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Jan 16, 2014 · 29m · mad

Joe Reisinger, Premise // Data Driven NYC 21 // Dec 2013 (Hosted by FirstMark Capital)

Joe Reisinger · 23m spoken Matt Turck · 45s spoken Charlie Ferrari · 24s spoken Margaret Oest · 14s spoken
0:00 / 0:00
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions

In this Data Driven NYC talk, Premise CTO Joe Reisinger discusses the critical limitations of traditional economic statistics and unrefined Big Data, introducing Premise's crowdsourced smartphone network for tracking real-time global inflation and macroeconomic trends.

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 2.8% of the talking time here. How this is scored →

Matt as informed peer 0.8 Guest teaching 2.4 Guest disagreement 1.2 Matt pushing back 0.6
05100:0010:0020:002:04–7:10 · Matt as informed peer 0/10 Economic Theory of Surge Pricing and Jungle Markets Joe delivers a presentation monologue applying graduate microeconomic theory and jungle market models to Uber surge pricing. The host does not speak during this segment.7:10–11:13 · Matt as informed peer 0/10 Macroeconomic Data Exhaust and Modern Statistical Failures Joe outlines the failures of legacy economic statistics and public food crisis tracking in a monologue format without host engagement.11:13–13:58 · Matt as informed peer 0/10 Premise: Real-Time Global Network for Inflation and Price Tracking Joe explains Premise's crowdsourced Android mobile network for inflation and CPI tracking in a continuous monologue without host participation.13:58–19:33 · Matt as informed peer 0/10 Adaptive Sampling Design and Avoiding Big Data Pitfalls Joe details adaptive sampling design and big data biases like the Bieber flu trend anomaly in a monologue without host interaction.19:33–29:35 · Matt as informed peer 4/10 Q&A on Government Data Sensitivity, Tech Stack, and Commercial Value Host Matt Turck joins for Q&A, asking about Premise's former web crawling feature and teasing their tech stack, leading to detailed clarifications from Joe.2:04–7:10 · Guest teaching 2/10 Economic Theory of Surge Pricing and Jungle Markets Joe delivers a presentation monologue applying graduate microeconomic theory and jungle market models to Uber surge pricing. The host does not speak during this segment.7:10–11:13 · Guest teaching 2/10 Macroeconomic Data Exhaust and Modern Statistical Failures Joe outlines the failures of legacy economic statistics and public food crisis tracking in a monologue format without host engagement.11:13–13:58 · Guest teaching 2/10 Premise: Real-Time Global Network for Inflation and Price Tracking Joe explains Premise's crowdsourced Android mobile network for inflation and CPI tracking in a continuous monologue without host participation.13:58–19:33 · Guest teaching 3/10 Adaptive Sampling Design and Avoiding Big Data Pitfalls Joe details adaptive sampling design and big data biases like the Bieber flu trend anomaly in a monologue without host interaction.19:33–29:35 · Guest teaching 3/10 Q&A on Government Data Sensitivity, Tech Stack, and Commercial Value Host Matt Turck joins for Q&A, asking about Premise's former web crawling feature and teasing their tech stack, leading to detailed clarifications from Joe.2:04–7:10 · Guest disagreement 1/10 Economic Theory of Surge Pricing and Jungle Markets Joe delivers a presentation monologue applying graduate microeconomic theory and jungle market models to Uber surge pricing. The host does not speak during this segment.7:10–11:13 · Guest disagreement 1/10 Macroeconomic Data Exhaust and Modern Statistical Failures Joe outlines the failures of legacy economic statistics and public food crisis tracking in a monologue format without host engagement.11:13–13:58 · Guest disagreement 1/10 Premise: Real-Time Global Network for Inflation and Price Tracking Joe explains Premise's crowdsourced Android mobile network for inflation and CPI tracking in a continuous monologue without host participation.13:58–19:33 · Guest disagreement 1/10 Adaptive Sampling Design and Avoiding Big Data Pitfalls Joe details adaptive sampling design and big data biases like the Bieber flu trend anomaly in a monologue without host interaction.19:33–29:35 · Guest disagreement 2/10 Q&A on Government Data Sensitivity, Tech Stack, and Commercial Value Host Matt Turck joins for Q&A, asking about Premise's former web crawling feature and teasing their tech stack, leading to detailed clarifications from Joe.2:04–7:10 · Matt pushing back 0/10 Economic Theory of Surge Pricing and Jungle Markets Joe delivers a presentation monologue applying graduate microeconomic theory and jungle market models to Uber surge pricing. The host does not speak during this segment.7:10–11:13 · Matt pushing back 0/10 Macroeconomic Data Exhaust and Modern Statistical Failures Joe outlines the failures of legacy economic statistics and public food crisis tracking in a monologue format without host engagement.11:13–13:58 · Matt pushing back 0/10 Premise: Real-Time Global Network for Inflation and Price Tracking Joe explains Premise's crowdsourced Android mobile network for inflation and CPI tracking in a continuous monologue without host participation.13:58–19:33 · Matt pushing back 0/10 Adaptive Sampling Design and Avoiding Big Data Pitfalls Joe details adaptive sampling design and big data biases like the Bieber flu trend anomaly in a monologue without host interaction.19:33–29:35 · Matt pushing back 3/10 Q&A on Government Data Sensitivity, Tech Stack, and Commercial Value Host Matt Turck joins for Q&A, asking about Premise's former web crawling feature and teasing their tech stack, leading to detailed clarifications from Joe.

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

0:00 · Matt 11.7% · guest 88.3%0:00 · Matt 11.7% · guest 88.3%3:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%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 0% · guest 100%18:00 · Matt 0% · guest 100%21:00 · Matt 12.1% · guest 87.9%21:00 · Matt 12.1% · guest 87.9%24:00 · Matt 2.8% · guest 97.2%24:00 · Matt 2.8% · guest 97.2%27:00 · Matt 1.9% · guest 98.1%27:00 · Matt 1.9% · guest 98.1%
Sharpest disagreement ▶ 22:05 Rejecting online price crawling accuracy

Joe firmly rejects web crawling as a reliable primary price index source, pointing out the severe demographic bias and price inelasticity of online shoppers in developing nations.

 Hardest push from Matt ▶ 21:26 Host probing missing web crawling component

Matt Turck challenges an omission in Joe's presentation, directly asking why web crawling was not highlighted despite being part of Premise's original pitch.

 Biggest teaching moment ▶ 15:10 Explaining sampling pitfalls through Bieber fever

Joe educates the audience on sampling design flaws by demonstrating how uncalibrated social media data creates spurious correlations between Justin Bieber concerts and flu trends.

 Matt holds his own ▶ 21:26 Host recalling Premise's dual-data strategy

Matt Turck demonstrates strong prior knowledge of Premise's tech architecture by remembering their original dual strategy of combining human field networks with automated web crawling.
the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
Economic Theory of Surge Pricing and Jungle Markets 0210 Joe delivers a presentation monologue applying graduate microeconomic theory and jungle market models to Uber surge pricing. The host does not speak during this segment.
Macroeconomic Data Exhaust and Modern Statistical Failures 0210 Joe outlines the failures of legacy economic statistics and public food crisis tracking in a monologue format without host engagement.
Premise: Real-Time Global Network for Inflation and Price Tracking 0210 Joe explains Premise's crowdsourced Android mobile network for inflation and CPI tracking in a continuous monologue without host participation.
Adaptive Sampling Design and Avoiding Big Data Pitfalls 0310 Joe details adaptive sampling design and big data biases like the Bieber flu trend anomaly in a monologue without host interaction.
Q&A on Government Data Sensitivity, Tech Stack, and Commercial Value 4323 Host Matt Turck joins for Q&A, asking about Premise's former web crawling feature and teasing their tech stack, leading to detailed clarifications from Joe.

Statements from this episode (7)

Assertion Partly supported
Foreign governments fabricate economic stats to guide macroeconomic policy
“You get countries that just straight up, you know, lie about economic stats, right? They make they make macroeconomic decisions based on complete fabrications about the price of goods in their countries, right?”
Joe Reisinger Jan 16, 2014 ▶ 9:26
Assertion Supported
University of London researchers link food price spikes to civil unrest
“There's some researchers at the University of London kind of did this really cool study on the incidents of violence and then the correlation between that and, like, food price spikes, and they found, like, you know, pretty significant correlation there, espec…”
Joe Reisinger Jan 16, 2014 ▶ 10:50
Assertion Contradicted
The Bureau of Labor Statistics spends $250M annually collecting price data
“Two hundred fifty million dollars a year, it takes the BLS to collect this data”
Joe Reisinger Jan 16, 2014 ▶ 13:13
Insight
Small, carefully structured data samples outperform large, sloppy data sets
“You're better off with small, carefully constructed, structured sample, rather than a large, sloppy sample.”
Joe Reisinger Jan 16, 2014 ▶ 14:14
Assertion Supported
Indian onion prices spiked 300 percent over a two-month period
“Onions in India have gone up, like, 300% in the last Couple of months.”
Joe Reisinger Jan 16, 2014 ▶ 18:47
Assertion Supported
The Reserve Bank of India changed interest rates over soaring onion prices
“The RBI actually went and changed interest rates because onion prices did this.”
Joe Reisinger Jan 16, 2014 ▶ 19:03
Disclosure
Premise opted for MySQL over NoSQL for its database infrastructure
“We use MySQL, for example. We're not a big NoSQL shop.”
Joe Reisinger Jan 16, 2014 ▶ 24:50
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