, outreach, fund-raising, & retention efforts.

How?: By integrating silos and shadow systems, streamlining internal processes & enhancing user experience through a

federated strategic technology architecture.

Ecosystem Defined

3

Ecosystem At a Glance

4

Ecosystem in Practice

Event Management

Event category syndication maximizes exposure to key events contextually by publishing to multiple locations (e.g. college homepage, affiliate websites, & CUNY calendar).

Events may be promoted to Social Media channels & calls-to-action facilitate user engagement. Google analytics tracks traffic spikes and conversion points.

5

Ecosystem in Practice

Event Management

Event category syndication maximizes exposure to key events contextually by publishing to multiple locations (e.g. college homepage, affiliate websites, & CUNY calendar).

Events may be promoted to Social Media channels & calls-to-action facilitate user engagement. Google analytics tracks traffic spikes and conversion points.

6

Ecosystem in Practice

WordPress Newsletter:

Intuitive tagging automates the publishing of college news, blogs, and announcements to department and affiliate websites.

Calls-to-action facilitate

user engagement, and Google analytics track traffic spikes and conversion points.

7

Ecosystem in Practice

Digital Connect: Media Asset Repository

College videos may be published to YouTube, Vimeo, or iTunes U and published to Digital Connect, Lehman’s one-stop-shop for rich media content.

Through an intuitive categorization system, videos are published to multiple web properties from a single content source.

8

Ecosystem in Practice

Personalized Delivery of Content

Via Active Directory login, student course schedules, grades, alerts, and notifications can be delivered to our secure intranet site, Lehman Connect.

Personalized content will soon be sent to students via college’s mobile app. Critical alerts will appear as notifications.

From Data to Knowledge

Big Data: Data from traditional & digital sources for

discovery and analysis. Characterized by 3 V’s.

Business Intelligence: Tools and practices used to

analyze & optimize decisions and performance.

Analytics: Statistical discovery of meaningful

patterns for predictive scenarios

9

Different Questions & Tools

10

Reporting/BI > Analytics > Prescriptive

Davenport,

12/13 HBR

Lehman Examples

What is happening: LCD/BI reporting on

enrollment and retention

What is likely to happen: Rapid Insight

Analytics/predictive modeling

11

Lehman College: Predictive Analytics

Lehman is pursuing the power of regression and

predictive analytics.

Regression analysis: study of statistical relationships

among dependent and independent variables.

Based on the variables, we may be able to impact

student attrition, enrollment, graduation rates, etc.

End result of the analysis: a predictive model,

suggesting intervention strategies and possible

outcomes in future semesters.

12

Student Attrition Model

We studied attrition in a cohort of 454 FT/FT freshman students

that started in Fall 2011& followed their attrition rates through Spring 2014.

Relationships among attrition and 100+ parameters were

examined, including probation status, SAT scores, credits

attempted/earned, cumulative GPA, etc., for each semester.

The model showed a 26% attrition rate though Spring 2014:

336 students were retained and 118 attrited.

The model predicted that 109 students would attrit at the end of

the Spring 2014 semester.

Actual data shows 118 students attrited.

13

Attrition Prediction Model

Visualization: Relationship between Attrition &

First Semester Earned Credits

15

Attrition and First Term Probation

16

Predicted attrition probability for

each student in the sample.