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Hands-On Analysis Track

Generate ideas and discover insights from your data. Check out the sessions in the Hands-On Analysis track.

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Day 1, Tuesday, Feb. 27

10:15-11:05 AM
Developing Ways to Tie Predictive Analytics for Prospect Scoring to Development Officer Performance

Learn how to build a basic predictive model to score alumni major gift prospects, explore ways to best distribute those prospects to front-line development officers, and discover how to use those scores to provide a deeper look at a development officer's performance metrics-and ultimately help them be a better fundraiser.

Lucas Moss, Director of Business Intelligence, University of Tennessee Foundation

11:25 AM-12:15 PM
Measuring Alumni Engagement: A Model-based Analytical Approach

Donor engagement is a key concept in fundraising. Strong donor relationships will lead to high monetary donation and high advocacy/volunteering activities. While most research in the area of engagement measuring has focused on providing a single score for each individual based on historical giving/volunteering activities, this session examines alumni engagement from three different perspectives: monetary giving, loyalty and social connectedness. Learn how this multidimensional analytical approach can capture alumni engagement in a "full profile" format.

Heather Campbell, Director of Analytics and Data Management; and Min Xu, Associate Director, Data Scientist, Princeton University

1:45-2:35 PM
Prospect Probability Engine: Using Data Science to Optimize Fundraising at a Leading Academic Medical Center

The Prospect Probability Engine is a new, highly-customized system designed internally at Thomas Jefferson University and Jefferson Health that integrates data analytics, prospect management, reporting and data visualization technology as the fundamental ingredient in preparing for Jefferson's upcoming $1B+ comprehensive fundraising campaign. On a daily basis, the Prospect Probability Engine applies machine learning technology to evaluate various characteristics of approximately 500,000 to 600,000 patients, alumni and friends in an effort to isolate those constituents who could or are likely to make a major gift in support of the upcoming bicentennial campaign. Join this session to learn how the Prospect Probability Engine has enhanced business.

Amy Bryant, Senior Director of Prospect Management and Research; Joseph A. Carroll, Assistant Vice President, Information Management, Office of Institutional Advancement; and David Ritchie, Senior Director, Business Intelligence, Analytics, and Data Services, Thomas Jefferson University and Jefferson Health


Day 2, Wednesday, Feb. 28

10:00-10:50 AM
Bridging the Gap Between Fundraising Activity and Budgetary Impact

Have you ever been asked to measure fundraising's impact on your institution's budget? It can be extremely difficult to identify the aggregate fundraising impact; endowed gifts provide payout in perpetuity, bequest expectancies will (hopefully) be realized at some point in the near future, and expendable gifts, while expendable, can have restrictions tied to the way the funds are spent. Explore reconciling fundraising data with its corresponding budgetary impact, selecting the relevant data in building a model (or models) to forecast fundraising's impact on the budget, and strategies to communicate current results and fiscal year trajectory with key stakeholders within your organization.

Matt Hopkins, Senior Associate Director, Financial Analytics; and David Murphy, Budget Director and Associate Vice President for Finance, University of Chicago

11:10 AM-NOON
Build an Analytics Dashboard from Scratch with Python/Flask

Learn how to upgrade your dashboards to webapps that allow user input and real-time analytics on those inputs. This session looks at two webapps, a simple interface for a briefing automation project and a portfolio stress test webapp that guides MGOs through an annual portfolio strategy workshop. It will include the process/administrative side (of working with the IT/networking team to get it secure and accessible to the people who need access to it) as well as the technical infrastructure of the webapp. Once you know how to get up and running with Python and Flask, you'll find you can implement webapps into your workflow with ease. You'll leave this session with the know-how to build your own webapp and with the knowledge to make it work for your organization.

John Connelly, Research Manager, Georgetown University

A Predictive Model to Forecast MBA Internship Placement Success

The BYU Key Performance Indicator (KPI) and Data Analytics process offers an innovative approach to change the conversation around the job hunt process with MBAs. Using the predictive model, we can drive and improve the process with students for more transparency and accountability on their job hunt performance, and at the same time clarify and highlight the critical activities that increase the likelihood of success. This approach demonstrates a method for highlighting and identifying top performers in certain key performance ratios and points students to key experts. KPIs offer a real-world experience, allowing students to hold themselves, and others, accountable for greater effectiveness.

Rick Patterson, Assistant Director, Marriott School of Business, Brigham Young University

Data-driven Partnerships

Using data to drive our advancement programs is a sure key to success, but we often find that the fundraiser and the report writers don't speak the same language. We lose time going back and forth on requests to get at the heart of what is needed, often missing data points that can inform our actions and influence our goals. Learn how to be a bridge between the front-line and the back office, using data to your advantage. Done successfully, your colleagues will see you as a partner in their quest for more gifts and higher engagement.

Cassie Hunt, Director of Advancement Operations, Washington and Lee University

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