Karate masters know that when aiming for an opponent, you need to anticipate where he or she will be when your strike lands. The same is true with supply chain visibility: It's not enough to know where your inventory has been, or even where it is right now; you need to know where it's going to be and when. Only then can you make the most of the often-underutilized data and analytical tools now available to supply chain managers.

Of course, this is only possible because the industry has embraced the idea of gathering vast quantities of historical data — again, to the effect that you can't know where something is going if you don't know where it's been. But logistics visibility isn't an end in itself. While the supply chain is arguably connected as a chain of events, the processes of data flow and decision-making are typically extremely disconnected. 

The goal must always be to make logistics operations serve your company's broader interests overall, rather than driving the business. The real benefits come when you figure out how to automate processes that can and should run without intervention. Even more importantly, you must be able to identify problems and proactively address their root causes. 

The recent challenges of the COVID-19 pandemic have emphasized that in order to operate with greater resiliency and agility, the industry must shift to modern, networked supply chains designed to be transparent enough to see, understand, learn and act rapidly.

In this information age, we're able to take advantage of the transformational benefits of leveraging a networked, holistic view of supply chain operations, powered by artificial intelligence (A.I.). Although we've been talking about logistics visibility platforms for years, there has been significant progress in their efficacy and sophistication. Initial efforts focused on working with manufacturers and their suppliers to make sure everyone was playing from the same sheet of music in terms of the end results — in other words, making sure there is enough inventory available to meet demand at the point of sale. That collaborative effort necessitated the building of a supply chain management platform that allowed users to look at the entire supply chain holistically, from brand owner through manufacturing and distribution and all the way to the end consumer. This included data from brick-and-mortar retailers' point-of-sale systems, online retailers, value-added resellers and many others — allowing the brand owner to assess how much inventory was actually in the channel, what was selling, and what wasn't. Then, it was possible to use that input to predict what was going to happen and to actually sense future demand. A.I. gives us 40% to 50% more accurate demand predictions than before, and those predictions can be used to arrive at more accurate forecasts on the manufacturing side.

Visibility is also essential to create a holistic, responsive worldview for logistics. In the past, logistics management tended to be a reactive process. Shipping managers would identify which loads were ready to go and then look for transportation, often causing unnecessarily long lead times, especially when ocean transport was involved. But if logistics needs are considered from the get-go — from the moment an order is generated — it's possible to bake in awareness of delays and problems within the entire planning process. The goal is to create multiple feedback loops that generate an environment in which there's full awareness of what's going on, and to know whether that environment is providing the best outcomes on a continuously updated basis.

Part of the challenge is a lack of universally agreed-to standards for supply chain data and the applications that handle the information. It was necessary to build a framework that gives all participants in the supply chain a come-as-you-are approach to data, supporting any and all connectivity formats or data protocols — from application programming interfaces (APIs) and electronic data interchange (EDI) to Microsoft Excel spreadsheets and flat files. Platform providers must take on the burden of transforming it all into usable information that can be integrated into one single digital twin of the physical supply chain. Then, on the output side, the platform can produce information in any form required and send it to upstream and downstream partners.

What this looks like in real life is that a platform provider will build a connection to a shipping company like Maersk, for example, to harmonize data related to bills of lading, bookings and so on. Then, that one pipe can be leveraged by 35,000 shippers who are booking freight with Maersk. There's no need to build 35,000 pipes — just one, reusable pipe.

Ultimately, the result is this: If you're connected to your supply chain partners in a holistic, data-rich environment, you can identify an opportunity or disruption immediately and have enough runway to exploit it or solve it. This means that, in a scenario where a new laptop is selling more than you expected, you can quickly ramp up your supply chain and repurpose supply capacity, while realigning your freight options in terms of air versus ocean, or choosing different distribution points to shift priorities. This can be the difference between empty shelves and beating your competitors.

To return to the karate metaphor: It's well known that in order to break through a wooden board with your bare hands, you need not focus on hitting the board's surface, but on a point a few inches beyond it. Today's supply chain executive needs to constantly look beyond the obvious obstacles and aim beyond them to reach better outcomes. The best way to do that is by connecting to a modern, networked supply chain platform that’s designed to be transparent and powered by A.I. in order to act with foresight.

John Lash is vice president of product marketing at E2open.