Ask Siri to

Roll the dice

and she’ll roll two dice for you, reporting

Rolling… it’s two and six.

Or, if you prefer a coin toss, ask her to

Flip a coin

to which she might respond

It’s tails.

Good luck.

Researchers compared predictions made about the overall outcome (win/draw/lose) of sporting events with predictions made about the actual scoreline. Scoreline predictions are also overall outcome predictions—e.g. if the score is Manchester United 3, Arsenal 1, then that is a win for Manchester United. Hence, scoreline predictions are a “more detailed” approach to predicting the overall outcome.

Analysis of 19 billion commercial bets suggested that people do worse when they attempt to predict the scoreline. These findings were confirmed in laboratory experiments.

The paper offers the insight that, in studying the minutiae, we may miss factors that have a much greater impact—i.e. we miss the forest for the trees.

So, less thinking = better results. Great.

It currently contains data on over 250 million events, stretching back to 1979—and the intention is to extend that all the way to 1800.

Events are geotagged to city level and contain information on the type of confrontation, the parties involved and the action that occurred. The types of confrontation recorded are:

• material conflict
• material cooperation
• verbal conflict
• verbal cooperation

Events like bombings and riots are currently captured, drawing on traditional news sources, and the intention is to expand coverage to include, for example, financial events.

Founder Kalev Leetaru says

The goal of the project is to create a free and open global resource for the quantitative study and mapping of global conflict and cooperation and thus the data is being made available completely free and open for any use.

The screencast makes extensive use of Decision Workshops’ proprietary Microsoft Excel-based modeling tool. More information on this tool can be obtained by contacting Decision Workshops directly.

Those interested in modeling their own confrontations may wish to consider our Confronteer iPhone app.

The Open Knowledge Foundation has officially recognized this through its Frictionless Data initiative. They propose:

• simple formats (e.g. CSV, JSON)
• simple tooling—i.e. the ability to get data in and out of standard software packages, such as Excel, R and Hadoop.
• bootstrapping the system with essential data (e.g. countries, postal codes)

It’s early days, but the direction is encouraging.

I was interested to see books like “Blink” (instinctive decision-making) and “Thinking Fast and Slow” (behavioral decision-making) on the list. Maybe “Nudge” should be there too.

Also of note is General Sir Rupert Smith’s book “The Utility of Force”—Smith is a proponent of confrontation analysis.

However, in general, the list has a bit of an “MBA” feel to it. There’s lots of analysis, but very few original sources. I’d have expected a lot more texts that originate in different (non-Western) cultures. Even if one believes, as suggested in “The Dictator’s Handbook” (another omission), that all leaders are driven by their political survival, arguments are still cloaked in cultural history.

Still, these lists provoke debate. And that’s a good thing.

James Kwak, in an article where he describes spreadsheet modeling problems at JPMorgan, said (of Excel)

Because it’s so easy to use, the creation of even important spreadsheets is not restricted to people who understand programming and do it in a methodical, well documented way.

For more spreadsheet disasters, have a look at the recent Fortune article titled “Damn Excel! How the ‘most important software application of all time’ is ruining the world”.

We’ve written about this before—and, sadly, probably will again.

Every organisation that’s abusing spreadsheets needs to clean house. Now.

What are the problems?

Open data is a bit like a hammer looking for a nail. There needs to be greater transparency about the problems facing government. Politicians are incentivized to present everything as rosy. This makes it more difficult for citizen developers to focus their resources for the greater good.

So, we need open problems—a list of what governments think is most pressing.

We need the right data

Once we’ve identified the problems, we need the ability to source the data that will help solve them. This isn’t necessarily the data that is already published. There needs to be a feedback loop where governments focus on publishing the data that will have the most impact—not just the data that they feel happy about publishing.

Real-time data feeds are required

Publishing data annually is imposing an archaic model on a new technology. Data could, and should, be published as it is collected. Everyone knows that the rate of change in society is accelerating. Without real-time data we’re, at best, solving last year’s problems.

So, open data is great. Let’s just try and get it right.

The book explains how compelling stories are comprised of structured elements. One thing that struck me is how closely these structures and elements are aligned with confrontation analysis.

Page 93 quotes literary agent Peter Rubie as saying that a good scene will:

• cause a subsequent scene to occur, creating cause and effect
• be driven by the main character’s needs and wants
• explore various ploys by the character to get his own way
• include action that changes a character’s position, relative to the end of the story

This general theme, of a protagonist who must overcome a series of challenges in pursuit of a goal, forms the “arc” of every great narrative.

This is exactly how we tackle problems using confrontation analysis.

Parties (protagonists) have positions (goals) that they attempt to advance by overcoming a series of dilemmas (challenges) through the exchange of (kinetic and non-kinetic) messages (action). Resolutions to one confrontation set the scene for the next as the parties struggle to achieve their goals.

Compelling narrative needs dilemmas.

It appears that confrontation analysis has potential as a design tool for creating compelling narrative. Strategic narratives, used to help us understand real-world issues and organizations, might be enhanced through a confrontation analysis treatment.

Without a formal process, there is a danger that a narrative will fail to draw out the essential elements. And, if the narrative is not compelling, those reading it will not be drawn in, making it difficult for them to extrapolate the story into the future—essential if the narrative is to influence what comes next.

Without a formal process underpinning the development of a narrative there is a danger that it’ll be a hard-nosed, “just the facts, ma’am”, news report—safely unbiased, but hardly absorbing. Strategic narrative, like all narrative nonfiction, needs to draw the reader in.

There is also much the confrontation analysis practitioner can learn from Storycraft—for example, when writing up an analysis in a way that brings it to life. Deft use of verbs and dialogue creates a sense of movement…action…that propels your narrative along. As columnist Jimmy Breslin said

News is a verb

The book also reminds us of the importance of developing character and scene—elements that are important when trying to understand a confrontation, but that are not formally addressed by the confrontation analysis process.

Read Storycraft. I promise you’ll learn something.

However what struck me most in the article was a discussion of problems with an early, high profile agile project—Chrysler’s C3 payroll project.

The author argues that this project failed because it attempted to develop a comprehensive replacement for Chrysler’s existing system. While this system was perceived to have many problems, there were also many things about it that worked. So, a wholesale replacement was an ambitious undertaking.

What would have been better, it is suggested, would have been to focus on just replacing the parts of the system that were causing the most pain—sort of replacing the entire system one hated piece at a time.

It seems to me that this is very similar to the idea of designing larger systems as ecosystems of simple apps. Processes can be broken down into simpler tasks and each task can be solved using a loosely-coupled, highly focused app (see the article on “Mobile First”, for example).

Each app has relatively clear, well-defined requirements, making it easier to estimate. Granted, it may need to provide a variety of hooks for communicating with other apps in the ecosystem, but these can be added as required. Also, the tight focus of the app makes it easier to provide an outstanding user experience.

And, if the process changes, an app or two can be dropped and the ecosystem reconfigured—the “app swarm” can recover.

The “app swarm” concept is already working. It’s effectively how you use your smartphone—jumping comfortably from app to app as you go about your day.

Maybe it’s time you invited the “app swarm” into your organization…