Next Generation Impact Measurement | July 19, 2016
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Delivered by Peter York, Founder and CEO of Algorhythm, at the 2016 Annual Community Meeting & Nonprofit Expo. Attend our next event: http://www.unitedwaynca.org/events/members
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Next Generation Impact Measurement | July 19, 2016
- 1. Next Generation Impact Measurement Measuring What Matters to Nonprofits
- 2. Why Do We NOT Know If We Are Making a Difference?
- 3. What are Nonprofits Being Asked to Measure? 10% Have Some Output Data Disconnected datasets <500 cases per dataset No ”true” outcomes 1% have a Little Bit of Outcome Data Disconnected datasets <250 cases per dataset 30%-50% aren’t using valid and reliable metrics 100% of 501c3s Have 990s Shared Dataset 600,000 cases No program quality or outcome data 600,000 60,000 …. $400M spent on filing 990s $12B $30B
- 6. Lots of Outputs Little Outcomes The Balance of What We Measure
- 7. The Unfair Economics of the Nonprofit Sector Consumer Buyers “Bulk” Proxy Buyers A Consumer Buys Personal Outcomes A Funder Buys Population Impact
- 8. Postpartum Doula Services Bought by Me, for Me Postpartum Home Visitation Services Bought by Others, for a Population The Act of “Bulk” Proxy Buying Creates Unrealistic Accountability
- 9. Postpartum Doula Services Bought by Me, for Me Postpartum Home Visitation Services Bought by Others, for You Outcome Metrics aren’t Realistic Lower Stress Reduction in Child Abuse
- 10. Postpartum Doula Services Bought by Me, for Me Postpartum Home Visitation Services Bought by Others, for You Outcome Metrics aren’t Realistic Better Infant Care Skills and Knowledge Achievement of Developmental Milestones
- 11. Postpartum Doula Services Bought by Me, for Me Postpartum Home Visitation Services Bought by Others, for You Outcome Metrics aren’t Realistic Improved Maternal Physical Recovery Reduction in Subsequent Pregnancies
- 12. Postpartum Doula Services Bought by Me, for Me Postpartum Home Visitation Services Bought by Others, for You Outcome Metrics aren’t Realistic Better Sibling Adjustment Reduction in Risky Behaviors
- 13. Postpartum Doula Services Bought by Me, for Me Postpartum Home Visitation Services Bought by Others, for You Outcome Metrics aren’t Realistic Better Communication with Providers Kindergarten Readiness
- 14. Show Us Don’t Show Us As a Result, Our Current Impact Metrics… How Much We Are Doing Direct Results What Works
- 16. Does a Program Work for the Average Participant? How Does a Program Work for Targeted Segments? Means versus Me
- 17. Did the Program Recipe Move the Average? Were Always Above Average Still Below Average The Average Moved
- 18. Which Program Ingredients Work for You? You are like me! Can you tell me how you did it?
- 20. Analyses Describe What Just Happened
- 21. The Unresolved Challenges of Impact Measurement Challenge #3: Data Analysis Analyses Describe What Just Happened Amount, Frequencies, Averages, Trends Statistical Significance of Outcomes
- 22. Predict What Might Happen Provide Insight on What Might Work Very Few Existing Analyses…
- 23. Describes Never As a Result, Our Current Impact Metrics… Often, What We Just Did Sometimes, Our Results Diagnoses Problems Predicts What Might Happen Provides Insights About What To Do
- 25. We Don’t Share Stories, Insights or Lessons Data Analytics Findings
- 26. The Solution
- 27. Step One: Come Together w/in Fields of Practice
- 28. Come Together w/in Fields of Practice There’s no one-size-fits-all ideal business performance and impact model for ALL for-profit service companies Each ”industry” has it’s own standards, and when it comes to evaluating their services, each business within an industry competes on a set of common market-driven (customer- driven need and demand) outcomes. Academic Achievement Consulting/Capacity Building Employment Career Advancement It’s time to do the same within our sector Youth Development Nonprofit Capacity Building Senior Services Workforce Development Environmental Policy Etc.
- 29. Step Two: Agree on Shared Metrics
- 30. Develop Shared Metrics Target Population Field Practices Achievable Field Outcomes
- 31. Step Three: Real-World Methods
- 32. Natural ExperimentControlled Experiment Conduct Natural Experiments
- 33. Add Predictive Analytics “Predictive analytics tells you what will [likely] happen” Jeff Bertolucci, Information Week
- 34. Add Prescriptive Analytics “…prescriptive analytics tells you what to do about it.” Jeff Bertolucci, Information Week Find the Positive Deviants!
- 35. Step Four: Make Meaning, Together
- 36. Everyone Gathering Stories, Finding Positive Deviants and Sharing How They Did It
- 37. Data-Driven Decision Making for Impact
Editor's Notes
- Output data: (revenue X .65 (program revenue)) X .01; ((assumption: revenue x .65) / 60,000 (to figure out number of staff)) X 35 cases to figure out how many cases per avg org. really loose, just an estimate. $30B = overall rev for orgs over $5M, x .65 for program budget, X.03 for eval spend. Based on innonet study (state of the sector re evaluation investments). This is very conservative!