Imagine for a second that you’re entering a friendly betting pool for the 2018 World Cup. Germany won the contest in 2014 (the most recent tournament), so you decide that it stands to reason that Germany will win again this time around. Hindsight being 20-20, we now know that you would have lost your bet, as France won the tournament and Germany didn’t advance out of the first round. Your betting strategy of assuming that past results would continue to hold ultimately wouldn’t prove to be the best approach.

Let's say you've got big event coming up—maybe an awards ceremony, or an important anniversary. You and some of your friends are going to the event together, and to make the whole affair a little more special you decide to rent a limousine take you there and back. Though the venue is only an hour’s drive away, your friends’ homes are spread throughout your town in ways that make planning the optimal order in which to pick them up (and drop them off after the party’s over) a challenge. On top of that, not everyone will be ready at exactly the same time, and those who would be picked up later in the process would like to know in advance so that they can spend more time preparing. Where do you begin when it comes to planning out a tour that works for you?

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.

In theoretical computer science, the traveling salesman problem asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city and returns to the origin city?" Anyone who has worked in transport logistics or transportation management knows that in most cases there is no easy answer to this question, and that finding the optimal route between different cities or even different stops along the same tour can be a serious logistical challenge—one that requires planners to manage customer delivery windows, anticipate traffic patterns, and optimize time and distance.

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? 

Let's say you're an OEM, with a sleek manufacturing space and a sophisticated, technologically cutting edge process for creating a particular automotive part. But you have a problem: At this point, your incredibly sophisticated production techniques aren't not being complemented by an equally sophisticated, multi-level approach to production planning and resource scheduling. This results in a disconnect between the high quality of your products and your ability to maximize capacity and meet customer delivery requirements. How can you build towards a production planning workflow that complements your product and fulfills your business goals? 

Imagine you’re packing up supplies for a backpacking trip across Tuscany. You’re limited by how much you can comfortably carry for many miles of walking, and you have to decide which items and in what quantities you’ll need in order to make it the entire length of the trail. You start with clothing and a first aid kit—but how much food do you bring? You want to pack light, and you think that you’ll reach the next town (where more food could potentially be acquired) within a day or two, but if you’re forced to slow down for some reason you don’t want to run out of things to eat. Bringing more food, however, means leaving behind one or two of the books you planned to read in your more leisurely moments. 

Let’s say you’re moving into a new home. After a long day of loading boxes and furniture into your car and driving them to your new place of residence you’ve finally transported everything into your new house and you’re almost ready to start unpacking and get the place settled. Before you get down to the work of opening up all of your packed boxes, you realize that you haven’t eaten all day, and should probably whip something up before you do any more manual labor. It should be pretty easy to find your kitchen supplies and snack foods, because you made a list of what was in each box before you moved them. One problem: you don’t know which box the list is in. 

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.