Stella Salisu Hickman - Press the Green Button

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Dr. Stella Salisu Hickman, currently Vice President Sensory & Insights at Brisan Group, has over 18 years of experience in the flavor and fragrance industry. Stella holds a Doctorate degree in Organization & Management, a Masters’ degree in Biochemistry and a B.S. in Analytical Chemistry.

She started her career at IFF. From there her career led her to sensory management at Coca-Cola, to building a global sensory program at Martek/DSM Nutritional Products, and an international opportunity as Global Sensory Director at McCain Foods.

Stella’s love for fragrance led her to pursue a role as Senior Director of Fragrance Development with Belle Aire Creations where she developed winning fragrances and created programs associating instrumental correlations with different scents.

Stella’s strengths include building sensory programs, trained panels, facility infrastructure, insights that lead to product innovation, and correlating sensory findings to analytical instruments.

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Transcript (Semi-automated, forgive typos!)

John: So, Stella, welcome to the show.

Stella: Thank you, John. It's exciting to be here today.

John: Oh, that's great. All right. So, Stella we were talking before the show about, you know, I mean, obviously the whole pandemic is affecting I mean, it's affecting the whole world. It is certainly affecting sensory. It's affecting our ability to do central location testing. And there are really some unique challenges when it comes to descriptive analysis. I know you have some really interesting thoughts on, you know, adapting descriptive analysis to a kind of decentralized paradigm. So it'd be great to start the show hearing your thoughts on that topic.

Stella: Well, thank you again for having me on the show. I think we all know that descriptive sensory from a foundation is one that involves having a group of panels depend on a type of descriptive sensory, group of panel, a panelists together to discuss talk about programs, to talk and discuss about products. Now that we are in this new climate where it's all about social distancing and virtual space, there are still some descriptive things that we can do via Zoom or any type of virtual media. I think where the struggle now comes and where we sensory professionals need to start thinking about how to overcome this is where we have products that are not temperature safe. So, you know, temperature that need to be heated up, need to be fried, need to be cooked. There are certain aspects that are required. You now in homes, even with descriptive panelist, we all have different types of appliances, kitchen appliances. We don't have the restaurant style or industrial style equipment. So I'm wondering what we can do in that space to ensure that when we're doing evaluations, all the panelists are seeing the same product pretty much when their product that are involved with cooking, you know if you're doing a burger, if I use my grill at home and somebody else uses their grill, how would we be able to say, okay, we're cooking it the same way or we're using the same instrument. You know, our companies going to start figuring out a way so there are two ways to look at it. What companies say, well, maybe just measure temperature and it doesn't matter how it's cooked, which I don't think is the right answer, or will they now will we have to now make descriptive more expensive where we're, you know now hiring food trucks possibly that would be parked in front of some panelist's homes? You know, so these are some of the things that we actually have to think about from a sensory professional standpoint. I think ASTM is a perfect plug for us to start looking into methodology that will allow for virtual platforms, for descriptive sensory programs that would involve foods that have temperature sensitive mechanisms to it. So it's something that I've been struggling with from a vendor space where I'm able to do virtual for room temperature products, candies, liquor, beverages, all that I can do from a virtual space. You know, granted, there is that Internet that you have to worry about, but that usually is overcome when you have a hard wired plug in. But still, you know, it’s a lot to really think about. So we really have to be diligent in putting together some form of methodology now. We now have to start evolving with the world because I don't see this pandemic going anywhere. But work still has to get done. And we have to ensure that one, our panelist feel a sense of safety and if it's them being in their home, in their space, we need to provide the necessary equipment for them to be able to do whatever it needs to be done. I know that with this pandemic, especially cases rising up, there are some panelists that don't feel comfortable coming into the facility. So what are we going to do with products that require descriptive sensory? How are we going to do that with products that require a special kind of equipment that is not necessarily a home appliance, but more industrial appliance?

John: Yeah, this is also fascinating stuff. For one thing, I had never really thought about the bias that you might be getting into nowadays. If you do have still centralized location, that you are going to have the selection where some people are comfortable coming in, probably if they're younger or lower risk, etc., and you're going to now have potentially biased data. So that's something that people should definitely be watching out for. Right? Even if you are able to get your numbers up in a central location test, maybe it's not the same people, right? Maybe it's not the same population because now you've got some groups of people that are more concerned than others about the virus. Right? So that's interesting. Another idea I'd like to kind of get your thoughts on is I've been hearing about this idea that a decentralized location test, which is you know, like with a food truck idea, maybe you send food trucks out around the city, you have a food truck, and there's some locations throughout the city where people can come. The testing might be outside this kind of thing. I mean, how do you see this, but I know that it's something you're interested in is historical data. I mean, we're going to collect all this data in new ways like what do you, how do we even make sense of this? This data that's now collected in a kind of novel, in a novel environment? What are your thoughts on, what should we be doing in order to know that, you know, what we're measuring is relatable to the past?

Stella: So I think one thing I think we have to start right? We have to start collecting data. And if we can look at some of the historical products we've tested, if they're still available, maybe start to test them in this new environment and see if there are trends, you know numbers may not be the same, but are they trending similarly? So if the trend is similarly in that space, then we feel comfortable with saying now that we have this decentralized way of testing, that at least we feel comfortable in saying, based on what we've done in the past, we now see that testing this way. You know, there isn't that much bias to the data and it's relatable to what was done in the past. So I think we have to press to start by. And I think we need companies to be that, you know, front and looking for new ways. And it's going to be very, very difficult to convince companies to be able to look at data that way. But we just have to start, I think, coming from a supplier side, perhaps we just take the on and say, look, we've done some homework in our backyard where we've done some decentralized type testing and we kind of related it to some of the words that we've done in a centralized location tested. And we found that there are similar in how they trend with override or descriptive data, et cetera. So we have to press the green button to say, let's do it. I think that's a great idea. But I think companies have to feel that level of comfort to say now that we're in this new world, we now have to start looking at new ways. And that’s a good way to start. So I would be open to testing that way to saying, you know what, I want to see what we did in the past. Let's test products that we've done in the past from a CLT standpoint or from a descriptive standpoint. Let's do it in a different setting and see how data is trended, right?

John: Definitely. Yeah, that's really interesting that just directionally, because actually a lot of the times for our models, for our insights, it's true sometimes you have historical benchmarks that you're trying to target, trying to hit or whatnot, but a lot of the time is the directional effect that matters. This product is higher than that product or this product is like more like you said, or maybe the Delta. But it's yeah, as long as you're getting preserving the order of things, then I think you can have some confidence that what you're collecting is essentially the same information, just maybe in the new form. Yeah that's a really good idea. Okay, and so, maybe some people maybe not as familiar with Brisan Group. Maybe you could talk a little bit about what you all do there and what your role is, the kind of projects you typically work on.

Stella: So Brisan Group is a market research facility actually that has a whole arm to it. The owner, Brian Vogt actually acquire product dynamics. And Brisan group is a subsidiary of different small businesses that he has. He has a development farm to it and he also has an ingredient supply side to it, too. So I would say Brisan Group is one of, I could feel confident in saying it's probably one of the companies that have a little bit of everything involved in it where others don't want to compete in that space, where the supply of ingredients, it also has a development arm to it. So we work with clients not only from a renovation standpoint, but we're able to assist clients in doing innovation type want work, front-end type work because we have a development piece to it. We also have a large facility that allows for consumer CLT's. We were able to do focus groups, all of that. So we're one. I think we're a little different in how we provide research to companies. Brian is a very smart man where he loves disruptive type sensory. And I think that's why he and I get a lot where we recognize that you still have to go traditional, but also with all these small businesses, with the fact that people are looking for quick and efficient type of sensory methodologies, we're able to provide those type of methodologies and or services to organizations across the globe, which is great.

John: So you're really kind of multidisciplinary. It sounds like...

Stella: Oh, yes. And my role there is I'm the VP for Research, as you indicated in my bio, but is provide work with clients across the globe, while in the US for the most part in providing sensory services or consumer services, working with them, either from an innovation standpoint companies from chocolate to beverages to food, even some companies we work on non-food type work with them.

John: Yeah. Now, I actually really think there should be more sensory in the non-food world. It's kind of, I think an artifact of history that so much sensory is...

Stella: Absolutely. You know, food everybody has to eat, right? So that's probably why sensory is more important. Well, I wouldn't say more important. It seems to be more prevalent in the food space. You know, not everybody has to take a shower and everybody has.....So, yeah, it is important that we start looking into developing more and more and more programs to support sensory products in the non-food space.

John: Yeah, definitely. Okay, so speaking of that, I mean, you're someone with a wide background. Whenever I have someone is on the show who has such a diverse background as you have, these interesting kind of you know, kind of trace through your career, could you talk to our listeners a little bit about the changes you've seen? I mean, this show is really about new technologies and sensory consumer science. So how have you seen the field evolve, change, embrace new technologies? What do you think we should be doing more of, you know, based on your experience?

Stella: So I think one of the things that so when I started sensory, I would go to my what I would call my sensory bible. This is the Gail Civille Sensory Evaluation Techniques book, which is a great resource. And I've seen it evolved as far as different editions are concerned. And I see that one of the things that you've been doing is introducing some type of artificial intelligence space to it. I think that needs to be more of that. I think we are used and I think I fall victim of that is I'm used to this traditional way. And more and more, we need to start opening up into other spaces in how we see sensory. So, for example, descriptive. There are different kind of descriptive methodologies out there. How do we take all of that seminal knowledge and create something quick and easy for users to do? You know, from a CLT standpoint, we all stick with, oh it has to be end of a hundred, end of this and of that to be meaningful. Is there a way that we could do something where it's fewer numbers? Are there things that we can do from that space? Right now, I think all of the sensory professionals will probably be screaming in your head saying, what is she saying? But I think as we start to evolve more and more, we need to be open into providing, you know, really solid research. But then fast, quick, easy enough to feel confident in saying if we have a certain subset of consumers, we feel comfortable with either launching a product for trial, obviously, depending on the kind of risk that a company is trying to take. So I think the space that we need is evolving methodology has this continues to evolve? You know, we are I would say I'm definitely not a millennial. But as we're starting to introduce more younger professionals into the industry, you know, grant them in the foundational knowledge, but then start to open up into other areas of opportunity where we can drive innovation, drive thought leadership from a hybrid methodology where we're not it has to be black or white. Sensory has to start evolving into more a great area, you know, where there's still solid research. But it's not the traditional way. It has to be a disruptive way. And that's why my boss and I kind of gel Brian, where we're looking into disruptive methodology, into creating fabulous products out there. So to answer your question, there's a lot of work that needs to be done from our standpoint with finding new methodologies that's grounded in traditional and seminal knowledge, but enough to be flexible that users can feel comfortable when they can afford traditional solid research, not even from affordability standpoint. But they're looking for a quick and easy way to launch product or to get information about their products and all.

John: Right. Yeah, because there's a time component to. It's not always money that's limitation.

Stella: Right.

John: Now, that's fascinating. A lot of things in there that I'd like to respond to. One thing is I think that we have tenet as a field to be kind of methods driven, right? And I really like what you're saying about being a little more flexible and more adaptable. I think some of these questions are experimental, where you can look at historical data and you can say, okay, suppose that we were to randomly take subsets of our data and do the same analysis? Would we have gotten the same conclusion? What sample sizes are really needed? In different arenas? Maybe there are situations where the differences are small enough. You would need a reasonable, large, reasonably large sample size. But yeah, I really like that. I think that's really interesting. So, okay, well that's great. What about data collection technologies. I mean that of course something I'm interested in. I mean I'm a big fan of the smart speakers. We're looking at other, I've gotten really into computer vision lately, actually have had some interesting conversations lately where see how much you can learn from pictures. You probably can learn a lot from pictures. What are some of the things that you're thinking about in terms of new technologies you're excited to start experimenting with or maybe that you've been using?

Stella: So I know that I have not, like I said, I fall into a traditional mindset when it comes to, you know, data collection methodologies. I would love to see, you know, like an Alexa, Siri do some type of descriptive, you know, over time. I would love that, you know, but I don't know how that would be possible if there's a taste component to it, right? So I've seen a lot when it comes to filling out surveys, you know, and I like the idea of Alexa and I think you introduced that. I think we had a series with you where I think we saw with Alexa doing some survey data, somebody did a presentation. I can't remember who did what. So I thought that was great. You know from an online survey standpoint and having consumers fill out data, some taste an element where they taste a product and then fill out have the Alexa compute that. I think I want to learn a little bit more about that, to see how that might be, how I might be able to adapt that into what we do regularly. I know, Brian, my boss has consistently said we need to find new ways of doing things we have over the shoulder. How can we, you know, have over the shoulder do stuff with this and all that? So I think it would be great to see a machinery help collect information as well. Obviously, there has to be that human element and maybe it's the human dictating to the machinery to be able to collect the information. But making sure I'd like to see data with human dictated to machinery collecting data and historical data on human actually doing the data collection themselves and seeing how they relate before I become really sold to it. But I'm interested in that idea and I'd love to see how that would work in a descriptive mindset.

John: Yeah, that's really interesting. And just to make to kind of make sure that I give credit here to everyone involved. So the talk you're talking about was from General Mills. That was some pilot research where we compared the smart speaker based surveys to online surveys to traditional online. And it is interesting to get back to what you're saying about directional effects, because we found very consistent directional effects. The scale uses was just different. And really, I think you have to change how you, like I don't think it's either war. I think you can have a survey where it's online until there's a point where you're at the product evaluation, ask a few key questions and then go back to online. But I kind of want to probe a little bit different, a little bit deeper into what you're saying about the descriptive. So, yeah, that's really interesting. I mean, the benefit of a smart speaker is someone can be eating something and answering questions.

Stella: Absolutely.

John: Hands, they've got, you know, like barbecued chicken. Their hands are covered in barbecue sauce and their answering questions. May they have headphones on? So what are your thoughts? I mean, it's interesting to hear you say there could be some limitations when it comes to tastes. What are your, I haven't really thought that much about smart speakers in a descriptive context. So what are your kind of reaction when you're thinking about implementing that?

Stella: You mentioned scales that think skills are important depending on the methodology that you use. How would you set up skills in that space? How would you tell it to measure to, you know, one of the descriptive methodology that I use is the spectrum methodology, obviously founded by the guru Gail Civille. How would you be able to tell it? Alright, on a 15 point scale, it's this, you know, how would you be able to name the attributes associated with it? Is it that you would have told the machinery or the smart speaker these are the attributes to look for? And how would you accommodate for a time during discovery when you're trying to discover a new product where even though you have a preloaded, a list of attributes and there are new attributes that you discover and doing discovery. How would you be able to speak to that? So those are some of the areas where there would need to be some a lot of work done to be able to accommodate for that, where it's not something that's already preloaded, but the ability to have some type of openness to a new attributes discovered, you would be able to tell it to account for that. That's just where I don't see, I'm not sold into that for a descriptive mindset just yet.

John: Yeah. That's interesting and I do think that is not the case, that every attribute you would need to evaluate in the moment, right? I mean, things like juiciness, maybe that's an attribute that you really would like to capture at the moment. What other attributes maybe, and certainly the visual attributes you can do that evaluation or on the tablet or whatever it is. Yeah. That's interesting. That's something we should talk about because, yeah, there are some strengths and weaknesses of the smart speakers. And so yeah, that's definitely interesting. What are some other things that you think about? What are your thoughts on, I mean of course, augmented reality, virtual reality, that kind of stuff. What is this over the shoulder that you're talking about? Is this is a technique of Brisan Group?

Stella: Oh, no, it's I think it's over the shoulder is shopping with consumers. It's actually a company itself and they use machinery to be able to tell the consumers what to do when the consumers are able to talk to it, to give it information around the experiences in the supermarket space and all that stuff. It's the company itself.

John: Oh okay, I see. Yeah, that's fascinating because, you know, that's going to blend with wearables, right? It's just a matter of time before you've got your Alexa glasses on or whatever, and it will be talking to you. Yeah, I'm eventually like this, the neurolink will happen and that will become side works. That's for the future. Yeah, that's interesting. And, so then what are some of the other thoughts have you all been doing focus groups on during this time? Is that something that Brisan group also..?

Stella: Absolutely. We've been doing a lot of focus groups in a virtual space and even face to face. I know I had to moderate one couple weeks ago. We all had our masks on. So it was a little different experience. And this because of the client that we working with wanted us to have we had already signed up for a face to face focus group, and we didn't want to disrupt any type of uncovering with an online platform since they were already coming in to do a CLT anyway. So it was a peel off from CLT. So it was interesting to do it with masks on. And we've been working with some of our vendors also from an online perspective and able to collect data with from an online perspective, with focus groups as well. So the online platform is definitely good for focus groups because, you know, especially when it comes to sometimes they don't need the food. If you're doing concepts and if you do need the food, obviously we make sure that your food that if it's a microwavable foods where the microwave send it doesn't really matter. We have it sent to them ahead of time and we are all talking about it. So it's great.

John: It's interesting. Yeah. It's exciting to think about all the improvements that are going to stick around even once the pandemic kind of recedes, hopefully at some point.

Stella: Yes, I know, whatever that is.

John: Yeah, exactly. We are actually almost out of time. I would I mean it's been a very interesting conversation. It caused me to think about a lot of things.

Stella: I like to give people something to think about.

John: So I always like to conclude with the question, you know, especially with someone like you who's got so much experience. If you're going to give some advice to a younger, sensory professional, what should they be working on, thinking about doing over the next couple of years here in order to make sure that they're set up for success into the future?

Stella: So one of the very things that I knew that was big for me is networking. I know I made sure that I inserted myself with sensory gurus, Gail Civille has been my mentor from the very start when I started to transition into sensory and I've acquired a lot of other mentors, you know I have Lisa Bach. You too sometimes I talk to you every now and then, but making sure that focusing on being a part of the sensory organisations, SSP being one of them. ASTM, although is very little. That's one space where I felt like I developed a lot of friendships from a friendship perspective, also from a career perspective, looking at all those gurus that have been there and making sure that I, you know, insert myself with them, call it bothering them or be my mentors, you know, reaching out to them. Don't be shy when you don't know anything. You know, talk to them, network with them, have them be that mentor because they love the opportunity to be mentors, to mentor someone. Making sure that you insert yourself in those picking the right career path. I know for a sensory you have to go through food science I think. I don't know, I did chemistry and I fell back in sensory. But I think networking is important. You know, being a part of sensory organizations is important. Being involved, even from the littlest point of view is very, very, very important. I think that's what has made me in my mind. I've been a little successful be having mentors and not being ashamed to say, you know, if I need help reaching out to my network, to say I do need your assistance, what can you help me with?

John: Yeah, I can agree with that more. I mean, be in motion, and have conversations with people.

Stella: Right. Be involved.

John: I totally agree to that. And, if someone wants to reach out to you, Stella, how can they get in touch with you?

Stella: I'm available on LinkedIn. I would love to share the knowledge that I have with anyone in the industry. So, yes, I'm on LinkedIn so they can reach me. I think Stella Salisu Hickman on LinkedIn so you can reach me on there.

John: Yeah, we'll put the link in the show notes. This has been great, Stella. Thank you so much for being on the show.

Stella: This is excellent. Thank you, John. This was great. You're doing a good job. I'm excited to see how AigoraCast will evolve over the future, especially now in the space. So I'm looking forward to new things that you're going to be doing.

John: Oh, thanks. You know, we're almost at 50 episodes. It's hard to believe.

Stella: Yes. Great job. I remember when you started just last year, right?

John: Last year. Yeah.

Stella: This is great. Thank you very much, John. Alright. Take care, bye.