Using Analytics to Increase Efficiencies of Portfolio Growth and Management

Cindy McGirk, RN, MBA, JDManager, Strategic InitiativesH. Lee Moffitt Cancer Center Foundation

Michael C. Hibler, MPASr. Associate Director of DevelopmentThe Johns Hopkins Kimmel Cancer Center

Johns Hopkins Kimmel Cancer Center

Matrix Cancer Center in Baltimore, MD

6,000 New Patients / 72 inpatient beds

7 Fundraisers / 1 Professional Support / 4 Admin

FY 13 - $98M

Raised over half of $500M Campaign 2010-2017

H. Lee Moffitt Cancer Center

“Stand-Alone” NCI Comprehensive Cancer Center in Tampa, Florida

More than 17,500 new patients (FY13)/206 Inpatient beds

Goal FY14 $23.3 Million

$300 Million Comprehensive Campaign

Mission: “…to contribute to the prevention and cure of cancer…”

Moffitt Cancer Center Foundation Vice President

4 Management Team (3 with revenue goals)

5 Gift Officers (3 MGO, 2 PGO)

1 Annual Fund/Direct Mail Staff

2 Grant Writers (1 PT)

1 Prospect Research/Development Staff

3 Special Events Staff

5 Operations/Data Analyst Staff

3 Support Staff

25 TOTAL

Overview

Introduction to analytics

Mythology around big data/predictive modeling

Analytics as philanthropic opportunity

Utility of analytics based on program

Analytics

All about analysis

Putting data into decision making

• Business Intelligence

Replaces “I think…”

Big Data & Predictive Modeling

Big data is normal data

Is your data good?

Ask a question of your data – data mining

Predictive Modeling – scoring data

Predictive ModelingIdentify patterns in data

Strength of variables and correlation -quantitativeThere is a correlation between years on file, frequency of giving, lifetime giving amount, and whether a donor is likely to lapse. The stronger the correlation between variables, the more likely that the model will predict the outcome correctly.

Causation and human element – qualitativeTaller people make more money. If we ran an analysis of this, we would find that there is a high correlation between taller heights and higher incomes. This does not mean that height causes higher incomes, but more likely that the largest population of unemployed in the United States are children, and children tend to be shorter than adults. It is better and more accurately correlated with age.

Philanthropic Opportunity

Build it, Buy it, or Borrow it

Find new donors

• Campaign analysis

Segment donors

• Annual / direct mail / social media

New way to visualize data

Case Study – Direct Mail

Comprehensive Direct Mail Program

FY13 -

• $735K gross

• 12,000 total gifts

Case Study – Direct Mail

Donor loyalty • 10+ lifetime gifts• Lifetime revenue of $100-$4,999• Largest gift of $99.99 or less• Most recent gift between August – December, 2013• First gift 6 or more years ago• All made gifts in FY14 and then 3,4,5+ consecutive years in

a row prior to that

Case Study – Direct Mail

399 Donors Identified

Made 6,977 gifts representing $173,444

Average Gift - $24.86

Planned Giving Prospects

H. Lee Moffitt Cancer CenterCase Study

Moffitt Case Study

…the biggest challenge of managing data is making

sure it’s not just a data dump…

Case in Point

• Wealth screened and assigned highest scored to MGO/PGO

• Suppressed from all mailings and “strategic calling”

• Theoretically would receive personalized communications from MGO/PGO, including personalized high-end packets

The results….

Results

• Inconsistent follow-up

• Names suppressed from other modalities

• MGOs/PGOs had unmanageable portfolios

• Move toward Campaign necessitated new, strategic thinking

• Enter Analytics and Predictive Modeling

Comparing Screening and Modeling

Wealth Screening

• Identifies wealthy constituents

• Public asset data

• Never tells the whole story, but classifies into bands effectively

Modeling

• Provides filtering and prioritization according to likelihood

• Comparative analysis to existing donors

• Never tells the whole story, but classifies into high-yield segments effectively

Slide courtesy Bentz Whaley Flessner

The Moffitt Foundation is moving toward an analytics model which will move us to the

“Science of Development”

Analytics and Modeling

• We are statistically identifying our donors

• Using analytics to “data-mine”…our own data

• Removes “personality”…however….

…we still close gifts in the living room…

Using Connectivity

• Multiple points of touch

• Example: event vs. education

• Re-adjusting and rebalancing portfolios

Content courtesy Bentz Whaley Flessner

Estimated Capacity

Very Connected

Not Assigned Connected

NotAssigned

$100M+ 1 0 3 0

$10M-$99.9M 3 0 6 0

$5M-$9.9M 1 0 6 2

$1M-$4.9M 24 3 96 53

$500K-$999K 27 9 178 102

$100K-$499K 107 10 2,507 1,693

New Prospect Research Role

• Traditional research role that includes prospect pipeline management

• More robust and analytics-based prospect research

New patient DOES NOT

“opt out”

• Proceed with HIPAA compliant process

Wealth Screening

• Demographic info screened

High capacity patients identified

• Wealth indicators assigned as “A” sent to Foundation for evaluation

Leadership visit may reveal cues

• Feedback from Moffitt experience evaluated and triaged

LEADERSHIP VISITSEngaging High Capacity Patients

New patient DOES NOT

“opt out”

• Proceed with HIPAA compliant process

Wealth Screening

• Demographic info screened

High capacity patients identified

• Wealth indicators rated as “B” and “C” sent to Foundation for evaluation

Development Staff Remind Faculty to Listen for Cues

• Follow-up by Development Staff as appropriate

“B” and “C” RatingEngaging High Capacity Patients

And a word about HIPAA…

• Recent changes present even better opportunities to refine data

• But compliance continues to be critically important

“Success is a science; if you have the conditions, you will have the result.” Oscar Wilde

Thank you!