The document discusses challenges faced by the Northwestern Memorial Foundation database team prior to implementing automation solutions. It summarizes key issues such as:
1) Managing duplicates was extremely time-consuming, with an estimated 16,500 duplicates that would take over 2 years to merge manually.
2) Event registration and participant management for 31 events was inefficient, taking over 1 minute to complete basic tasks.
3) List management was difficult with separate spreadsheets, slowing gift entry and analysis.
4) Lack of profiling made affinity-based engagement and predictive modeling impossible.
5) Data was segmented in silos, leading to duplicated efforts and inconsistencies.
The document argues that implementing Omatic automation
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1. Eddye Ervin (bCRE-Pro), Philanthropy Associate, Database
Management of Northwestern Memorial Foundation
Sylvia Piszczor, Philanthropy Application Analyst, of
Northwestern Memorial Foundation
Top 5 Raiser’s Edge Challenges we
Automated
3. Systems and Data Management Team
Purpose
The database mission and vision defines what we strive to be and what we strive to achieve in the
context of the organization as a whole. It gives the team common goals and aspirations to keep us
tightly engaged and highly motivated. This will increase the efficiency of the team and help guide us to
focus on the right things and not waste time and resources as we work toward a common goal.
Vision
Improve fundraising operations and decision-making by providing data that is accurate, reliable,
accessible and consistent.
Mission
To support Northwestern Memorial Foundation in fulfilling its mission, we strive to make information
from our databases and related systems accessible and understandable to all stakeholders, while
protecting the integrity and preserving the confidentiality of all data.
4. Northwestern Medical
Faculty Foundation
Cadence Health
KishHealth & Marianjoy
To Be Announced
Northwestern
Medicine
Launched
4
Rapid Growth
The Challenge Begins
2017 est.
2016
2015
2014
2010
2009
Lake Forest Hospital
Employee
FTE
Donors
24,000 TBD
6,400 3,777
7,600 6,385
7,600 8,747
17,000 11,587
21,000 19,664
6. _____
What are we not going to do?
The Dual Bottom Line Matrix
_____
Boston Consulting Group's Growth-Share Matrix
https://nonprofitquarterly.org/2014/04/01/the-matrix-map-a-powerful-tool-for-mission-
focused-nonprofits/
7. Dual Bottom Line Matrix For Fundraisers
How does it work for Fundraisers?
Critical
MissionImpact
Limited
Good
Not Needed
Moderate
Abundant
$
=
Financial Sustainability
$STOP
$
8. The Dual Bottom Line Matrix Supporting Fundraisers
How does it work for non-fundraisers?
Safe
DatabeIntegrityImpact
Resource SustainabilityInefficient
Mild Risk
Detrimental
Manageable
Efficient
STOP
=
Critical
Good
Not Needed
Limited
Moderate
Abundant
9. The Dual Bottom Line Matrix
What are we not going to do?
STOP
$
MissionImpact
Resource Sustainability
STOP
DonorIntegrityImpact
Resource Sustainability
12. Can’t trust
the data
Invent
creative
solutions
Routine
tasks take
longer
Suppressed
or
deceased
receive
mailings
Inaccurate
reports and
calculations
Disjointed
donor
history
Duplicate Management
Prior toAutomation - Consequences
Erodes Donor TrustErodes RE User Confidence
13. Duplicate Management
Flag the
duplicate
records
Pick the
record that will
be the
“survivor”
Manually
correct bio info
on the
“survivor”
record
Merge the
record.
Remove
duplicate
data
Remove
duplicate flag
from “survivor”
records
Delete
“spare”
record
Prior toAutomation
3 databases into 1
+330,000 constituents
+880,000 gift
+860,000 actions
+685,000 notes
+370,000 participants
NM Estimated: 10% overlap in donors
Raisers Edge: 15% duplicate rate reported
Actual: 18% duplicate rate
We tried to manage it ourselves…
16. Duplicate Management with Automation
Using MergeOmatic
Review
identified
duplicate
records
Manually correct bio
info on the “survivor”
record
Batch merge
the records.
MergeOmatic
Dropped the duplicate rate from
18% to 5%
And you won’t believe how easy it was…
32. List Management
Prior toAutomation
• Enter entire employee list into RE as full
constituentsEmployee List
• Stored in a separate spreadsheet
• Only added as a constituent when gift
received
• Spreadsheet was referenced to do analysis
Patient Lists
7,000 employees
to
24,000 employees
1 hospital
to
7 hospitals
33. CHALLENGES
• Dirties the data
with records that
that will never
become active
donors.
BENEFITS
• The constituent
information is
available to
capture
appeals, actions,
etc.
• Gift entry is
more efficient,
because the
data is on the
constituent
record.
CHALLENGES
• Gift entry takes
longer
• Information on
the spreadsheet
is separate
from the
gift/donor
record.
• Makes analysis
harder.
BENEFITS
• Doesn’t “dirty”
the data with
records that
will never
become active
donors.
Enter the records into Raiser’s
Edge as full constituent
Keep a separate
spreadsheet
34. CHALLENGES
• Dirties the data
with records that
that will never
become active
donors.
BENEFITS
• The constituent
information is
available to
capture
appeals, actions,
etc.
• Gift entry is
more efficient,
because the
data is on the
constituent
record.
CHALLENGES
• Gift entry takes
longer
• Information on
the spreadsheet
is separate
from the
gift/donor
record.
• Makes analysis
harder.
BENEFITS
• Doesn’t “dirty”
the data with
records that
will never
become active
donors.
Enter the records into Raiser’s
Edge as full constituent
Keep a separate
spreadsheet
35. BENEFITS
• The constituent
information is
available to
capture
appeals, actions,
actions, etc.
• Gift entry is
more efficient,
because the
data is on the
constituent
record.
Enter the records into Raiser’s
Edge as full constituent
Keep a separate
spreadsheet
BENEFITS
• Doesn’t “dirty” the
data with records
that will never
become active
donors
List Management
39. A Long Term Donor Strategy
Donors Giving $1MM+
First gift <=$1,000 First gift >$1,000
61%
Planned Giving Donors
First gift <=$1,000 First gift >$1,000
Handle each prospect as if they are your next major or planned gift prospect
66%
39
Our most generous donors started off with a gift under $1000
40. List Management with Automation
Using ImportOmatic, List Management, and FindOmatic
Safe
IntegrityImpact
Process Sustainability
Inefficient
Mild Risk
Detrimental
Manageable
Efficient
=
42. _____
What is the one thing that every single donor to
any organization has in common?
_____
43. Affinity Engagement and Scoring
43
Building a Predictive Model
0.00%
0.50%
1.00%
1.50%
2.00%
2014 2013 2012 2011 2010 2009 2008 2007 2006
Response Rate by Date of Last Visit
Expected Actual
44. Affinity Engagement and Scoring
Building a Predictive Model
Positive Indicators –
>1% response rate
Negative Indicators -
<0.25% response rate
Neutral Indicators
• Age: 70-99
• Location: Out of
state
• At least one inpatient
visit
• Seen by 3 or more
physicians
• 8 or more visits
• Seen by specific
Physicians
• Age: <40
• Location: certain IL
ZIP codes
• Everything else
46. _____
What are the threads that make up the donors
to your organization?
Other programs give you a value –
None allow you to define what is valuable.
_____
47. Affinity Engagement and Scoring
47
Building a Predictive Model
0.00%
0.50%
1.00%
1.50%
2.00%
2014 2013 2012 2011 2010 2009 2008 2007 2006
Response Rate by Date of Last Visit
Expected Actual Actual - Low Score Actual - High Score
48. _____
To pull this type of analytics together, it takes:
_____
“Many Tears”
- Annual Giving Director
49. Positive
Indicators –
>1% response
rate
Negative
Indicators -
<0.25%
response rate
Neutral
Indicators
• Age: 70-99
• Location:
Out of state
• At least one
inpatient
visit
• Seen by 3
or more
physicians
• 8 or more
visits
• Seen by
specific
Physicians
• Age: <40
• Location:
certain IL
ZIP codes
• Everything
else
Affinity Engagement and Scoring
Building a Predictive Model
50. Affinity Engagement and Scoring
50
Building a Predictive Model for Our Patients
0.00%
0.50%
1.00%
1.50%
2.00%
2014 2013 2012 2011 2010 2009 2008 2007 2006
Response Rate by Date of Last Visit
Expected Actual Actual - Low Score Actual - High Score
51. Affinity Engagement and Scoring
Using ScoreOmatic
Safe
IntegrityImpact
Process Sustainability
Inefficient
Mild Risk
Detrimental
Manageable
Efficient
=
53. Segmenting Data
Prior toAutomation- Impact on the organization
Fundraising processes occur in silos
− Each office does their own thing
Multiple efforts geared toward same donor
− Are the right people being solicited for the right
effort?
− Are the right people being excluded from efforts?
In-house knowledge and expertise is not fully
utilized across the system
− Inconsistencies among shared processes
− High level work is being shortchanged to meet
immediate needs
− Duplication of efforts
− Fundraising efforts are not measured consistently
across system
Is my money
supporting a
new hospital
in the
Central?”
Why am I being
asked for an annual
gift at Central when
I am considering a
major gift at North?
Who should I call
to make my
donation to
North?
55. Segmenting Data
Replication:
− “Hand out recipe cards to 12 people and ask
each to make 1 cupcake before frosting it
according to their preference.”
Scaling:
− “The best baker bakes a dozen cupcakes in 1
batch and then simply have each person apply
their preferred frosting.”
Do we need to replicate or can we scale?
56.
57.
58. Segmenting Data with Automation
Using SegmentOmatic
Safe
IntegrityImpact
Process Sustainability
Inefficient
Mild Risk
Detrimental
Manageable
Efficient
=
59.
60. The Dual Bottom Line Matrix
What are we not going to do?
STOP
$
MissionImpact
Resource Availability
STOP
DonorIntegrityImpact
Resource Availability
68. Questions?
1. Duplicate Management MergeOmatic
2. Event Participant Management EventOmatic
3. List Management List Management
4. Constituent Profiling ScoreOmatic
5. Segmenting Data SegmentOmatic
6. Holding people accountable AudOmatic
With Omatic Software
69. Thank you!
Eddye Ervin (bCRE-Pro)
Philanthropy Associate, Database Management of
Northwestern Memorial Foundation
etollive@nm.org
Sylvia Piszczor
Philanthropy Application Analyst, of
Northwestern Memorial Foundation
spiszczo@nm.org
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