Jeffrey Saltzman's Blog

Enhancing Organizational Performance

The Forecaster’s Dilemma

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Most of us spend a good deal of time making forecasts or predictions along the lines of “if I do X, the outcome will be Y”. What activities or set of behaviors will make me lose weight, get my child accepted into college, will set me up for a comfortable retirement, will keep the dog from barking in the middle of the night, will get me that promotion or raise…and on and on. Whole industries have sprung up to help people, to guide them (or fleece them) as they struggle with these decisions.

Organizational leaders continually search for insight into which decisions, or even more challenging which set of decisions will lead to organizational success. What products do we bring to market, do we grow organically or through acquisition, do we hire or reorganize, what will be most effective in generating sales or increased profit, what goals are in fact the right goals to be chasing…and on and on. Whole industries have sprung up to help organizations, to guide them, (or fleece them) as they struggle with these decisions.

When the National Weather Service (NWS) sees a set of conditions, they issue various kinds of warnings. For instance, a Heat Advisory is issued when temperatures are significantly above normal and the humidity is high. Along with a Heat Advisory often comes a suggestion, that older people should stay indoors, as the prediction is that older people are more susceptible to ill effects from high heat and humidity and are more at risk. Invariably the emergency rooms fill with older people who fall ill during a heat wave. In 2006, professors at Kent State University looked into this and found that while 90% of the older people knew the dangers associated with high heat and humidity, the older people who ignored the advice did so either because they 1. did not consider themselves old, or 2. thought that they belonged to a special class, were an exception, whereby the general rule did not apply in their particular circumstance.

So, the obvious solution for the NWS is to get more specific, right? Tell people that if you are older than 65 you should stay in the air conditioning during the weather event. So, what do the forecastors say when lots of 64-year old’s get ill or 66-year old’s do not? The more specific the prediction, if X is done, Y will be the outcome, the less accurate the prediction will be, but the more general the prediction the more likely it will be subject to various interpretations by different people.

Most people want perfect knowledge, with absolute answers, if you do X, Y will happen. But scientists know the dilemma they are facing, and the scientific method is to talk about tendencies and confidence limits, building error into the answers and knowing that as specificity gets higher the likelihood of being accurate in all circumstances gets lower. Science is about the preponderance of evidence, not any one study. Giving undue credence to specificity is a natural human bias and specificity itself is very attractive. Scott Highhouse, at Bowling Green University, ran a series of experiments looking at what kind of descriptions people give more credence to. Those with more specificity, more detail, were inherently thought to be more accurate. For instance, which outcome do you feel is more likely? 1. New York City will flood again. Or 2.  New York City will flood again, due to global warming and the more frequent occurrence of severe weather, such as super storm Sandy.  You are invariably drawn to number two, even though a simple Venn diagram will show that number two is a subset of number one and hence mathematically is less likely to happen. (And you are drawn to number two even though I told you the answer prior to showing you the statements. It is a very powerful effect.)

Smoking causes lung cancer, except I can find the individual who smoked their whole life and did not get cancer, or I can find someone who never smoked and got it. People, even while knowing the overall likelihood of getting lung cancer is much higher in smokers than non-smokers, will hang onto the notion that they are an exception to the rule, for that is how they deal with the cognitive dissonance that their smoking causes (attitudes usually follow behaviors). Smokers who have trouble quitting will tend to assume that they belong to that exceptional group, the lifelong smokers who don’t get lung cancer. Do they really feel that way, or deep down inside do they recognize that they are likely not exceptional and the odds are against them? If people did not have that built in bias, that somehow, they would beat the odds, lotteries and gambling would not be as successful as they are.

The older people who ignored the National Weather Service advice also had a definitional problem. Defining old. Definitional problems are very common. In 2008, Jeff Jolton and I looked at how various groups defined ethics within an organization. What we found is that the definition of what is ethical behavior or unethical behavior varied by occupation and level. Blue collar workers tended to define ethics as personal treatment and was relationship driven. Benefit cuts, layoffs, schedule changes, who got promotions or training opportunities would fall into that definition of ethics. As you moved into professional occupations within the organization ethics was defined more by walking the talk, the organization doing what they said they were going to do. In managerial occupations ethics tended to be defined by contractual obligations, either being fulfilled or not, and at the higher levels the definition zeroed in on violations of the law. So, when an organization in their values statement says, “We will do our work with the highest degree of ethics and integrity”, (and many of them say something like that), what does it mean to a typical employee?

In American today there is a great divide, and a corresponding need for people of differing political points of view to talk to each other to get past the profound challenges we are currently facing (many of them of our own making). The challenges defined above, the Forecaster’s Dilemma, about how differently people can view the same circumstance makes getting past our challenges more difficult.

For instance, would a racist (or other assorted bigoted types) know they are racist (or homophobic, or misogynist, or xenophobic etc.)? The short answer is likely to be somewhat unsatisfying. Perhaps, perhaps not. Those today, who march under Nazi banners, or along with white supremacist flags or a confederate flag certainly know what they are doing, for it is not an unconscious act. But all of the issues above can come into play. Racism, misogyny, xenophobia etc. are not binary conditions, they exist along a continuum. What is racist to one person is not racist to another, so there is a definitional problem. Remember Archie Bunker? He would sit there in his lounge chair blithely unawares that he was racist, misogynist (even though occasionally, Edith put him in his place), and xenophobic. There are a lot of Archie Bunkers out there.  And there is the exceptionalism problem, that somehow the definition of racism or other characteristic simply doesn’t apply because of special circumstance.

Can we forecast which set of behaviors we can undertake to make us a more cohesive, less divided society? A society which respects and values each of us regardless of our individually unique backgrounds? I do know one thing. If we don’t try, we are guaranteed to fail.

 

Written by Jeffrey M. Saltzman

September 25, 2017 at 10:30 am

Posted in Human Behavior

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