[00:01:00] Rodney Apple:
Welcome back to the Supply Chain Careers Podcast. This is our new series, A Day in the Life of a Supply Chain Professional, where we interview folks that work across all the different functions, industries, and working in different size companies as well with the goal of cutting through the noise and giving our audience, especially those that are either new to supply chain or thinking about starting a career in supply chain, or maybe even wanting to switch their career into supply chain. Giving them real world perspectives through talking to others that are working in this fascinating and ever evolving profession. Today our guest is Aviva Kosansky.
[00:01:44] Aviva Kosansky:
Hi everybody, my name is Aviva Kosansky. I am a supply chain consultant at Profit Point. I’ve been with Profit Point for five years now.
[00:01:51] Rodney Apple:
So, we’ve got Chris Gaffney with us today as the cohost. I know you’ve done some work before with Aviva, so I’ll let you get started with the interview and looking forward to it.
[00:02:03] Chris Gaffney:
Now thank you Rodney, and again, welcome Aviva. We’re excited to have you with us. Of all the things I do today, work in supply chain design and optimization and the analytics that support that are a key part of that. And we’ve been fortunate to work together in some engagements with Profit Point. So I’d love for you to talk a little bit more about how long you’ve been in this area in terms of the work that we’re gonna talk about and really what got you interested in this space of supply chain.
[00:02:34] Aviva Kosansky:
Yeah, thanks Chris. So, I’ve been working in this for about five years now. I started my career not in supply chain. I was actually more in the finance world. And after years of that, I burned out and was looking for a new adventure. Supply chain has been something that has always been in the back of my mind. It’s been a family business for my whole life. And so, I decided that maybe it was time to venture into that, and that’s when I ended up at Profit Point. And after a few years there, I realized that there’s a lot of supply chain that I didn’t know and that led me to wanting to go back to school. And so, I went and I got my master’s in supply chain management from MIT. And then coming out of that experience, my capstone focused around network design and that really led me into wanting to build a career in network design. And so, that’s the path that I’m looking to take over the next foreseeable future.
[00:03:31] Rodney Apple:
Excellent. I think it’s a fascinating area to work in. And perhaps before we get going here, maybe you could give us the highlight reel of what is network design and what are the goals and objectives of performing those types of analysis and so forth.
[00:03:47] Aviva Kosansky:
So, formally network design I would say is that long term footprint of what does my long-term footprint look like. Whether it’s manufacturing footprint, warehouse footprint, Right? All of the above. What does that look like? And I would say in the past year or so, we’ve been exploring with even more short term, what does that network look like in the next year? And not necessarily over the next five to 10 years, but what does that also look like in the next year?
The work I do primarily focuses on manufacturing footprint. A lot of the focus is on where do I wanna open my plants? What products do I wanna make at these plants? Where are there plants that I could close over the next five to 10 years? And how do I optimize my overall network?
[00:04:31] Rodney Apple:
Very good. So very, very strategic aspect with a lot of analysis.
[00:04:36] Aviva Kosansky:
[00:04:36] Rodney Apple:
What does it really take from those building blocks and the foundation, the skills, both the hard, the soft skills, to qualify for a position, how do folks get into a role like that?
[00:04:48] Aviva Kosansky:
I think it’s really important to have data analytics skills. I would say that’s probably the number one thing that I would look for. Can someone really analyze data? Because, the way I see network design is that, it’s a lot in the details. And it’s being able to really dive into the details of the data and understand the nitty gritty, but not get lost in them, and still be able to step out and really see that big picture of how does that all play into the overall network and what is that balance and how does production and demand, and inventory and transportation and warehousing, how do they all affect each other.
It’s really having a strong data analysis background and skill set, but also being able to step out and see the big picture and analyze the data in a overview, kind of big picture way.
[00:05:39] Rodney Apple:
It sounds like you also have to be pretty dialed in on the commercial side of the business. Even up into the executive suite, where they looking to take the company, what new products might be in the works, are there any acquisitions on the horizon? And probably a lot of confidential information too that’s not shared with the public.
[00:05:59] Aviva Kosansky:
Yep. Absolutely. And it brings up a good piece that’s important and I think sometimes forgotten about, is you can run all these scenarios and all these models, but what’s the cost implication? Are you optimizing this to save a hundred dollars or are you optimizing this to save a hundred million dollars? If you make this change in your network, what’s that value add back to you as a company?
[00:06:20] Chris Gaffney:
Some of this work is ongoing, some of it’s project based, but how do you describe, in the work that you do, what kind of objectives are out there and how does that turn into what the day to day starts to look like?
[00:06:32] Aviva Kosansky:
Yeah. So I would say my day to day is a mix, I spend a lot of time in Excel and in the details and in the data. And at the beginning stages of a project, collecting the data, and going through it and cleaning it and, working with our clients on understanding their data. I think there’s a lot of value add that a lot of companies don’t always have a solid understanding of their data and the implications of it. So, spend a lot of time on that. A good amount of time in meetings. So, working with folks, I would say across the spectrum. So, it’s depending on who the decision makers are, who the folks are that get the data for you, and so helping understand how to collect that data and what data we’re looking for. You know, big picture, what are our goals for the project? What are the objectives? Presenting that back. And then, a good chunk of time, day to day too on then analyzing the data. So, I would say the process typically is there’s a good bit of data prep and data analysis that I’ll feed into an optimization model. You know, sit around while that runs and then, take the output and look at it, does it make sense, and start to tell that story from the output of the data to then present back to our client.
[00:07:45] Chris Gaffney:
Aviva, you mentioned in these type of projects, and I can tell you from my time at Coke, it kind of looks the same whether you’re doing it in house or you’re doing it as a partner with somebody. What’s the breadth of all those different functional team members that you have to interact with in order to get that full picture, to do the analysis, build the model, draw the insights out, and guide to recommendations?
[00:08:10] Aviva Kosansky:
I mean, it’s all over, I would say, Chris. And that’s the beauty of it. And I think part of what I like about my role so much. So, it’s kicking off a project, ending a project. A lot of times we will talk with global leadership across all functions. So, finance, operations, customer success, manufacturing. But then to really set the objectives and set the overall goal of the project. And then we start working with data analysts and IT folks, and finance and everyone across the board to be able to start collecting that data, running the models, and understanding the implications of it. The folks who work at plant managers. Is this how your plant really runs? Are we modeling this correctly so that when we look at a future scenario, are we capturing the differences? We wanna make sure we have a solid baseline, that the model represents how the company operates today, so that when we compare it to future states and future scenarios, you know there’s trust in the data, there’s trust in the model, and there’s trust in the output that these changes, if they were to be implemented, really would provide value and savings.
In terms of what goes into them, I would say step one is always determining an objective function. And then, what model you use and how you build it will come from there. Are you trying to minimize cost or you trying to maximize profit? And that will determine the data you need going into it. Some of it will be the same across both, and what you wanna ultimately get out of it. In terms of what’s happening kind of behind the scenes as the model runs, a lot of it has to do with the goals that are set for the project. What are the constraints you wanna give to the model, where is something where a customer always has to come from a certain plant or a product can only be made right at these three plants. There’s always gonna be constraints to the network that can or can’t change. So, defining those become constraints to the model and how it’s gonna optimize.
So there’s lots and lots and lots of them. And, part of being a consultant that I love is every company that we do studies with, those are always different. And also across industries, right? They’re different and then they’re also so similar. It’s how do you pull the similarities and how to use your experiences across industries too, to guide and help companies. And then, the meat I would say of what I do comes in is on the output side and is on the analytics of it and being able to understand what the model is saying. What comes out of the model? What are the decisions that it’s making? Where’s the difference from maybe how things are done today? What’s the impact of that? And then what’s the network effect of that? Because you know, a change here is gonna affect five, 10 other nodes in your network. And what does that mean to the business? And I think that that’s where it differs from maybe a pure data analyst role is really being able to tell that story and see how are these changes impacted if something moves from A to B, how does that change? It’s not just gonna change your manufacturing network, it’s gonna change everything else. Maybe inventory jumps up or jumps down because of it, right? Maybe your transportation blows up or gets a lot better. It’s not always bad. A lot of times hopefully it’s good. You’re going in a positive direction.
[BREAK at 11:39]
[00:12:04] Chris Gaffney:
What are the three or four things that you would really pinpoint as the most enjoyable things that keep you coming back to it every day?
[00:12:12] Aviva Kosansky:
It’s the storytelling and the puzzle solving, I would say are the big things for me, and working with people. Straight out of my undergrad I knew, I got an undergrad in computer science. And I have more of a technical programming background, but I knew I did not wanna just be a software developer. My goal was always to work with people from day one. And I would say that’s really true about this role too, right? I love what I do because of the people I get to interact with and the people I get to work with. And I can see the impact that my work has on them and on their work and the positive impact there. And to me, that’s really rewarding.
[00:12:46] Chris Gaffney:
We’ve been in some of the same environments and I think the intersection of that analytical piece and the people piece is you’ve got to take something that’s very complex and help guide a business leader to make a decision and you want them to be confident enough that the guidance is not coming out of a black box. That’s something I would add onto your list that I think is really valuable. And I would say, I think you do that exceptionally well. There are also some challenging parts of it. So, talk to me about a bit some of the challenges that someone would experience in this world.
[00:13:21] Aviva Kosansky:
At Profit Point, we have an approach that we take, which is to all of our projects, people, process, and technology. And we typically try to run our projects in that order, right? And it’s getting the right people in the room. And we’ve talked about people a little bit already. Who are the stakeholders? Who are the decision makers, right? And who are the people we need to help us get there? Defining the process. And then, what’s the technology that we’ll use? And that always comes last, I would say.
And I think a lot of times people think that the problem comes in the technology. But I will say where I struggle the most and where I think there are challenges, are in the first two and people in process. And so, where I think there’s speed bumps is if you haven’t defined who those stakeholders are and those decision makers are, it’s really easy to get caught up in a project because people may not wanna be making decisions or they may not feel like they have the authority to, and it’s easy to start spinning your wheels there.
So really defining that and knowing who those people are and making sure that they’re a part of the process then is really important. And then if there’s no process to get things done, it’s really easy to get caught up part way through it, and never be able to take that final step to finish the project, to finish the analysis and present the results. So, I would say it’s really those first two that can provide challenges.
A lot of companies strive for perfection, right? And for perfect data. And I think it’s also the understanding that we don’t live in a perfect world and there’s gonna be a level of tolerance when it comes to executional level detail. It’s, we can create this perfect plan five years out, and everything looks amazing, but then, other things happen in the world, natural disasters happen and everything gets turned on its head and you have to be able to adjust, right? So, it’s also creating a process that allows for you to be able to be flexible and nimble and adjust within your supply chain, and not focus on a singular perfect plan moving forward.
[00:15:28] Rodney Apple:
You’re coming up with some recommendations, often involving some enormous CapEx investments, right? Is it factoring in, in light of all the talent and labor shortages, is that data being included? Because what I have found in the past, especially recruiting and manufacturing, is that for some reason, and I don’t know who makes these decisions, if it’s some real estate or finance person, cheap dirt, let’s build a factory there. And then next thing you know, I’m called in to help staff it. And well, did anyone think about the labor market in this area? Does that go into the equation?
[00:16:05] Aviva Kosansky:
Sometimes yes. And sometimes as a proxy, and sometimes no. And when it’s no, it’s usually a big oversight. And I would say that comes back to the people piece of not having the right people in the room, right, making the decisions. In some models yes. It will be explicit. Especially if that becomes one of those hard constraints. Sometimes it’s just as proxies, right? So, we’ll use a proxy cost if labor’s gonna be higher in a certain area or maybe a little bit more difficult to acquire it, land might be cheap, right? But we try when we look at total cost, especially if we’re minimizing for lowest costs.
We’ll try and proxy some of this with caveats, so there has to be, I would say it doesn’t always get in the model, but as the analyst that goes through it, I have to keep those in the back of my head, right? Or I’m not giving a complete analysis.
[00:16:58] Rodney Apple:
Fascinating. It’s fascinating work. The fact that you get to cut across industries. Are there any particular things you want to call out in terms of those either nuances or differences as the work may change from industry to industry?
[00:17:13] Aviva Kosansky:
Where it comes in industry to industry, here’s a lot of commonality, right? Making product, selling product, it’s pretty straightforward, right. Doesn’t matter what it is. But what’s the special sauce in your industry? And I think that that’s where it starts to differ. It’s flow in, flow out, holding stuff in the middle, that’s all, that’s common across everything. But what’s that differentiator? What’s the special sauce within the industry that can make a company different or make them exceed?
But it really varies across every industry, and to me, that’s where the value is, right? That’s where companies can start to really save and differentiate themselves is if they can figure that out. And a lot of companies don’t, at least in my experience, and the ones that do are the ones that really become successful.
[00:18:05] Rodney Apple:
And I wanted to segue into a related question on company size. I’m just envisioning, I don’t wanna make assumptions to this, I’d love to hear your perspective. Large companies have these challenges, it’s inherent, but what about smaller companies or midsize companies, are you getting involved with even startups?
[00:18:22] Aviva Kosansky:
You know, challenges are across the board. Large companies definitely have them, and we work with a lot of large companies, but small companies do too. I would say the big difference is that it’s a lot more complex in large companies and in small companies it’s a lot simpler. And so, a lot of the smaller companies I’ve worked with, they don’t necessarily need a complex optimization engine. They need help with just simple demand planning, which we do also. And I love working on those projects too, because I think it’s also understanding when someone needs something complex and when someone needs something simple. And I think a lot of companies get caught in, and I think a lot of people get caught in the fancy technology that we have available to us today.
But that’s not always needed to get a really good answer. I’d say that’s the big difference, is that a lot of times in smaller companies we’ll build them simpler optimization engines that really get the job done for them. And it’s really rewarding to see that too, right? But it’s very different than some of these complex problems in big companies, but provides just as much, if not maybe more value, and so that’s, I would say that’s the big difference.
[00:19:35] Chris Gaffney:
Aviva, I know you in working with a lot of these companies, you work side by side with lots of team members who are working with you and carrying on some of those outputs. In your experience, for somebody who gets involved in this type of work, what does it prepare ’em to do? Where have you seen people advance? What’s your guidance for folks around if you invest in this space, it may help you get into other aspects of running a business.
[00:20:03] Aviva Kosansky:
Well, and I think it does exactly that, right? I think understanding the network, having a picture of financials of the company and the implications of the whole business. I think supply chain is unique. And why I really love supply chain is that it touches almost every function within a company. You get exposure and to do it well, you have to understand all of it, right? You don’t really get sucked or siloed into one. And I think when you do this well, you start gaining this deep understanding of all parts of the business, which really leads you to be able to take on more of a global leadership role, as you move throughout your career because you have a deep understanding of every part of the business and not just your one specific function.
It can sometimes be difficult, people who are good at network design and a lot of our clients we work with do move into those roles. And so, we see a lot of turnover, I would say, with who we work with, which is great. It’s great that it’s something that leads to progression in career. And we’ve seen that a lot.
[00:21:12] Rodney Apple:
Wonderful. Aviva, we’d like to just close with asking you if for our audience members or anyone that may be looking to move into network modeling, network optimization, network design, what would you advise to those folks?
[00:21:26] Aviva Kosansky:
I would say, find what you’re passionate about and really work towards that. I think to be really successful at it, if you’re passionate about data and you’re passionate about telling a story and solving problems, I think you have the ability to be really successful here. And that’s what this is. It’s a niche, the niche thing. But a really rewarding thing, to get a network model run, to analyze it, to see the savings, to pull out that picture, is really rewarding at the end of the day. And I would say to ask yourself, do you like solving puzzles? Is this what you like, that’s really what you need to be successful here.
[00:22:02] Rodney Apple:
So thank you Aviva, for joining us today and sharing your career and job insights, on network design, network optimization and planning. It’s been a very fascinating conversation. I hope our audience has gained some new perspectives. And on that note, if you think of anyone that could benefit, that might have interest or should be aware of this type of career path, feel free to forward the podcast. And if you’ve enjoyed what you heard, please drop us a good rating on your primary podcast platform.