Supriya Thote is the Director, Product Development, at Plantly. Plantly is a chef-created, plant-based food and beverage brand. She explores best practices for scientific project management, from methods for effective roadmapping, to getting the most value from product sprints.
This interview has been edited for length and clarity.
Aoi: Supriya, do you think you could tell me a little bit about your scientific background and your journey to Plantly?
Supriya: I’m a food scientist by training, but I didn't start there. I graduated with a bachelor's in chemical engineering and, while I was taking my classes in chemical engineering, realized I didn't want to be a chemical engineer.
I got a little lucky because I was doing undergraduate research work in converting vegetable oil into biodiesel. Many of the scientific articles I was reading were published in food science journals. So I got connected with the department of food science at the University of Arkansas.
I joined the department and got my master’s researching aflatoxins and rice. I wanted to research sustainability, and aflatoxins and stored rice are a major problem in countries like Africa and India. My research was a small contributing piece to solving that problem. It was very rigorous and made me realize I didn't want to get a PhD. But it was enough to drill down my basics in the sciences and build my work ethic.
Today, I work as the product development director at Plantly. Plantly is a plant-based provisions company. So we have plant-based products like oak milk, almond milk, coconut milk, plant-based crumbles, and plant-based broths. I've been working on commercializing them along with our team of wonderful chefs. The idea is to have a very clean label product available to customers. There are more and more customers asking for plant-based products, and the science for this is developing every day.
Aoi: You've worked at a number of companies in the food industry space in the past. Do you think the food industry approaches project management differently from other industries?
Supriya: I think how companies manage product development, and product management, is very related to how many resources they have at their disposal.
I've worked in the past at JM Smucker in their pet food division, so it had multiple labs, facilities, pilot plants available at our disposal. There were multiple teams for each line of the product. There was a dedicated project manager as well, assigned to those teams. Even the scientists were specialized, whether it was product development, process development or product research.
Now I work at a startup, and things are a bit different. Most people wear multiple hats, including myself, and you work with whatever you have. Usually, a method that doesn't require as many resources is preferred, but that doesn't mean that you're not trying to build in those guardrails for product management and project management into a startup. And that is one of my areas of expertise. I come into a startup environment like Plantly, and about 30 to 40% of my time is spent just building those resources and putting together tools to have a better project management process for product development.
Project management in the food world is, I think, a little bit different because the product is different. Like you're talking about something that is perishable in most cases. So you are working against a deadline. A lot of the project management in the food world is driven by the timeline and how you can source your ingredients, source your raw materials, get the time that you need at a particular plant on the schedule, and then build your timeline backward. Your particular raw material might be in Italy, and it's going to require 16 weeks for it to come to the particular country or plant you're planning to do your trial.
Overall, I do think the principles remain the same. A lot of the training that you may get to manage your product in just regular industry is also applicable to the food industry.
Aoi: Science notoriously has timelines that are very difficult to predict. How do you effectively roadmap for your projects while leaving room for error?
Supriya: You have to build time in for error. Expecting a trial or an experiment to go right the first time is the biggest flaw you can build into your timeline. So building some redundancy, and even planning to fail, is quite critical.
When food product trials are done, usually a margin of 50% is used. Let's say you assume it takes four hours to make the product, so you'll book eight hours and have enough ingredients available. You don't want to run out of materials to test and achieve your objective. What I've experienced is that quick sprints of smaller iterations of experiments are better.
It's important to prioritize, especially with the food industry. You can always make a better product. There is always room to improve. You can make it healthier; you can make it tastier; you can make it longer lasting on the shelf. There's always something that you can do. What is good enough? What are the top criteria that you need to meet?
The rest of it is nice to have. Once you have those two different buckets, then it's a lot easier to build that into your timeline because you know exactly what the objective is. And if something is on the nice-to-have list and it doesn't happen, then you already have that planning done ahead of time.
Aoi: You were mentioning redundancy and leaving room for margins of error. Is there a good rule of thumb for how much margin-of-error to leave? For example, I remember I used to be told by my lab manager just to estimate how long a project will take and just imagine it's going to take twice as long. Do you have any other similar types of best practices?
Supriya: If you have no idea where you're starting, doubling the timeline is usually a good place to start. But, let's say you've made the product five times, and you know what the product's supposed to be. If you already have a base formulation, plan 25% of extra time because you know what you're trying to go for. The 25% time is for delays in your ingredients coming in, or there's some downtime in the equipment – something that's outside your control.
At the early stage of the project, doubling your timeline is a good practice.
Aoi: Project management in the scientific space is interesting because so much of it is non-linear; it’s not like you can predict when certain experiments will have the conclusions you need. When you plan for these sprints, I've got to imagine that timelines change often. What happens when you don't finish your experiments in time? What happens when the results of those experiments result in you needing to change direction mid-cycle?
Supriya: That's the idea of sprints as well. Like you are incrementally improving. So you do one sprint, and it's not just trying it out and seeing if it works. The idea, usually, is doing something, and you're learning something. You take those learnings, and maybe it doesn't work again, but then you take your learnings from the first sprint and learnings from the second sprint, and you analyze those, look for any interactions, and do a deep dive.
At that point, either you learn that this is something that is achievable, but perhaps the effort’s too much, or you might learn that there are some things that are not achievable right now because the technology or the processes are not there, or you might learn that something is achievable.
As long as you record your failures and don't forget the lessons that your mistakes have taught you, it is always possible to innovate. Like when you're learning from these mistakes, you might be trying to make a cup of chai, but you might end up making the best cup of mixed protein drink. It’s being open to those ideas as you're experimenting on the bench job and digging into those learnings, and seeing if they can be applied to something else. Maybe you didn't succeed in what you were trying to do, but did you succeed at something else? When you spend so much time in the lab trying to solve a real problem, you've definitely solved something; it just requires digging to discover what it was.
Aoi: It sounds like the way you design your sprints is not so much on the successful completion of a particular objective, but the completion of a study or an experiment or studying the relationship between two variables or something. It doesn't need to succeed for the sprint to succeed.
Supriya: You might think that you're working on the formulation piece for the first 15% of the project. But you might discover that the formulation piece is quite easy, and it's the scale-up and the commercialization piece that's quite complicated as you go through the project. So having that flexibility in your timeline is critical because the original assumption, in my experience, is usually never true. There are always more wrenches that can be thrown into the process.
Aoi: What would you say are the key principles to better prioritizations?
Supriya: It's usually related to return on investment. Ultimately, our prioritization is related to, “How much revenue is it going to bring in? Is there a way to scale it up?” And depending on that, you prioritize your projects. It's hard to say sometimes, so this is where expertise comes in.
You can use industry resources as well. In the food world, we use Nielsen. Consumer Insights are very useful as well. Doing your own surveys is also a good idea.
Aoi: Where did you learn your best management practices? Is it mostly through these resources that you mentioned, or are there any books, courses, or lectures that you might be able to direct people to?
Supriya: I did a project management course at UC Davis. I would recommend that if you have the time, it does take a significant amount of time each week. The UC Davis course is equivalent to getting a PMP – that's another good resource for someone starting in project management; getting a PMP certification is still recognized in the industry.
Aoi: Are there any skills that you're working on today and trying to improve?
Supriya: As scientists, it's very important for us to continue learning. At the moment I'm taking a course with the Good Food Institute. It's the leading non-profit, and they have a course on plant-based foods and meat analogs.
I've been taking that because I make plant-based products, and I think it's important to learn the current science. And there's a lot of science in this world right now around plant-based or cellular agriculture, for example, that we weren't taught in school. It didn't even exist when we were in school. It was just happening in the lab somewhere.
And then the other thing I'm also slowly doing is getting a Six Sigma Certification. I work in processes, and it's still recognized as an industry tool. I think the statistical process is valuable in the food industry because it’s so much more scientific than traditional food – we're talking about using pharmaceutical-grade equipment to make products at this point. So having Six Sigma is something that I think would be helpful for bringing those practices into the food industry as we start scaling up these products that have rigorous quality requirements.
Aoi: Supriya, thank you so much for your time. This was a great conversation.
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