Right now, even if your factory is relatively well equipped with IoT devices and RFID chips that can send production information back to your control tower, there’s a good chance that you’re still relying heavily on time-triggered events as your products make their way across the production floor. Sure, you’re gathering data at various stages of the production process, but that data isn’t automatically causing anything to happen. If something seems to be going catastrophically wrong, a production planner might get an alert and perform some manual triage, but most of the time the data functions as something of a post-mortem.

Life in the digital age is meant to be easier for manufacturers: rather than using spreadsheets to plot out potential production and logistics plans that attempt to meet customer needs within existing constraints, you’re supposed to be able to plan digitally—arriving automatically at the optimal route for your fleet to take from the factory floor to the distribution center, or the right production ratio to minimize downtime. This is where things like advanced planning and scheduling come in. They offer digital planning processes for the digital era, helping manufacturers to boost efficiency and limit disruptions.

People say that the only constant is change. When they say that, they’re usually not talking about sales and operations planning (S&OP). And yet, what could be more relevant? If you’re an automaker, for instance, your business constantly needs to adapt to changing market conditions, customer expectations, technological realities, and other factors that can have a big impact on the success of your production plans, supply chain, and profits. There are any number of strategies that decision-makers use to try and address these constant internal and external changes, but one of the most commonly talked about (in some circles, anyway) is S&OP.

If you could see the future, what would you do? Well, first off you would probably buy a bunch of winning lottery tickets—but you might also attempt to optimize your day to a certain extent. Instead of being taken off guard and having to scramble to make arrangements when you get an unexpected call from school that your kid is sick, for instance, you’re already on the road, having made arrangements to work from home for the day so you can tend to him or her. On the way home, you know that your child’s going to want their favorite comfort food, so you’ve already called in a pizza order.

Let’s say you’re a homebrewer, and you’ve just finished drafting your recipe for a dry-hopped pale ale that you plan to brew in the coming weeks. If you’re like most people, you go to a homebrew supply site and order your hops, malt, and yeast all at once, plus some clean bottles for your brew to wind up in. This strategy works perfectly well, but as you go, you find that it leaves something to be desired. While your beer is fermenting, you have a bunch of bottles taking up unnecessary space on your floor; and by the time you’re ready to dry-hop (which involves adding more hops during the fermentation period), the ones you bought from the homebrew site are a little stale.

One of the most common metaphors you hear for forecasting in supply chain management is that it’s like the rear-view mirror in your car: you need to understand what’s happening behind you, but it’s not necessarily enough information to keep you slamming into the car in front of you. As the supply chain has evolved, however, forecasting has evolved along with it. So, for that matter, have cars: in the modern supply chain, forecasting can encompass not just the rear-view mirror, but the back-up camera, and even the smart sensors that alert you when you’re getting too close to another car.

These new processes that move beyond the scope of the rear view mirror use technology to take in additional information, and then spit out new insights for the driver to use—from immediate course-correct notifications to more granular data about when you’re going to hit the curb while parallel parking. In each case, digitization has played a big role in giving you a more comprehensive overview of events that are about to take place. In an industrial context, we might think of these digital enhancements as things like IoT (internet of things) devices and other smart sensors that provide live information to planners. In this way, forecasting becomes more thoroughly integrated into the way that businesses make decisions and optimize their supply chain management. And it’s lucky for us that it does so, because accurate forecasts are becoming more important than ever in the world of supply chain planning.  

Let’s says you’re playing chess. Traditionally, a chess player looks at the whole board and comes up with an overarching strategy, which she can then adjust as needed when new conditions (i.e. her opponent's strategies and maneuvers) emerge. For this game, however, you decide to do something different: you have a series of different plans, one for the pawns, one for the bishops, one for the queen, etc. with no obvious connections or interplay between them. As situations arise in which multi-step, cross-functional movements would be helpful, you stay in your lane and stick to the separate plans for each function. At the end of the game, your rooks have performed admirably, and everything went according to plan for your pawns, but you still found yourself in checkmate.

Supply and demand are the first two concepts that most people learn about with regard to economics—and they’re also two of the most crucial elements of any manufacturing supply chain. In order to effectively meet customer demand, you need to ensure that you have enough supply on hand; and in order to profit by that demand, you have to make sure that your supply doesn’t wildly exceed your needs. As with so many things in manufacturing, this is easier said than done.

Even manufacturers themselves may sometimes forget how tremendous the global manufacturing sector really is. Manufacturing in the U.S. on its own, for instance, would be in the world’s top 10 economies. Because this sector encompasses so many different businesses with so many different missions and products, it’s easy to prove or disprove almost any prediction. Sure, someone among the incredibly diverse array of global electronics producers is probably using voice activated AI in their plants—just as someone else is probably bucking every emerging trend by continuing to eschew digitization and connectivity. Still, as general trends emerge, it can be helpful to identify and understand them. To that end, here are some predictions for the world of global manufacturing in 2020.

Let's say you’re a bartender in a sleepy neighborhood pub in your city. Your place might reasonably be called a dive bar, and you have a handful of regulars who come and order basically the same drinks week after week. As a result, your ordering process for restocking the bar is extremely simple. With little variation, you expect to go through predictable quantities of gin, tonic, bourbon, and cheap beer every month, and you’ve simply placed a standing order with the local distribution company to restock these things in the same quantity every so often. Life is pretty easy.