University of Arkansas

Walton College

The Sam M. Walton College of Business

Episode 54: Marat Davletshin

Marat Davletshin is a PhD student in the Department of Supply Chain Management in the Sam M. Walton College of Business. Marat is a co-author of "Integrating Blockchain Into Supply Chain Management: A Toolkit for Practical Implementation."



More Episodes

Listen on Apple Podcasts
Listen on Spotify
Listen on Google Podcasts
Listen on Amazon Music
Listen on iHeart Radio
Listen on Stitcher

Episode Transcript

[music]

00:07 Matt Waller: Hi, I'm Matt Waller, dean of the Sam M. Walton College of Business. Welcome to Be Epic, the podcast where we explore excellence, professionalism, innovation and collegiality and what those values mean in business, education and your life today. I have with me today, Marat Davletshin, who is a PhD student in the Department of supply chain management in the Walton College, and he's doing some really ground-breaking research on the use of networks in understanding supply chain management. Would you mind telling me a little bit about what is a supply network?

00:50 Marat Davletshin: Sure, absolutely. A supply network is usually, it's a set of a firms direct and indirect contacts. It's direct suppliers, direct customers and their own suppliers and their own customers. It's like in our social world, we have friends, and those friends have their own friends, so we might even not know friends of friends but they, they are in our networks. So to me, it's not a supply chain, it's a supply network. A chain is a very simple network where nodes are sequentially connected to one another. So it's been our fundamental perspective for many years, and it has yielded a lot of fundamental insights for us as a discipline. But when we look at modern companies, it's really hard to imagine that each company has only one supplier and that supplier has only one supplier. So from what we see in our research, it's essentially companies, especially the big ones, they have extraordinary systems of suppliers and customers that are interlinked together. And we see a lot of stuff, not just physical goods, not just money flowing around those systems, it's also information, it's ideas, it's knowledge and it's power.

02:14 Marat Davletshin: So as we get data, and this is pretty much the first time in our history when we can get some idea about what those networks are, so we can measure and quantify those structures and we can see what structures facilitate knowledge diffusion or diffusion of ideas, practices.

02:37 Matt Waller: Now, as your research has shown, when companies understand the subtle nuances of their supply networks and the networks they're a part of, it can actually give them a competitive advantage. Could you give me a concrete example that would be, maybe not business-oriented, but something that people could really understand, a story or something?

03:06 Marat Davletshin: I think a good example comes from the early American history. On an April night in 1775, two men rode the same distance from Boston to Lexington. The two men were Paul Revere and William Dawson. They rode through the same number of towns, they rode the same number of miles, and they carried the same message that the British Army was coming to arrest the colonial leaders and seize the colonial arms and ammunition. So their goal was to deliver the message through the communities around, at Boston. Now, what happened was that Paul Revere, Paul Revere's message actually spread like wildfire. Now, William Dawson's message didn't quite catch fire, and what we see now is that Paul Revere has a statue in downtown Boston.

04:23 Matt Waller: Yeah, I have seen it.

04:23 Marat Davletshin: Right, we have a poem by Longfellow actually glorifying Paul, Paul Revere's Ride, but unfortunately nobody remembers William Dawson. So the evidence suggests that it was actually a network, so the network amplified Paul Revere's message and the same network actually kind of dampened William Dawson's message. And remember, it's the same message, across, very close, across the same number of towns. So, historians suggest that... Evidence suggests that Paul Revere actually thought in network terms. So, when he would come up on a town he would knock... He didn't have time, he didn't have much, much time, so he would knock on the right door. So he would warn just one person, or a couple of people, and then move on to the next town. But he would warn the right people. So he intuitively understood that those people would spread the message to their own contacts who would spread to the next town. So, in other words, somehow intuitively he understood the structure, the social structure of that community. It was a cluster structure and a lot of inter-cluster, cross-cluster ties. So, while William Dawson...

06:04 Marat Davletshin: So he thought about the network as one big cluster, Paul Revere thought about that network as a system of clusters connected through cluster ties. So he... Historian suggests, that he intuitively chose the right people, to deploy those across cluster ties and make sure that the message traveled through as many communities and towns as possible.

06:37 Matt Waller: So stock analysts perform analysis to understand and forecast firms stock prices, earnings per share, et cetera, et cetera, and they really are important intermediaries between firms and capital markets because investors follow their forecast and they compete with one another on forecast accuracy. Based on your research, do you think that if they did network analysis, supply network analysis, do you think they can improve their accuracy or at least know which forecast are more accurate than others?

07:12 Marat Davletshin: Absolutely, this is a great question. This is what we actually see in our research. We took all the data that are available to equity analysts for their analysis. Of course, they don't do network analysis like we do it. Yes, they are important intermediaries between firms and capital markets, and in fact, their forecasts can make companies flourish, or perish. And they are trying to understand what's going on around companies by diving deep into their supply networks. Now as they're a little deeper they are really confronted by complexity, because the further we go from the firm, the more and more companies we see in the network.

07:56 Marat Davletshin: So all those interconnections can really confuse an analyst, and we ask ourselves, does it really help them to go deeper? And our research shows that, yes, they can go deeper, but they have to be careful because some structures do facilitate some networks for example, cluster networks they do help analysts make better decisions. Now, small world networks in which clusters are interconnected by a large number of inter-cluster ties, they can really hinder the accuracy.

08:34 Matt Waller: So, an analyst could potentially study a supply network and say, because this firm is a part of this kind of supply network, my forecasts are probably not gonna be as accurate as they will for these firms.

08:50 Marat Davletshin: Yes, yes, and I would say that this is one of the actionable insights that this research provides. So when an analyst is aware that a company's network has a small world structure, the analyst must go to some other source because he or she would know that this structure can actually mask camouflage some important dynamics of [inaudible].

09:15 Matt Waller: So it's possible that a firm could be a part of a network... Supply network, that would make it hard to forecast accurately, And another firm, firm A might be a part of a network that lends itself to forecasting and another one firm B doesn't. So if I'm investing in firms, firms like firm A are kind of safer bets, 'cause they can forecast more accurately. Firms like firm B are less accurate. So maybe I should use options, an options strategy. Have you thought through those kinds of things yet?

09:58 Marat Davletshin: I think that the structure of a company's supply network definitely affects an investment strategy that you would choose when you are considering one firm over the other. At the very least, I think to understand how the company is embedded into the whole economy. You should do more research, you should come to the Walton College of Business and ask us how the company is embedded, and we'll tell you more. The best investment decisions must have some understanding of a company's environment and how it is embedded into its own environment.

10:33 Matt Waller: When you look at a company like Apple, which has an incredible market capitalization, they recently talked about upgrading some of their technology to be 5G enabled, and that affected their stock price. How did it affect their network?

10:54 Marat Davletshin: Well, I remember in March, stock analysts from Bank of America, Merrill Lynch, issued a forecast for... A very positive forecast for Apple and they cited supply chain stability as well, one of the reasons. Some other reasons were the employment of 5G technology, analyst cited supply chain stability as one of the advantages for Apple. Now that, just that news made these Apples stock price rise $20 over just a few weeks. Now, in the case of Apple that's billions of dollars, analysts do watch supply chains and supply networks of firms, and supply chain phenomena do matter. I think this example just shows how much does a supply, can a supply matter for investors, for a firms market cap.

11:48 Matt Waller: Well, you know, if you look at Tesla in 2018, they had an excessive amount of debt on their balance sheet, and it increased uncertainty and I don't know what it did to the stock volatility. Do you know?

12:03 Marat Davletshin: Actually, it increased Tesla's stock volatility, it significantly... It increased. And it became really hard for Elon Musk and Tesla to, to get money from the capital market because it became more difficult and costlier for them to obtain capital from the capital market because of the volatility and uncertainty around Tesla. So it was an interesting time, an interesting but difficult time for Tesla because on the one hand, it was experiencing problems with launching one of its newest models to the market, and at the same time, it had problems getting capital, getting money from the capital market because it was... Because of the uncertainty around it. Now, what Tesla did, and I think a lot of companies are doing this, is it started to pinch its direct suppliers. So when Elon Musk asked his direct suppliers to reduce prices, to extend additional credit, to allow late payments. Now, for suppliers who are dedicated to Tesla, it was a big deal and, of course, they tried their best to accommodate Tesla's request. Now to do that, they had to borrow themselves, and they had to pinch their own suppliers. So the uncertainty around Tesla actually proliferated throughout the network.

13:34 Matt Waller: Now, you've used some terms a few times in talking about different structures of networks, but how do you think about this, what are the terms you use to describe different kinds of supply networks?

13:50 Matt Waller: Well, in network theory, there are two major terms, a network is a set of nodes connected by ties, and nowadays it can be anything, it can be a firm, it can be a person, it can be a thing that is connected to something else or someone else. So a node is a primary building block of any network.

14:12 Matt Waller: Another term you use is average path length, what's that mean?

14:16 Marat Davletshin: Now, in any network there is a path from one node to any other node. For example, a path length from me to my direct friend is one, is just one step. The path length is, from me to a friend of a friend, is two. I have to... First I have to call my friend who would connect me to his friend. So, before I form a tie to the friend of a friend, the length is two. So the distance from me to the friend of a friend is two. What's amazing is that in our world, the average distance between all of us, between all eight billion people in the world is just six. We are separated by degree of six. It means, on average, it takes six steps to reach from one person to reach any other person in the world. So the average path length is just an average distance from any node to any other node in a network.

15:29 Matt Waller: And you also mentioned clustering coefficient, what's that?

15:32 Marat Davletshin: Clustering coefficient refers to... It's all networks within networks. Clusters are those dense communities of nodes, can be communities of firms, can be communities of people. They are densely interconnected with each other. In a clustered network, in other words, in a network with a high clustering coefficient, we would see those communities, a lot of those communities that are very interconnected with each other and sort of sparsely connected to other clusters.

16:08 Matt Waller: So these are some of the terms you used to describe networks. You also used the term hub, what's a hub?

16:15 Marat Davletshin: A hub is a very, very, very well-connected node. In the social world it would be, think about a celebrity who is known by pretty much anywhere in the world. In terms of supply networks, it would be Walmart or Microsoft.

16:34 Matt Waller: So what's the difference between a hub and a cluster, 'cause you've used those terms as well?

16:40 Marat Davletshin: I think the best way to think about it is, a hub is just a very well-connected node. In a cluster... A hub can be in a cluster as well. It can dominate a cluster but at the same time, a cluster can be just a network within the network, just a community, just a group of very, very interconnected nodes. Now they're connected together, to each other, they may not be hubs. A hub is a node that is more connected relative to others in the network. So a cluster may or may not have hubs.

17:23 Matt Waller: When there's more clustering of a firms network, does that have any impact on the accuracy of the forecast of the firms performance?

17:34 Marat Davletshin: Our research shows that it really does. Clustering can help analysts to sort of decompose a very complex network into several simpler networks. For example, think of a cluster as a group of companies around a particular product or around a particular manufacturing process. So in a network of a large firm we'll have firms from many different industries. So firms in each one of those industries would form a cluster around some product or some part or some manufacturing process. In this case, analysts can actually decompose the big network into those clusters and actually analyze them separately because most of the links, most of those pipes to which a risk can travel would be in clusters with very few cross-cluster ties so they can really catch the dynamics of... If there is something going on they can really catch the dynamics. Now, if there is something going on, they can really catch it, and they have time to catch it because that thing will stay within a cluster, it will not spread through many other clusters.

18:12 Matt Waller: Well, I know we've only touched on a small fraction of all the research you've done on this already, and it's very interesting, and really you're creating a new way to really look at supply networks. And I know this... What we were talking about is really just from one of your three essays in your dissertation, but I think it gives listeners an idea of how vast this area is, and this could easily be your career from a research perspective.

19:26 Marat Davletshin: Oh, absolutely. I think the way supply networks both enable and constrain companies outcomes, their profits, and their behavior, it's a very fascinating topic for me to explore. I think we don't know... We're just starting to scratch the surface of how networks affect companies, and we're just starting to realize that our world is essentially a network phenomenon. Think about how you met your spouse. In most cases, what happened was that somebody made an introduction. So initially, your most significant person in your life wasn't your direct connection. Someone closer to you, your friend, decided to make that connection. So if we assume that on average, we have 20 close friends and each one of those friends also has 20 friends, so it's 20 people one step away from us, 400 people two steps away from us. If they have 20 friends, that's 8,000 people three steps away from us. This is only about 8,500 people that happen to be connected to you, that your spouse actually came from. So networks have tremendous implications for us as people for our lives, and they have tremendous implications for companies.

20:52 Matt Waller: Thanks for listening to today's episode of The Be EPIC Podcast from the Walton College. You can find us on Google, SoundCloud, iTunes, or look for us wherever you find your podcast. Be sure to subscribe and rate us. You can find current and past episodes by searching beepicpodcast, one word, that's B-E-E-P-I-C podcast and now, be epic.

[music]