In supply chain management, as with anything else, it can often be difficult to see past the hype and figure out which technologies are worthwhile and which aren’t. With things like cloud-based ERP, blockchain-based tracking, AI, and other buzzy new technologies flooding the SCM technology market in recent years, you might find yourself wondering what features and capabilities to prioritize when choosing a software vendor. Do you really need neural nets to analyze vendor performance in the cloud in real-time, or would you be better off leveraging your resources elsewhere?
By all accounts, advanced analytics are becoming a more important part of the manufacturing sector than ever—and it’s easy to see why. By McKinsey’s estimates, the combined effects of using advanced predictive algorithms to proactively schedule machine downtime and prescriptive analytics to optimize machine yields can add up to a whopping 10% increase in gross earnings. How is this possible? Well, for starters, predictive analytics trained to predict machine breakdowns can help reduce machine downtime by up to 50%, which not only improves your production plant’s throughput, it also extends the lifespan of each machine, saving additional costs down the road.
Though the manufacturing sector has traditionally not been the fastest adopter of cloud technology, there’s no denying that the demand for cloud-based apps and services in the industrial world is increasing. One estimate suggests that the cloud manufacturing market could nearly triple in just a few short years, from just shy of $40 billion in 2018 to more than $110 billion by 2024. Based on the way people talk about cloud technology, it’s easy to see why: it’s often cited among the most important drivers of the Fourth Industrial Revolution, and insiders often suggest that it has the power to revolutionize ERP, power improved demand forecasts, and improve operational visibility.
For a recent report, McKinsey tracked the progress of a group of Industry 4.0 “Lighthouses,” i.e. operations that had successfully undergone or were undergoing digital transformations in the spirit of the Fourth Industrial Revolution. So far, these manufacturers have been fairly successful at creating a smarter end-to-end value chain, and their agility, productivity, and waste reduction have by and large shown real improvements as a result.
Sales and operations planning (S&OP) is one of the most popular methods that businesses employ for creating a smarter, more responsive supply chains—and with good reason. S&OP can help you identify and take advantage of strategic opportunities that you otherwise might have missed, all through the careful collection and analysis of supply chain data that your value stream is producing anyway. It’s not a panacea—nothing is—but it’s a great start for manufacturers and other businesses who are seeking a leaner and more flexible way to administer supply chain activities.
The actual production of automobiles on the factory floor has been getting more efficient for decades. In the ‘80s, it would take General Motors about 40 labor hours on average to produce a new vehicle—today, that number is much lower. Since 2007, Toyota’s average labor time per vehicle has dropped from 29.4 hours to 17-18 hours. This is an encouraging trend from a planning perspective. And yet, we know that in reality the process of getting any single car made starts well before the stamping and welding. After all, the 30,000 or so parts that make up a typical car have to get produced first, and even then there are long lead times involved in the sales and planning process before the materials and time get allocated to a particular vehicle.
It’s a popularly quoted statistic that supply chain inefficiencies can waste as much as 25% of operating costs, which only goes to show how much an impact you can have on your bottom line by working to reduce waste. This is, of course, easier said than done: supply chain waste comes in myriad forms and is notoriously difficult to root out. Why? Because every decision you make across the entire value stream has the potential to introduce unforeseen costs down the road.
Remember when you were in school? No matter the class, every term you got a syllabus for each class that laid out when exams, quizzes, and term papers were all due? Then you set about working each syllabus into your own personal calendar, with short-term items like quizzes, mid-range ones like exams, and the long-game term papers for each class. There’s a similar way to look at your production planning schedule, with short-, mid-, and long-range goals and KPIs. Long-range is handled by your annual strategic plan, mid-range duties fall to S&OP, and today we’re going to dig into the short-range process of S&OE. Specifically, we’re looking at how to know if your sales & operations execution process is successful or not.
We all have different ways of getting a handle on our supply chain activity. Some folks might check a series of KPIs every morning to see what small fluctuations in supply and demand have occurred overnight, while others might be more interested in the big picture, seeking out a comprehensive visualization of the supply chain at the end of every month. However you like to think about and analyze your supply chain data, your routine probably revolves around a dashboard.
Industry 4.0 technology is making its impact felt all along the supply chain as we enter the third decade of the 21st-century. Alongside IoT sensors, GPS trackers, smart pallets, and robotic picking technology, the progress made in supply chain management software has been unstoppable. Whereas once Excel sufficed to layout a strategic plan and track forecasting, today this method is becoming increasingly outdated and outpaced by more collaborative options. These new systems allow for real-time updates and enable real-time collaboration on planning documents by multiple stakeholders at the same time.