• John Ennis

Christine Van Dongen - Quality not Quantity


Welcome to "AigoraCast", conversations with industry experts on how new technologies are transforming sensory and consumer science!


AigoraCast is available on Apple Podcasts, Stitcher, Google Podcasts, Spotify, and PodCast Republic. Remember to subscribe, and please leave a positive review if you like what you hear!



Dr. Christine Van Dongen is an experimental psychologist who has enjoyed an extensive career in the sensory evaluation field, helping companies make products that work for consumers. Her early career consisted of teaching experimental psychology at various universities and doing research in sensory, perceptual, and cognitive processes. Her career as a sensory professional has involved research on a variety of sensory questions such as discrimination methodologies, team tastings, and how sensory creates and delivers value. She actively contributes to various professional organizations such as ASTM, ISO and SSP to share best practices and standards in the sensory field. She is currently a Fellow at the University of Minnesota – Twin Cities working in the Sensory Center to create a bridge between the academic and the business world.


LinkedIn


Transcript (Semi-automated, forgive typos!)



John: So, Chris thank you so much for being on the show today.

Christine: Glad to be here.
John: Alright, great. So, Chris, you and I have been friends, I guess for 12 years now, thanks to ASTM. I've always admired your broad background and your breadth of experience. I would really be curious to start the show by hearing your thoughts, a kind of the big picture. What do you see as the kind of important point, what you think about the relationship between technology and the sensory profession?

Christine: Well, I've thought about this quite a bit, and I think to take the you know, the big picture view, which pretty much that's the way I start with things. I think sensory needs to keep it's eye on the value it creates because I don't think we have a good handle on that. I don't think we have as much clarity as we should. And I think that plagues us when we're serving in a rolling industry. So the relationship between sensory and technology, I think it's a complex one and I think the effect or what technology brings it really depends. It depends. And the reason it depends is I think the big picture in sensory is their sort of three parts to it. There's the conceptualization of the study. You know, the why. Why are we doing this? What's our aim? What's our purpose? What's our goal? And that's conceptualization. That's what question are you answering. How are you going to solve the problem? What tools are you going to use in the design, etc. But then the middle phase is the implementation. That's the process. That's heavily process. It's how you're going to do the study. The third phase is the interpretation, which is the so what? What decision are you going to make? You know, how are you going to use the information? How have you addressed your central question? And I think technology does is that fills in or has it's focus on the middle phase, the implementation, the method on how. So in that case, I really and I don't want to reveal my age or, you know, we can say 30 years in the field. And we didn't start with abacuses, but I started out coding data by hand or entering it into I think I was starting my career at the start of the personal computers and software that allowed I think excels around maybe an early version of Excel. So I'm all for the technology that speeds up, creates efficiencies in our process. So automated data collection, how I think automated statistical analysis, I think that's a mixed bug because I think we are have raised or brought out in the field a collection of people with sensory knowledge and put into sensory roles who can push buttons but don't really understand what's behind the statistics. So not that I want people to be doing an analysis of variance by hand or who knows how you do multivariate analysis by hand.

John: I've done that, actually. It's good exercise.

Christine: Well, I've done an ANOVA by hand. My first one for my master's, it took me a week. It was not something I'd want to repeat, but I could do it. And I do understand what's happening in ANOVA. So I think the tools that have created efficiencies and implementation and speed are great. It's taken some of the what I call the sliding out of sensory. I also have a new tools like Alexa and the capabilities for video of both recording transmission, etc., augments or capabilities. So we were not so tied in a location. We can get real time. And on some level, we can get a not less scripted, but more direct and, you know, a range of information we couldn't without those tool. So I'm all for that with the you know, again, my age is showing I am concerned about privacy with things like Alexa. And I think our use of the tools is going to happen faster than we put limits or guidelines. I think that's a problem for our field.

John: Right. I do think in ASTM, we need to start addressing the use of some of these new technologies and some of the documents and also thinking about how data should be managed. I mean, that's another topic. But not to interrupt you, so please continue.

Christine: I absolutely agree. Colleagues and I were preparing a talk about the state of our profession and what we need to stop and start doing. So I picked my topic was to define what a profession was and what it means in sensory. And one of the essential elements of a profession is that you have ethics. So we do not have ethics, a document that represents our ethics.

John: That's very interesting.

Christine: So yeah, that was something that I learned. Anyway, that will be next year's IFT. So, I think all those process tools are great. But I think the downside again, all of these tools I think have a double edged swords. I think on some level, there's a distance that's created between the experimenter or the person responsible for the study and what the data really are. I mean, if processing data as closely as we used to do 20-30 years ago, you had a good sense of what the data are. And, you know, you looked at the columns, you did some validation, you checked rows and columns. Now, I think we could do that much more efficiently now. But I think the pressure to be productive, to do many many tests has made us not necessarily check road totals and columns. And does this mean make sense or you know I don't think we've got data cleaning or reviewing the way we did 20 years ago. I also think when I'm having a dark day that these tools that have helped us be more efficient and collecting and processing data has for some people led to what I call sensory meals, sort of like people who get on a wheel that that goes so fast they just churn out study after study because they can process it and they can collect the data without really stepping back and saying, what value is this adding? Should I be doing this volume of work? You know, there's sort of this there was a speed in the field that I experienced as I ended my career that I thought, you know, how do people have time? I hardly have time to think about what I'm doing, what's valuable. I'm on to the next new study or there's a new initiative or whatever. And I've seen departments that just churn out a phenomenal number of studies. But to what value or to really adding value to the company? I'm not so sure. And I think some of that was lost, so I think that's the downside of this process tools. I don't want to go back, but I want to really use them wisely to keep eye on what value they create. And the value is we can do more faster, but it doesn't necessarily feel better. We are not doing better unless we are really looking at what we've collected. The other problem I have with some technology is it distracts us because it takes us away from the front end, which is the conceptualization. And sometimes, you know, as a psychologist, I was taught what you're independent variable? What's your dependent variable? What's my hypothesis? What's the relationship? And I don't know how much sensory people again, most a lot of the training is food science. But I don't know if that's the thought pattern that sensory people go through setting up a study. But I know if you have a fancy tool or something cool, you can do or some technology. Sometimes people drift to that or say, well, let me use this and I just switch if it's the appropriate thing, right? And the last piece that I think this is where sensory is really adding value is in the interpretation of the sensory outputs. I don't think technology at this point is helping us at all, and that's where, again, that's where our biggest value add is. You know, the so what what decisions are we going to make if it's a business or what did we learn or how do we advance the method or, you know, what value does this particular sensory tests create? I don't think technology helps us at all. And I don't know what your thoughts are on that.

John: It's interesting. Let me challenge that a little bit. But before we go into that, I would like to just hear your thoughts in general on when someone asks you within a business context, what's the value of sensory? Why should we fund this sensory program? What are the sorts of answers that you get? What do you see as the ways that sensory contribute value with business people?


Christine: Well, I think what sensory can do or does do or should do is give companies some real information, some objective information about what the consumer response is and what's perceived in their products. So this link between sensory attributes or response to a product in the consumer or a perceiver, that's really the territory we own. And nobody else can do it the way we do it and we can do it objectively, which I don't think any other applied science does. And I think we can do it subjectively, although I think we wouldn't say be playing footsie with market research and the consumer of the product, but I would say it's sort of not a proxy war, but that territory is under dispute, shall we say, the response to a product, the subjective consumer response.


John: Or you access come along to user experience, of course. I mean, I think there's a lot of overlap between user experience and sensory, actually, so when you get into the tools from design but anyway, please continue.

Christine: Yeah, user experience is that a formal way of saying....

John: Well, UX has sort of come up really in the tech world as the people in the tech sector have realized that they need to understand the consumer experience from people on an app or on a website that kind of thing. How should they design the app or the website? So it's to give the kind of religious experience. That is actually has many overlapping concepts with sensory. Well, that is a lot like sensory, isn't it? And so many of those tools, I think, come up in different guises.

Christine: Absolutely, and I thought that exactly when I listened last year to the gentleman from Dyson talking about how they were making a hairdresser. And I thought, this is sensory, this is just putting together a different sources of information, different ways of measuring, different sensory cues. The talk was wonderful, but it also made me worried about sensory. Are we still talking about central location tests where we have, you know, it made me realize that this way of designing products was broader than what, you know some people in sensory operate it was a broader context and we needed to perhaps train people and get people to think that way.

John: Yeah, definitely. I mean, I do think that when it comes to design, user experience and sensory, there is a lot in common. I think that what we have special in sensory is a deeper understanding of the human senses and a deeper understanding of some particular applications for sure. Certainly sensory is very versed in food and beverage and personal care products, that kind of thing. It is interesting, Thierry Lageat was on our show a few months ago and his company Eurosyn has I think, pioneered a lot of ways the use of sensory and kind of non-food settings like, you know, for the leather of a car seat or the you know, actually they're working on luxury jets. What should be the sensory experience be inside a luxury jet. These kinds of, I mean there are really design questions, actually. So I do think that there's a lot that we bring in terms of a deep understanding of the sensory experience of a product that could be seen through the eyes of design or UX. But I think we bring the kind of human psychology and also the human senses piece that they don't really maybe they'll do things a little more holistically, maybe a little more big picture. I think we have specialized tools that are really well-suited to taste and smell, and then you see texture and sound come in more. What are your thoughts on that? I know you spent most of your career with them at CPG, were you mainly worked on food and beverage? Is that correct?

Christine: Well, half of my experience was a non-food. I worked on Gums and Confections, then some personal care products, Listerine, but then I went to household care products, which we smell things, dish detergents, fragrance is a big deal and also the tactile experience with cleaners, as well as the appearance of the surface sheet clean. And then I went to edible fats and oils. So that was back to taste and smell and I probably got my classical training at Best Foods. You know that shalt always make your nine point hedonic scale. Well, you use these anchors and so on and it has the vertical, not horizontal and whatever. Don't forget, I came to sensory via answering an ad and being hired by my experience professionally and education was as a psychologist and I did extensive training in for formal education and the census but I can tell you 80% of that, maybe 90% of that was in vision, an audition. And yeah, we mentioned smell and taste and the cutaneous senses, but it was a much smaller part of my education about perception. But anyway, that's on the side. But then I went after edible fats and oils to razors and blades, and I can tell you there was no tasting there to nutritional beverages. So specialty products, nutrition. And we tried to build taste, but.....

John: And what was the kind of common thread in terms of your career, I mean, you've talked about that the scientific process of the, you know, the kind of the why and then how and then so what? I mean, what would be the big lessons looking back on your career that you would, when it comes to designing experiments, what are the key threads that you saw emerging regardless of product category?

Christine: Well, the design experience for me, I'm very attuned to it, because, again, I start always broadly and look at big picture, so I think at its very core sensories about measuring the human response to some stimulus. And the stimulus can be a consumer product, but it can be, as you say, the ambient noise in an environment. It can be the way a violin bow feels in the hand or the way a pen does. Again, the core is what's the human response? And then comes, what are you measuring? And maybe just the product or it may be something broader than that. So I'm very I think what the design experience people are doing is really what we're doing. They're just doing it perhaps more broadly and maybe with or without the tools we have. I just I don't see much difference. Again, I'm not a classically trained sensory scientist, so I don't believe that at our core, it's just analytical. I think what's similar is we shouldn't venturing things objectively.

John: Right. Well, that more in measurement, I think is really important. You know, my wife is a psychologist. She's a clinical psychologist. But it's funny, whenever I talk to her anything, she always wants to know the details of how the data were collected. And I think that definitely is missing with some of the rush to use technology for process automation or for statistical analysis, is there isn't enough questioning of where did this data come from? How are they collected? What do they really need? Actually, you know, we see that a lot with just coronavirus, that there's this question of what's the right thing to measure. Like you always have to focus on the measurement. So I guess that would be curious to know your thoughts on measurement and how do you approach designing experiments so that the measurements that you're taking are actually reflective of the kind of underlying concept that you're trying to quantify?

Christine: Well, I think measurement, I think you have to look not just at the tool or the method, but I think you have to gather as broad of information about what you're trying to learn as possible. So when I'm being tasked with a project goal or a question that I want to answer the answer with a sensory test, I probably go to my books. I have a professional library and I look about the topic in some of my books and sometimes, you know, I read a lot about the senses outside of just sensory text. I have all my site, many of which are classics. But sometimes there's a psychological concept or issue that I can look at. I have a lot of I used to teach experimental psych, so I go and poke around those and then I go on the Internet and then if I really am stumped, I have a collection of friends in the field that I chit-chat with just to get a different perspective. So that's kind of my process, to start conceptualizing what I would do. And then I also look at, is this a meaningful measure I can critically evaluate? And if I disagree with some of my people I chit-chat with, it forces me to really dig deep and to think about does this make sense? So that's front end process. Again, I firmly believe in all the tools that help us in the middle part, which is the implementation, all those speed efficiency, real time tools. I also think anything that's done iteratively in sensory like tables or writing reports that should be as automated as possible. You can't replace the human for the interpretation or the conceptualization very well, unless it's a standard type tests of what we used to call a bread-and-butter test.

John: Right. Quality control or something.

Christine: Yeah. Something, you know, a standard scrims type of test. I don't know if there are any of those anymore. But anyway, I think the technology to create and I never had that within the companies I worked in, but to create tables and graphs, I had colleagues who I knew had automated some of that process. And I thought, gosh, I wish I could get that done. And also the tools and I don't know what they are specifically, but to aggregate data, because I always tracked the consumer response to our prototypes and when I have the resources to hire a statistician to aggregate, I did. But to have that done automatically, to be able to aggregate and do meta analysis, I know those tools are available and I wish it had those when I was working in industry.

John: Yeah, well, of course, I mean, I'm a big fan of I mean, the acknowledgement of graph databases, that's kind of thing. That's another topic. I mean, I think there's good infrastructure out there. Well, Chris, you know, we are actually, amazingly almost out of time. I do want to get your thoughts before we're done about what you see as the exciting new technology? You've mentioned a little bit like the fact that we can use technology now to collect data in new ways, that we have, for example, smart speakers or, you know Stan Knoops from IFT in fact, was on the show and he described a tool that they developed in partnership with Blue Yonder, where it's a clicker where when they throughout the day, any time you smell the fragrance, you could click this device and it would capture kind of throughout the day somebodies experience with a fragrance. So it's kind of real-time in the moment low friction, data collection. Obviously, there's all the Internet. And I think social media on the one hand it's convenient because there's a lot of data easily available, on the other hand it's not clear that it is in fact, reflective of the measurements that we would like to make, right? Because there's a big bias in terms of who's posting on social media. Are they even representing their authentic self? I mean, there's some, I think, real questions about social media. But when you look at the kind of available technologies, what gets you excited in terms of new ways of collecting data that you would have liked to have had access to once upon a time questions, you would like to investigate that maybe now you can use technology to investigate?

Christine: Well, I think Alexa is a great way to collect information about non-food product, possibly food products. But when I was in the household cleaners or the personal care arena, you know, the whole idea of having people come in and shower or use products. I think those kinds of real time in-home tools should help the collection of data for products that the people use in their home and doesn't make sense to have, you know, a bag of dishwashers or a bag of laundry machines or, you know, to ask consumers to come in and shower and use the shower gel. So I really I think those kinds of tools are great. And I think the video tools where if consumers are willing to be videoed or show how they use the product, I think there's lots to be learned that way. So those tools I'm very happy with and I would assume that they're going to really accelerate what we learn about those kinds of products.

John: What do you think about the use of things like Zoom or remote interviews, that kind of thing?

Christine: We towards the end of my career, I looked at a number of focus groups that were video, and I think you get 60-80% of the information. The problem is if you're watching it after the fact, you can't say ask this question or you use some of the nuances. And I don't know, I think some of the underlying tone emotions and the visual facial expressions, you lose that.

John: Yeah, non-verbal. So that's very interesting.

Christine: Yeah. I think if some of the general learning you're getting, so I'm okay with that, I don't know what to substitute.

John: Yeah, this is a trade off. I think there's a scalability. Right? There's the fact that more people can participate now because they don't, and in fact, in some sense, it's more inclusive. Right? Because you now don't have the limitation that only people who can come to the central location at a given time are able to participate. So I think in that sense, it's good. Yeah. So it is a trade off. Many of these things are trade off and it's hard to find the right balance. So, Chris, this has been actually quite fascinating. I mean, I find your passion for science to be very inspiring, that you're really interested in making sure that we're conducting the science, that we're not just going through the motions. Now phrase I think about often is John Wooden, who, as you probably know, he was the coach of the UCLA basketball team that won like 11 championships or something. And he would say never mistake activity for achievement. Just because you're doing a lot, doesn't mean you're accomplishing anything. So I think that's a good kind of connection. And I definitely share your desire for us as sensory scientist to focus on science rather than just turning out outputs instead of just participating in sensory. So let me ask you here before we wrap up, what are the piece of advice that you would give to a young sensory scientists just starting out in her/his career in the field?

Christine: I think I have probably three. One is get an internship, don't go from your academic, your formal training to industry without an internship. Get some practical experience. Probably the second one is take an experimental psych course. Nobody should be in the sensory field without taking an experimental psych course, because that what you're doing. And probably the third one is take more statistics.

John: That's what I hear from them as well. That's good. I agree with that for sure. And I would add to that data science. I think that it's important for people to learn some basic coding for the sake of automating.

Christine: Yeah.

John: Alright, Chris, this is wonderful. So if someone wants to reach out to you, how would they follow up? I mean, I think wealth of knowledge and experiences.

Christine: I'm on LinkedIn so people can send messages via LinkedIn.

John: Okay, I will put your LinkedIn address in the show notes so people can just click through it and find you that way. Alright, Chris this has been great. Any last comments, bits of some words of wisdom, anything on that?

Christine: Well, I really appreciate your sharing with me data, you know, data science and some of the new things that are happening. And I hope when I see you in meetings that you will continue to keep me refreshed because I do, you know, in spite of my reservations about some of the technology, it's really I think there's a lot of advances that we can achieve if we use them properly in our field.

John: Yes, I totally agree. They're simply tools and they can be used for, you know, to root the field or distractions. Okay, great. Thank you so much, Chris.

Christine: You're most welcome.

John: Okay, that's it. Hope you enjoyed this conversation. If you did, please help us grow our audience by telling your friend about AigoraCast and leaving us a positive review on iTunes. Thanks.

That's it for now. If you'd like to receive email updates from Aigora, including weekly video recaps of our blog activity, click on the button below to join our email list. Thanks for stopping by!



©2020 Aigora