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BBCON 2016 - Top 5 Processes We've Automated
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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Similar to BBCON 2016 - Top 5 Processes We've Automated
BBCON 2016 - Top 5 Processes We've Automated
- 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
- 2.
- 3. Systems and DataManagement 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 CadenceHealth 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
- 5. 51,041 80,911 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 5 Year Average Rapid Growth GiftTransactions - Fiscal Year 2016 Fiscal Year 2016
- 6. _____ What are wenot 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 LineMatrix For Fundraisers How does it work for Fundraisers? Critical MissionImpact Limited Good Not Needed Moderate Abundant $ = Financial Sustainability $STOP $
- 8. The Dual BottomLine 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 BottomLine Matrix What are we not going to do? STOP $ MissionImpact Resource Sustainability STOP DonorIntegrityImpact Resource Sustainability
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- 12. Can’t trust the data Invent creative solutions Routine taskstake 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 Pickthe 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…
- 14. Duplicate Management Prior toAutomation 30MERGES IN 4 HOURS
- 15. Duplicate Management 15 Prior toAutomation 16,500 Duplicates toget to 5% 132,200 Steps to Merge 550 days = 2.2 years 5% - what we estimate is manageable
- 16. Duplicate Management withAutomation 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…
- 18. Duplicate Management Prior toAutomation 30MERGES IN 4 HOURS
- 19. 1,000 MERGES IN4 HOURS
- 20. 12,000+ MERGES IN6 MONTHS
- 21. Here is PROOF!! OurCurrent Duplicate Status
- 22. Duplicate Management withAutomation Using MergeOmatic MergeOmatic And there are additional benefits RE Merge
- 23. Duplicate Management withAutomation Using MergeOmatic Safe IntegrityImpact Process Sustainability Inefficient Mild Risk Detrimental Manageable Efficient =
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- 25. 31 Events $6,080,137 Net FY16Event Activity Overview Fundraising Events 14,618 Attendees 31 Events Stewardship and Recognition Events 3,172 Attendees 32 Events
- 26. Event Management Prior toAutomation Register a participant Add participant’s spouse as guest Add 3 unknown guests 2 m 56 s
- 27. _____ Although the eventmodule is the most popular module to purchase 80% of organizations keep event data outside of RE in Excel _____
- 28. Event Management withAutomation Using EventOmatic 1 m 10 s Register a participant Add participant’s spouse as guest Add 3 unknown guests
- 29. Event Management withAutomation Using EventOmatic Safe IntegrityImpact Process Sustainability Inefficient Mild Risk Detrimental Manageable Efficient =
- 30.
- 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 thedata 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 thedata 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 informationis 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
- 36. List Management AfterAutomation Import informationinto List Management The “Holding Tank” All RE fields available to use Speeds up gift entry Avoid data entry errors
- 37. List Management AfterAutomation FindOmatic Searches forconstituents and non-constituents Easily promote to a full constituent. Searches other record types (i.e. query, reports, etc.)
- 38. _____ Typically, acquisition responserates are low and they bring in low dollar amounts. So why do we care how we handle these lists? _____
- 39. A Long TermDonor 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 withAutomation Using ImportOmatic, List Management, and FindOmatic Safe IntegrityImpact Process Sustainability Inefficient Mild Risk Detrimental Manageable Efficient =
- 41.
- 42. _____ What is theone thing that every single donor to any organization has in common? _____
- 43. Affinity Engagement andScoring 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 andScoring 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
- 45. 45 No single threadprovides the totality of beauty
- 46. _____ What are thethreads 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 andScoring 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 thistype 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 andScoring 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 andScoring Using ScoreOmatic Safe IntegrityImpact Process Sustainability Inefficient Mild Risk Detrimental Manageable Efficient =
- 52.
- 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?
- 54.
- 55. Segmenting Data Replication: − “Handout 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?
- 58. Segmenting Data withAutomation Using SegmentOmatic Safe IntegrityImpact Process Sustainability Inefficient Mild Risk Detrimental Manageable Efficient =
- 60. The Dual BottomLine Matrix What are we not going to do? STOP $ MissionImpact Resource Availability STOP DonorIntegrityImpact Resource Availability
- 61.
- 62. Tracking Changes What arewe not going to do? Garbage In Garbage Out
- 63. Tracking Changes Prior toAutomation Dependenton Record Properties Required manual review of audit queries Unable to identify personalized training needs
- 68. Questions? 1. Duplicate ManagementMergeOmatic 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
- 70. Did we leaveyou inspired, wired, or fired up? Tell us in a session survey on the mobile app, and you’ll be entered to win a complimentary pass to bbcon 2017 in Baltimore!