Imagine for a second that your factory is essentially a black box. Materials go in, and finished products come out, but what happens in between is fundamentally mysterious. What challenges would this present from an advanced planning and scheduling perspective? Sure, in this environment you can get a small sense of the correlation between raw material volumes and finished product volumes—you might even be able to gain a sense of which raw materials loosely correspond to which products. But surely there’s a lot of information you’d really like to have: how do different products differ in resource usage? What are the most common causes of delays and disruptions? How can you more effectively align your capacity with emerging demand levels?
As the global scope of the modern supply chain continues to increase, there’s going to be more data available to supply chain planners than ever before. For some businesses, this data will likely just sit there collecting dust—but in point of fact it’s increasingly going to be an important source of value for planners. Why? Because modern analytics processes, powered by technologies like AI and machine learning, are making that data exponentially more valuable as a source of usable insights.
Topics: Advanced Analytics
Digital supply chains can help manufacturing businesses reduce costs and disruptions in a variety of ways. They make it possible to predict potential breakdowns and bottlenecks far enough in advance that you can take steps to address them, just as they help you to boost operational efficiency through smarter sourcing, inventory management, and capacity management. More than that, going digital makes it easier for your business to integrate with other highly-digitized operations, meaning that especially sophisticated supply chain partners (whether they’re suppliers or logistics providers) will be more excited to partner with your business.
There’s been a big push towards lean manufacturing and logistics in the past few years, with manufacturers doing everything in their power to reduce inventory levels and rely less on their buffer stock. Because there’s a considerable element of risk involved in a truly lean supply chain, virtually all supply chains stop short of completely lean workflows. The one significant exception? The newspaper industry. While newspapers aren’t usually thought of as manufacturers in the traditional sense, they do produce a product in a systematic way in order to be shipped to end-users—with the crucial difference that anything resembling a buffer stock or inventory is rendered useless by the impossibly short lead times, as papers become obsolete just hours after they’re distributed.
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 his seminal work of economic theory, “The Wealth of Nations,” Adam Smith famously uses a pin factory as his example to illustrate a number of basic concepts in what was then modern capitalism. Today, the production of something as simple as a pin can essentially be a global affair. In all likelihood, your production facility needs to receive shipments of raw material from elsewhere in the world via a complex set of routes and distribution points. The factory itself may be part of a larger, international organization with diffuse planning processes taking place in parallel all across the world. And the finished product, once it’s been produced, might be sent anywhere in the world—after all, people all of all nationalities and backgrounds sometimes need pins.
Let’s say that you run a pizza delivery joint. As orders come in by phone or through your website, you have one employee who’s in charge of giving delivery estimates and getting the pizzas to the relevant doorsteps, and another who’s in charge of running back and forth between the storeroom and the kitchen to make sure that the chefs have everything they need to actually make the pizzas. If any of the ingredients in the storeroom get too low, that employee calls the relevant suppliers and arranges to receive and store the delivery. One day, you get a bright idea: what if the delivery person and the employee in charge of restocking the storeroom had direct visibility into one another’s processes?
Sales and operations execution, or S&OE, is a little bit like flying an airplane. In the modern era, you already have a host of processes that have been digitized and automated, including many of the actions that pilots themselves used to be solely responsible for. Your point of departure and destination, as well as the route that you’ll take from one to the other, is already fixed—all of which means that as a pilot your job is mostly to monitor incoming information and make slight adjustments as needed, even if those adjustments are just a fairly rote response to alerts being sent to you by your instruments.
Whether you’re a freight forwarder seeking out a new ERP system that helps to manage the flow of goods from origin to destination or a manufacturer looking to add visibility and bolster efficiency within your own transportation management processes, selecting the right logistics or transportation management software can be a difficult task. In some ways, the process of selecting the right technology is a lot like finding a 3PL (third party logistics provider) with whom to partner. In both instances, you need to consider price, customer service, existing relationships, and scalability—but you also need to take stock of your organization’s values and provide a clear roadmap for the future of you're your operations. Even if you choose the most reputable partner in the business, the partnership likely won’t be a success if their goals aren’t well-aligned with your own.
Ah, the old dilemma: make to order vs. make to stock. The debate has been raging in the world of manufacturing for many years. On the one hand, making to stock (i.e. the process of creating products in anticipation of demand that hasn’t yet materialized) involves a lot of guesswork, with potentially costly results: if demand for a particular product doesn’t meet forecasted levels, you could find yourself in possession of large quantities of unsold stock, which you might have to sell at a loss in order to free up costly warehouse space. Making to order (in which you start your production process only once an order has been placed), on the other hand, presents its own potential pitfalls: you risk meeting demand comparatively slowly, and the relatively lean nature of the typical make-to-order supply chain makes it more susceptible to risk in some ways.