Meet Justin Kistler, an assistant professor at the University of Tennessee, Knoxville’s Haslam College of Business, whose expertise lies in manufacturing and service operations. Through his past research, Kistler has explored redesign and the interface between regulatory policy and service operations, particularly in the healthcare industry. Prior to joining the University of Tennessee, Knoxville, Kistler held roles in project development and process engineering at HCA Healthcare and project management at a General Electric gas turbine laboratory. Kistler holds a PhD in management science from the University of South Carolina and an MBA from Wake Forest University. 

Can you walk us through the impacts that data visualization in a supply chain is having on creating new efficiencies and better insights?

There’s a common dilemma that routinely perplexes organizations: how do you gain better visibility into what’s happening outside of your ‘four walls’, especially within your supply chain, both downstream and upstream? Thanks to data visualizations, companies now have access to data that can more readily inform them. If properly utilized, this can help organizations become more efficient across their supply chains and better serve customers and other partners throughout the supply chain.

If you think about it from a high level, almost all large businesses–no matter the industry–have a wealth of data at their fingertips. In fact, many companies have more data than they know what to do with. That’s where data visualization comes in; visualizations can support the translation of these massive amounts of data into a format that is simpler to interpret, which helps organizations and individuals within these organizations make more informed decisions. In doing so, this data allows businesses to become more efficient because they don’t have to wade through mountains of data to find what they’re looking for. In essence, data visualizations can help companies better understand what has happened in their supply chain so they better view not only what’s happened in the past, but also, how what has happened might help better prepare for what’s coming next. 

“In essence, data visualizations can help companies better understand what has happened in their supply chain so they better view not only what’s happened in the past, but also, how what has happened might help better prepare for what’s coming next.”

What are some of the greatest advantages that visualization tools bring to Supply Chain Management? 

One advantage is the ability to share that information across an organization more readily. There’s research that shows the more access people have to information, the better, in terms of making decisions, serving their customers and corresponding with their suppliers. At large organizations, a lot of information is typically centralized or restricted, be it within an analytics department, middle management or in the C-suite. Now, data visualization tools offer ways to interpret and translate massive amounts of information into something that’s more manageable and legible for everyone, no matter their level within the organization. This has led organizations to share information more freely across the supply chain.

What are some specific tools that companies are using to increase visibility into their supply chain? 

If we think of data visualization as being defined by any picture that can portray information, then even a basic graph could qualify. Graphs help us better understand the seasonality of demand for our products in the past and we can then take this information and use it to support more accurate production planning in the future. 

Another tool that we might not traditionally think of as data visualization is a control chart; that’s a tool that we teach across a number of the courses in our supply chain curriculum at the University of Tennessee. It helps organizations assess the ongoing level of quality within our processes. 

In addition to these more traditional uses, what we’ve also seen more recently is the deployment of advanced tools like data dashboards and heat maps. These types of tools are updated in real time, so we’re able to take information that’s flowing directly off of production lines or directly from the flow of goods through supply chains, and feed this into eye-catching dashboards and heat maps. These tools can capture complex relationships between multiple systems or multiple departments across an organization, or multiple organizations even. These newer tools have the ability to tell more nuanced and complex stories and even highlight some patterns about the underlying processes that could otherwise be overlooked.

What type of decisions are data visualization tools influencing the most?

Let’s say I’m a large multinational organization, and I’m trying to figure out how best to deliver produced goods throughout my supply chain to my end consumers. Historically speaking, in “normal” times, we may have been able to get goods that are produced in our European plants to our consumers in the US in a relatively short time, maybe a week or less. Now, we’re seeing those times drastically increase with delays at ports and staffing shortages across the transportation spectrum. Instead of focusing the bulk of our production at one of our European plants, one way to adjust for this is to temporarily shift how much we are producing in one plant in one country versus another plant in another country. And that can help us to reduce the delivery time to our consumers. Having access to that visualization and the real-time information that comes with it–which is updating every single second of every single day–can really help us make more informed decisions in terms of where we produce and how we ship.

What’s the biggest obstacle to telling a clear, concise story with data like this?

One major concern is analysis paralysis, where an organization or set of decision makers within an organization has access to too much information. Perhaps they’re trying to make a decision quickly, but they’re looking at too many dashboards or too many heat maps; as a result, there’s the risk of spending too much time haggling over the pros and cons of all these alternative options, and, in laboriously weighing various options, it’s possible that a great opportunity to improve their business passes them by.

Users of data visualizations can also find themselves in a situation of over-reliance, in the sense that too much emphasis is placed on one set of visualizations which leads to other data being ignored. It’s always incumbent upon organizations and decision makers within supply chains to strike a balanced approach between relying too heavily or not enough on data visualization as an asset. 

Finally, data visualizations are only as good as the information that goes into them. If your visualizations are based on incorrect time-capture or an inaccurate representation of movement of goods through a supply chain, then you’ve got bad data which will, more often than not, lead to bad decision making. 

What types of advances in visualization would you expect over the next ten years? 

Recently, we’ve seen massive growth in the use of radio frequency identification (RFID). My computer and my monitor both have barcodes which can tell my IT department where this stuff is at almost any day of the week. If we apply this to the supply chains, we’ve got a lot of information that’s being generated from RFID. I anticipate seeing a lot more of this type of information that gets updated on a real time basis then presented using data visualization. 

Heat maps are another area to watch: they track the flow of goods at every stage of movement within our supply chains. And so I think we’ll continue to see them serve an integral service of utilizing the data we have at our fingertips; eventually, they will be propagated into even more visualizations. 

Another aspect that I would raise here is the use of unstructured data. Take camera or surveillance footage, for example: how do you use this data within an organization? One answer is to integrate it into a data visualization that allows us to use information that we might not typically have followed as being applicable for data visualization. Now, one set of industries I think has done really well and it’s sort of applied in a cool way are major league sports. If you watched the World Series, you may be aware that they now have cameras and software placed throughout the entire baseball stadium that can capture real time information on nearly every facet of a baseball pitch, play and result. Same goes for an NBA arena: they can tell the exact coordinates where a player shoots from, what the outcome was and what the defense was that they were playing against. I think these same tactics can be applied to supply chains to better understand how our goods are flowing, and how we can make that flow more efficient.

A final area for growth is the way that we think about our supply networks and our business relationships further upstream and downstream. Supply chain organizations typically have a good idea of their first-tier suppliers as well as their immediate customers. Where there is often less comprehension or knowledge is much further upstream or downstream in the supply chain, and I think there’s a real chance that data visualization, if properly harnessed, can help companies better interact within these arenas. 


Driving institutional value through empowering supply chain leaders to embrace technological advancements and evolving best practices is one of the ways the Global Supply Chain Institute educates the next generation of supply chain leaders. If you are interested in gaining the skills and insights to set yourself apart from other supply chain professionals, an MS in Supply Chain Management Online at the Haslam College of Business can help advance your career goals.