According to McKinsey’s estimates, the rise of the Internet-of-Things (IoT) will have more than a $11 trillion economic impact within the next 7 years. Much of this value will come in the rapidly evolving world of connected consumer goods, such as the internet-enabled products that make up the modern smart home, but the impact will also be felt widely in a number of industries, from health care to natural gas production to, of course, automotive manufacturing. We’ve spoken briefly on this blog about the application of IoT devices for tracking inventory usage and traffic patterns, but what impact will this explosion of connected devices have on factory production processes themselves? More to the point, how can you leverage them into meaningful value propositions within your business’ existing workflows.
Imagine you’re living in a smart home. One evening after work you decide to drive to the grocery store to pick up snacks and drinks for an upcoming party that you’re hosting. When you take the road to the market rather than your usual route home, your car sends a notification to the appliances awaiting you at your house. The refrigerator, sensing that you’re low on milk, sends a reminder to your phone to pick some more up. Your dishwasher, tracking your detergent usage over time, estimates that you will run out before you next go shopping, because you usually wait at least a week between trips. Lastly, your car sends a text alert to your spouse, who might remind you of your guests' snack food preferences or other salient details.
Although automotive manufacturers have been hearing for years that Big Data is the next big thing, studies often show that executives, not just in automotive but across many different industries, fear that their organizations aren’t ready to take advantage of the new advancements in analytics. Big Data analytics can and will be a huge value-added proposition for companies hoping to stay competitive in the world of Industry 4.0, but it’s true that reaping the benefits of new technological insights often requires significant changes in workflows and IT infrastructure. Luckily, these changes are often not as daunting as they first appear. Here are a few suggestions for getting the most out of your advanced analytics.
Murphy’s Law states that whatever can go wrong, will go wrong—and nowhere is that more true than in the world of global supply chain management. Risk is simply a fact of life in almost all business spheres, but automotive industry manufacturers in particular frequently deal with incredibly complex supply streams that face a near-certainty of disruption. Managing complex relationships between suppliers, shippers, and production processes can lead planners to the brink of numerous potential pitfalls, but, luckily, in the era of Industry 4.0 there are more tools than ever designed to alleviate the pain points of the past.
Imagine for a moment that you’re an employee at an automotive manufacturing company. Every year of two, the owners create and share a strategic vision for the long-term future with management. Managers, in turn, create shorter-term plans of several months to put the longer-term vision into practice with Sales and Operations Planning (S&OP). As an employee, you manage your day-to-day tasks in accordance with those plans, responding the small crises of the workday with whatever resources and insights are available to you. Perhaps in responding to these situations, you find yourself wishing that there was something to bridge the gap between S&OP and those day-to-day processes. Sales and Operations Execution (S&OE) is that bridge, and it represents the path to the most responsive possible supply chain.
As the year draws to a close, we at flexis look forward to a new year's worth of innovation and insight as we renew our commitment to keeping readers informed on the new challenges and solutions that define the ever-changing world of supply chain management. 2018 promises to be even more exciting than its predecessor and we promise to help our readers stay up to date on the arising trends that may impact their businesses.
Today’s blog entry features thoughts and insights on the connected nature of Industry 4.0 and increased supply chain visibility and agility from Shay Sidner, flexis North America, Inc’s Director of Operations (pictured middle). As a respected thought-leader in the supply chain industry with more than 10 years experience in supply chain software and optimization, here Shay speaks in her own words about how Industry 4.0 connects to visibility and how this development in planning and production programs is the engine which drives modern manufacturing processes.
Ask anyone in the automotive industry about the future of artificial intelligence (AI) and you’re likely to hear one thing: Driverless cars. Yes, the development and proliferation of driverless cars or assisted driving is perhaps one of the greatest innovations on the horizon in today’s automotive manufacturing industry. Yet even so, AI has the potential to impact the automotive manufacturing supply chain in equally profound and interesting ways beyond the idea of the driverless car. In fact, AI has the potential to be a truly disruptive force in the way automotive manufacturing companies produce vehicles and how the consumer interacts with the end product.
With AI as an increasingly common technology platform, the automotive industry is set to experience significant changes in the coming years in terms of production and supply chain management. As vehicles become more integrated, individualized, and complex, manufacturing companies will have to leverage more lean methods of production and supply chain logistics to keep pace with the demands of such a variant-rich industry.
There are some terms or concepts in today’s modern supply chain management landscape that even industry insiders have difficulty defining or understanding. Whether it’s because the lack of visibility surrounding these concepts or a failure to fully embrace them as part of lean manufacturing and supply chain management, postmodern ERP is perhaps one of the most least understood or realized element of manufacturing and supply logistics. Not only does postmodern ERP have the potential to transform a company’s manufacturing and supply logistics, but it’s a key element in cutting the complexity of global supply chain management and leveraging enhanced operational functionality.
The question becomes: Why is postmodern ERP such an important value proposition for global manufacturing companies lacking visibility and understanding? What is it about postmodern ERP that proves difficult for planners and managers to embrace? What do we mean when we use the term postmodern ERP?
Fact or fiction. Trend or mindset. Fad or fixture. While Big Data has certainly permeated nearly every aspect of today’s manufacturing and supply pipeline, some industry analysts still question the validity, value proposition, and staying power of Big Data for companies as they strive to streamline their operational platforms and leverage lean manufacturing principles for optimal productivity and profitability.
First introduced to the manufacturing and supply chain landscape in the early 1990’s as a method of grouping, sorting, and analyzing large and complex data sets into executable actions. The sorting of these large, unstructured datasets gives manufacturing companies the capability to apply predictive analytics and other forward-looking logistic strategies to increase the efficacy, efficiency, and cost-effectiveness of planning and production programs.