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Dec 5, 2013 · 37m · mad

Michael Flowers, New York City // Data Driven NYC #17 // June 2013

Mike Flowers · 25m spoken Matt Turck · 7m spoken
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions

At Data Driven NYC #17, New York City's first Chief Analytics Officer Mike Flowers and data analyst Ben present how the Mayor's Office of Data Analytics (MODA) leverages cross-agency data to optimize municipal operations, improve public safety, and establish sustainable city data governance.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 23.2% of the talking time here. How this is scored →

Matt as informed peer 0.6 Guest teaching 6.0 Guest disagreement 1.4 Matt pushing back 0.0
05100:0010:0020:0030:000:59–17:10 · Matt as informed peer 0/10 Keynote on NYC Data Analytics Applications and Successes Mike Flowers delivers a keynote presentation detailing the creation and early wins of NYC's data analytics office, including fire risk triage and 911 system response time unification. The host acts purely as a quiet presenter/listener, making host expertise and pushback zero for this monologue format.17:10–20:00 · Matt as informed peer 0/10 Tactical Data Deployment and Field Tools Flowers presents tactical data deployment tools for field inspectors and firefighters, highlighting real-time building intelligence before entry. The host does not intervene during this monologue segment.20:00–25:52 · Matt as informed peer 1/10 Data Science Methodology vs. Ground Domain Expertise Data scientist Ben contrasts pure algorithmic data science with domain-informed field expertise, explaining how an outside firm's complex model failed while their domain-driven model delivered a 2.5x higher ROI. The host moderates smoothly without challenging the guest's findings.25:52–32:06 · Matt as informed peer 1/10 Panel Q&A on Inter-City Models, Financial Data, and Continuity Flowers answers audience questions regarding inter-city analytics sharing, financial data transparency exceptions, and institutional continuity across mayoral administrations. The host facilitates audience questions neutrally.32:06–37:48 · Matt as informed peer 1/10 Panel Q&A on Agency Engagement, Open Source, and Sandy Lessons Flowers and Ben explain how they handle reluctant city agencies using an iron fist and velvet cloak strategy and discuss open-sourcing geo-data tools on GitHub. The host enforces time limits and concludes the session.0:59–17:10 · Guest teaching 7/10 Keynote on NYC Data Analytics Applications and Successes Mike Flowers delivers a keynote presentation detailing the creation and early wins of NYC's data analytics office, including fire risk triage and 911 system response time unification. The host acts purely as a quiet presenter/listener, making host expertise and pushback zero for this monologue format.17:10–20:00 · Guest teaching 6/10 Tactical Data Deployment and Field Tools Flowers presents tactical data deployment tools for field inspectors and firefighters, highlighting real-time building intelligence before entry. The host does not intervene during this monologue segment.20:00–25:52 · Guest teaching 7/10 Data Science Methodology vs. Ground Domain Expertise Data scientist Ben contrasts pure algorithmic data science with domain-informed field expertise, explaining how an outside firm's complex model failed while their domain-driven model delivered a 2.5x higher ROI. The host moderates smoothly without challenging the guest's findings.25:52–32:06 · Guest teaching 5/10 Panel Q&A on Inter-City Models, Financial Data, and Continuity Flowers answers audience questions regarding inter-city analytics sharing, financial data transparency exceptions, and institutional continuity across mayoral administrations. The host facilitates audience questions neutrally.32:06–37:48 · Guest teaching 5/10 Panel Q&A on Agency Engagement, Open Source, and Sandy Lessons Flowers and Ben explain how they handle reluctant city agencies using an iron fist and velvet cloak strategy and discuss open-sourcing geo-data tools on GitHub. The host enforces time limits and concludes the session.0:59–17:10 · Guest disagreement 1/10 Keynote on NYC Data Analytics Applications and Successes Mike Flowers delivers a keynote presentation detailing the creation and early wins of NYC's data analytics office, including fire risk triage and 911 system response time unification. The host acts purely as a quiet presenter/listener, making host expertise and pushback zero for this monologue format.17:10–20:00 · Guest disagreement 1/10 Tactical Data Deployment and Field Tools Flowers presents tactical data deployment tools for field inspectors and firefighters, highlighting real-time building intelligence before entry. The host does not intervene during this monologue segment.20:00–25:52 · Guest disagreement 2/10 Data Science Methodology vs. Ground Domain Expertise Data scientist Ben contrasts pure algorithmic data science with domain-informed field expertise, explaining how an outside firm's complex model failed while their domain-driven model delivered a 2.5x higher ROI. The host moderates smoothly without challenging the guest's findings.25:52–32:06 · Guest disagreement 1/10 Panel Q&A on Inter-City Models, Financial Data, and Continuity Flowers answers audience questions regarding inter-city analytics sharing, financial data transparency exceptions, and institutional continuity across mayoral administrations. The host facilitates audience questions neutrally.32:06–37:48 · Guest disagreement 2/10 Panel Q&A on Agency Engagement, Open Source, and Sandy Lessons Flowers and Ben explain how they handle reluctant city agencies using an iron fist and velvet cloak strategy and discuss open-sourcing geo-data tools on GitHub. The host enforces time limits and concludes the session.0:59–17:10 · Matt pushing back 0/10 Keynote on NYC Data Analytics Applications and Successes Mike Flowers delivers a keynote presentation detailing the creation and early wins of NYC's data analytics office, including fire risk triage and 911 system response time unification. The host acts purely as a quiet presenter/listener, making host expertise and pushback zero for this monologue format.17:10–20:00 · Matt pushing back 0/10 Tactical Data Deployment and Field Tools Flowers presents tactical data deployment tools for field inspectors and firefighters, highlighting real-time building intelligence before entry. The host does not intervene during this monologue segment.20:00–25:52 · Matt pushing back 0/10 Data Science Methodology vs. Ground Domain Expertise Data scientist Ben contrasts pure algorithmic data science with domain-informed field expertise, explaining how an outside firm's complex model failed while their domain-driven model delivered a 2.5x higher ROI. The host moderates smoothly without challenging the guest's findings.25:52–32:06 · Matt pushing back 0/10 Panel Q&A on Inter-City Models, Financial Data, and Continuity Flowers answers audience questions regarding inter-city analytics sharing, financial data transparency exceptions, and institutional continuity across mayoral administrations. The host facilitates audience questions neutrally.32:06–37:48 · Matt pushing back 0/10 Panel Q&A on Agency Engagement, Open Source, and Sandy Lessons Flowers and Ben explain how they handle reluctant city agencies using an iron fist and velvet cloak strategy and discuss open-sourcing geo-data tools on GitHub. The host enforces time limits and concludes the session.

speaking balance: gold is Matt, purple is the guest (3 minute bins)

0:00 · Matt 5% · guest 95%0:00 · Matt 5% · guest 95%3:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%6:00 · Matt 0.4% · guest 99.6%6:00 · Matt 0.4% · guest 99.6%9:00 · Matt 0% · guest 100%9:00 · Matt 0% · guest 100%12:00 · Matt 0% · guest 100%12:00 · Matt 0% · guest 100%15:00 · Matt 0% · guest 100%15:00 · Matt 0% · guest 100%18:00 · Matt 14.9% · guest 85.1%18:00 · Matt 14.9% · guest 85.1%21:00 · Matt 100% · guest 0%21:00 · Matt 100% · guest 0%24:00 · Matt 73.5% · guest 26.5%24:00 · Matt 73.5% · guest 26.5%27:00 · Matt 15% · guest 85%27:00 · Matt 15% · guest 85%30:00 · Matt 4.9% · guest 95.1%30:00 · Matt 4.9% · guest 95.1%33:00 · Matt 20.5% · guest 79.5%33:00 · Matt 20.5% · guest 79.5%36:00 · Matt 89.5% · guest 10.5%36:00 · Matt 89.5% · guest 10.5%
Sharpest disagreement ▶ 32:14 Iron Fist Strategy for Resistant Agencies

Flowers describes his forceful approach to non-compliant city agencies, explaining that he uses an iron fist wrapped in a velvet cloak when departments resist data sharing.

 Hardest push from Matt ▶ 25:05 Host Asserts Session Control for Q&A

Host Matt Turck intervenes to end the presentation monologue and transition directly to audience Q&A, setting aside his own prepared questions.

 Biggest teaching moment ▶ 16:00 Exposing Flaws in 911 Response Metrics

Flowers educates the audience on how major cities miscalculate 911 response times by only measuring dispatch-to-arrival rather than call-ended-to-arrival.

 Matt holds his own ▶ 20:33 Host Summarizes Core Analytical Dilemma

Host Matt Turck succinctly synthesizes the central theme of the presentation, contrasting traditional agency focus group intuition with empirical data testing.
the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
Keynote on NYC Data Analytics Applications and Successes 0710 Mike Flowers delivers a keynote presentation detailing the creation and early wins of NYC's data analytics office, including fire risk triage and 911 system response time unification. The host acts purely as a quiet presenter/listener, making host expertise and pushback zero for this monologue format.
Tactical Data Deployment and Field Tools 0610 Flowers presents tactical data deployment tools for field inspectors and firefighters, highlighting real-time building intelligence before entry. The host does not intervene during this monologue segment.
Data Science Methodology vs. Ground Domain Expertise 1720 Data scientist Ben contrasts pure algorithmic data science with domain-informed field expertise, explaining how an outside firm's complex model failed while their domain-driven model delivered a 2.5x higher ROI. The host moderates smoothly without challenging the guest's findings.
Panel Q&A on Inter-City Models, Financial Data, and Continuity 1510 Flowers answers audience questions regarding inter-city analytics sharing, financial data transparency exceptions, and institutional continuity across mayoral administrations. The host facilitates audience questions neutrally.
Panel Q&A on Agency Engagement, Open Source, and Sandy Lessons 1520 Flowers and Ben explain how they handle reluctant city agencies using an iron fist and velvet cloak strategy and discuss open-sourcing geo-data tools on GitHub. The host enforces time limits and concludes the session.

Statements from this episode (10)

Assertion Not publicly verifiable
New York City mortgage fraud totals roughly $400 million annually
“Mortgage fraud is about four hundred million dollars a year in the city of New York.”
Mike Flowers Dec 5, 2013 ▶ 5:44
Assertion Contradicted
Total real estate turnover in New York City is roughly $1.25 trillion
“The total overall property turnover is about 1.25 trillion, right?”
Mike Flowers Dec 5, 2013 ▶ 5:48
Assertion Partly supported
New York City has approximately 650,000 one- or two-family residential structures
“There's about 650,001 or two family structures in the city of New York.”
Mike Flowers Dec 5, 2013 ▶ 12:27
Assertion Supported
Cities historically measured 911 response times from dispatch, not call termination
“The city of New York has never, and no other city in the United States, or, you know, some of our larger counterparts in Europe that we were able to check with, ah, everybody does not do it from that. They do it from this. The moment of dispatch to the arrival…”
Mike Flowers Dec 5, 2013 ▶ 16:05
Assertion Partly supported
NYC integrated six emergency systems to track end-to-end 911 response times
“So, what we were able to do was take these six different systems involved with nine one response, and we're talking about crime, fire medical, right, about 30 to 40,000 a day. And stitch them together. So that I now know from the moment we hang up, right, the …”
Mike Flowers Dec 5, 2013 ▶ 16:17
Assertion Not publicly verifiable
FDNY staff manually searched city websites while trucks rolled to active fires
“Every time a truck goes out to a fire what they do is they have five people basically searching city websites to find out what else the city knows about those locations.”
Mike Flowers Dec 5, 2013 ▶ 17:59
Assertion Contradicted
Mike Flowers says every major US city police department uses CompStat
“I don't know of a single police department in a large city in the United States that isn't going a ComStat model.”
Mike Flowers Dec 5, 2013 ▶ 27:13
Assertion Not checkable as stated
Mike Flowers notes very few US cities leverage cross-agency data
“The question is, are you leveraging what another agency knows on the map of delivering your widget? And the answer to that is I think it's a very, very small number.”
Mike Flowers Dec 5, 2013 ▶ 27:30
Prediction Held up
Mike Flowers predicts future NYC mayors must burn money to rebuild silos
“The data silos thing, that's busted. So somebody's literally going to have to throw money away to reverse that. Reverse the fact that the fire department knows what the buildings department knows, what the finance department knows, et cetera. So I don't see th…”
Mike Flowers Dec 5, 2013 ▶ 30:38
Disclosure
NYC secured a grant to release its geo-support codebase on GitHub
“We got a grant from The eponymous learning foundation. And we're going to use that to put the geo support in the, on GitHub in the hopes that people such as yourself will go out and come up with apps that will allow us to leverage what the citizenry is doing a…”
Mike Flowers Dec 5, 2013 ▶ 35:01
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