Using Analytics to Increase
Efficiencies of Portfolio
Growth and Management
Cindy McGirk, RN, MBA, JD Manager, Strategic Initiatives
H. Lee Moffitt Cancer Center Foundation Michael C. Hibler, MPA
Sr. Associate Director of Development The 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
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
Overview
Introduction to analytics
Mythology around big data/predictive modeling
Analytics as philanthropic opportunity
Analytics
All about analysis
Putting data into decision making
•
Business Intelligence
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 Modeling
Identify patterns in data
Strength of variables and correlation -quantitative
There 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 – qualitative
Taller 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
Case Study – Direct Mail
Comprehensive Direct Mail Program
FY13 -
•
$735K gross
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
H. Lee Moffitt Cancer Center
Moffitt Case Study
…the biggest challenge of managing data is making
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
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
The Moffitt Foundation is moving toward an
analytics model which will move us to the
Analytics and Modeling
•
We are statistically identifying our donors
•
Using analytics to “data-mine”…our
own
data
•
Removes “personality”…however….
Using Connectivity
•
Multiple points of touch
•
Example: event vs. education
Content courtesy Bentz Whaley Flessner
EstimatedCapacity Connected Very Assigned Not Connected Assigned Not
$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
New patient
DOES NOT
“opt out”
• Proceed with HIPAA compliant processWealth
Screening
• Demographic info screenedHigh capacity
patients
identified
• Wealth indicators assigned as “A” sent to Foundation for evaluationLeadership
visit may
reveal cues
• Feedback from Moffitt experience evaluated and triagedLEADERSHIP VISITS
New patient
DOES NOT
“opt out”
• Proceed with HIPAA compliant processWealth
Screening
• Demographic info screenedHigh capacity
patients
identified
• Wealth indicators rated as “B” and “C” sent to Foundation for evaluationDevelopment
Staff Remind
Faculty to
Listen for Cues
• Follow-up by Development Staff as
appropriate
“B” and “C” Rating
And a word about HIPAA…
•
Recent changes present even better
opportunities to refine data
•
But compliance continues to be critically
“Success is a science; if you have the conditions,
you will have the result.”
Oscar Wilde
