Tag Archives: election

Election 2008: Struggle Between Tradition and Innovation

Today is Monday, November 3rd. Election Day, when the U.S. picks its 44th President, is less than 24 hours away. And as of Saturday night, just 72 hours before the polls close, 27 MILLION early votes and absentee ballots had already been placed. This represents almost 13% of the total population that’s eligible to vote this year, and 22% of all the people who voted in 2004. (The numbers are from Michael McDonald’s dataset; he is an associate professor specializing in voting behaviors. The VEP column in his table represents the total number of eligible voters over 18 and not in prison, on probation or on parole. )

Remember, long ago (or maybe more recently) in statistics class, when you learned that you could learn a lot about the properties of a population by taking a random sample? Having approximately 20% of the vote already in from a sample expected to be between 120 and 150 million is extremely significant – remember, these are actual votes, and not someone’s report of what they may or may not vote “for real”. Assuming that systematic errors have not played a large part in early voting behavior, the winner is already determined, and we just don’t know it yet.

“We go around in a circle and suppose, but the answer lies in the middle and knows.” –Robert Frost

However, ignoring systematics is indeed a significant assumption, one that’s discussed by Peter Norvig, Director of Research at Google, in his excellent explanation of the accuracy of polls. Which is why the campaigns are rightly pushing EVERYONE to get out there and vote – to mitigate the impact of systematic errors. (After all, you don’t want to stop voting if the other side keeps voting.) So if you are reading this and you haven’t voted yet, DO IT! Go vote!

I see three potential scenarios:

  • Breakthrough: the decision has already been made, is accurately reflected in the actual sample of early votes, and the votes placed on Tuesday won’t change the pattern at all. The additional votes amount to nothing (other than beating down or insuring against systematic error).
  • Breakdown: a flood of voters overwhelm the capacity of the voting stations, the voting machines just can’t handle it, and the polls close before everyone can get through the door and get an error-free ballot submitted. I think there might be social unrest if this is the case.
  • Breakout: a single demographic (or two) comes out in droves to vote on Tuesday, breaking out of wherever they’ve been hiding, and shifting the balance of the race in a huge upset. Certainly a possibility.

Whatever happens, the 2008 Election reflects a mythical struggle between structure, order, hierarchy, stability, and tradition on one side; revolution, dynamism, community, collaboration, and exploration on the other. One potential leader clearly has more experience on one side of the coin, and the other potential leader is stronger in the opposite area. Each candidate has plenty of experience on the side of the coin he’s promoting. The difference will be how the voter determines which standard the candidate’s experience should be measured against!

Why am I interested in all this? First, because polling is measurement, and quality assurance requires effective measurement. But more importantly, because the themes of this election parallel the struggle that many organizations face with quality and innovation – getting the job done reliably is paramount, and experience is important, but we cannot lose sight of the way we need to reinvent ourselves and our companies to continue being competitive. Accepting the wilder side, where structures are not sacrosanct and community is more productive than hierarchy, is hard to swallow.

The old methods that tell us how to manage projects, do budgeting, evaluate employees, and manage change are incomplete in such a global, dynamic competitive environment. New organizational models that help us deal with complexity more effectively will be required, but will the 2008 Election usher one into the institution of government?

36 hours from now (hopefully), we’ll know.


Other Resources:

  • Peter Norvig, Director of Research at Google, keeps a 2008 Election site with the most comprehensive collection of data-based reports I’ve encountered
  • CNN’s early voting map shows how many early ballots were cast according to state and proportion of Democrats/Republicans voting
  • If the whole world could vote, according to the Economist, the “Global Electoral College” would be stacked.
  • Polls, Margins of Error, and Six Sigma Data-Driven Decision Making

    One of the most critical skills that a technology manager can have – or any manager, really – is the ability to interpret data and assess whether or not it reflects reality. Why is this important? Because good managers base their decisions at least in part on data, so the quality of the decision is often related to the quality of the data on which the decision is based. (One of the tenets of Six Sigma, for example, is “data-driven decision making”.)

    So what if you were basing a decision on the quality of the election polls currently being conducted? Six Sigma experts and practitioners, take note: today’s election polls offer up a really effective lesson on threats to validity which, if human subjects are ever a part of your quality improvement efforts, you need to be aware of these sorts of issues:

    [Poll results and margins of error work] pretty well if you’re interested in hypothetical colored balls in hypothetical giant urns, or survival rates of plants in a controlled experiment, or defects in a batch of factory products. It may even work well if you’re interested in blind cola taste tests. But what if the thing you are studying doesn’t quite fit the balls & urns template?

    • What if 40% of the balls have personally chosen to live in an urn that you legally can’t stick your hand into?
    • What if 50% of the balls who live in the legal urn explicitly refuse to let you select them?
    • What if the balls inside the urn are constantly interacting and talking and arguing with each other, and can decide to change their color on a whim?
    • What if you have to rely on the balls to report their own color, and some unknown number are probably lying to you?
    • What if you’ve been hired to count balls by a company who has endorsed blue as their favorite color?
    • What if you have outsourced the urn-ball counting to part-time temp balls, most of whom happen to be blue?
    • What if the balls inside the urn are listening to you counting out there, and it affects whether they want to be counted, and/or which color they want to be?

    If one or more of the above statements are true, then the formula for margin of error simplifies to:

    Margin of Error = Who the hell knows?

    Because, in this case, so-called scientific “sampling error” is completely meaningless, because it is utterly overwhelmed by unmeasurable non-sampling error. Under these circumstances “margin of error” is a fantasy, a numeric fiction masquerading as a pseudo-scientific fact.

    Read the whole article at http://iowahawk.typepad.com/iowahawk/2008/10/balls-and-urns.html. It’s a winner. (And thanks, Mary Pat, for posting this on Facebook.)

    Technology, Competitiveness and the 2008 Election

    Competitiveness is the “capacity of people, organizations and nations to achieve superior outputs and especially outcomes, and in particular, to add value, while using the same or lower amounts of inputs.” (Caryannis & Gonzalez, 2003) Basically, how can you make the best of the resources you have – and produce high quality stuff while you’re at it? On the national scale, competitiveness is often assessed by how well the organizations, institutions, infrastructure and economic policies of a country (inputs) can be leveraged by people to enhance the collective quality of life (outputs). Adding value to peoples’ lives by enhancing the quality of life is the goal!

    These inputs are all technologies – elements that contribute to social groups providing themselves with the material objects of their civilizations. When changes in any of them either improve or inhibit the performance of people, companies or countries, those technological outcomes also influence competitiveness. Reducing waste, improving reliability, creating new products and defining new, needed services all contribute to increasing competitiveness. However, we shouldn’t forget that improving institutions like schools and healthcare systems, improving infrastructure for transportation and communications, and sharpening the economic policy so that it supports sustainable progress are also important.

    How do the candidates’ proposed innovation policies stack up against one another? Here are a few of the best resources I’ve found to help explain the differences to me:


    Caryannis, C. & Gonzalez, M. (2003). Creativity and innovation = competitiveness? When, how and why. In L.V. Shavivina (Ed.), The International Handbook on Innovation. Oxford: Elsevier, pp. 170-179.

    Ezell, S.J. & Atkinson, R.D.(2008). Comparing the candidates’ technology and innovation policies. Report of the Information Technology & Innovation Foundation (ITIF). Available online.