Let's say you're an OEM, with a sleek manufacturing space and a sophisticated, technologically cutting edge process for creating a particular automotive part. But you have a problem: At this point, your incredibly sophisticated production techniques aren't not being complemented by an equally sophisticated, multi-level approach to production planning and resource scheduling. This results in a disconnect between the high quality of your products and your ability to maximize capacity and meet customer delivery requirements. How can you build towards a production planning workflow that complements your product and fulfills your business goals? 

IT pioneer and philosopher Ted Nelson, who coined the term hypertext, once famously said, "The good news about computers is that they do what you tell them to do. The bad news is that they do what you tell them to do." Historically, in the automotive supply chain, this couldn’t be more true. New technological developments like early computerized workflows and simple process automation were hampered by information silos and integration issues not because the technology lacked sophistication, but because they still had to be told what to do in very specific ways.

For decades, production planners in non-clocked production environments have been trying to optimize their job shop scheduling processes, and for decades the problem has continued to elude them, owing in large part to the tremendous complexity of uncovering the most efficient route for each product to take through a non-linear production environment. Luckily, new advancements in supply chain technology are constantly presenting planners with new tools and tactics they can use for gaining the maximum possible value from their production workflows. In many ways, the most significant of these advancements come in the form of the new technologies that make up the Industry 4.0 revolution. But what, exactly, is it that makes Industry 4.0 and job shop scheduling a match made in heaven? 

New technologies—from steam power to modern computers—have been the driving forces in supply chain management since the beginnings of industrialized society. Today, supply chain technology is changing at an exponential rate, providing supply chain planners with possibilities that would have seemed like science fiction even a few decades ago. If you follow the news and trends in SCM, you’ve no doubt noticed that machine learning (ML) is often touted as the next major innovation in this long line of technological evolutions—but what, exactly, is it, and how can supply chain managers put it to use?

Let’s say you and a coworker are attempting to find areas of waste in your supply chain. You have a large conference table on which you’ve laid a file that contains all of the transport plans utilized by the company for the past few years. When your coworker hypothesizes that a different grouping of goods would improve fuel efficiency, you need new documents with additional information, meaning that you have to leave the conference room and descend to the basement level where the files are kept. By the time you’ve returned, a new idea has occurred to your coworker, and you have to make a new trip to wherever your files are stored in order to retrieve the necessary information. The result of all this walking to and from the files? Some good cardio, but no plan to speak of.

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 21^st 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.