In the past few years, sustainability has become a topic of considerable importance throughout the automotive industry. As the automotive supply chain becomes increasingly globalized, businesses are now more than ever faced with the Herculean task of managing not just the logistics and costs associated with a complex web of global suppliers, but with the environmental impact and long term sustainability of the associated businesses practices. While this process is often daunting, it has grown in importance to the point where manufacturers ignore it at their own peril. Even beyond supply chain considerations, many businesses are finding that discussions of sustainability bring up questions and dilemmas that they’ve never faced before, from deciding on acceptable trade offs between sustainability and profitability and uncovering areas where sustainability increases profitability, to developing new KPIs for managing vendors and suppliers.
Buying health insurance in the U.S. is an odd business. Essentially, you have to balance your monthly premium (i.e. the amount that you pay your insurance provider each month for continued coverage) with your deductible (the amount that you have to pay out of your own funds before the insurance company will contribute to your care, broadly speaking). In general, if one of those two costs is particularly high, the other is likely to be lower, and vice versa. If you’re thinking about your choice in terms of total cost, a high deductible is risky, but has the potential to be cheaper if you can avoid getting sick over the course of the year. A high premium, on the other hand, might put you in a position where you’re essentially paying for medical care that you’re not receiving. The question, then, is how much risk are you willing to take on?
Baseball may not be the most popular sport in many parts of the world, but when one considers all of the analytical and statistical breakthroughs the game has made in the past two decades, it really deserves to be a favorite of supply chain managers in the Industry 4.0 era. Since the dawn of the “Moneyball” era, scouts, commentators, and prognosticators have developed new, increasingly complex ways of measuring past performance and forecasting future outcomes. Because everything that happens in the game of baseball, from a stolen base to an outfielder dropping the ball, can be represented numerically, entire seasons can be simulated in granular detail, and insights can be gained from those simulations. By integrating these systems with real-time game data, we can now make an ongoing estimate of the win probability of each team in the middle of each contest.
Imagine for a moment that you’re a manager at a large restaurant. Part of your job entails assigning sections to your servers in a way that ensures that as soon as a customer’s food comes out of the oven it’s being moved to the appropriate table. Other than the short lead times, this may seem simple enough—but let’s say the restaurant is split up into a few sections. There is a bar area, which has happy hour specials during some days and times, which means that your servers need to know that these patrons might be receiving slight variations from the usual menu that wouldn’t be appropriate in the other parts of the restaurant. These items are still being cooked on the same lines as the others, which means that all parts of a given meal might not come out of the kitchen simultaneously.
Let’s say your manufacturing outfit is looking to hire a new employee, and you’re tasked with creating the job listing. What are you likely to ask for in your potential new hires? Depending on what type of IT environment your business runs on, you might require that they be familiar with a certain software or suite of software products, so that they can easily assimilate into your existing workflows. You might also ask for references from previous employers, so that you can be sure that they don’t present any obvious red flags. Going a little bit deeper, you might make a point of searching for employees who exhibit the potential to learn and grow, i.e. people who can potentially take on more responsibility as they go forward, helping your business to grow and adapt over time.
Let us consider the smart fridge. This modern convenience, part of the much-vaunted Internet of Things and a key component of many smart homes, give you the ability to track its contents and see them displayed via smart phone or tablet when you’re away from home. To some, this might seem like somewhat of a frivolous piece of technology, but imagine the following scenario: you’re at the grocery store, doing your weekly stocking up; you have a whole shopping list full of items that you expect to be depleted within the next few days, from eggs and butter to fresh produce. What you’re not planning on buying is milk, because when you left the house you still had most of a gallon left. Then, all of a sudden, you receive an alert from your phone letting you know that you’re out of milk. Unbeknownst to you, your partner has accidentally taken the existing gallon out of the fridge and spilled it. Luckily, she instructed the fridge to send you a real-time update and you were able to add it to your shopping list before you left, saving yourself an extra trip to the store or a week without any milk.
Lots of businesses across disparate corners of the supply chain like to talk about their efforts to go lean, i.e. to drastically reduce their inventory usage by reducing lead times between production and shipping. This is often a logistical high wire act, requiring businesses to improve their production control, their demand forecasting, and their transport logistics. It’s also something that many furniture manufacturers have been doing since long before there was a trendy name for it. In fact, many modern furniture manufacturers rely on workflows that skip the inventory stage altogether, with products going straight from their respective production lines to the delivery vehicles that will bring them to their ultimate destinations.
Let’s say, hypothetically, that you’re a big fan of baking, and every so often your officemates are happy to act as guinea pigs by trying out whatever inventive confections you dream up. The one problem here is that your business involves a lot of travel and a lot of semi-remote workers, so it can be difficult to estimate how many people are going to be in the office on a given day—i.e. it's tough to know how large a batch of cookies to bring in when you decide to bake for your coworkers. You might simply base your batch sizes on past demand levels, assuming that because the last time you baked there were X number of people in the office, similar numbers are likely to hold true again, but this strategy has the potential to miss the mark drastically.
In a recent poll, PwC found that while 60% of respondents were “dabbling” with Industry 4.0 technology, only 3% had truly achieved a working Industry 4.0 paradigm. To some of you, this might come as a big surprise. After all, Industry 4.0 has been the subject of countless news stories, opinion pieces, blog posts, and whitepapers in the last several years—almost all of them pointing out its unprecedented potential for changing the face of manufacturing. Some readers, on the other hand, probably aren’t surprised by this statistic in the slightest. Why? Because they know how difficult it can be to find and implement the kinds of technology solutions that make Industry 4.0 possible. Businesses often have to wade through jargon to understand what’s on offer, and a solution, once selected, might require large-scale operational changes that can be difficult to implement. To help mitigate some of these challenges, here are a few questions to ask yourself as you evaluate Industry 4.0 technology solutions for your manufacturing outfit.
We tend to think of the (first) industrial revolution as a moment where the world changed in the blink of an eye. One morning, the world was dominated by cottage industries, and the next, steam power had completely transformed the nature of commerce, manufacturing, and modern life. What we sometimes forget is that the period we think of as the industrial revolution actually lasted more than 60 years—more than the length of a human life span during that era. Sure, things move a lot more quickly now, but it’s still a nice reminder that for all the talk about Industry 4.0 (aka the fourth industrial revolution), nothing happens overnight. The process of factories getting more connected and supply chains going digital might not take 60 years, but in the meantime it still remains a work in progress. That said, it's increasingly likely that the rewards will be worth the challenges.