Welcome back to our course, Quantitative Customer Insight Techniques. I'm James Lenz with the University of Illinois and today, we're going to start on module two which is dealing with the topic of concept testing. In this module, you'll explore a method for quantifying customer benefits and also experience this firsthand by coming up with a survey yourself. Of course, this module will be full of two quizzes as well as some readings as part of preparing you for developing this survey. By now hopefully, you have got feedback about your idea and what your ideas come up with and I want to stress it's important for everyone to think about an idea and coming up with their own idea and working on their own idea. And through this exercise hopefully, you've enjoyed this and you have a definition of what your ideas and now you've gotten some feedback as well from at least three or four people, hopefully, you've even included other people outside the course that have given you some feedback about this idea. And as part of the evaluation, people should have, in your peer review, given you a score against our three criteria of understanding where the technology is or where the idea is, how well the products define, and how well the market forecast is. So, I would encourage you to fill the data into your spreadsheet so that you can compare them. When you're comparing these, you might look at these numbers as just a little bit of quick feedback, again a quantitative way of looking at the feedback for your idea. First of all, do the numbers agree? And if they agree but they're are different, like the other ones all agree but they don't agree with yours, [inaudible] why. And can you figure it out? Can you figure this out yourself? Can you understand what they might be thinking? Hopefully as they scored things, they gave you some comments or why they were thinking, give you a low number or give it a high number, whether it was completely ready or not ready or not very well defined. Another thing that's very common in this type of scoring is what's called Olympic scoring, where you can throw if there's one number that's outlier that doesn't seem to fit, you can throw that score out and not try to deal with it in your analysis. Again, it's thinking about numbers and these numbers, I want you to experience of these numbers meaning something for you and bringing insight into you as you start to perfect your idea. Now, I want to talk a little bit more and as we do all of these courses is we have some onsite learning for you, but also to give some background of the new product development, energy, and ideas and activities and how complex this problem is. So one question you might ask is, "How many ideas does it take to make one successful product?" And this is a question I've had a chance to ask several people. I'd like you to watch this video. It's a friend of mine, Professor Adamchuk out of McGill University. He goes by the nickname Slava and you'll see I interviewed him about his understanding of ideas and his experience with taking ideas to production. I met Slava several years ago when I was living in Germany and he was keynote speaker at a precision agricultural conference at the University of Bonn. I invited him to dinner that night and ever since then, we've probably worked on a dozen projects together about new ideas and bringing them into production related to precision agriculture. Watch this video and then, we'll be back after that. How many ideas have you worked on? That would be about 100 or so different. Yeah. In how many have you been part of coming up with all of them? Yes. Yes. So how do you come up with an idea? You look for need first. You identify what's necessary. Do you do market research? Do you have some way of doing market research to find these needs? Yes, you see what doesn't work. Of these hundred ideas, how many have been gone to where you develop prototypes? About half. Half get to the point to make prototypes and then, how many of those 50 have gone into some sort of limited production or at least some commercialization? Maybe 10. It was easy to figure out which ones are going to be successful, which ones are not? Sometimes yes, sometimes no. Can you control it? There are some ideas that you know from the beginning that it's going to be brilliant ideas and there are some ideas that you do it because it's a milestone that you need to go over to go to next ideas that might be successful in the future. Do you think anybody can come up with ideas? Oh, yes definitely. And how do you encourage people to come up with ideas? If people come up with ideas, they don't need to be encouraged, they do it all the time. What's the main thing you should be, to be a good idea generator? The key point is just, think out of box. So just reach, make parallels, look at what works in one industry, maybe can transfer to another industry, or the trends. And what's more important, what's the need? And to move an idea forward, you need to have, again, opportunity, resources, and justification, and those things need to all fall in the same place. And don't be afraid to try new things. Okay. Thank you. Thank you for your comments, Slava. So hopefully you enjoyed listening to Slava, and the interview with him. You see he made three important points about getting an idea to product. He talked about, the opportunity needs to be defined, and you have to have appropriate resources, and then finally come up with a clear justification for doing this type of project. You can find out, that's interesting, that for him, the generating ideas and creating things is just what he does. It's part of his life, it's part of his world. The challenge with the ideas is now getting them into this opportunity, finding the resources and justification. Well, where does that data come from? The data for ideas comes from his work as a technologist. Where does the data related to come in for, addressing the issues and he says about the main issues of taking an idea to product? Well, it comes from market research, it comes from customer insights. So you can see that here is a strong technologist as a professor. He sees that, and he's probably one of the best that I've met at really understanding the market, and understanding the market research and how to collect data. He has his own ways about collecting this data, but it's very interesting that here is a technologist and he really talks about market research as being the main activity associated with getting an idea to product. There's been a number of studies done on this and in the old world always was, it took a thousand ideas to get to one product. Here is a survey that was done by McKinsey and shows three different industries: venture capitalist industry, the chemical industry, and the pharmaceutical industry. And it sort of shows three different steps. First it talks about how many ideas were generated, and then how many of those ideas went to some type of evaluation and development. And of course these industries are pretty easy to understand because in a venture capitalist, they're very open about defining what they're trying to do, because they're trying to raise additional funding, so they're showing their progress. As just as well as the pharmaceutical industry, there's very key evaluation steps to try to get their products into the marketplace. So there's data that's available for these types of industries. They go through this three steps of idea generation, evaluation, and development. Maybe I would call that the world of prototypes, and then finally some type of commercialization. And you can see the numbers here: 60 to six to one for venture capitalists. In the chemical industry, the arguers, takes 400 ideas to come up with one successful product. And in the pharmaceutical industry, it takes 750 ideas to come up with one successful product. In fact, many people claim that the pitfalls of all these industries are, is they have too few of ideas. There's too few of ideas, of people generating ideas, and that's why I think it's important for you to be part of that when you work for a firm or when you move into your careers. Being able to come up with ideas is an important part, an important responsibility of your company and to your company and to yourself, to help grow these things, and you see this is one of the major pitfalls that most industries go through today. And in fact, in one of the next modules, you'll hear some lectures from other companies that are talking about this issue of, how do you come up with new ideas? Let me talk about another concept, or another aspect of this whole new product development and how many projects it takes. I've had a chance to work for Honeywell for 20 years in the R&D center. Honeywell is a company that does high tech controls, sensing controls for aerospace, buildings, and industries. Here's a picture of the Boeing 777 cockpit. There's a fascinating story about those displays and the development of those displays. And there is market research that was done that said that, "This is the first glass cockpit. " So before this, there used to be round dials and knobs and so on that showed all the flight controls, and we went to a glass display that could put up that type of information. The big debate was, "Should those displays be black and white or color?" When we did just market research, simple market research, the customers were saying, "Just leave them black and white because that's what we have today and they're just fine, just put us the same gauges up there." But then we talked to advanced people, more people involved in the operations of the entire airline assembly, and running airports and so on, and they said, "You know, there's more information that's needed, especially with weather information, so that pilots can make better decisions." So you can see, we had to invest at Honeywell $50 million to develop this flat panel display technology, that could work inside this cockpit. So I'll come back to that here in another course. We'll talk a little bit more about this, what I call, "New to the world" type product developments. So at Honeywell, I did the study over 20 years and kept track of how many projects started every year, how many were funded in what I call technical feasibility type projects, and how many were funded in what I call market feasibility type projects, which is a little bit different emphasis, and then how many got to product. So we can walk through this a little bit. Typically, every year of about 200 people worked in our research center, we came up with about 3,000 ideas. In fact, it was very much encouraged to come up with ideas and tell ideas. About 300 of them got funded every year to be pursued as a project. And they typically got one person, one and a half people were able to work on that project for a year. At the end of that project, about 250 of them were successful. 50 were not, they didn't achieve what the technical goals were, so they would either rebid those ideas and try them again or we'd go on to new ideas. Now, at the end of that annual year, we would also then address this, "What is the unmet need?" As part of doing the technical feasibility project, you had to then define what is the unmet need, specifically, that your technology is trying to address. This was a harder question to answer. And of those 250 projects that finished, only 25 were able to really address that question. And of those 25 of them, we funded them, projects now were almost double in size, or a little bit larger than the technical feasibility, because it takes more work to understand the market feasibility and develop the technology related to that. And as part of that, only about 20 of those projects finished, and now we were talking to our commercialization business units about now commercializing these. And we'd go through what we call a business plan, and you'll have that in the next course. We'll talk more about developing a business plan based on these ideas. From this, only about two of those 20 ideas were then brought into a product launch, commercialization. And once our business units did this, they were successful. Very few failed because enough was known about this product idea, and enough about the market, to make it successful. But what's also interesting, is only about one and a half of them were financially successful. So you can start a project, start on an idea, but still, even if you get to product, it's not clear that you've still, there's still uncertainty in whether that product's going to be of commercial success and really make money or not, or just be a product that you can sell, but you're not making much money on. Another way to look at this, is just to look at the finances, and I'll go through this quickly. If you look at the technical feasibility, about 84 percent of those projects were successful. We spent about 30 full time people working on a year on those projects but only point five percent of that money actually led to a commercial success. So, many companies are quite concerned about how to improve that efficiency. Of the money you spend in R&D on this activity only zero point five percent is going to be paying back some type of commercial success. If we go to the technical feasibility projects, which is even more money, four times more money is spent by our R&D center on this. Only three percent of that money is going to return in some type of commercial success. And as I showed in the product launch, we spend a fair amount of money on this as well in our research center, supporting that commercial activity. And now only 67 percent of this. So you can see R&D is a very inefficient process. But also, what does happen, and I'll show you this later, is when you do have a commercial success it pays for all of this. This idea of 1000 ideas generated, one product, it turns out that that one product, when it's so successful, it will pay for those thousand ideas to be explored. And this is the way of running a portfolio of projects and working through an R&D process. Here are some of the products that I've been involved in. They're a little bit older because, you know, this type of data now can be shown, whereas more recent things that I'm working on is still a little sensitive to be able to show these things. So I'm showing things that are a little bit older but you can just get a timeline, a little bit of what it takes to take some of these products through, and I call it from when the idea was originated, when the first breadboard was built, when the product development was started, when the product was introduced, and what the total number of years are. And you can see it varies from, like, dot-com type industries, very fast moving, that's what's exciting today, is apps and dot-coms, how fast they can come to the marketplace. Whereas a safety and control environment, something like if you're flying an airplane, it takes many years to prove out this technology, that it can really serve the need of the marketplace. So, in summary of our Module Two here, we want to show that there's many ideas that are not made into products. In fact, most of R&D is learning what doesn't work. But this is an important part of any company's portfolio of developing really innovative products. The more innovative products you try to develop, the more risk, and the more uncertainty that's going to be involved in those. And that's why market research really serves an important part of the base for defining these opportunities, obtaining resources, and justifying the launch of development product. So now, in completing this Lecture One, there will be a short quiz for you to take, and then we'll pick this up again in the next lecture. And thanks for watching.
