What is the importance of data?

David Henderson

It has none.

“Data is only useful if it informs decision making”

- Every Carnegie Mellon University professor of public policy

There are lots of cool analytic techniques• Econometric modeling

• Linear programming

• Machine learning

• Social network analysis

• Etc.

• Selecting data points

• Assigning value to data

I will focus on two data prerequisites

Selecting data points

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

Tracking the wrong data points leads to the wrong decisions

Example

We trackWe care about

Arrest ratesCrime reduction

Public perceptionFeeling safe

People felt safer in higher arrest areas

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

Funder wanted a workforce development program to maximize job placements

Assigning value to data

Before diving into data, we need to be explicit about our own utility frameworks

Likely overly simplistic

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

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The vulnerability index is a good example of a utility framework in homeless services

Prioritizes those most likely to die on the street

Without establishing an organizational utility framework, everyone makes decisions according to their own values

Different utility functions + same data

=

Different decisions

How do we model a utility framework?

Utility elicitation is common in the business world

Model a decision maker’s risk reward preferences through a series of hypothetical investment scenarios

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

Developing a utility framework enforces consistent investment decisions

Makes investment priorities clear

Can be tested and refined through time

• 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:

End