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Dennis McCarthy
Gilman Sullivan
• Gilman -Introduction & Context
• Dennis
• What is (are) Analytics?
• Leveraging Analytics – tomorrow
• Case Studies – solving problems
• Gilman
• Organization Issues in Implementing
• Key Questions to Ask?
• Duet – Summary Q & A
The Analytics Journey
2
• Efficiency
• Relationships
• More $$$$$
• Too many Priorities
• Too few resources
• Coins in the couch cushion!
Context
3
GOLD MINE
• Your supporter & donor information is an endowment!
• Do you sit on the data or grow your relationships?
• Analytics is a way to cultivate your supporter
Context
4
What is (are) Analytics?
5
What are Analytics and why do I care
What are Analytics and why do I care
• Key Types
DESCRIPTIVE
How are things
Going?
PREDICTIVE
Forecasts future
behavior or
performance
PRESCRIPTIVE
Suggests a prescribed
next step or action
#1
#2
#3
Now that I care…what do I do?
8
Now that I care…what do I do?
9
TYPE #1 Descriptive Data #2 Predictive Data #3 Prescriptive Data
Defined What is happening now? What is likely to happen? Do what next?
Examples • Wealth Screening
• Philanthropic Giving
History
• Consumer
Demographics
• Social Media Profiles
• Who will respond?
• Who will give a Major
Gift?
• Who will attend an
event?
• Who will reactivate?
• Assign to a Major
Gift Officer
• Ask for $50k
• Ask for $50 Direct
Mail
• Contact a person
NOW
Why? To develop a profile on a
donor, prospect or a
segment of people with
common traits
To identify individuals
who are likely to take
action and prioritize them
ahead of others
To take a very
specific action
knowing that
statistically it is likely
to be the best
approach
Some examples of analytics informing non-profits.
10
Baptist Health Foundation of Greater Lousiville
Challenge:
Small development staff – how do they
expand their work and remain efficient?
How do you create business processes to
cultivate the right relationship with the right
donor?
And then how do you create an authentic
stewardship of your best supporters?
E.F Schumacher: adaequatio
Operation Smile on the path to learning &
kaizen
A high performing international NGO, recognized as
Non-Profit of the Year in 2008.
Challenge:
How do we compare to our peers?
How do we learn in an open and collaborative
process?
Are we prepared to make the paradigm shift of
measurement, sharing and change management
• Organization Issues
• Leadership support – embracing
• Leveraging the tools
• Engaging & Educating
Considerations in Implementing
14
• Key Questions to Ask
– Data?
– Capabilities in house for analysis?
– Current decision process?
– Organization ready to tackle this?
CONSIDER - Culture trumps all else !
15
• Pollyanna Principles
• Prioritization
• Embracing means supporting!
– And asking questions
CONSIDER - Leadership
16
• Involve many in the idea
• Critically evaluate abilities
• Educate & Train where necessary
• Start slowly
CONSIDER - Engaging & Educating
17
• Benefits/Value
• Cautions
Summary
18
What are your questions?
Thank you!
Dennis.McCarthy@Blackbaud.com
Gilman.Sullivan@Blackbaud.com

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2015 afp slides v7

  • 2. • Gilman -Introduction & Context • Dennis • What is (are) Analytics? • Leveraging Analytics – tomorrow • Case Studies – solving problems • Gilman • Organization Issues in Implementing • Key Questions to Ask? • Duet – Summary Q & A The Analytics Journey 2
  • 3. • Efficiency • Relationships • More $$$$$ • Too many Priorities • Too few resources • Coins in the couch cushion! Context 3 GOLD MINE
  • 4. • Your supporter & donor information is an endowment! • Do you sit on the data or grow your relationships? • Analytics is a way to cultivate your supporter Context 4
  • 5. What is (are) Analytics? 5
  • 6. What are Analytics and why do I care
  • 7. What are Analytics and why do I care • Key Types DESCRIPTIVE How are things Going? PREDICTIVE Forecasts future behavior or performance PRESCRIPTIVE Suggests a prescribed next step or action #1 #2 #3
  • 8. Now that I care…what do I do? 8
  • 9. Now that I care…what do I do? 9 TYPE #1 Descriptive Data #2 Predictive Data #3 Prescriptive Data Defined What is happening now? What is likely to happen? Do what next? Examples • Wealth Screening • Philanthropic Giving History • Consumer Demographics • Social Media Profiles • Who will respond? • Who will give a Major Gift? • Who will attend an event? • Who will reactivate? • Assign to a Major Gift Officer • Ask for $50k • Ask for $50 Direct Mail • Contact a person NOW Why? To develop a profile on a donor, prospect or a segment of people with common traits To identify individuals who are likely to take action and prioritize them ahead of others To take a very specific action knowing that statistically it is likely to be the best approach
  • 10. Some examples of analytics informing non-profits. 10
  • 11. Baptist Health Foundation of Greater Lousiville Challenge: Small development staff – how do they expand their work and remain efficient? How do you create business processes to cultivate the right relationship with the right donor? And then how do you create an authentic stewardship of your best supporters?
  • 13. Operation Smile on the path to learning & kaizen A high performing international NGO, recognized as Non-Profit of the Year in 2008. Challenge: How do we compare to our peers? How do we learn in an open and collaborative process? Are we prepared to make the paradigm shift of measurement, sharing and change management
  • 14. • Organization Issues • Leadership support – embracing • Leveraging the tools • Engaging & Educating Considerations in Implementing 14
  • 15. • Key Questions to Ask – Data? – Capabilities in house for analysis? – Current decision process? – Organization ready to tackle this? CONSIDER - Culture trumps all else ! 15
  • 16. • Pollyanna Principles • Prioritization • Embracing means supporting! – And asking questions CONSIDER - Leadership 16
  • 17. • Involve many in the idea • Critically evaluate abilities • Educate & Train where necessary • Start slowly CONSIDER - Engaging & Educating 17
  • 19. What are your questions?

Notes de l'éditeur

  1. Baptist Heath Foundation of Greater Louisville had a business challenge – Small development staff and a large health care provider, the question becomes how do we expand our work and make staff more efficient? How do you create business processes to cultivate the correct relationships with the correct donors? And then do you create an authentic stewardship of your best supporters? The non-profit licensed tools to structure a process to identify is both their major donor and potential major/midlevel donors as they enter the hospital. Start stewardship early. Potential supporters were moved into a Grateful Patient program – with initial results strong . Again small organization but after a few weeks they had identified over 100 new major donor prospects through advanced analytics and business process.
  2. The Foundation used tools to structure a process to identify who are their potential major donors and then potential major/midlevel donors as they come to the hospital. For potential donors they were moved into a Grateful patient program with strong initial results. And identifying over 100 new major donor prospects through changes in business process and advanced analytics.
  3. How do we learn what we don’t already know? The earliest notion of the Black Swan event was not Nassim Taleb but Lincoln Steffens, the muckraker. Operation Smile, awarded Non-Profit of the Year by the DMA in 2008, they wanted to evaluate how they compared to their peers. They had no idea. Step #1 – clean the data Step #2 Understand their own KPI’s versus their vertical performance. Step #3 Identify gaps in process and channels to test into the changes. Outcomes: Improve retention of new donors by 25%, and increased reactivation rate by 71%. Learning: Leverage knowledge to in understand what you do not know..
  4. Step #1 Clean your data…please GIGO. Step #2 Begin a journey with facilitated discovery and benchmarking – look at their KPI’s versus their verticals. Step #3 Identify Gaps in process and go to market strategies & test into the changes. Outcomes: they improved retention of new donors by 25%, and increased reactivation by 71%. Learning: Leverage knowledge and share experiences to understand what you do know and cannot know.