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.

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.

Depending on your background, when you were a child your parents might have told you that your Christmas presents came from Santa Claus. From a supply chain planning perspective, this would have made things difficult for you, since your only source of information was fairly opaque, and you had little insight into the distribution mechanisms for toys and gifts. As a result, you were stuck jumping through whatever holiday hoops were presented to you, whether that was mailing a letter to St. Nick or putting out milk and cookies the night before. Once you realized the truth, however, all bets were off. At that point, you knew that the things that wound up under the tree just came from the toy store, and if you were feeling enterprising you could change your supplier relations to arrive at more favorable terms.

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?

It’s a story one hears surprisingly frequently: a mid-sized enterprise company adopts a new mega-ERP solution, and they’re almost immediately mired in constant disruptions. Of course, changing out your entire IT infrastructure all at once (instead of piecemeal) is bound to cause some short-term disruption, especially if the process is long overdue—but that doesn’t account for all of the late or missed orders, the expensive IT support requirements, and other issues that we see in these scenarios.

In the past few years, the industrial world has seen an increase in the use of so-called digital twins, i.e. digital representations of physical factories. Maybe you’ve heard about technology that makes use of this concept—maybe you’ve even wondered why and how this concept could theoretically be applied to your own operations. If you have, then you’ve come to the right blog. Today, we’ll give a quick rundown of the top 5 uses for factory simulations, and how those uses can drive value and reduce disruptions for modern manufacturers.

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.  

Whether you're creating a more synergistic relationship with a supplier of raw materials as an auto manufacturer or developing special relationships with retailers to improve the performance of your packaged consumer goods, collaborative supply chain partnerships often feel like the holy grails of the modern value stream. This is with good reason: a strong partnership in which information, risk, and benefits are shared equitably can add real value on both sides of the relationship in the form of reduced costs, smarter forecasting, or any number of other benefits. It's easy to see why people are willing to devote time and mental energy to it. 

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.