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E-Mail Tip #30 - Avoiding Inappropriate Counterpoints

Guest post by: Robert Whipple

Article Overview: Online exchanges can become traps for rancor if we are not careful. It is easy to take something written the wrong way and fire back a snippy reply. Then, we are off to the races. If you watch the tone of your counterpoints, you can avoid many problems online. This article provides examples of the problem and suggests some antidotes.

E-Mail Tip #30 - Avoiding Inappropriate Counterpoints

Be careful when making counterpoints to e-mail messages, that you do not shift from general statements to specific examples. It is a common trap. The problem is not unique to e-mail discussions, but it is more noticeable with online communication because of the tangible evidence trail. For example, if there was a discussion about how stockholders of your company feel about the recent revaluation of stock option base prices, it would be an attempt to describe a broad population of individuals and groups. Let's say the conversation so far has concluded that, for the most part, shareholders are supportive of the move because it will help the company retain key leaders. Suppose your counterpoint read like this:

• "Well, my uncle is a shareholder too, and he is totally against the revaluation. He thinks it is just an attempt by the current leaders to line their own pockets."

Your uncle may have a good point, and others may feel the same way, but your counterpoint is not relevant to the discussion unless you have evidence that his feelings are shared by a substantial percentage of stockholders. You have made the mistake of trying to describe a general situation by referring to one isolated data point. The information is interesting, but anecdotal. A more appropriate note would read like this:

• "I am sure there are some people out there who are against the revaluation because my uncle is one of them. How can we determine the size of this dissenting group without creating more problems for ourselves?"

Addressing the issue in a way that results in statistically significant information would enable the group to make decisions that are more informed.

People make inappropriate extrapolations of data all the time, and it skews the data. It is a version of what the legendary quality guru, W. Edwards Deming, called "tampering."

When you have a system that is "in control," meaning that the variation is based on naturally occurring fluctuations in conditions (Deming called it "common cause variation"), there is a human tendency to want to reduce the variation by manipulating the conditions.

An example of common cause variation is trying to measure the height of the ocean in one spot. At any second it will be different from the second before. Variation is occurring naturally. It is predictable in general, but is impossible to predict at any particular moment. "Special cause variation" is like a tsunami caused by an underwater earthquake. The earthquake is unpredictable, but the tsunami is not. When it occurs, the results are easily observed and can be traced back to that special event. Deming taught that when you try to control a process that is "in control" (meaning the process variation is due to common cause) by making adjustments, you actually increase the variation.

Let me illustrate with an example. If the thermostat in your home is set to 72°, the temperature will fluctuate around that level. Sometimes it will be warmer, sometimes cooler. Imagine what would happen if every time you walked by the thermostat, you adjusted the setting. If you see the temperature has gone down to 69°, you would increase the setting by three degrees. Then, later you notice the temperature is 78°, so you lower the thermostat by five degrees. Deming called that practice "tampering," and what happens is you actually increase the variation in temperature in your home. If you don't believe me, try it yourself. Now, let's relate this concept to measurement abuse.

When we measure something in business, it is to help achieve goals. Often it becomes a way to punish people because of slight variations in a process that is really in control.

In all companies, every day, people are asked to explain why something happened when the observation is a result of common cause variation. For example, let's suppose you are a sales manager for a book company and you plot sales every month on a control chart. Sales typically vary by as much as 15% per month due to common cause and the process is in statistical control. Imagine the reaction if your boss asked you why your sales were down by 10% last month and you responded, "That's an improper question that I am not going to waste my time answering. The sales figures for last month are actually in control and what you noticed was just common cause variation." GULP! You probably would not be employed there very long, yet you would be absolutely correct and Deming, if he were still alive, would pat you on the back and pin a medal on your chest.

Imagine that you worked in an area where people were all trained in statistically valid thinking and took it to heart. You would avoid hundreds of wild goose chases trying to explain things that were the result of common cause variation. You would not be trying to invent fixes to problems resulting from simple variation as if they had a special cause. Imagine the time and expense you would be saving your company. That improved efficiency is why as many people as possible should be trained in the right way to analyze and respond to data.

The same phenomenon occurs when someone cites a single data point as a reason why there is a global force driving it. Be careful to use statistically valid data to draw conclusions.

Often people believe their message was not correctly interpreted, which leads to some kind of explanation or justification for what they were trying to prove.

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Article Tags: communication, email, leadership, rancor, trust



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