We’re surrounded by redundant expressions every day. Close proximity and basic fundamentals spring immediately to mind. Unintended mistake, past history, and plan ahead follow close behind. When hearing the phrase “advanced analytics,” many people jump to the conclusion that this is just another business-speak example of redundant word use. Aren’t all analytics advanced? In truth, the expression has a specific use, particularly in a discussion of data use in supply chain management.
From 2018 to 2019, Gartner’s outlook on Industry 4.0 adoption seemingly became a little less sanguine. It’s certainly not the case that their opinion of the potential of this massive industrial paradigm shift has lessened in any way, but the focus of their Industry 4.0 predictions for 2018 was how CIOs could find useful models of successful digitization, while for 2019 their focus was on dealing with the gap between expectations and reality that numerous industrial businesses are encountering with new technology. Again, it’s not that the outlook on Industry 4.0 itself is any less rosy than it was a year ago, but it seems like we’re reaching the point where real implementation hurdles are beginning to show themselves.
They say that those who don’t learn from history are doomed to repeat it—but in point of fact, relying too heavily on historical knowledge can often be just as bad. History tells us a particular new innovation will never work, or a new strategy will never succeed, and as a result we’re often blindsided when something truly innovative or unusual comes around. This is particularly true in the logistics industry, where changes in the global economy and the nature of supply chain technology are causing an exponential increase in the number of paths that any given cargo might take from producer to consumer.
Is your boss starting to ask uncomfortable questions? Like what your average order cycle time is? Or what the latest shrinkage numbers are? Sounds like it’s time to line up your metrics and develop a solid plan for tracking and reporting to management.
As the era of Industry 4.0 approaches in earnest, production managers will soon have access to more data and information than ever before. Internet of things (IoT) sensors and RFID chips throughout the production chain will offer real-time monitoring for your planned production programs, just as robust software integration will help you to better understand what’s happening at various other touchpoints on the supply chain. This is exciting, but it can also be a bit daunting. After all, what exactly are you supposed to do with all of that data?
Artificial Intelligence (AI) can refer to a number of things, from machine learning to computer vision, but in general the phrase is used to indicate computer programs that can reason, learn, and problem-solve from data in a way that’s reminiscent of human intelligence. This takes any number of forms, from digital personal assistants like Siri and Alexa to competitive chess playing to autonomous vehicles—each of which involves a slightly different understanding of what AI is and does. For manufacturers, the most pertinent uses of AI are likely going to be the ones that are most heavily focused on gathering insights from large quantities of data—simply because of the sheer amount of information collected and stored by most industrial and supply chain planning platforms. The question still remains, however, of what manufacturers in general and production planners in particular should expect from AI in the coming months and years.
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.
Remember the “paperless office?” Back in the early days of computing for the masses, and particularly after the invention of the public internet, it was all any of the pundits could talk about. They expounded on the wonders of digital this and online that, with the underlying theme being the elimination of physical copies of paperwork. It’s been well over two decades, and I don’t know about you, but my last office had a 30’ run of filing cabinets that certainly weren’t empty. Today, those same pundits are going into great detail about the “disruption” of the automotive industry that electric vehicles (EVs) signal. But is the shift to EVs really going to have that much of an impact? As with so many things, the answer is a resounding “it depends.”
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.