Question

Supply chain technologies that deliver competitive advantage

Facing globalisation, increased product complexity, and heightened customer demands, companies are taking up advanced technologies to transform their supply chain from a pure operations hub into the epicentre of business innovation. Using sensors and ever-improving internet connectivity, forward-thinking companies are collecting data at every checkpoint, from the status of raw materials flow to the condition and location of finished goods. Machine learning, artificial intelligence (AI), and advanced analytics help drive automation and deliver insights that promote efficiencies making on-the-fly route changes to accelerate product delivery, for example, or swapping out materials to take advantage of better pricing or availability. 3D printing allows firms to localise production of goods closer to customers, allowing for faster turnaround, reduced transportation costs, and greater personalisation. Additive manufacturing is also opening doors to easy production of spare parts, enabling companies to slash inventory, cut costs, and create supplementary revenue streams. These advanced technologies are serving as a springboard for new business models, for example, many firms are piggybacking off the "internet of things" (IoT) to offer predictive maintenance services that guarantee product uptime while generating recurring revenue. "Looking into the future, it's about resiliency and an ability to adapt to changes in the marketplace and new business models," said Simon Ellis, programme vice president with IDC Manufacturing Insights, a market-research firm. "If a competitor comes along with a next generation, digitally fuelled capability, [companies] need to find a way to avoid being disrupted." Here are some of the technologies poised to overhaul supply chain operations: The internet of things (IoT) With IDC projecting double-digit annual growth for worldwide IoT spending through 2022, there is ample opportunity for connected and sensored "things" think finished goods, shipping containers, or warehouse stations to communicate information and deliver insights that will upend traditional supply chain practices. IDC expects discrete manufacturers, process manufacturers, and transportation companies to spend the most on IoT deployments, primarily to support manufacturing operations and the management of production assets, and, in the transportation space, for freight monitoring and fleet management. By tracking location, weather conditions, environmental status, traffic patterns, and more, suppliers can leverage AI and advanced analytics to determine, for example, if a shipment of refrigerated goods is at risk for equipment failure. Armed with such knowledge, suppliers can automatically reroute delivery to a closer distribution center or proactively dispatch a repair crew to prevent spoilage. The ability to monitor assets throughout the logistics journey also helps eliminate misplaced inventory and lost shipments, further reducing risk and revenue loss. "With just-in-time manufacturing, we care a lot about where a product is, when it's going to arrive, and how it fits into the overall logistics flow," said an emeritus professor of information technologies at the MIT Sloan School of Management. "IoT devices, combined with the cloud and AI, make all that much more effective and comprehensive." On the downside, IoT opens the door to increased cybersecurity risks, and even worse, physical exposure, especially for large-scale, mission-critical industrial assets. "The more IoT becomes a part of manufacturing and logistics systems, the risk isn't just in data attacks, but physical dangers" like an oil rig or manufacturing line explosion, said Madnick, the founding director of the Interdisciplinary Consortium for Improving Critical Infrastructure Cybersecurity. "Change, although good, always comes with risk. People have to go in with their eyes open," Madnick said. Blockchain While primarily associated with cryptocurrencies, blockchain, the distributed ledger technology, also ranks high on the list of technologies poised to bring improved visibility and transparency to supply chain processes. Because blockchain creates an immutable record of transactions, the technology is well situated to track the provenance of goods and establish trust in shared supplier information, especially when the parties have competing agendas and don't particularly engender trust. "What blockchain brings to the table is the notion of immutability nothing can ever be erased," Madnick said. "It also goes back to the issue of trust nothing is ever lost or altered." Blockchain can establish an audit trail that is far more effective than traditional methods like email or simple electronic record keeping, proponents say. As a result, blockchain's biggest potential is for facilitating track-and-trace applications that help companies document the chain of custody of goods. Doing so can prevent leakage, help identify counterfeit items and fraud, pinpoint at-risk suppliers, demonstrate that regulatory requirements are being met, and create transparency around sourcing. IDC projects that a quarter of OEMs will leverage blockchain to source spare parts by 2023 a move it predicts will improve accuracy of usable parts by 60% and lower costs by 45%. A lot of early blockchain supply chain use cases are food related. For example, Walmart is running a pilot project with IBM's Food Trust Solution to track lettuce from its suppliers to Walmart shelves on the heels of recent E. coli outbreaks. SAP and Bumble Bee Foods are collaborating to use the SAP Cloud Platform Blockchain service to trace the journey of yellowfin tuna from the point of catch to the store shelf to address consumers' demands for safe and sustainably sourced food. One of the biggest hurdles to leveraging blockchain is that it takes a village. In most cases, it's not one company implementing blockchain to garner traceability for its singular supply chain. Rather, to succeed, efforts will require an industry consortia-backed initiative that benefits a variety of competing partners. AI, machine learning, and analytics Every modern supply chain has a vast treasure trove of data that can unlock insights into complex global supply networks. By harnessing a combination of technologies like AI, machine learning, and predictive analytics, companies can automate warehouse operations, improve delivery times, proactively manage inventory, optimize strategic sourcing relationships, and create new customer experiences that increase satisfaction and boost sales. "In the past, the problem was we didn't have enough data now we have massive amounts of data, and the problem relates to what can we do with it," said Sergio Caballero, a research scientist at the MIT Center for Transportation and Logistics. That's where AI and machine learning come into play. Using algorithms and predictive methods, companies can parse through larger data sets and garner insights at a granular level all with little to no human intervention. According to IDC, half of all manufacturing supply chains will invest in AI by the end of 2021, garnering a 15% productivity spike. Consider the logistics nightmare of coming up with a transportation plan for thousands of product SKUs needing to ship out to hundreds of warehouses and distribution centers scattered across the globe. "You need a way to automate the collection and analysis of data [other than] manually," Caballero explained. Using machine learning to optimize the SKU data, "you can come up with a master shipping plan that's truly optimized." Predictive analytics are also a high priority. Deloitte's 2019 Supply Chain Digital and Analytics Survey found that surveyed companies are investing in predictive analytics primarily to drive cost reduction (cited by 81% of respondents) and improve customer experience (60%). The most promising use cases for supply chain analytics cited by respondents: Inventory visibility and optimization (32%), strategic sourcing and optimization (26%), and real-time product intelligence (22%). While most understand the big-picture potential of the technology trio, supply chain managers tend to underestimate what's required in terms of skills and boosting data quality to deliver real business value, Cabellero said. "Many companies still don't have a clear business case for the technology or understand how it can be beneficial," he said. A high-stakes makeover While there's still a huge learning curve with some of the more advanced technologies, there's no question that the supply chain is in the midst of a high-stakes makeover. That said, IDC Manufacturing Insights' Ellis reiterated the cautionary tale of focusing too much on technology at the expense of what's good for the business. "Technology is the bright shiny object, but at the end of the day, it must either solve a business problem or put the company in a possible to seize on new opportunity," Ellis said. "It all goes back to the goal of resiliency and pursuing new business models."

Question 35 marks

"Supply Chain 4.0 - the application of the Internet of Things, the use of advanced robotics, and the application of advanced analytics of big data in supply chain management: place sensors in everything, create networks everywhere, automate anything, and analyse everything to significantly improve performance and customer satisfaction"

Regarding the above information, elaborate on how predictive analytics in demand planning can enable organisations to develop a more efficient supply chain process.