Data is hardly ever static. If an organization is using the most up-to-date data, that information is always changing. Much like the movement of goods along the supply chain, where an issue in one part of the world could have an impact on the entire global chain, if one aspect of data changes, it can affect all other calculations an organization makes.
The beverage alcohol industry is as dependent upon the supply chain as any other industry. From raw ingredients to packaging materials, there are just as many moving parts for beverage alcohol companies to keep track of as organizations in retail, for instance.
In mid-May, the Federal Reserve Bank of New York announced that it was going to start including Supply Availability Indexes (SAIs) as part of its monthly regional business surveys. The SAIs are meant to help measure how widespread supply disruptions are, provide an understanding of whether availability is improving, and track inflationary pressures and the impact on local firms.
Two years ago, the Biden administration introduced a new digital platform for supply chain monitoring, Freight Logistics Optimization Works (FLOW). FLOW aims to provide more transparency into the supply chain by bringing together industry stakeholders to share real-time data. Those stakeholders have included retail companies, logistics companies, and port and marine terminal operators.
Now the program has expanded to include data from inland freight ports, including rail terminal and warehouse end-destination data. FLOW originated with the idea of preventing the kinds of supply chain issues that were exposed during the pandemic, but it has become more than that. “Supply chains in some form…explain more than 80 percent of the disinflation [decreased inflation] the U.S. has experienced since 2022,” according to a recent White House economic analysis.
Here are a few examples of how supply chain data is making a difference for businesses, whether or not they are a part of FLOW.
Retailers work from in-store dates, the date a product must be available in the store. Those dates rely on the smooth function of the supply chain, from the time a product is picked up overseas, brought into a port, and distributed to stores. There are any number of reasons why that might not happen on time, from weather to work stoppages to international unrest or a global pandemic, to name a few.
When there is some kind of disruption, companies are forced to make an expensive decision, such as paying for air freight to make sure the products arrive at their destination on time. FLOW can provide the data those companies need to avoid having to spend more money than they budgeted.
PetSmart is one such example. The company can use FLOW data like bookings, marine terminal slots, chassis availability, and gate moves to understand what their next move should be. If they know there will be a delay of some sort, they can arrange for another product to be on store shelves until the scheduled shipment arrives. Instead of guessing at when that will be, they can draw a firmer conclusion. In doing so, they not only avoid having to make a reactionary decision that might cost more money, but they can also make a different move that allows business to continue without missing a beat.
Other companies are using their own data to help improve supply chain efficiency:
These types of analytics are not exclusive to these companies that are finding success. Any company looking to make gains can learn from what they have been able to do. One major component is communication. FLOW data comes from a collaborative effort from organizations throughout the supply chain. Any organization that has traced its supply chain from beginning to end can reach out to stakeholders each step of the way to get the data it needs to help make important decisions where shipping is involved. If an organization is worried about where it can save money within its own processes, it can communicate internally to make sure everyone is on the same page as far as desired outcomes and opportunities for efficiencies.
In addition to communication, the other important piece is the right analytics tool. Knowing which information your organization needs is half the battle. Having the right tool to put it to work, producing reports that can help decision-makers with their work, is the final step to seeing improved results. Whether that data comes from a large government program like FLOW or the hard work of people in your organization, it can end up producing the same actionable insights.
Supply chain data can mean many different things to different organizations. For some it can be used to make sure goods are being delivered in the most efficient way — whether that’s getting raw materials to a factory or from production to the consumer. For others it could be used to track an item down to its origins to make sure sustainability goals are being met.
There are many aspects to consider when thinking about data analytics in the beverage alcohol industry. An organization can focus solely on sales, whether that is from the product point of view or to check on how its employees are doing. Data can be used to gauge the effectiveness of incentives programs, or to see how products perform in different regions, and whether changes need to be made. The data can be used to provide answers to any number of questions, but in order to track product performance, the product needs to be delivered in the first place.
Beverage alcohol has its own unique challenges within the supply chain industry. From the raw materials to packaging to a sale at your local store, there are many factors to consider when it comes to getting alcohol where it needs to be. Here’s how analytics can help.
For a long time, advanced uses of artificial intelligence (AI) in industries like the supply chain were largely aspirational. AI could perform certain tasks that might help ease administrative workloads or help address customer concerns through chatbots, but organizations dreamed of the day it could help make a significant impact on decisions and improve business outcomes.
In many ways, the technology has finally caught up to the aspirations. We’re beginning to get a clearer picture of how AI can be used to work with data in the supply chain, and there are specific examples of how organizations use AI to make a difference.
When it comes to disruptions in the supply chain, there are the kinds an organization can prepare for and the kinds that are harder to anticipate. The disruptions brought about by the pandemic fell into the unanticipated category, and even though the problems brought on by some natural disasters can be expected, a bigger-than-expected weather event can be hard to work around.
Organizations can expect certain disruptions, though, for which customers will hold them accountable. Product shortages, for example, or shipping delays are frustrations that an organization might not have complete control over, but are expected to be able to handle. And the way they can handle them is through data.
One of the most complex industries when it comes to supply chain management is healthcare. Some of those complexities were brought to the public’s attention as a result of the pandemic. It was widely known that some healthcare organizations ran out of personal protective equipment (PPE), and some hospitals reacted by either overpaying for supplies, not getting supplies that met the usual standards of quality, or both overpaying and getting less quality.
There are a number of aspects to consider when looking at the supply chain from a healthcare point of view, and data is used in all of it. It is especially important now, as healthcare organizations are looking to cut costs where they can. They are examining their supply chains for opportunities, and they’re using data to help.
Artificial Intelligence (AI) has played a role in the supply chain for years. Like any technology, though, it continues to grow, and that can lead to more opportunities. As the technology improves, and awareness about what exactly AI can do increases, people are looking at AI and its role within all industries with a new set of eyes.
It comes at an important time in particular for the supply chain industry, as after a period of disruption after disruption, organizations are putting more emphasis on quickly analyzing data and making better decisions. Here’s a look at the ways AI is already established in supply chain analytics, and how it might be used moving forward.