Tag Archive for: rationality

Decision Making and Rationality – Part 4

This is the final installment in the series on decision making. The information I’ve been discussing was derived from a survey I conducted over a month ago with readers.

Question 8 on Survey A was: Your company is surviving in this economy but is looking for ways to save money. Inflation is 0% and the company has decided to cut wages across the board by 3%. Is this fair? Nearly two-thirds (62%) said this was not fair.

On Survey B the question was slightly different: Your company is surviving in this economy but is looking for ways to save money. Inflation is expected to be 6% this year and the company has decided to give a 3% wage increase to everyone. Is this fair? Slightly more than two-thirds (67%) said this was fair.

Here’s the point: Both questions are really the same. In each case your buying power will fall by 3% because of inflation. The first case it unpalatable because no one likes to lose (scarcity) and that’s how it feels when your pay is cut. The second scenario doesn’t seem so bad because at least you got something. However, at the end of the day both employees have the same buying power if inflation turns out as predicted. Never forget, how you position things can make all the difference.

Question 9 on Survey A: You’re playing a game and your partner was given $100 to share with you any way they see fit. The two of you get to keep the $100 but only if you think you’ve been treated fairly. What’s the least amount you would want in order to not reject the deal?

Just over two thirds of the respondents said sharing $50 would be fair. The average of fair for all responses was $41.88.

On Survey B the question was: You’re playing a game and you’re given $100 to share with the person you’re playing with. The two of you get to keep the $100 but only if the other person agrees you’ve been fair. How much will you give the other person?

Here 93 0f 100 respondents said $50 w0uld be fair and the average of fair was $50.33.

Here’s the point: Both questions put survey takers in opposite positions. You know you can lose everything in Survey A if your offer is not perceived as fair so you better consider what the other person thinks is fair. As we’ve seen, most people view fair as roughly equal portions.

In Survey B the tables are turned and you can reject the deal which means the other person loses out too if you feel they’re not being fair. However, wouldn’t it be foolish to reject any offer because accepting even $1 makes you better off than you were before the game? What’s the point in teaching the other person – who you’ll probably never see again – a lesson because you didn’t think they were being fair?

Of course, in either scenario there’s lots to be considered if you will see the other person again, especially of you have an ongoing relationship. People take being fair very seriously and you’d best get to know the other person and try to learn their value system if you expect to have a good, long-term working relationship.

Question 10 dealt with salary increases relative to others in the same department. In Survey A the question read: You got a raise from $65,000 to $80,000. You’re now the highest paid person in your department. On a scale of 1-100 (1 least, 100 most) how happy are you?

The question was very similar for Survey B except how your new pay ranks in the department: You got a raise from $65,000 to $80,000. You learn you’re only the 3rd highest paid in your department out of five people. On a scale of 1-100 (1 least, 100 most) how happy are you?

As you can imagine, people in Survey A were happier, the average score being 83.6%with men coming in at 82% and women 86%. In Survey B the average was 74.2% with men being less satisfied at 72% and women reporting happiness of 76%.

Here’s the point: Sometimes we’re better off not comparing ourselves to others. There are times when comparisons are needed to make sure we’re not taken advantage of but quite often that’s not the case as we make comparisons. I wrote a blog post, “The Secret to Happiness,” where I shared a personal philosophy, “Happy is the man who wants what he has.” I must say my thinking in this area is impacted by Biblical principles which continually tell us not to compare ourselves to others because that becomes a source of greed, lust and envy.

I hope you found the survey and resulting posts helpful in understanding how and why people make decisions. If you’re trying to influence people recognizing they don’t always make decisions in the most rational manner is helpful because you can adjust your presentation accordingly. Doing so in an ethical manner can lead you to me more persuasive and hear “Yes” more often.

Brian, CMCT
influencepeople
Helping You Learn to Hear “Yes”.

Decision Making and Rationality – Part 3

For the past few weeks we’ve been looking at data from a survey I conducted with Influence PEOPLE readers. My goal in doing the survey was to understand how people make decisions. If you’d like to know more about the survey background click here. This week we’ll continue to explore some interesting things about how people make decisions.

Question 6 on Survey A had to do with selling your home. I realize there’s a lot to consider when selling a home but nonetheless the question read as follows: You bought your home for $189,000. At the peak of the housing market it was appraised for $279,000, so even though you don’t have to move you decided to try to sell it. With the recent market all prices have come down. You’re offered $212,000. Will you sell?

Under these circumstances 77% declined to sell.

On Survey B the question was essentially the same except the peak value was much lower: You bought your home for $189,000. At the peak of the housing market it was appraised for $229,000, so even though you don’t have to move you decided to try to sell it. With the recent market all prices have come down. You’re offered $212,000. Will you sell?

In this economic scenario 53% of people said they would sell.

Here’s the point: If you take another look at the questions you’ll see the selling price is the same in both cases, $212,000, which means the profit is the same on each sale. The difference is what people thought their house was worth during the housing bubble. It’s a classic “compared to what” situation and loss aversion. People who thought their house was worth $279,000 at one time are very, very reluctant to sell. As I noted last week, the same thing happens with stocks when people hang on to losing stocks hoping they’ll rebound.

In the second survey with the peak price being much lower made people feel less pain thinking about what they might have gotten and as a result more than twice as many were willing to sell when compared to Survey A. Knowing the housing market was over inflated due to bad loans shouldn’t the real question be; is a $212,000 selling price a good return on an $189,000 home? Take the comparisons out and people make very different decisions.

Question 7 on Survey A went like this: You’re playing a game and you’re given $100 to share with the person you’re playing with. Between the two of you, you get to keep the $100 no matter how you choose to split it. What would you give to the other person?

On Survey B the question was: You’re playing a game and your partner was given $100 to share with you. Between the two of you, both get to keep the $100 no matter how they split it. How much would the other person have to give you to for you to consider it a fair split?

On Survey A the average response was $50.38 and on B it was $47.76. As you can imagine the vast majority of people put $50 on both surveys (87% on Survey A and 84% on Survey B) as being the fair amount.

Here’s the point: We have an ingrained idea that “fair” is an equal split when in reality, if you were given $100 and could share that amount however you wanted, anything you would give to someone else would make them better off. Just because you had the luck of the draw so to speak does that mean everyone should have such luck? Regardless, it’s apparent what people call fair usually means equal shares for all, so you’d do well to keep that in mind when sharing.

Next week we’ll conclude our look at the survey results and implications for you when it comes to understanding how people make decisions.

Brian, CMCT
influencepeople
Helping You Learn to Hear “Yes”.

Decision Making and Rationality – Part 2

Last week we started looking at data from a recent survey I conducted with readers. The goal of the survey was to analyze how people make decisions. To understand a little more of the survey background take a look at last week’s post. This week we’ll start to get into the meat of the survey and explore some interesting things about decision making.

Question 4 on Survey A had to do with gambling and potential winnings: You have an 80% chance of winning $4000, or 100% chance of winning $3000. Which do you choose?

The vast majority, 74% said they’d take the sure bet at 100% rather than gambling a bit for the $4000. Simple math shows in the long run people will win more risking a little (80% x $4000 = $3200 average winning vs. a sure $3000).

On Survey B, question 4 was essentially the same except it had to do with losing: You’re being sued and you have an 80% chance of losing $4000, or 100% chance of losing $3000. Which do you choose?

In this scenario the same dollar amounts are at stake but when faced with the prospect of a sure loss 56% of people are willing to gamble a little to avoid that sure loss. However, if they play the odds they’ll lose less in the long run by just accepting the $3000 loss.

Here’s the point: Everything I’ve read says people dislike loss more than gain, even when it comes to the same amount. In other words, there’s more pain associated with losing $100 than there is joy in winning or finding $100. When it comes to sales, customers will be more motivated to buy if the sales person talks about what the customer stands to lose as opposed to what they stand to gain should they make the purchase.

In the scenarios I set up we clearly see people don’t want to risk losing out on a sure thing. On the flip side, because they hate losing they’re willing to possibly lose even more for a shot at possibly losing nothing. Both decisions by the majority of people fly in the face of conventional logic which the math clearly shows – gamble for more, take the sure loss. That’s important to understand when you have options to present with different risks associated with each.

I think the psychology being described here also tells us why people hang onto losing stocks longer than they should. Quite often if people see a stock in decline they’d be better off selling it and cutting their losses but all too often, too many hang on because they hate the thought of losing and believe the stock might turn around.

Question 5 on Survey A had to do with saving money: You are at a store considering buying a high-end electronic item for $879. While there you learn you can drive across town and get the same item for $859. Will you make the trip (approx. 30 minutes)?

An overwhelming majority, 87% said they would not make the drive.

On Survey B it was also a question about saving money: You are at a store considering buying an electronic item for $79. While there you learn you can drive across town and get the same item for $59. Will you make the trip (approx. 30 minutes)?

This was almost an even split with 49.0% saying they would make the drive.

Here’s the point: Look at both questions again and you’ll see the savings is the same in both case, $20. I find it interesting that half the people are willing to make the drive to save $20 on a $79 purchase but nearly 9 in 10 said they would not when considering the same savings on a big ticket item. Should the price of the item that’s for sale really matter? Why is saving $20 any less valuable use of time for the big ticket item vs. the lower priced item? If you think about it it’s not rational.

I bet most people reading this would drive across town if they heard someone was giving away $20 bills for free (limit one per person) which is really the same as saving $20. As you can see, much of the response is dictated by the set up and what the $20 is compared to. Free is always a big incentive.

I should also point out that I think the current spike in gas prices impacted the response on the low value purchase. If the savings had been more like $30 or $40 I believe the response would have been up by a good bit but I doubt it would have changed too much on the high value purchase.

One final point of note; I’m willing to bet many people taking the surveys would go well out of the way to save 10-15 cents per gallon on gas which might only amount to $20. Interesting.

We’ll continue our look at decision making in next week’s post as we look at more survey questions.

Brian, CMCT
influencepeople
Helping You Learn to Hear “Yes”.

Decision Making and Rationality – Part 1

First let me say thanks to all of you who participated in my most recent survey. The results are in and I’ll be sharing the data and my interpretation of the data over the next four posts.

I’m fascinated by the process people go through to make decisions and that’s what my survey was attempting to get at. I’ve enjoyed Dan Ariely’s books, Predictably Irrational and The Upside of Irrationality, and his work ties into much of what I’ll be sharing. Another very interesting book on this subject is William Poundstone’s Priceless: The Myth of Fair Value (and How to Take Advantage of It). All three books had a profound impact on my thinking in this area so I decided to see if what I’ve read about would bear out in the real world with my readers.

Before we begin, let me put out this disclaimer: I’m not a social scientist or behavioral economist. This was not a rigorous scientific study, just my attempt to see how people would respond to certain scenarios so I could see how the responses correlated to things I’ve learned over the years. I also need to tell you I’m not a professional surveyor either. I’m learning as I go and point this out because I had a few people contact me because they had issues with certain questions. Sorry if a question or two rubbed you the wrong way but thanks for participating and for taking the time to reach out to me.

The Surveys I asked people to take one of two surveys based on the letter their last name started with. There was no psychology to this. My only goal was to get an even, random split between the two surveys and I accomplished that. As I share the questions you’ll see both surveys were very similar but with slight twists on each question and those twists will be the points of comparison when it comes to decision making. So without further adieu let’s get started.

Question 1 asked the sex of the participant because I was interested to see if there were any significant differences in the answers given by each gender. In case you’re interested, 58% of the people taking Survey A were male and 42% were female. On Survey B it was a 50-50 split which meant the overall split for all participants was 54% male and 46% female.

Question 2 on Survey A people were asked to enter their four-digit birth year while Survey B had people put in their two-digit birth year. That question was only to prime you because many different studies show that mere exposure to words or numbers can change people’s responses and behaviors and I wanted to see if that was the case with those who took my survey when they answered question 3.

In case you’re curious, most people who took the surveys were in their mid-40s. On Survey A the average birth year was close to 1964 and on Survey B the average was 1966.

Question 3 asked, “If you could get paid what you really believe you’re worth (not what you’d love to earn) what annual salary would you ask for?”

Priming would lead me to believe people who entered a four-digit birth year, like 1963, would be subtly influenced to put down a higher salary than those who entered a two-digit year like 63. With 100 responses for each survey those who entered a four-digit birth year thought they were worth $147,413, whereas those who put in a two-digit birth year said they’d ask for $142,775.

I doubt the $4638 spread, a 3.2% difference, is statistically significant. However, what seemed to have influence was the male-female ratio because generally women would ask for a lot less on the salary. The average salary entered by women was $126,005 vs. $161,644 for men. In other words, the men thought they should get 28% more than the women! The average birth year was 1965 for both men and women so it would be hard to explain the difference based on eligible years in the workforce.

Maybe unknowingly the real priming was having participants enter their sex at the start of the survey. I say that because there’s lots of interesting data that shows entering sex or race can impact performance on things like tests. In Asia, entering gender tends lead to lower test scores for women whereas in the U.S., African-Americans scored lower on tests when they had to enter their race. To learn more about that I’ll refer you to the work cited in Malcolm Gladwell’s best seller, Blink.

Here’s the point: What you’re exposed to first can make a big difference in your thinking – good or bad. The first number a realtor or car salesman puts out can have a significant impact on what you ultimately pay. It’s a form of priming called anchoring. Your best defense might be having a firm number (monthly or total) for that dream house or car that you won’t deviate from. And when it comes to race, sex, religion and other factors we’d all do well to understand the preconceived ideas we hold because we might unknowingly be negatively influencing ourselves.

Brian, CMCT
influencepeople
Helping You Learn to Hear “Yes”.