Has your supply chain management situation changed recently? We’d wager it has. With the introduction of Industry 4.0 technologies to the value chain over the last few years, things have been changing at an ever-increasing pace. Where once there were information silos, spreadsheets, and clipboards, now there are SCMS solutions, AI-powered advanced analytics, and IoT sensors. Rather than being the purview of autonomous managers acting in their own departments’ best interests, there are CSOs (chief supply chain officers) acting in the best interest of the whole company. And along with that shift has come a renewed understanding that the company’s best interest is generally synonymous with the customer’s.

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.

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?

There’s a coffee shop down the road known for ham & cheese croissants. So you stop by one morning only to discover that they’re out. The barista says they only get 3-4 each day and that they’re generally gone before 8:00 AM. The 2 people behind you sighed and said they were looking for the same thing. This is the best (and smallest scale) analogy I’ve ever seen for poor demand capacity planning. The shop knows there is a demand for the item, and they know the bakery makes more than they order, yet they never have enough to even come close to meeting demand. Leaving many unhappy, and unsatisfied, customers debating the breakfast options down the street. For you, the demand capacity planner, this is the scenario you dread more than anything—being unable to meet your customers’ demands and losing them to competitors as a result. Follow along with the following steps, and you’ll be on your way to avoiding this situation by keeping production and demand evenly matched.

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.

How are you using your ERP software? Strictly for resource planning, as intended? Or are you stretching that definition to include aspects of your supply chain management needs as well? ERP solutions are an offshoot of financial software, and most of it functions as such and can be clunky when pressed into alternative uses. A dedicated SCM software solution, on the other hand, is as flexible and multifunctional as your supply chain itself. Think of it like this: would you rather build your personal daily calendar out of an Excel spreadsheet, which is totally doable, or just use a ready-made calendar tool like Google Calendar? Yes, both are workable solutions, but only one is actually made to help you keep track of lunch dates and offer reminders for those important meetings you just can’t miss.

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. 

Imagine you’re hosting the family reunion this year. 75 people are going to be expecting a great venue, amazing food, and some planned activities. But you’re just one person, with some help from your girlfriend. Are you going to cook all the food, decorate the community hall, schedule and set up for the band, AND be there to greet everyone as they arrive? I certainly hope not. You’re going to hire a caterer for the food, be sure the band brings their own crew to set up and tear down the stage, and rope your girlfriend into being the greeter so you can still supervise the proceedings. On the other hand, if you’ve got a wife, 3 grown kids with their own significant others, and a circle of close friends, maybe you can do it all in-house. This is the power of outsourcing, it keeps the playing field even for even the smaller players. The question is—how do you maintain control over the cooks, musicians, crew, and cousins?

The manufacturing industry is in a bit of a pickle. Emerging technologies are coming at it from every direction, as digital transformation and integrated supply chains are being touted as the solution to all their woes. Industry 4.0, Logistics 4.0, AI, IoT, RFID, there are enough buzzwords and acronyms to make even the most seasoned production planner’s head spin. What’s a planner to do? As with so many areas of life, the key is to move one step at a time. See if any of the following five challenges apply to you, and if so, start by addressing them. Then, when you can see your way clear of that challenge, you’ll have a better understanding of what to address next for the greatest impact.