As of a 2017 survey, just 6% of companies felt they had reached supply chain visibility. Elsewhere, nearly a fifth of companies listed visibility as their number one operational challenge (it ranks the third highest priority overall), but more than 60% admitted that they didn’t use any technology for monitoring their supply chains. By the same token, more than 90% of businesses have listed digital transformation as a huge driving force in the evolution of the modern supply chain, but fewer than half of those businesses have an actual plan in place for managing that evolution.
Of all the stages of the supply chain, logistics often gets a bad rap. This appears to be largely due to a combination of the seeming unpredictability of the unknowns like weather patterns and fuel costs; and the skyrocketing costs associated with last-mile delivery in recent years. This potent combo makes it all the more unexpected that logistics is also quite often overlooked when it comes to applying learnings from demand forecasting. The predictive analytics used by demand forecasting solutions takes historical data, runs it through advanced AI algorithms and generates predictions for demand in a specified upcoming time period. That sounds pretty useful for cutting logistics costs and leveling out some of the uncertainty that’s endemic to this sector, doesn’t it?
You know that one product that seems to be in every outgoing order? The one kept all the way in the corner of warehouse 2, opposite from the loading dock? How much is it costing you to keep sending the forklift across 10,000 square feet of warehouse, multiple times per day? What if you moved that item to an empty bay 2 rows away from the docks? How much time, energy, and money would that save your logistics budget? If you don’t know the answer to any of these questions, it’s time to take a good, hard look at the logistics end of your supply chain to weed out the wasteful spending and tighten things up a bit. To get you started, we’ve pulled together a list of our top 5 areas of waste in supply chain logistics. If you can get these under control, you’ll be well on your way to a streamlined value chain and much-improved logistics ROI.
In our last look at Logistics 4.0 statistics, we discussed 5 that we feel will help define the shipping and logistics sector in the coming years. Today, we’re going to add to that list with 5 numbers we feel might be getting short shrift in coverage of this arena. Logistics is undergoing a collection of disruptions that seem to have hit out of the blue. There’s a seeming tsunami of dissatisfied customers, rising fuel costs, and global weather pattern changes, to name but a few. In order to respond appropriately, the shippers of the world have had to pivot, fast. Many are choosing to dive headfirst into the emerging world of Industry 4.0 technologies that promise to help predict at least some of these disruptions far enough in advance that alternative plans can be set in motion. Among the technologies seeing increasing adoption are AI, machine learning, RPA, and IoT. These technologies, combined with intelligent deployment tactics, are already having a big impact on the global supply chain.
Anyone who has ever rented a moving van for a day knows how hard it is to move furniture safely and efficiently. Loading a table and chairs into the back of a truck without getting them scuffed up is difficult enough—imagine trying to do the same thing on an industrial scale. But, for many in the furniture industry, moving goods that are designed to spend most of their lives sitting in one place is just a daily fact of life. Unsurprisingly, this tends to come with a lot of challenges that many logistics planners outside the furniture industry don’t have to face.
In 1963 the National Council of Physical Distribution Management was created to help give visibility to the emerging field of supply chain management. In the following decades, records keeping and other traditionally manual processes would become the province of newly-emerging computer technology, leading to significant changes in the industry. In the ‘80s, the council changed its name to the Council of Logistics Management to reflect the industry’s increasingly nuanced view of the complex process of sourcing raw materials for production and distributing finished products to customers. Supply chain management as a field went through plenty of change during that span, including the continued rise of computers as a tool, just as it's going through big changes now with the advent of Industry 4.0. Below, you’ll find our predictions for what might change about supply chain management in the coming year.
Over the course of human history, many of our most critical technological advances have been put to use in helping people and goods get from Point A to Point B more effectively. Take air travel, for instance: only a few years ago, most travelers needed travel agents in order to cut through the complexity involved in bundling together connections and return flights in the most sensible manner. Cut to the modern day, and a simple Google search can give you the times, connections, and prices for your various options based on your desired travel dates and destinations. Not only that, but once you’ve booked your travel itinerary, you can check in online (rather than at the airport), receive your boarding passes via e-mail, and receive alerts about your flight on your phone. All of sudden, life as a traveler is about connectivity and convenient digital workflows.
Let’s pretend that you and a friend are both mixologists at an upscale cocktail lounge. On weekends, there tends to be a rush of patrons late in the evening who ask for drinks faster than you can produce them. As a supply chain or logistics manager in real life, in this scenario you might be tempted to suggest that you and your fellow bartender start creating a buffer stock of drinks before the big rush, so that people can receive their drinks as soon as they order them. Unfortunately, you can’t really know what drinks people will order in advance (to say nothing of the fact that the ice will melt), so creating a buffer stock is impractical. You can, however, do some prep in advance, like preparing garnishes and simple syrup. When the rush comes, you’re still slammed, but you’re able to create drinks more efficiently.
Buying health insurance in the U.S. is an odd business. Essentially, you have to balance your monthly premium (i.e. the amount that you pay your insurance provider each month for continued coverage) with your deductible (the amount that you have to pay out of your own funds before the insurance company will contribute to your care, broadly speaking). In general, if one of those two costs is particularly high, the other is likely to be lower, and vice versa. If you’re thinking about your choice in terms of total cost, a high deductible is risky, but has the potential to be cheaper if you can avoid getting sick over the course of the year. A high premium, on the other hand, might put you in a position where you’re essentially paying for medical care that you’re not receiving. The question, then, is how much risk are you willing to take on?
Imagine for a moment that you’re a manager at a large restaurant. Part of your job entails assigning sections to your servers in a way that ensures that as soon as a customer’s food comes out of the oven it’s being moved to the appropriate table. Other than the short lead times, this may seem simple enough—but let’s say the restaurant is split up into a few sections. There is a bar area, which has happy hour specials during some days and times, which means that your servers need to know that these patrons might be receiving slight variations from the usual menu that wouldn’t be appropriate in the other parts of the restaurant. These items are still being cooked on the same lines as the others, which means that all parts of a given meal might not come out of the kitchen simultaneously.
Topics: Supply Chain Logistics