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Visualizing Global Risks 2013

Visualizing Global Risks 2013

A year ago we looked at Global Trends 2025, a 2008 report by the National Intelligence Commission. The 120 page document made surprisingly little use of data visualization, given the well-funded and otherwise very detailed report.

By contrast, at the recent World Economic Forum 2013 in Davos, the Risk Response Network published the eighth edition of its annual Global Risks 2013 report. Its focus on national resilience fits well into the “Resilient Dynamism” theme of this year’s WEF Davos. Here is a good 2 min synopsis of the Global Risks 2013 report.

We will look at the abundant use of data visualization in this work, which is published in print as an 80-page .pdf file. The report links back to the companion website, which offers lots of additional materials (such as videos) and a much more interactive experience (such as the Data Explorer). The website is a great example of the benefits of modern layout, with annotations, footnotes, references and figures broken out in a second column next to the main text.

RiskCategories

One of the main ways to understand risks is to quantify it in two dimensions, namely its likelihood and its impact, say on a scale from 1 (min) to 5 (max). Each risk can then be visualized by its position in the square spanned by those two dimensions. Often risk mitigation is prioritized by the product of these two factors. In other words, the further right and/or top a risk, the more important it becomes to prepare for or mitigate it.

This work is based on a comprehensive survey of more than 1000 experts worldwide on a range of 50 risks across 5 broad categories. Each of these categories is assigned a color, which is then used consistently throughout the report. Based on the survey results the report uses some basic visualizations, such as a list of the top 5 risks by likelihood and impact, respectively.

Source for all figures: World Economic Forum (except where noted otherwise)

Source for all figures: World Economic Forum (except where noted otherwise)

When comparing the position of a particular risk in the quadrant with the previous year(s), one can highlight the change. This is similar to what we have done with highlighting position changes in Gartner’s Magic Quadrant on Business Intelligence. Applied to this risk quadrant the report includes a picture like this for each of the five risk categories:

EconomicRisksChange

This vector field shows at a glance how many and which risks have grown by how much. The fact that a majority of the 50 risks show sizable moves to the top right is of course a big concern. Note that the graphic does not show the entire square from 1 through 5, just a sub-section, essentially the top-right quadrant.

On a more methodical note, I am not sure whether surveys are a very reliable instrument in identifying the actual risks, probably more the perception of risks. It is quite possible that some unknown risks – such as the unprecedented terrorist attacks in the US on 9/11 – outweigh the ones covered here. That said, the wisdom of crowds tends to be a good instrument at identifying the perception of known risks.

Note the “Severe income disparity” risk near the top-right, related to the phenomenon of economic inequality we have looked at in various posts on this Blog (Inequality and the World Economy or Underestimating Wealth Inequality).

A tabular form of showing the top 5 risks over the last seven consecutive years is given as well: (Click on chart for full-resolution image)

Top5RisksChanges

This format provides a feel for the dominance of risk categories (frequency of colors, such as impact of blue = economic risks) and for year over year changes (little change 2012 to 2013). The 2011 column on likelihood marks a bit of an outlier with four of five risks being green (= environmental) after four years without any green risk in the Top 5. I suspect that this was the result of the broad global media coverage after the April 2011 earthquake off the coast of Japan, with the resulting tsunami inflicting massive damage and loss of lives as well as the Fukushima nuclear reactor catastrophe. Again, this reinforces my belief that we are looking at perception of risk rather than actual risk.

Another aggregate visualization of the risk landscape comes in the form of a matrix of heat-maps indicating the distribution of survey responses.

SurveyResponseDistribution

The darker the color of the tile, the more often that particular likelihood/impact combination was chosen in the survey. There is a clear positive correlation between likelihood and impact as perceived by the majority of the experts in the survey. From the report:

Still it is interesting to observe how for some risks, particularly technological risks such as critical systems failure, the answers are more distributed than for others – chronic fiscal imbalances are a good example. It appears that there is less agreement among experts over the former and stronger consensus over the latter.

The report includes many more variations on this theme, such as scatterplots of risk perception by year, gender, age, region of residence etc. Another line of analysis concerns the center of gravity, i.e. the degree of systemic connectivity between risks within each category, as well as the movement of those centers year over year.

Another set of interesting visualizations comes from the connections between risks. From the report:

Top5Connections

Top10ConnectedRisks

Finally, the survey asked respondents to choose pairs of risks which they think are strongly interconnected. They were asked to pick a minimum of three and maximum of ten such connections.

Putting together all chosen paired connections from all respondents leads to the network diagram presented in Figure 37 – the Risk Interconnection Map. The diagram is constructed so that more connected risks are closer to the centre, while weakly connected risks are further out. The strength of the line depends on how many people had selected that particular combination.

529 different connections were identified by survey respondents out of the theoretical maximum of 1,225 combinations possible. The top selected combinations are shown in Figure 38.

It is also interesting to see which are the most connected risks (see Figure 39) and where the five centres of gravity are located in the network (see Figure 40).

One such center of gravity graph (for geopolitical risks) is shown here:RiskInterconnections

The Risk Interconnection Map puts it all together:

RiskInterconnectionMap

Such fairly complex graphs are more intuitively understood in an interactive format. This is where the online Data Explorer comes in. It is a very powerful instrument to better understand the risk landscape, risk interconnections, risk rankings and national resilience analysis. There are panels to filter, the graphs respond to mouse-overs with more detail and there are ample details to explain the ideas behind the graphs.

DataExplorer

There are many more aspects to this report, including the appendices with survey results, national resilience rankings, three global risk scenarios, five X-factor risks, etc. For our purposes here suffice it to say that the use of advanced data visualizations together with online exploration of the data set is a welcome evolution of such public reports. A decade ago no amount of money could have bought the kind of interactive report and analysis tools which are now available for free. The clarity of the risk landscape picture that’s emerging is exciting, although the landscape itself is rather concerning.

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Posted by on January 31, 2013 in Industrial, Socioeconomic

 

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Faceplant with Facebook?

With the Facebook IPO coming up this Friday there is a lot of attention around its business model and financials. I’m not an expert in this area, but my hunch is that a lot of people will lose a lot of money by chasing after Facebook shares. Why?

I think there are two types of answers. One from reasoning and one from intuition.

For reasoning one needs to look at a more technical assessment of the business model and financials. Some have written extensively about the comparative lack of innovation in Facebook’s business model and core product. Some have compared Facebook’s performance in advertising to Google – the estimates are that Google’s ad performance is 100x better than that of Facebook. Some have pointed out that many of Facebook’s core metrics such as visits/person, pages/visit or Click-Through-Rates have been declining for two years and go as far as calling this the Facebook ad scam. One can question the wisdom of the Instagram acquisition, buying a company with 12 employees and zero revenues for $1B. One can question the notion that the 28 year old founder will have 57% of the voting rights of the public company. One could look at stories about companies discontinuing their ad Facebook efforts such as the Forbes article about GM pulling a $10m account because they found it ineffective. The list goes on.

Here is a more positive leaning infographic from an article looking at “Facebook: Business Model, Hardware Patents and IPO“:

Analysis Infographic of pre-IPO Facebook (source: Gina Smith, anewdomain.net)

To value a startup at 100x last year’s income seems just extremely high – but then Amazon’s valuation is in similarly lofty territory. As for reasoning and predicting the financial success of Facebook’s IPO, people can cite numbers to justify their beliefs both ways. At the end of the day, it’s unpredictable and nobody can know for sure.

The other answer to why I am not buying into the hype is more intuitive and comes from my personal experience. Here is a little thought experiment as to how valuable a company is for your personal life: Imagine for a moment if the company with all its products and services would disappear overnight. How much of an impact would it have for you as an individual? If I think about companies like Apple, Google, Microsoft, or Amazon the impact for me would be huge. I use their products and services every day. Think about it:

No Apple = no iPhone, no iPad, no iTunes music on the iPod or via AppleTV on our home stereo. That would be a dramatic setback.

No Google = no Google search, no GMail, no YouTube, no Google maps, no Google Earth. Again, very significant impact for me personally. Not to mention the exciting research at Google in very different areas such as self-driving vehicles.

No Facebook = no problem (at least for me). I deactivated my own Facebook account months ago simply because it cost me a lot of time and I got very little value out of it. In fact, I got annoyed with compulsively looking at updates from mere acquaintances about mundane details of their lives. Why would I care? I finally got around to actually deleting my account, although Facebook makes that somewhat cumbersome (which probably inflates the account numbers somewhat).

I’m not saying Facebook isn’t valuable to some people. Having nearly 1B user accounts is very impressive. Hosting by far the largest photo collection on the planet is extraordinary. Facebook exploded because it satisfied our basic need of sharing, just like Google did with search, Amazon did with shopping or eBay did with selling. But the entry barrier to sharing is small (see LinkedIn, Twitter or Pinterest) and Facebook doesn’t seem to be particularly well positioned for mobile.

I strongly suspect that Facebook’s valuation is both initially inflated – the $50 per account estimate of early social networks doesn’t scale up with the demographics of the massive user base – as well as lately hyped up by greedy investors who sense an opportunity to make a quick buck. My hunch is that FB will trade below its IPO price within the first year, possibly well below. But then again, I have been surprised before…

I’m not buying the hype. What am I missing? Let me know what you think!

UPDATE 8/16/2012: Well, here we are after one quarter, and Facebook’s stock valuation hasn’t done so well. Look at the first 3 month chart of FB:

First 3 month of Facebook stock price (Screenshot of StockTouch on iPad)

What started as a $100b market valuation is now at $43b. One has to hand it to Mark Zuckerberg, he really extracted maximum value out of those shares. It turns out sitting on the sidelines was the right move for investors in this case.

 
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Posted by on May 16, 2012 in Financial, Socioeconomic

 

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Sankey Diagrams

Sankey Diagrams

Whenever you want to show the flow of a quantity (such as energy or money) through a network of nodes you can use Sankey diagrams:

“A Sankey diagram is a directional flow chart where the width of the streams is proportional to the quantity of flow, and where the flows can be combined, split and traced through a series of events or stages.”
(source: CHEMICAL ENGINEERING Blog)

One area where this can be applied very well is that of costing. By modeling the flow of cost through a company one can analyze the aggregated cost and thus determine the profitability of individual products, customers or channels. Using the principles of activity-based costing one can create a cost-assignment network linking cost pools or accounts (as tracked in the General Ledger) via the employees and their activities to the products and customers. Such a Cost Flow can then be visualized using a Sankey diagram:

Cost Flow from Accounts via Expenses and Activities to Products

The direction of flow (here from left to right) is indicated by the color assignment from nodes to its outflowing streams. Note also the intuitive notion of zero-loss assignment: For each node the sum of the in- and outflowing streams (= height of that node) remains the same. Hence all the cost is accounted for, nothing is lost. If you stacked all nodes on top of one another they would rise to the same height. (Random data for illustration purposes only.)

The above diagram was created in Mathematica using modified source code originally from Sam Calisch who had posted it in 2011 here. Sam also included a “SankeyNotes.pdf” document explaining the details of the algorithms encoded in the source, such as how to arrange the node lists and how to draw the streams.

I find these a perfect example of how a manual drawing can go a long ways to illustrate the ideas behind an algorithm, which makes it a lot easier to understand and reuse the source code. Thanks to Sam for this code and documentation. Sam by the way used the code to illustrate the efficiency of energy use (vs. waste) in Australia:

Energy Flow comparison between New South Wales and Australia (Sam Calisch)

Note the sub-flows within each stream to compare a part (New South Wales) against the whole (Australia).

Another interesting use of Sankey Diagrams has been published a few weeks ago on ProPublica about campaign finance flow. This is particularly useful as it is interactive (click on image to get to interactive version).

Tangled Web of Campaign Finance Flow

Note the campaigns in green and the Super-PACs in brown color. The data is sourced from FEC and the New York Times Campaign Finance API. Note that in the interactive version you can click on any source on the left or any destination on the right to see the outgoing and incoming streams.

Finance Flow From Obama-For-America

Finance Flow to American Express

Here are some more examples. Sankey diagrams are also used in Google Flow Analytics (called Event Flow, Goal Flow, Visitor Flow). I wouldn’t be surprised to see Sankey Diagrams make their way into modern data visualization tools such as Tableau or QlikView, perhaps even into Excel some day… Here are some Visio shapes and links to other resources.

 
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Posted by on May 14, 2012 in Financial, Industrial

 

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Quarterly Comparison: Apple, Microsoft, Google, Amazon

Quarterly Comparison: Apple, Microsoft, Google, Amazon

Last quarter we looked at the financials and underlying product & service portfolios of four of the biggest technology companies in the post “Side by Side: Apple, Microsoft, Google, Amazon“. With the recent reporting of results for Q1 2012 it is a good time to revisit this subject.

Comparison of Financials Q4 2011 and Q1 2012 for Apple, Microsoft, Google, and Amazon.

Market cap has grown roughly by 25% for both Apple and Amazon, whereas Microsoft and Google only added 5% or less. A sequential quarter comparison can be misleading due to seasonal changes, which impact different industries and business models in a different way. For example, Google’s ad revenue is somewhat less impacted by seasonal shopping than the other companies.

Sequential quarter comparison of financials

Apple and Microsoft seem to be impacted in a similar way by seasonal changes. For Amazon, which already has by far the lowest margin of all four companies, operating income decreased by 40% while it increased its headcount by 17%. This leads to much lower income per employee and with increased stock price to a doubling of its already very high P/E ratio. I’m not a stock market analyst, but Amazon’s P/E ratio of now near 200 seems extraordinarily high. By comparison, the other companies look downright cheap: Apple 8.8, Microsoft 10.5, Google 14.5

Horace Dediu from asymco.com has also revisited this topic in his post “Which is best: hardware, software, or services?“. What’s striking is that all three companies (except Amazon) now have operating margins between 30-40% – very high for such large businesses – with Apple taking the top near 40%. Over the last 5 years, Apple has doubled it’s margin (20% to 40%), whereas Microsoft (35-40%) and Google (30-35%) remained near their levels.

(Source: Asymco.com)

Long term the most important aspect of a business is not how big it has become, but how profitable it is. In that regard Amazon is the odd one out. Their operating income last quarter was about 1% of revenue. Amazon needs to move $100 worth of goods to earn $1. They employ 65,000 people and had revenue of $13.2b last quarter, yet only earned $130m during that time! Apple earns more money just with their iPad covers! Amazon’s strategy is to subsidize the initial Kindle Fire sale and hoping to make money on the additional purchases over the lifetime of the product. In light of these numbers, do you think Amazon has a future with it’s Kindle Fire tablet against the iPad?

But what really struck me about the extreme differences in profitability is this comparison of Apple and Microsoft product lines (source: @asymco twitter):

(source: @asymco twitter)

This shows what an impressive and sustained success the iPhone has been. And the iPad is on track to grow even faster. Horace Dediu guesses that Apple’s iPad will be a bigger profit generator than Windows in one quarter, and a bigger profit generator than Google (yes, all of Google) in three quarters. We will check on those predictions when the time comes…

 
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Posted by on May 2, 2012 in Financial, Industrial

 

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Side by Side: Apple, Microsoft, Google, Amazon

Side by Side: Apple, Microsoft, Google, Amazon

Ed Bott at ZDNet.com wrote a post with the title: Microsoft, Apple, and Google: where does the money come from? He looked at the quarterly reports of these companies (links to sources in the article) and displayed a pie-chart of the revenue mix for each of them. Inspired by that, I added a fourth company – Amazon (source: 10-K for 2011) – and aggregated those pie-charts into one graphic.

Revenue Mix for Apple, Microsoft, Google, and Amazon

All four are large consumer-oriented technology companies; like millions of customers, I use many of their products and services every day. They each operate with different businesses models:

  • Microsoft: Software
  • Apple: Hardware
  • Google: Advertising
  • Amazon: Retail

Yet as a consumer I rarely think about these differences. All of them use state-of-the-art technologies like cloud-computing and mobile devices to achieve integrated end-to-end experiences geared to increase revenues in personal computing (Microsoft), smart mobile devices (Apple), online search (Google) or shopping (Amazon). And arguably all of them derive major competitive advantage from their software, such as Apple’s iOS which introduced the touch interface.

Perhaps most surprising is Google’s almost singular reliance on advertising, which makes it a very different business model. They offer all their technology for free – from search to mapping to operating systems and social media – to grow and retain online attention as enabling condition for advertising revenue. For a business this big the near complete dependence on one source of revenue is unusual; perhaps its time for Google’s leadership to seriously consider a diversification strategy? Without it Google is arguably more prone to disruption (such as from Facebook) than the other companies. Speaking of disruption: Apple derives almost 3/4 of its revenue (73%) from iPhone and iPad, neither of which existed 5 years ago. As Ed Bott points out, those two products now drive an astonishing $33.5b revenue per quarter!

To compare the companies by their absolute numbers, here is a bar chart of market capitalization, revenue and profit: (all in billions of Dollars and for Q4 2011, market cap as of 2/3/12)

Market Cap, Revenue and Profit for Apple, Microsoft, Google, and Amazon

Market cap of these four companies combined is approaching $ 1 trillion. Much has been written about the differences in market valuations relative to revenue and most importantly profit. The markets undervalue Apple and overvalue Google and Amazon. Let’s compare these dimensions (and number of employees) in the following radar plot:

Relative business performance for Apple, Microsoft, Google, and Amazon

The plot shows the relative performance of all with the highest in each dimension normalized to 100%. Amazon shows by far the smallest profit in the last quarter. Given it’s retail nature, it’s profit margins have always been smaller; and CEO Jeff Bezos has long emphasized the strategy of investing in future growth at the expense of present profits. Microsoft continues to enjoy very solid profit margins in a large, well diversified business. Google has incredible talent and for now is the undisputed king of online advertising. But Apple leads in all three factors, and it achieves 2x Microsoft’s results with less than half the number of employees! Apple’s profit is 1.5 times that of the other three combined! And it makes more than 60% of the profit with less than 20% of the employees. In fact, Apple’s market capitalization is now higher than $10m per employee! It must feel pretty special to be one of them these days…

Postscript: On Feb-13 analyst Horace Dediu at Asymco.com published an article with time-series data for the above companies (except Amazon) over the last 18 quarters (since 2007). It shows the evolution over time as depicted in this chart:

Apple Microsoft Google - Revenue and Operating Income 2007-2011

The article is called “The World’s Biggest Startup“. It’s main point is this: Microsoft and Google both grew their businesses steadily, but did not change their type of business. Apple did some of that in its established business segments, but more importantly and disruptively it added new categories (iPhone and iPad) for dramatic growth. That’s what startups do. Just so happens that Apple – whose stock today for the first time hit $500 – is also the most highly capitalized company in the world (around $460B). If Apple is a startup now, what will they look like when they are fully established?

 
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Posted by on February 6, 2012 in Financial, Industrial

 

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Global Trends 2025

Global Trends 2025

If you like to do some big-picture thinking, here is a document put together by the National Intelligence Council and titled “Global Trends”. It is published every five years to analyze trends and forecast likely scenarios of worldwide development fifteen years into the future. The most recent is called “Global Trends 2025” and was published in November 2008. It’s a 120 page document which can be downloaded for free in PDF format here.

To get a feel for the content, here are the chapter headers:

  1. The Globalizing Economy
  2. The Demographics of Discord
  3. The New Players
  4. Scarcity in the Midst of Plenty?
  5. Growing Potential for Conflict
  6. Will the International System Be Up to the Challenges?
  7. Power-Sharing in a Multipolar World

From the NIC Global Trends 2025 project website:

Some of our preliminary assessments are highlighted below:

  • The whole international system—as constructed following WWII—will be revolutionized. Not only will new players—Brazil, Russia, India and China— have a seat at the international high table, they will bring new stakes and rules of the game.
  • The unprecedented transfer of wealth roughly from West to East now under way will continue for the foreseeable future.
  • Unprecedented economic growth, coupled with 1.5 billion more people, will put pressure on resources—particularly energy, food, and water—raising the specter of scarcities emerging as demand outstrips supply.
  • The potential for conflict will increase owing partly to political turbulence in parts of the greater Middle East.

As interesting as the topic may be, from a data visualization perspective the report is somewhat underwhelming. I counted just 5 maps and 5 charts in the entire document. The maps are interesting, such as the following on World Age Structure:

World Age Structure 2005

World Age Structure 2025 (Projected)

These maps show the different age of countries’ populations by geographical region. The Northern countries have less young people, and the aging trend is particularly strong for Eastern Europe and Japan. In 2025 almost all of the countries with very young population will be in Sub-Saharan Africa and the Arab Peninsula. Population growth will slow as a result; there will be approximately 8 billion people alive in 2025, 1 billion more than the 7 billion today.

In this day and age one is spoiled by interactive charts such as the Bubble-Charts of Gapminder’s Trendalyzer. Wouldn’t it be nice to have an interactive chart where you could set the Age intervals and perhaps filter in various ways (geographic regions, GDP, population, etc.) and then see the dynamic change of such colored world-maps over time? How much more insight would this convey about the changing demographics and relative sizes of age cohorts? Or perhaps display interactive population pyramids such as those found here by Jorge Camoes?

Another somewhat misguided ‘graphical angle’ are the slightly rotated graphics on the chapter headers. For example, Chapter 2 starts with this useful color-coded map of the Youth in countries of the Middle East. But why rotate it slightly and make the fonts less readable?

Youth in the Middle East (from Global Trends 2025 report)

I don’t want to be too critical; it’s just that reports put together with so much systematic research and focusing on long-range, international trends should employ more state-of-the-art visualizations, in particular interactive charts rather than just pages and pages of static text…

 
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Posted by on January 4, 2012 in Industrial, Socioeconomic

 

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Underestimating Wealth Inequality

Underestimating Wealth Inequality

What are people’s perceptions about estimated, desirable and actual levels of economic inequality? Behavioral economist Dan Ariely from Duke University and Michael Norton from Harvard Business School conducted a survey of ~5,500 respondents across the United States to find out. Their survey asked questions about wealth inequality (as compared to income inequality), also known as net worth, essentially the value of all things owned minus all things owed (assets minus debt).

Addendum 3/9/2013: A recently posted 6min video illustrating these findings went viral (4 million+ views). It is worth watching:

The authors published the paper here and Dan Ariely blogged about it here in Sep 2010. One of the striking results is summarized in this chart of the wealth distribution across five quintiles:

From their Legend:

The actual United States wealth distribution plotted against the estimated and ideal distributions across all respondents. Because of their small percentage share of total wealth, both the ‘‘4th 20%’’ value (0.2%) and the ‘‘Bottom 20%’’ value (0.1%) are not visible in the ‘‘Actual’’ distribution.

It turned out that most respondents described a fairly equal distribution as the ideal – something similar to the wealth distribution in a country like Sweden. They estimated – correctly – that the U.S. has higher levels of wealth inequality. However, they nevertheless grossly underestimated the actual inequality, which is far higher still. Especially the bottom two quintiles are almost non-existent in the actual distribution. There was much more consensus than disagreement across groups from different sides of the political spectrum about this. From the current policy debates one would not have expected that. They go on to ask the question:

Given the consensus among disparate groups on the gap between an ideal distribution of wealth and the actual level of wealth inequality, why are more Americans, especially those with low income, not advocating for greater redistribution of wealth?

In the last chapter of their paper the authors offer several explanations of this phenomenon. One of them is the observation that the apparent drastic under-estimation of the degree of inequality seems to reveal a lack of awareness of the size of the gap. This is something that Data Visualization and interactive charts can help address. For example, Catherine Mulbrandon’s Blog Visualizing Economics does a great job in that regard.

The authors go on to look at other aspects from the perspective of psychology and behavioral economics. While fascinating in its own right, this excursion is beyond the scope of my Data Visualization Blog. They conclude their paper with general observations

…suggesting that even given increased awareness of the gap between ideal and actual wealth distributions, Americans may remain unlikely to advocate for policies that would narrow this gap.

 
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Posted by on December 12, 2011 in Socioeconomic

 

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