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Comfortable Speaking About Statistics?

by Paul Barsch  |  
April 29, 2010

Statistics have been called “an engine of knowledge” by one risk management expert. And while it’s true that some business managers don’t have a fundamental grasp of statistical concepts, we also know there is opportunity for misuse of mathematics. Is statistics the “new grammar” or are efforts to attach certainty to life’s events doing more harm than good?

In May 2010’s issue of Wired Magazine, author Clive Thompson laments the poor mathematical literacy of his fellow citizens. For example, he cites people laughing at the concept of global warming as they face some of the harsher winters on record, or the extra-vocal debate on vaccines and possible links to autism. Mr. Thompson would tell us that it’s the trend lines that matter, and we too often look at the trees and miss the forest.

The problem, he says, is that “statistics is hard” and an overall understanding of this important discipline is severely lacking. He says, “If you don’t understand statistics, you don’t know what’s going on, and you can’t tell when you’re being lied to.”

Thompson is correct that statistics are difficult for most of us, and that thinking by the numbers takes training and much effort. It’s also true that one must understand statistical concepts, especially when percentages, populations, and probabilities are bandied about in business and technical press. However, broader acceptance of the power of statistics should be tempered with limitations of this mathematical science.

Before accepting any statistic, study or experiment as gospel, the following should be considered (there may be more…):

1. Assumptions: What are the assumptions underpinning the research? As seen from recent debate on CBO numbers for the U.S. health reform package, assumptions matter tremendously.
2. History: How much historical data was used in the study? What was the time scale? As seen from the 2008 financial crisis, the models used by Wall Street mavens often only took into account 10 years of data in judging the volatility and probability of failure of complex financial instruments.
3. Samples: Are the samples selected randomly? From what populations? Is there enough data for statistical significance?
4. Data Quality: The output is only going to be as good as the quality of data feeding the analysis. Garbage in, garbage out.
5. Survivorship Bias: Author Nassim Taleb points out that “losers are often not in the sample.” Does the analysis include a population of survivors and those who also failed?
6. Falsification and Omission: Yes, in an era of IPCC’s Climate Gate, one needs to ascertain if data are hidden, missing or outliers ignored.
7. Association equals causation fallacy: Correlation does not equate to causation (a common mistake made by marketing and finance executives alike).
8. Proper Application of Statistics: The effective use of statistics by insurance actuaries, scientists, and even casino managers is well-documented. However, real danger results when mathematical concepts are used to denote certainty indecision-making and divining behavior of markets.

Now, please don’t get me wrong. Statistical analysis is very important for many industries (e.g., health care, transportation, and manufacturing). Statistics, however, can give us an illusion of control in a world that’s much more complex than our models suggest. Nassim Taleb, author of the Black Swan likes to remind us that “(real) life isn’t a casino.”

Statistical analysis is definitely a powerful gadget in the business manager’s decision-making toolkit. But one needs to understand the limitations of this science.

After all, Taleb points out that many of today’s statistical models work as though we have “full knowledge of the probability of future outcomes.” And this just isn’t so, especially when it comes to fat tails, or the “ten sigma” event. Indeed, sometimes those rare events have extremely large impacts. Were he alive today, the former captain of the Titanic, E.J. Smith would wholeheartedly agree.

• Clive Thompson calls statistics "the language of data." How important is it for marketers to understand and apply statistical concepts?
• "Lies, damned lies, and statistics" is a phrase popularized by Mark Twain in the context of using statistics to unduly persuade, obfuscate or even swindle. Can statistics get its reputation back? If so, how?

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Paul Barsch directs services marketing programs for Teradata, the world's largest data warehousing and analytics company. Previously, Paul was marketing director for HP Enterprise Services $1.3 billion healthcare industry and a senior marketing manager at global consultancy, BearingPoint. Paul is a senior contributor to MarketingProfs, a frequent columnist for MarketingProfs DailyFix, and has published over fifteen articles in marketing, management, technology and healthcare publications. Paul earned his Bachelors of Science in Business Administration from California Polytechnic State University, San Luis Obispo. He and his family reside in San Diego, CA.

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  • by Claire Ratushny Thu Apr 29, 2010 via blog


    Just questioning how much "statistics" mean in many sectors that are undergoing a paradigm shift. I'm thinking principally of consumer products since that's my sphere of experience and interest. As for assumptions, the late, great management thinker C.K. Prahalad asked us all to challenge our basic assumptions about everything. What I'm saying is: I'm not sure whether all the analysis in the world and the compilation of statistics, as well as our past assumptions, mean much in certain sectors of our economy that are undergoing serious transformation. Your thoughts?

  • by Paul Barsch Thu Apr 29, 2010 via blog

    Good question Claire! When it comes to sectors undergoing a paradigm shift, I can think of few that will experience more transformation than healthcare. In healthcare statistics run rampant, especially in insurance (actuaries), hospitals (measuring quality of patient care, tracking error rates, inventory mgmt), and pharma (design, testing, and efficacy analysis).

    I don't want to paint myself as a CPG expert, but I believe any company that manufactures a product would be looking at things such as quality control, fulfillment, warranty analysis, inventory optimization and more. I found this article that may provide some additional insights into the CPG space:

    You make a final query that I might summarize as, "how well does the past predict the future?" especially in terms of industries that are experiencing rapid transformation. These are domains for which analysis of historical data and predictive analytics may not provide much assistance, especially since "conditions" have changed or will change drastically. It is in these instances that the past may not offer a suitable guide for predicting the future, and one must rely on experience and executive judgment.

    Love the question! FIX readers, your thoughts?

  • by Chrissy Carney Thu Apr 29, 2010 via blog

    Paul, I think you make a great point with this article and in your response to Claire. Overall,
    I think it's necessary to exercise one's own judgment in whatever industry or case a statistic is used to form an opinion. In public relations and marketing especially, they tend to be powerful tools as they disseminate information immediately and succinctly. But users should be aware that stats can usually only provide a snippet of the story and take them in relation to the bigger picture.

  • by Paul Barsch Fri Apr 30, 2010 via blog

    Chrissy, great comment: "Users should be aware that stats can usually only provide a snippet of the story and take them in relation to the bigger picture." The Mark Twain quote is appropriate here, isn't it? Especially due to the misuse of this mathematical science, we've trained our customers to ignore or put up mental resistance when we use statistics in our marketing materials. Transparency is the "in" word in so many circles these days, perhaps there's also room for transparency in marketing's use of statistics...

    Appreciate your comment!

  • by Randy Krum Tue May 4, 2010 via blog

    Paul, great points. This immediately reminds me of Arthur Benjamin's TEDTalk from Feb 2009, which makes the plea that the ultimate goal of our high school math programs should be statistics, not calculus.

    I think most of the misuse of statistics is not malicious, as Mark Twain's quote implies, but more misunderstanding and incorrect conclusions. Maybe it would be more appropriate to say "Mistakes, Blunders and Statistics"?

  • by Paul Barsch Wed May 5, 2010 via blog

    Randy, thank you for the pointer to Arthur Benjamin's TED talk. He's an energetic fellow isn't he? And his points are right on. Statistics is a daily life necessity, even simple concepts like mean, median and mode! I appreciate your thoughtful comments on this column.

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