The document discusses the importance of selecting the right data points and developing a utility framework when making decisions. It notes that in the social sector, many data points are proxies and tracking the wrong ones can lead to wrong decisions. It also states that without establishing an organizational utility framework to value different data points, everyone makes decisions according to their own values. The key ideas are to select data points that best approximate the goals, build a model to assign value to different points, and update it over time in order to make consistent investment decisions.

1. What is the
importance of data?
David Henderson

2. It has none.

3. “Data is only useful if it
informs decision
making”
- Every Carnegie Mellon University
professor of public policy

4. There are lots of cool analytic techniques
• Econometric modeling
• Linear programming
• Machine learning
• Social network analysis
• Etc.

5. • Selecting data points
• Assigning value to data
I will focus on two data prerequisites

6. Selecting data points

7. Selecting data points is difficult in the social
sector because a lot of data points are
proxies
Example
We trackWe care about
Graduation ratesEducation
Job placementsEconomic
independence

8. Tracking the wrong data points leads to the
wrong decisions
Example
We trackWe care about
Arrest ratesCrime reduction
Public perceptionFeeling safe

9. People felt safer in higher arrest areas

10. Focusing on the wrong indicators
can lead to negative (but rational!)
decisions

11. Funder wanted a workforce development
program to maximize job placements

12. Assigning value to data

13. Before diving into data, we need to be
explicit about our own utility frameworks
Likely overly simplistic

14. A utility framework is how we value data
points, including interactions therein

15. The vulnerability index is a good example of
a utility framework in homeless services
Prioritizes those most likely to die on the street

16. Without establishing an organizational utility
framework, everyone makes decisions
according to their own values
Different utility functions + same data
=
Different decisions

17. How do we model a utility framework?

18. Utility elicitation is common in the
business world
Model a decision maker’s risk reward preferences through
a series of hypothetical investment scenarios

19. The key is to find points of indifference
Housing one chronically homeless person is equivalent to
placing three people into jobs
Points of indifference allow us to compare unlike indicators

20. Developing a utility framework enforces
consistent investment decisions
Makes investment priorities clear
Can be tested and refined through time

21. • Select (likely a series) of data points that approximate
what we really care about
• Build a model that assigns value to data points, and
update it through time
Before diving into data:

22. End