INTEGRATINGOPEN DATA WITH OPERATIONSTO FIGHT BLIGHT

OLIVER WISEOffice of Performance & AccountabilityCity of New Orleans

In September 2010, roughly 25% addresses in NOLA looked like this

Source: David Grunfeld, Times-Picayune | nola.com

Source: Faubourg St. John Neighborhood Association. fsjna.org

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UPDATE #1:WE HIT OUR GOAL!

September 2010 Estimate (United States Postal Service data)

April 2013 Estimate (University of New Orleans survey data)

0

10,000

20,000

30,000

40,000

50,000

30% Reduction In Blighted Addresses In New Orleans:

More Than 10,000 Blighted Addresses Reduced

UPDATE #2:OPEN CODE AND OPEN DATA

Database

Flatfile export

Cleaning, manipulation, analysis

Visualization

Powerpoint for your

boss

Open data platform

Traditional BI in Public Sector

Open Code and Open Data for BI

Database

Open data platform

Cleaning, manipulation, and analysis coded in R

Reproducible, Sustainable,

Generalizable Reporting

UPDATE #3:ANALYTICS

11

Overview of the Blight Enforcement Process

LOT CLEARING

COMPLIANCE

JUDGMENT

3. RESEARCH

1. INTAKEAND INPUT

2. INSPECT 4. NOTICE

5. HEAR

Typical Blighted Property Blighted Property with <3 Violations

Blighted Property with <3 Violations in Strong Market

Cluster

0%

10%

20%

30%

40%

50%

60%

70%

19%

47%

58%

Compliance Rates for Different Types of Blighted Properties