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.

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.

In a recent Seattle Times Article, readers got an intimate account of how Cloudburst Brewing creates its seasonal fresh hop beers. While most hops used in beer production are dried before they’re shipped from the farm, fresh hop beers utilize fresh-picked, “wet” hops that haven’t been dried yet. As such, this popular style can only be brewed during and immediately after the annual hop harvest, and only under ideal conditions. A traffic jam, a flat tire, or a power outage at the brewing facility could jeopardize brewers’ efforts, owing to the extremely short shelf-life that these “wet” hops have.

Let’s talk about Amazon Go for a moment. The incredibly successful online retailer has recently made headlines with its latest foray into brick and mortar shopping, a series of convenience stores that, notably, don’t feature any human cashiers. Instead, shoppers (all of whom need an Amazon Prime account) use an app on their phones to scan each item they put into their (physical) shopping cart. This is noteworthy for a host of reasons, but let’s look at it from an inventory management perspective. The store is stocked with a considerable number of items, which all need to be replenished as they are sold, and Amazon is able to track the flow of goods out of their stores with no human intervention. Not only that, but they’re able to link each piece of inventory that leaves the store to a particular user account, and then make recommendations to that user based on analytics processes designed to predict future buying behavior.

Let’s say you’re an amateur baker, and you’ve just agreed to participate in a pie bakeoff with some of the other bakers in your town. You have a few pie recipes that you like, but because the stakes are suddenly much higher than usual, you want to create a new recipes that improves on your existing ones, in order to better compete with your opponents. Most likely, this is going to mean finding new or old recipes to adjust and adapt, and then taking those adapted recipes and producing test batches of them, trying out the results, and producing new test batches with the tweaked recipes. This process, needless to say, would be incredibly time and resource intensive—not least of all because baking is an extremely fickle business, and it’s often difficult to predict the results of changes in ingredients or cooking time.

Logistics 4.0, digital logistics, modern transport logistics: whatever you want to call it, the new paradigm emerging in the world of transporting goods from production plants to consumers is gaining steam rapidly. While, in the past, logistics was frequently a matter for pen-and-ink planning, relying on a set of well-trodden trade routes, the industry is becoming more sophisticated, more complex, and more connected than ever before. As the industry evolves, the utility of this new level of connectivity will become more and more apparent, resulting in exciting transformations in the way that goods are moved from place to place. Don’t believe us? Just take a look at some of these statistics.

As we enter an increasingly digitized era in supply chain management, owing to new technologies from IoT sensors to real-time freight tracking, the hurdles that face manufacturers and logistics providers alike are becoming ever more complex: software integration are becoming increasingly difficult, longstanding information silos are suddenly becoming huge operational hurdles, and increased globalization is adding complexity to virtually ever corner of the supply stream. What waits on the other side of those challenges? A world of increased connectivity and the promise of the Industry 4.0 revolution. Anyone who’s been following the global automotive supply chain the past several years know that, now more than ever, success is often a matter of turning mission critical data into concrete business insights.In the spirit of turning data into insights, here are a few statistics that might shed some light on the current state of supply chain management.

Raise your hand if you remember what it was like navigating on road trips in the pre-smartphone, pre-GPS era. Before you set out from your house, you had to find your destination on a roadmap, and chart a course that could, if the destination was far enough afield, involve multiple intersecting highways or interstates. If you were driving alone, checking your map could be hazardous during driving, meaning that you had to memorize most of the turns, even if they were on unfamiliar roads. If you needed to fill up on gas, finding out the location of the next gas station would be a matter of waiting for signs on the highway to appear and alert you to the exit number of the next rest stop. Once you left the highway, you had to navigate by street signs until you reached your destination. If, at any point, a road you intended to use was closed, you would be back to the drawing board.

Reports of your job’s impending obsolescence have been greatly exaggerated. Sure, as Industry 4.0 systems continue to gain traction the nature of work, not just in the automotive and industrial spheres but across the entire global economy, is likely to be affected in tangible ways by the rise of connected, cyber-physical systems and the increased use of internet of things (IoT) devices. But despite what you might have heard, this doesn’t mean that people’s jobs are going to vanish at an unprecedented rate. After all, the first three industrial revolutions (steam power, electricity, and computers, respectively) helped to expand the labor force rather than contract it—why should the fourth industrial revolution be any different? 

These days, when most people think of automation, one of their first thoughts is of self-driving cars. What many people don’t realize, as they picture themselves magically napping away their morning commutes, is that when it comes to autonomous vehicles there are actually six levels of autonomy. At level zero, you have a standard automobile, which requires the driver to make every decision and maneuver. At level five, the car itself makes and carries out all of the decisions without any human intervention. In between, we find cars that can maintain speed and avoid other cars on the highway, cars that can change lanes and make turns unassisted, and cars that can perform automated interventions in crisis situations like potential spin-outs.