Category: Analysis

Cognitive Biases: Three Common Types Illustrated


This post is by Omri Wallach from Visual Capitalist


In a world of information overload, we can fall victim to all sorts of cognitive biases. Since they can lead us to generate false conclusions, it’s particularly important to understand what these biases are and how they work, as the consequences can become quite drastic.

Confirmation bias, sampling bias, and brilliance bias are three examples that can affect our ability to critically engage with information. Jono Hey of Sketchplanations walks us through these cognitive bias examples, to help us better understand how they influence our day-to-day lives.

Confirmation Bias

Cognitive Bias Examples - Confirmation

One of the most-commonly encountered and understood, you’re likely to have already heard about confirmation bias. This cognitive bias affects the way we test and evaluate hypotheses every day.

In simple terms, confirmation bias is the tendency to seek out or interpret evidence in such a way that supports our own strongly-held beliefs or expectations. This means that, given access to the same set of data and information, different people can come to wildly differing conclusions.

Feeding into confirmation bias can lead us to make ill-informed choices or even reinforce negative stereotypes. For this reason, it is important to remember to seek out information that both confirms and contradicts your presumptions about a certain topic.

Sampling Bias

Cognitive Bias Examples - Sampling

Sampling bias is a kind of bias that allows us to come to faulty conclusions based on inaccurate sample groups or data. Generally, the cause of sample bias is in poor study design and data collection.

When polling individuals for survey (Read more...)

Here are 15 Common Data Fallacies to Avoid


This post is by Jeff Desjardins from Visual Capitalist


In today’s tech-driven economy, data is essential for gaining new insights, making decisions, and building products.

In fact, there is so much data out there, that the quantity of it is doubling every two years⁠—and by 2025, there will be 175,000 exabytes of data in existence.

This is an unprecedented figure, and it’s hard to put into perspective. To give you some sense, a single exabyte is equal to 1,000,000,000 GB of data, and five exabytes has been said to be roughly equal to “all of the words ever spoken by mankind”.

Common Fallacies With Data

As you can imagine, digging through all of this data can be quite the challenge.

Data comes in many different forms and not all of them are easy to analyze. As a result, it is tempting to take shortcuts with data, or to try and fit the incoming data we receive into our pre-conceived notions of how things ought to be.

Today’s infographic comes to us from Geckoboard and it shows the common mistakes that people make in analyzing data. We’ve reformatted their PDF to fit here.

15 Common Data Fallacies

Here are 15 Common Data Fallacies to Avoid

How do we avoid painting a bullseye around the arrow, so that we can interpret the meaning of data in a logical, consistent, and methodological way?

The key is to understand common mistakes that people make with data, and why these errors skew our interpretations.

Examples of Fallacies

Here are four examples of fallacies, and why each is considered a faux-pas by data (Read more...)

U.S. Venture Deal Activity during the COVID-19 Pandemic


This post is by Ian Hathaway from Blog - Ian Hathaway


Last month, I published an analysis of venture deal activity in the United States during the COVID-19 pandemic, which demonstrated that despite early warnings of an impending collapse, the pace of venture deal activity in the first half of 2020 was more or less on par with 2019. I concluded that many early observers failed to appreciate the ability of venture capitalists to adjust to a virtual environment and some analysts undercounted real-time deal activity by failing to account for the systematic reporting lags in venture capital databases—as a result, they hastily drew conclusions that have not withstood the test of time. I demonstrated that with a few small adjustments, the real-time data pointed to a venture economy that wouldn’t miss a beat this year.

We now have fresh data to extend that analysis. It shows that after a slight dip in the second quarter, venture deal activity (adjusted for the systemic data lags) rebounded in the third quarter to a level that was about the same as the first quarter. In fact, through the first three quarters of the year, 2020 is on pace to be the most active year for venture deals since the Dotcom era peak in 2000.

To demonstrate, I’ll present quarterly data on venture deal activity from the PitchBook-NVCA Venture Monitor (Q1-2016 - Q3-2020). The data are tabulated as a snapshot of the PitchBook database on the final day of the quarter, aggregated along dimensions of stage, sector, and others. As a dynamic database, new (Read more...)

U.S. Venture Deal Activity during the COVID-19 Pandemic


This post is by Ian Hathaway from Blog - Ian Hathaway


Last month, I published an analysis of venture deal activity in the United States during the COVID-19 pandemic, which demonstrated that despite early warnings of an impending collapse, the pace of venture deal activity in the first half of 2020 was more or less on par with 2019. I concluded that many early observers failed to appreciate the ability of venture capitalists to adjust to a virtual environment and some analysts undercounted real-time deal activity by failing to account for the systematic reporting lags in venture capital databases—as a result, they hastily drew conclusions that have not withstood the test of time. I demonstrated that with a few small adjustments, the real-time data pointed to a venture economy that wouldn’t miss a beat this year.

We now have fresh data to extend that analysis. It shows that after a slight dip in the second quarter, venture deal activity (adjusted for the systemic data lags) rebounded in the third quarter to a level that was about the same as the first quarter. In fact, through the first three quarters of the year, 2020 is on pace to be the most active year for venture deals since the Dotcom era peak in 2000.

To demonstrate, I’ll present quarterly data on venture deal activity from the PitchBook-NVCA Venture Monitor (Q1-2016 - Q3-2020). The data are tabulated as a snapshot of the PitchBook database on the final day of the quarter, aggregated along dimensions of stage, sector, and others. As a dynamic database, new (Read more...)

The Geographic Concentration of Venture Capital(ists)


This post is by Ian Hathaway from Blog - Ian Hathaway


Last week, The New York Times published an article arguing that a “wave of venture capitalists is heading to quieter, less-expensive locales, where they are helping fund start-ups.” The article supported this claim by pointing to three venture capitalists who left Silicon Valley and launched funds in other places. One of them, Mark Kvamme, left Sequoia Capital to found Drive Capital in Columbus, Ohio; but that was back in 2013.

I don’t doubt that some venture capitalists have left The Valley to start funds elsewhere. However, The Times is massively overselling the reality. It is already well-advertised that venture-backed startups (the recipients of venture capital) are highly concentrated by geography. However, venture capitalists (the ones investing in startups) are concentrated by geography even more. Let’s take a look at the data.

The chart below illustrates the geographic concentration of venture capitalists along four dimensions: firm counts, active portfolio companies, assets under management (value of portfolios), and dry powder (venture capital available to be deployed). I aggregated the four measures by U.S. metropolitan area according to each active venture capital firm’s headquarters location. The data are presented as a share of the U.S. total.

fig1.png

To no surprise, the San Francisco Bay Area (including the San Francisco and San Jose metropolitan areas) dominates: 28 percent of active venture capital firms in the United States are headquartered in this region, yet 42 percent of active portfolio companies, 55 percent of portfolio company value held, and 56 percent of venture capital available to (Read more...)

The Geographic Concentration of Venture Capital(ists)


This post is by Ian Hathaway from Blog - Ian Hathaway


Last week, The New York Times published an article arguing that a “wave of venture capitalists is heading to quieter, less-expensive locales, where they are helping fund start-ups.” The article supported this claim by pointing to three venture capitalists who left Silicon Valley and launched funds in other places. One of them, Mark Kvamme, left Sequoia Capital to found Drive Capital in Columbus, Ohio; but that was back in 2013.

I don’t doubt that some venture capitalists have left The Valley to start funds elsewhere. However, The Times is massively overselling the reality. It is already well-advertised that venture-backed startups (the recipients of venture capital) are highly concentrated by geography. However, venture capitalists (the ones investing in startups) are concentrated by geography even more. Let’s take a look at the data.

The chart below illustrates the geographic concentration of venture capitalists along four dimensions: firm counts, active portfolio companies, assets under management (value of portfolios), and dry powder (venture capital available to be deployed). I aggregated the four measures by U.S. metropolitan area according to each active venture capital firm’s headquarters location. The data are presented as a share of the U.S. total.

fig1.png

To no surprise, the San Francisco Bay Area (including the San Francisco and San Jose metropolitan areas) dominates: 28 percent of active venture capital firms in the United States are headquartered in this region, yet 42 percent of active portfolio companies, 55 percent of portfolio company value held, and 56 percent of venture capital available to (Read more...)

Europe’s Venture-Backed IPOs and American Exchanges


This post is by Ian Hathaway from Blog - Ian Hathaway


Last month, my friend Nicolas Colin, a Director at The Family, described Europe’s tech IPOs as “boring” in a newsletter. Among other points, Colin argues the need for a deeper ecosystem that links Europe’s entrepreneurs with capital markets. Large IPOs are a big part of this:

We may have IPOs of companies with a European footprint such as Spotify and Farfetch—and the resulting liquidity. But when a European company goes public in the US we miss out on the positive feedback loop that nurtures an ecosystem of investment bankers, analysts, and institutional investors, which in turn will help more European companies go public. What’s more, those IPOs in the US are dependent on the ups and downs of the (partially uncorrelated) US IPO market—and that’s a problem. Nothing like the WeWork debacle has happened here in Europe, but now our tech companies should shelve their IPOs because Adam Neumann was a fraud and SoftBank was negligent in its due diligence? What does it even have to do with us?

A debate over the veracity of Colin’s claim spilled into social media, which focused more so on what one considers “boring” than anything else. Word choice aside, I presume that by “boring” Colin meant “small.” On that, he has a point. In both a game of averages and outliers, many of Europe’s most valuable startups have in fact looked to American exchanges for public listings.

I analyzed data from PitchBook on European venture-backed companies that had an IPO (Read more...)

Europe’s Venture-Backed IPOs and American Exchanges


This post is by Ian Hathaway from Blog - Ian Hathaway


Last month, my friend Nicolas Colin, a Director at The Family, described Europe’s tech IPOs as “boring” in a newsletter. Among other points, Colin argues the need for a deeper ecosystem that links Europe’s entrepreneurs with capital markets. Large IPOs are a big part of this:

We may have IPOs of companies with a European footprint such as Spotify and Farfetch—and the resulting liquidity. But when a European company goes public in the US we miss out on the positive feedback loop that nurtures an ecosystem of investment bankers, analysts, and institutional investors, which in turn will help more European companies go public. What’s more, those IPOs in the US are dependent on the ups and downs of the (partially uncorrelated) US IPO market—and that’s a problem. Nothing like the WeWork debacle has happened here in Europe, but now our tech companies should shelve their IPOs because Adam Neumann was a fraud and SoftBank was negligent in its due diligence? What does it even have to do with us?

A debate over the veracity of Colin’s claim spilled into social media, which focused more so on what one considers “boring” than anything else. Word choice aside, I presume that by “boring” Colin meant “small.” On that, he has a point. In both a game of averages and outliers, many of Europe’s most valuable startups have in fact looked to American exchanges for public listings.

I analyzed data from PitchBook on European venture-backed companies that had an IPO (Read more...)

Hidden First Rounds


This post is by Ian Hathaway from Blog - Ian Hathaway


One of the drawbacks of venture capital databases is that they are dynamic. Information trickles in, often with significant time lags. This is especially true at the earliest stages, where rounds are often unannounced and many startups are too small for anyone to notice. It’s a structural challenge that I’m not sure will ever be fully resolved.

The underreporting and time lags associated with very early deals has become further compounded in recent years. Many startups in Silicon Valley and other leading startup hubs have increasingly relied on unpriced rounds (SAFEs or convertible notes) for their first or even second rounds of financing. Because these rounds are unpriced, they don’t appear in a company’s cap table until after it has raised a priced round later (and further, announced the deal—see above).

Combined, there are structural and cyclical reasons that the underreporting of very early venture rounds is especially acute now and fraught with severe reporting delays. This matters because people want to understand the market trends in near real time.

To test how much of a problem this has become, I grabbed data on first financings from an analysis I did last year and compared them to first financings from a data pull today. The chart below shows the number of first financings in US companies between 2005 and 2017, as reported 14 months ago in August 2018 (light bars) and as reported today (dark bars, residual). The green line shows the percentage increase in reported deals between these (Read more...)

Hidden First Rounds


This post is by Ian Hathaway from Blog - Ian Hathaway


One of the drawbacks of venture capital databases is that they are dynamic. Information trickles in, often with significant time lags. This is especially true at the earliest stages, where rounds are often unannounced and many startups are too small for anyone to notice. It’s a structural challenge that I’m not sure will ever be fully resolved.

The underreporting and time lags associated with very early deals has become further compounded in recent years. Many startups in Silicon Valley and other leading startup hubs have increasingly relied on unpriced rounds (SAFEs or convertible notes) for their first or even second rounds of financing. Because these rounds are unpriced, they don’t appear in a company’s cap table until after it has raised a priced round later (and further, announced the deal—see above).

Combined, there are structural and cyclical reasons that the underreporting of very early venture rounds is especially acute now and fraught with severe reporting delays. This matters because people want to understand the market trends in near real time.

To test how much of a problem this has become, I grabbed data on first financings from an analysis I did last year and compared them to first financings from a data pull today. The chart below shows the number of first financings in US companies between 2005 and 2017, as reported 14 months ago in August 2018 (light bars) and as reported today (dark bars, residual). The green line shows the percentage increase in reported deals between these (Read more...)