Imagine for a moment that you’re planning to do some small renovations to expand your house. They’re straightforward enough that you can do all of the work yourself, but since you have a day job, you can only do the work at night. What’s the first thing you buy? If you answered floodlights, flashlights, or any other light-emitting piece of equipment, then you have the right mentality for success in the modern supply chain. After all, doing work on a house that you can’t see can be dangerous and inefficient. In the same way, trying to grow your business in spite of low visibility can prove not just difficult, but risky. To prove it, here are five way that end-to-end (E2E) supply chain visibility plays an important role in building a smarter, more efficient business.
As the worlds of manufacturing and retail evolve to meet the unique challenges of the 21st century, logistics (including shipping and freight forwarding) will have to evolve with them. This will likely mean not just a push towards increased digitization, but a continued reimagining of how logistics operates and provides value. Though many of these changes will no doubt seem daunting, they will also present new opportunities for businesses to grow and gain competitive advantages. Here are a few of the most interesting emerging trends to watch out for:
Today’s supply chain managers are often in pursuit of that elusive measure of supply chain health: end-to-end (E2E) visibility. But how do you determine your business's existing level of visibility compared to the level that would best support its particular needs? Just as attaining a high degree of visibility can be a significant operational challenge, measuring visibility can be somewhat of a hurdle in its own right. To the end of helping you clear that hurdle, here are five strategies for ascertaining your level of supply chain visibility.
Each year, topics like big data, advanced analytics, machine learning, and artificial intelligence dominate conversations about supply chain technology, becoming the focus of increasing amounts of speculation as the real power of these technologies becomes clearer and more apparent. As a result, it can be difficult to parse the jargon from the meaningful discourse and the pragmatic analyses from the wishful thinking when deciding how to set expectations for the evolving global supply stream. In the spirit of helping to put all of the hype into context and give supply chain managers the tools they need to look towards an ever-uncertain future, here are a few predictions for the future of advanced analytics:
There’s no denying it: the pace of the global supply chain is getting quicker every day. Broad increases in connectivity have led to equally broad increases in customer expectations, meaning that when things inevitably diverge from expectations, it’s imperative that supply chain managers react swiftly and decisively. This growing need for lightning fast response times comes with increased pressure to build a value stream that is visible and connected enough to provide planners with the information that they need about existing operational plans and potential plan b’s—including inventory levels, transport routing information, and delivery requirements.
Imagine for a second that you’re an NFL quarterback: you have a plan to throw a forward pass to one of your wide receivers, to whom you’ve dictated a specific pass route. Unfortunately, you’ve neglected to inform any of your other teammates of what you plan to do. Even worse, you haven’t bothered to ask any of your fellow players if they have plans of their own and, if so, how they might conflict with the plan you’ve devised. As a result, when something goes awry, none of your teammates are able to make adjustments on the fly, and your plan has no way of overcoming whatever hurdles crop up.
In February of 2018, popular fast food brand KFC was in the midst of making some big changes to its UK supply chain. They were in the process of switching from Bidvest Logistics to DHL as their primary distributor, while simultaneously streamlining their warehouse system from six facilities serving the country to only one. Anyone who keeps current with supply chain management likely knows what happened next: the restaurant was forced to temporarily close more than 700 of its 900 locations in Great Britain. The reason? Chicken supplies were not reaching the stores.
Imagine you’re a trader on the floor of the New York Stock Exchange. Every morning, you check the prices of the stocks that you’re interested in, and you act on those numbers, not checking them again until the end of the day. Your competition, on the other hand, is using real-time information to inform their trading decisions. Which technique seems more likely to yield a profitable trading strategy? Your knee-jerk reaction is probably that you’re going to lose money virtually every day, because your competition has a more accurate picture of the real financial landscape while you’re using information that’s obsolete virtually as soon as you set foot on the trading floor.
Imagine a world in which trillions of individual pieces of information are gathered each day to create complex predictions about future supply chain disruptions and events. Extremely granular data on trade markets turns information about the movement of goods and services throughout the globe into cognitive systems with the power to illuminate new possibilities and intelligently predict changes in demand before they occur. While this may sound like science fiction, it’s increasingly becoming a reality as supply chains become more and more integrated with machine learning, artificial intelligence, and big data analytics. By 2020, IDC predicts that 50% of supply chains will utilize advanced analytics and artificial intelligence, and the effects on the global supply chain are sure to be widespread.
According to McKinsey’s estimates, the rise of the Internet-of-Things (IoT) will have more than a $11 trillion economic impact within the next 7 years. Much of this value will come in the rapidly evolving world of connected consumer goods, such as the internet-enabled products that make up the modern smart home, but the impact will also be felt widely in a number of industries, from health care to natural gas production to, of course, automotive manufacturing. We’ve spoken briefly on this blog about the application of IoT devices for tracking inventory usage and traffic patterns, but what impact will this explosion of connected devices have on factory production processes themselves? More to the point, how can you leverage them into meaningful value propositions within your business’ existing workflows.