Predictive analytics

Seeing what is coming, so a community can act first.

We build predictive models for community organizations: where and when violence is likely to rise, which blocks need outreach this week, how a season or a heat wave changes the risk. The models are built from public data, read by the people who know the streets, and used to move resources, never to label people.

How we work

Six principles

Public data, local reading

Dispatch feeds, crime reports, weather, property and blight data, census and health indicators. Every model is read with outreach workers before anyone acts on it.

Places and times, not people

We score places, hours, and seasons. We do not build lists of people. That line does not move.

Seasons and context

Cleveland has a rhythm: summer, school dismissal, holidays, heat. The models carry a seasonal baseline so a spike is read against what is normal for the week.

Results, not formulas

Partners see tiers, hot spots, forecasts, and return-on-investment figures. The weights and formulas are proprietary and stay in the research workspace.

Honest about error

Every forecast carries its uncertainty. A model that cannot say when it is unsure should not be trusted.

Built to be kept

A pipeline that runs itself each morning, a dashboard the team actually opens, and a review sheet for the weekly meeting.

A course

Predictive analytics for community organizations

Six sessions for program directors, outreach leads, and the person who ends up holding the spreadsheet. No coding required; the goal is to read a model, question it, and use it. In development.

1

What a prediction is

Baselines, rates, and why last year is not a forecast.

2

Finding the data

Open data portals, dispatch feeds, census, health and property data, and what each one leaves out.

3

Seasons and hot spots

Reading a map and a calendar together. Where, when, and how sure.

4

Risk without labels

Scoring places and times, protecting people, and the ethics of acting on a forecast.

5

From forecast to field

The weekly review: turning tiers into a deployment plan and a follow-up.

6

Measuring the return

What an intervention saved, in harm avoided and dollars, and how to say it to a funder.