Okay. The second step in the process is actually setting targets for these non-financial measures. Now, you hear a lot of times that more is better, 100 percent of your employees or customers need to be satisfied which may be true. But in a lot of cases, it may not be true. Again, it's not the same as a financial metric where more money and more profits is always preferred. The problem is, the companies we talked, to they have considerable difficulty setting goals for any of these non-financial performance measures. And there's a number of reasons for this. One, what do you do when the measures have no common denominator? Okay, this is not like financial results. I know how to do a budget because everything rolls up from the bottom to the top, because everything is in common currency. How do I compare a 10 percent decrease in customer complaints to a three percent reduction in defect rates? They're completely different, so if I wanted to say which one makes more sense, I've got to put them in a common denominator which just happens to be currency. Which is why we're going to try to link this to financial performance because it's going to allow us to kind of make trade-offs. The other big problem is you've got these nonlinear functional relationships and trade-offs. Okay, what that means is you can have either economies of scale or dis-economies of scale, right? More is not necessarily better, I probably do not want 100 percent satisfied customers. The reason is, it's really expensive. And ultimately, if what I'm trying to do is optimize financial performance, that may not be the right thing to do. Same thing with employee turnover. Yeah, employee turnover is very expensive, but it'd be expensive to keep people and in truth, a lot of companies actually want some turnover because it creates new opportunities for people to move up in the organization, it brings in new world views. So, you probably don't want zero employee turnover, you probably don't want 100 percent satisfied customers. The question is, where is this point of diminishing returns and how can we figure out where that's at? So, let's go through an example of this, okay, here's a personal computer manufacturer. It turns out the margins on a personal computer are very small. You do not make much money on each personal computer. The other thing with a personal computer is, you don't necessarily buy one every year. So, there can be a lag between me being satisfied and me deciding whether I'm going to buy from them again. On the other hand, if you don't like your personal computer, I bet you tell somebody. So you've got this whole issue with word of mouth. So here are some hypotheses in the business model of this PC manufacturer. One is, more satisfied customers recommend the company's products to others. It's also called positive word of mouth. Dissatisfied customers complain to others about the product or negative word of mouth. Turns out they've done studies in the auto industry. If you really like your car, you tell one person. If you really do not like your car, you tell 10. So it turns out the negative word of mouth can be worse than the positive word of mouth and especially in a business like this where you do not necessarily buy a PC every year. The word of mouth may be that the direct relationship and a lot of cases between improving satisfaction and short term financial performance. Okay. So, here are the hot hypotheses we can test. Greater positive word of mouth increases future financial performance; greater negative word of mouth reduces future financial performance. That's what they're hypothesizing. So, if you believe that, what are you going to do, spend money to increase satisfaction, because that should change your word of mouth. So, here's what they did when they actually went back and looked at this. So, what you have here if you think about when you buy a personal computer, you have a warranty card. You fill that out. They kind of know who you are as long as you filled out the warranty card. And what you're trying to do with a lot of these non-financial see if they are leading indicators of future financial performance. If I know something about satisfaction now, does it tell me something about future financial performance? Now remember, one of their hypotheses is, if I have higher customer satisfaction, I'm going to tell more people that I liked it, more positive word of mouth and vice versa. Well, their satisfaction scale, like a lot of companies, it's on a five point scale. Five is "I'm really satisfied", one is "I'm not very satisfied". So, when you do the analytics, here's what you find. Okay. And this is, first of all, we're going to start out with a positive word of mouth. Obviously, if I don't like it, I don't give any positive word of mouth. If I don't like it but not quite extremely bad, if I give it a two, which is the second red bar there, I might say something. After I get three, I'm kind of satisfied from three to five. Yeah, I recommend it. But if you look at that, those lines aren't that much different. In fact they go down a little bit if anything, but they're statistically the same. Basically, what this says is, if I'm moderately satisfied, I recommend it. After that, I could spend money making more satisfied, but you don't recommend any more than you would have otherwise. Now, here's why this is important, the company had a bonus plan. The bonus plan said, "Maximize the number of people that give us a five for customer satisfaction." It's called a top box measure. What percentage of the people answer in the top box of the customer satisfaction scale? Very common bonus plan. If I was the manager, and that's the bonus you gave me, all of those people in three and four, I would try to get them into five because you're going to pay me more. But looking at this, I'm spending money to get them into the five bucket, but they're not recommending any more. It may not make any economic sense. Let's go to the downside, the exactly opposite. Okay, if you look at negative word of mouth, obviously, if you don't like it you tell people. From three on, then you get the exact same answer here. So, one of the big issues that comes out of this is, how do you want to set your performance targets? Now, remember the target here was get everybody on five, over to the right on the bar. That means get anybody on those threes and fours, push them up. What this may say is that's really not a very good target. Now, I've asked a lot of students when I presented this, "Where would you set the target?" And in a lot of times they responded, "We set it at three because that kind of seems like the hot spot." Well in truth, that's not right. What you really want to do is set the target such that nobody gets into one. That's where the biggest bang for the buck is. Get everybody out of the one category. Targets do not have to be set at the top of the scales. We seem to think that that's where it has to be, get everybody up at the top? No, here get everybody out of the bottom. And the only way you would have known that for setting this target, is they actually do the analytics on it. Let's actually go back, test that prediction then if I have more satisfied customers, in the future they will recommend my product and that's going to lead to better financial performance. Okay. Now, this need not be true. So here's an opposite example, okay, this is a company, a financial company where you're going to invest your money with an investment advisor. So you get your retirement fund and I want to invest it there. What they wanted to look at was, is there a relationship between satisfaction with our firm and future financial performance? We did the analysis and guess what, we found absolutely zero. There was no relationship between satisfaction with the firm and firm performance. What you did find was satisfaction with your investment advisor. This is where you have to figure out what the right measures are. It's not just I'm satisfied with the firm. I don't care about your research reports. I don't care about your offices. If I'm satisfied with my individual investment advisor, then I tend to give you more money. Now, the thing you care about in an industry like this, is assets invested or what's also called assets under management. I want all your portfolio. Give it all to me because I make money on how much money I'm invested. So when you start looking at this, you see a relationship between investor advisor satisfaction and assets invested in that where they have an index that has many things in it. So here's low, the scale ranges from one is "I'm really not satisfied with my adviser." to seven "I'm very satisfied." So, here's the low end. It does start actually going up, as you're more satisfied, you start investing more there. We're not seeing that diminishing returns that we saw with the computer manufacturer. Now though, here's an example where you do want to spend money to get them as satisfied as possible. There is a huge jump here in how satisfied you are with your investment advisor and assets under management. This is after controlling for how much money you made. So, this is just not be made a lot of money for you. This is one where you get exactly the opposite result from what we had with the personal computer manufacturer. There it was, no, don't put people in the fours and fives because after three, it makes no difference. Here's one where it's exactly opposite, you get a huge jump between six and seven. So investing and trying to improve investor advisor satisfaction would seem to make a huge difference here as opposed to the other one. And that's where you need to do analytics. Don't let anybody tell you they know what's going to happen in these relationships without trying to test it. So, here's an example of trying to do the same analysis using external market data. It turns out there's something called the American Customer Satisfaction Index. What happens is, the University of Michigan goes out and surveys customers on their use of various products. And this is all published in one of the major business publications. So this has got to come out. The question is when this comes out, does the market actually respond to the satisfaction index? Right. Do they believe that if a company has very good satisfaction, they're going to future cash flows that are higher? If they're bad, is it going to be lower? Now this is done in many countries including many countries in Europe. So there is a lot of work on this. Now, what we're showing here is what happens to the valuation of your company depending on which your customer satisfaction level is. This is after controlling for your accounting book values. So, is your company worth more than your accounting book values would say based on what kind of satisfaction you have? Again, if you look at the bottom, the Quartile 1, yeah, if you have fairly low customer satisfaction based on this index, your market value is going to be lower. It goes up when you go into Quartile 2, better satisfaction. But again, look at three and four, even the stock market believes that more is not necessarily better. After you've kind of met that you got into the top end of the Customer Satisfaction Index, the market is not rewarding you with higher market value based on your customer satisfaction scores on this. Now again, if you look at what happened to your stock returns, when this was announced, did the market say, "Okay, now I know something about your satisfaction. I'm going to hurt your stock price today or increase it." This is looking over 10 days and it's called excess returns because we're taking out what happened to the stock market in your industry and things like that. They really hammered you. If you were in the bottom of the Customer Satisfaction Index, your stock price went down two percent over 10 days, which is pretty big. You look at two and three, it went up but fairly small amounts. But here in terms of the stock returns not the valuation, the market did reward you for being on the top end here. It turns out this actually differs depending on the industry. The one industry where you do not see this was retail. And in retail, what you found was that Quartile 4, the top one, it actually was negative. And you see all of that makes no sense until you start thinking about retail. Think of the high-end retailers with very high customer satisfaction scores. In the United States, at something like Nordstroms, you can go in there and there's a guy playing a piano. I don't go into stores because they're playing pianos, but some people do. There's apocryphal stories that Nordstrom will take anything back. So they've taken back tires, they do not sell tires. They've got very satisfied customers. What the market believes though is they've got a little crazy. They just too satisfied, you're spending too much money, it's just not paying off. So again, what you want to do is, even if you're going to look externally, make sure you kind of slice and dice the analytics to see does this hold across everybody, does it vary by location, does it vary by country, does it vary by which industry you're in. Because it turns out if you've got Chinese speaking customers, they answer on a different part of the customer satisfaction scale. So you need to control for that. So, if I'm trying to pool Chinese customers and non-Chinese customers, your statistics are going to show nothing. What you need to realize is you've got to estimates separate models with Chinese speaking people and non-Chinese. It's not a bias, it's just you tend to answer on a different part of the scale.
