Mona Wolf - New Documents for a New World
Welcome to "AigoraCast", conversations with industry experts on how new technologies are transforming sensory and consumer science!
Mona Wolf is a consultant, speaker, and trainer in the application of state-of-the-art sensory techniques. Mona is the President and founder of The Wolf Group, Inc. a private sensory-consulting firm. Mona has over 45 years of knowledge, experience, and practice in the field of sensory evaluations and has served as chair for the main committee of ASTM E-18 on Sensory Evaluation.
Transcript (Semi-automated, forgive typos!)
John: So, Mona, thanks a lot for being on the show.
Mona: Well, thanks very much for having me.
John: So, Mona as someone I think we met at ASTM, is that correct? Do you recall? Probably Cincinnati or some such?
Mona: Yes, we did met at ASTM.
John: Probably ten years ago at this point.
Mona: At least that far.
John: So as someone who is you know a fellow ASTM enthusiast, a question that I have for you, to kind of drawing on your experience and then all that you see in your client work, what do you think are some new documents that you think are needed at ASTM that are, you know, things that are missing right now from all of the changes that are happening at sensory, especially the changes that are kind of driven by the new technologies?
Mona: Wow. There's so much new technology coming out simultaneously. It's hard to hard to stay up with it. I definitely think there is room, if not new documents to upgrade old documents, because so many of them I mean, go back to when I first got into sensory, there wasn't even a laptop or an iPhone. You know we were working of an aquated things like, you know, a rotary dial phone is awful. So I've seen a lot of the documents still talk about paper ballots and data entry, of which now is no you use anymore. I mean, only time you'd get a paper ballot is if your computers went down, heaven forbid, just the use of laptops and what we're doing right now can be utilized in collecting data from your consumer. You can do face time with them, which you couldn't before. And if they're using a home use product and you want to face time with them, you want to see where they're scrubbing their toilets and what their shower looks like or their makeup collecting all kinds of data through new technologies that are coming out all the time. We have to have those in our documents. Otherwise, it's too easy for a novice to say, well, we can't do it that way because it's not in the document. Well, let's say we sure can do it that way and make sure that the new technologies are included. So, yes, I think that many of the documents need to be updated. And there's going to be needs for collecting the do's and don't's for collecting data on new technologies like podcasts and on face time and other mechanisms. Data entry off of someone's iPhone. We have done some data collection for people trying new products that impact them physically, for example, changing certain biomarkers as their consumer needs. And a lot of that data is collected electronically so we can upload say something like a sugar monitor directly into our data. And we know it's accurate. And we know we've got good data that way. Which is far easier and better and more accurate than what we were ever doing before.
John: Yeah. That's interesting. Actually, I hadn't heard about it. So is this blood sugar monitoring that sort of data? That's awesome. Yeah. I mean, there's all these data sources that are coming in of course, all the neurobiological measures you've got. I mean, there's the facial emotion recognition, and you've got things like the blood flow. You know, just earlier today, I was talking to another supplier that I kind of working relationship with. And we were talking about how you can have surveys, we're talking about Alexa-based surveys, but that you could have someone talking and giving their opinion, but at the same time, you could be measuring the blood flow in their face. There's very good technology for trying to figure out emotion as a result of different muscle movements and blood flow and this kind of thing. And the amazing thing is that you can look at like if someone is, let's say, they're eating some food, right? And they're giving you their answers. If they're talking just naturally, you're going to get a lot more emotional expressiveness, right? Whereas if they are putting their numbers into a phone, that's actually the same thing as if they're just talking to you, right?So you're going to correlate the exact moment that they say something with the emotion that they're feeling at that moment when they're talking. So it's just so amazing, the comprehensive view that we're getting.
Mona: Yes. And I think that one of the problems that we've had in the sensory community from way back is getting honest answers from a respondent because, you know, people want to ask consumers very technical information about their product. And if you ask consumer what you like about a product, they'll say the flavor, the way it looks. But, I mean, you don't get anything out of that. Whereas if you use the technology to do eye tracking and facial recognition, you get passes. I want to place the tester. I want to give you an answer that you like. And you can get a sensation, a sense of whether or not they're giving you their honest feelings or giving you something they think you want to hear. And so using the kind of technology we're talking about, I think gives us much more accurate data and the ability to really understand who our consumer is and what they're looking for. And that is so critical when we're measuring consumers response, because there's what they say and what they're really thinking and trying to draw a correlation between that from a human standpoint is not very easy. But if you add the other technologies to that, we start getting a clearer picture of how they actually feel about a product.
John: That's fascinating. So, would you say then that ASTM should have, which we should start thinking about, should we have a separate document? That's a novel methods of data.
Mona: Oh, I like that idea a lot because I think there are so many people that are underutilizing the technology that's out there or not thinking about it. Have a tendency to want to always do it the way they've always done it. I would've been out of business a long time ago if I am doing today what I did 45 years ago, because it just would not work. So let's keep ahead of the game and make sure that we've got the technologies available and we're teaching the new people that are coming into the field various ways of doing it, especially if you talk about a novice going into a company desk. Having their first sensory manager or first sensory technician and they don't have any way of learning this, even if they went to school for sensory evaluation. I remember a lot of what I learned in sensory all those many, many years ago was going to ASTM meetings and being a sponge and listening to people like Dave Parian and founders in the field talk about how things were changing. And you look way way way back to when the 9-point hedonic was introduced. That was novel at the time. Now we're looking at much more extensive analytics that we're applying to the consumers response. So having technical data to add to those analytics gives us so much more room to jump off into new territory.
John: Yeah, I totally agree. I mean, we should say a quick step back because I realized we never actually defined ASTM. You and I, of course, are very familiar, but maybe you could take a second and just tell our listeners who may not be aware what is ASTM? What is it ASTM E-18?
Mona: ASTM is American Society of Testing Materials. E-18 is their sensory committee. It's actually ASTM International now. And you can think of it very similar to ISO, which most people have heard of. But ISO has a tendency to be more for the Europeans, whereas ASTM writes the standards that the U.S. government likes to use when they're evaluating products. And so E-18 is a sensory group. And we have written many very viable documents, such as the ad claims document, the group assessment documents, the documents on tasting fish oil and oils and testing alcoholic beverages. And now we're getting into many areas of non foods, like the oral committee that's working on toothbrushes and toothpaste. And we've even talked about evaluating the sensory methods for textiles. And so we're looking at going into that area. So it's people from all over. They're from academia, they're from corporations, and they're consultants like myself who go in and work together collaboratively to have a consensus document that we agree. This is how we're going to do this method. And we all work together to come up with the appropriate method. So it's a collaboration of I think it represents like 250 different units. And so we have a huge brain trust that we can pull from. That gives us the ability to put together standards. The one key on those standards is their living documents. So every five years they have to either be updated or voted that they are still current or they have to be discontinued or replaced with something. So it's a great committee for people that are new in the field to come because anybody can come to the meetings. You don't even have to be a member of ASTM. But come sit in and talk to some people that have been around for a while and have extra knowledge especially such as yourself with artificial intelligence. You are the kind of people that you meet when you go to these meetings. People that have different expertise than you do and are more than willing to sit down, have dinner with you or lunch with you and share.
John: Right. Now, I agree. I mean, ASTM has been great for me and I would recommend it. I mean, it really is like sensory kind of in the real world. You get to see what sensory like under battle conditions when you go and you talk to people as opposed to the kind of abstract sensory you might read about a textbook. You know, this is how like sensory and practice. And it's been a valuable for me for getting a sense of what is actually going on, what's really needed. And I think you're right. I think that something on new ways of collecting data would be very appropriate.
Mona: I was going to say, the one other thing that I think is very valuable, and it's a little off topic, but you also get to share with other people that are there how to talk about sensory to people that are not in the field, how to communicate your ideas to upper level management, how to sell the concepts of running a study and the value of this study. And we think just being practitioners is sufficient. You still have to sell it. Even if you're working internally in a company, you have to sell it to your management or the people that are your clients within the company. That's very important.
John: Yeah, I definitely agree with that. And I do think that the business relevance of sensory is something that's kind of always been spin. I actually think that we now have more tools are available at our disposal to help answer some of the questions of business relevance. But yeah, it's good communications very important. So if we continue on the idea of new documents, what else do you see? Do you see? So we need to update some existing documents and maybe even consider a document data collection. What about the analytic side or interpretation? Do you see a need also to develop something that help people to make use of all this new data?
Mona: Absolutely. Understanding how to put it all together is key. Data for data sake gives us nothing other than a big hunk of IT, you know, I mean, it doesn't really give us anything. You've got to know what to do with it. And not everybody can be specialized in every area. So I have a tendency to lean heavily on my friends that are statisticians like yourself and also my internal statistician, but we have to not only know how to massage the data, but we also need to know how to understand what the data is telling us. So I'm pretty good about once it's all massaged to understand what it's saying, but you depends on a lot of different expertise. So understanding the statistical part of it and we have some powerful statistical documents out there that are really helping us communicate good methods and some bad methods. I mean, telling you what's not going to work for you. And then also assessing the difference between various methods and which one is better depending on the risk associated with the project you're working on. So I think all of those and perhaps as a subwing of the statistical group in the committee, we might want to have, what do you do with it after you get it? You know, how do you understand it?
John: Yeah. I mean, there is a document on the instrumental measurements, you know, this idea of like how you analyze data that come from instrumental measurements. And I've been kind of pushing to turn that into a machine learning document. So I think that it is important that we just start talking about some of these techniques from data science that may not be coming from classical statistics, but that allow us to take data from many sources and aggregated in a flexible model. So I think that there's a lot of big future in that, to be sure. What is your what are your thoughts on other modes of data collection, such as are you all doing anything with augmented reality? I know that that's becoming more and more of a hot topic.
Mona: I have not done anything with that, but it does fascinate me. I've heard it spoken about at all the meetings I've been to recently at IFT, EuroSense, SSP(Society of Sensory Professionals). There's usually at least one speaker or one booth in with this fires that are talking about the virtual reality and how the environment where you're doing the testing and how it impacts how we assess a product depending on where we're located. Previously, and again, for many, many years, we were told to test a product pretty much in an isolated environment. Whitewalls, no noise, no smells, no sounds. And that's all well and good, except for the fact that's not the way the consumer is consuming it. Even even to the point of, you know, do you serve the peanut butter with a cracker or a piece of bread or not at all. And when I think about, say peanut butter and jelly sandwich, am I making it for my child or am I making it for my own lunch and I might eaten it at my computer. And how does that impact? How do I even think about what it tastes like? Or do it just functional and getting me through the day.
John: I agree. Yeah. I mean, the whole issue of ecological validity is really fascinating to me. I mean, I think obviously there are some tests for, say, quality control where you really would like to know. Like, for example, I think classical discrimination testing, different testing has its place. If you doing an ingredient substitution and you want to know you want to basically have a torture test to see, you know, is it possible to detect any difference between these products when we remove all the distractors? Okay, I think that's fine. But I think that you need to complement that with really ecologically valid measurements. And I think that's where some of this augmented reality. You know, you've got the hololens, I think, so Joanne Hort, for example, she was on the show talking about how they're doing testing with the hololens. Which is a way here. It's basically a visor you're wearing where you can see things that aren't there, but it can help to create an environment for the tester. Yeah. So this is all really exciting. So what else do you see, Mona as you kind of look around and your client work, how would you say things have changed over the last five years there at the Wolf Group in terms of the requests you're getting at the speed at which things are happening? What sort of changes have you seen?
Mona: Well, the speed is obviously. Can we do it tomorrow? You know, we don't know what we're doing yet, but it's okay just do it tomorrow. We get that all the time. So the speed is always there. Companies are now looking for new ways of testing that versus the way it's always been done. You have to not only be able to understand what the new ways are, but you have to explain it to them in such a way that they understand that it's going to have greater value added to them if they do it in a way that like in the virtual reality or the visor setting you were talking about. What it does do? I know I'm going to have pay for. But what does it do? How much more information am I going to get? So, you know, in our industry, there's always that combination of being good stewards of our clients money, understanding how to do things. But you can't get away from selling the product that you're producing because the client on the other end has somebody that's also signing off on the checks and they have to sell it to them. So you have to present a compelling story that says this is why this is going to work better for you. You have to have a really good understanding of using new technologies so that we don't just accept it and say, oh, yeah, that's pretty cool. Let's do it. Let's explain why we do it in such a way that it makes sense to the non practitioners that are needing the data and the information, but don't quite understand what you're doing or why. So you have to be able to explain that, too.
John: Yeah, I definitely agree. I think that's one of your strengths motto. What I've seen is your excellent communicator. And I think there's a couple of things that field needs. But I would say one of them is more communication skills. And the other thing I would say is more on the kind of data management side. I see a lot of need for us to tighten up the way that we organize our data. That it is definitely a challenge for us to go back. I mean, I can't tell you how many large companies that I've worked with where important data are not organized in any kind of way at all. They're just in different Excel spreadsheets on different people's computers. And if you are to try to go through and say, okay, what's everything you know about this category or this group of people or whatever? It's not easy to answer those questions. So I would put that at the other end of what we do. There's kind of like plumbing the infrastructure. And then on the very top, you've got the communicators. So I think that kind of we need to work on both sides of that. But Mona, we actually are amazingly almost out of time. So before we run out of time, I would like to see what are your thoughts for a young sensory scientist? Someone who is just entering the field. What recommendations would you have for them for the next two years with all the changes that you see happening? How would you advise such a young, enthusiastic, smart sensory scientist?
Mona: I would say, be everywhere you can be where there are other sensory people. If it's a local IFT group or a local SSP group, be there. Go to meetings, as many meetings as you possibly can. And just be a sponge. Find people that are passionate about their field and just say, can I talk to you? Set up a phone conference and talk to you. I know you're passionate about what you do, and I know you've been very generous with your knowledge, with many many people. And, you know, you and I can talk over lunch or dinner for hours and hours on this field. And I know you've given that gift away to other people, too. So my biggest advice to anybody would be, be a sponge with as many places and as many people as you can possibly be with.
John: Right. And I would actually build on that by saying that LinkedIn is a great place to reach out to people. You know, people reach out to me on LinkedIn and they want to just have a phone call. They want to know about AI and sensory or whatever. They are not necessarily like trying to become clients. They're just young people are curious. And I don't mind talking to people. I'm sure you're in the same way, Mona if someone had questions. Yeah. Then don't be afraid to reach out. I think that's a really good thing to talk about. So speaking of which, if someone wanted to get in touch with you Mona, how would they find you? How would they hire the Wolf Group to do some research for them? How would they get in touch with you?
Mona: Well, the best way is go to our website, www.wolfgrp.com . And you can type in the info line and it'll get to me directly or it'll get to somebody that can help you with your problem. But if you want to just type in, Hey, Mona, can I set up a phone call with you about ASTM or sensory evaluation or ad claims or whatever it is they want to talk about. Then we can get together. I've also had like you, many people on LinkedIn reach out to me and you know, just said, hey, what's going on in this field? And I think many professional organizations and links that you can be part of the better you are. And I'm going to add one more thing. Don't always go up. Pass it down to. Don't be afraid to go into the universities and talk to the students about what they're learning and being willing to speak in front of a sensory class and talk to those students. I have found in my history that I have talked to students in schools and colleges that later on look me up when they're professionals. So I think share both with people that know more than you and people that know less with you. Don't ever say I'm only going to look for people that can help me up. Don't be afraid to reach back and help somebody else up.
John: Well, Mona I think that's a great advice. And I think it's really inspiring that someone of your stature would be looking out for everyone in the field the way that you do. So thank you very much for being on the show today.
Mona: Thank you for having me. It was a lot of fun.
John: Okay, great. Well, see you at ASTM, Mona at Boston before too much longer.
Mona: I won't be long. I'll see you then.
John: Okay, that's it. Hope you enjoyed this conversation. If you did, please help us grow our audience by telling a friend about AigoraCast and leaving us a positive review on iTunes. Thanks.
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