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.
In much of the world, we’re stuck in the grey doldrums of late winter—but let’s think back to the recent holiday season for a minute. Specifically, let’s imagine that you’re trying to send a last-minute gift to a friend via FedEx, UPS, or another package delivery company. You’re hoping that the package will get there before the holidays, so you do some research into your best shipping options: you’re hoping to figure out which company offers the best ratio of on-time or ahead of schedule deliveries to competitive rates, which carriers have the best track record on lost or damaged packages, and who has the best tracking options.
Sometimes, shipments get delayed—it’s just a fact of life, and it's the cost of doing business when you enter the global supply chain. Often, the cause of the delay will be fairly obvious on the outside: a hurricane blocks off a shipping route that usually goes through the Gulf of Mexico, or a strike in France brings all shipping through French ports to a halt. Just as often, however, the reason for the delay seems completely mysterious: despite ideal traffic, weather, and trade conditions, your cargo just doesn’t make it to the right place at the right time.
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.
Most prognosticators have pretty much agreed that Industry 4.0 is going to radically change the world of manufacturing through big data, cyber-physical systems, and internet of things (IoT) integration—but not everyone agrees on exactly what this new paradigm is really going to look like. This might seem like disagreement, but in reality it’s part of the point: Industry 4.0 is going to look different at different companies. It’s even going to look different during different seasons, or for different production flows. An easy, consistent definition and an easy set of IT expectations is anathema to the whole idea of the fourth industrial revolution.
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.
If you ever go to Las Vegas, you should be advised that casinos heavily frown upon card counting, and it’s easy to understand why. A game like blackjack is supposed to be more or less random in terms of what cards are dealt when, which puts the house at an advantage. Over the course of several hands (before the entire deck has been reshuffled), however, a careful observer can note the proportion of face cards that have come out in order to come up with a rolling estimate of how likely or unlikely they are to come up in future hands. This puts the player at a real statistical advantage over the house—at least until the casino politely (or not so politely) asks her to leave.
Raise your hand if you’ve heard the story of William James giving a lecture on the structure of the galaxy. After the lecture, an old woman comes up to him and says that his theory (in which the sun is at the center of the solar system) is no good, because the world actually rests on the back of a giant turtle. When James asks his interlocutor what the turtle stands on, she responds: "You're a very clever man, Mr. James, and that's a very good question… but I have an answer to it. And it's this: The first turtle stands on the back of a second, far larger, turtle, who stands directly under him."