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NACCDO Using Analytics to increase Efficiencies of Portfolio Growth and Management - Hibler, McGirk
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Transcript of NACCDO Using Analytics to increase Efficiencies of Portfolio Growth and Management - Hibler, McGirk
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
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….
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