Digital technologies and methods are rapidly transforming the capabilities, scale and scope of global logistics. In this video, we review some of these technologies and preview how global logistics are changing as a result. Digitalization of supply chains and logistic services will integrate and intertwine both. One of the constants in discussions about digital supply chains involves integration. The goal of integration is to transform the supply chain from a sequential network of information flows, to a web of information paths that connect all aspects of a supply chain from the beginning to its end, as shown in this table. Hopeful outcomes of an integrated supply chain are transparency for complete view of the entire supply chain, communication for real-time information and data, visibility for real-time knowledge about the state of the supply chain, flexibility for immediate adaptation to changes in problems in the supply chain, and responsiveness for fast real-time response to customer demands and changing requirements. With digitalization, a supply chain will become much more intertwined and integrated and therefore will become more analogous to a supply chain rope, as opposed to a supply chain. Here is a useful chart showing how various technologies can help facilitate a digital supply chain. These include character recognition or OCR technologies, robotic process automation or RPA, advanced analytics or AA, artificial intelligence called AI, Internet of things or IoT, and distributed ledger technologies such as DLT. Pause the video for a moment to examine this chart to see how these technologies are employed in supply chains. We'll describe them in more detail in the next pages. OCR or optical character recognition is the translation of physical text documents into digital format. Since much of the world still runs on paper, converting paper documents to digital records is fundamental. OCR software has capabilities far beyond just converting printed letters to ASCII characters on a computer. OCR can now check and verify its results, create documents, read handwriting, and much more. A perhaps familiar example is our current ability to take a picture of a check and then text it to our bank for deposit. Somewhere along the way, the digital picture of the check is converted to data and useful information that the bank can verify and act upon. Related to OCR is robotic process automation or RPA. RPA is a specialized software robots to automate and standardize repeatable business processes, such as invoices, bills of lading, customs documents, and many of the other documents required for global supply chain transactions. RPA is best suited for work that is consistent and routine, is high-volume, is prone to human error, but is however limited to work that does not require higher-level decision-making. Therefore, RPA is most suited for data entry type tasks. Central to digital supply chain implementation is the Internet of things or IoT. At the heart of IoT are ubiquitous sensors that measure and transmit data in real-time to back-end services, often via the Internet. Information collected can include almost anything that can be quantitatively measured, such as temperature and humidity, location information in warehouses and supply depots, and transit tracking of trucks, containers, and deliveries. At the front end, this measurable data is collected and assembled. At the back-end, the information is acted upon in some manner to assist making operating decisions, troubleshooting, emergency alerts, and so forth. Here's a more complete representation of what IoT sensors can identify, measure, and track in real-time. Take a moment to pause the video and examine the many types of sensors that could be used for measurement. Of particular importance for supply chain digitalization or radio frequency ID or RFID tags. These tags can be attached to individual items or containers and can easily be read with an appropriate RFID equipment. Their utility is similar to that of barcodes, but do not require line of sight to be used. For example, inventory in a supply room can easily be conducted and checked with an RFID reader that can quickly catalog all those items, with all the items within its range of operation. Eliminating the need for physical hand counting. Advanced analytics make it possible to analyze and interpret all data and information collected from RPA in OIT technologies. There are four levels of analytics. Descriptive analytics use summary statistics to tell us what happened. Diagnostic analytics use techniques such as regression analysis to tell us why it happened. Predictive analytics use methods such as demand forecasting to tell us what will happen in the future. Prescriptive analytics use sophisticated techniques such as math modeling that inform us how to do better in the future. Non-computer capabilities and abundant data make analytics far more powerful than in the past. Generally, artificial intelligence is complex software designed to synthesize and learn from abundant IoT data. At its broadest, AI develops software programs to mimic human intelligence using logic, if-then rules, decision trees, and machine learning among many other tools and techniques. You're again computing power and ubiquitous data makes sophisticated AI techniques feasible and economical. A subset of AI is machine learning, which allows computers to improve calculations based on experience. Experience means new data. For example, demand forecasting can be improved over time with more and more data. Much of this improvement can be automated so that improvement occurs without human intervention. A subset of machine learning is deep learning, which allows computers to make inferences based on examination of lots and lots of data. For example, self-driving vehicles learned to distinguish pedestrians from lampposts by analyzing vast amounts of data over time. Here's an example of machine learning in a supply chain. In this case, large amounts of data are collected from shipment histories, point-of-sale data and other information. Data and other information is analyzed to make demand forecasts and recommend restocking schedules. Once demand occurs, the accuracy or inaccuracy of the forecasts is then fed back into the forecasting algorithm and use that data to improve that forecasting model, so overtime the system gets better and better at making good demand forecasts. Another rapidly evolving tool for digital supply chains are Distributed Ledger Technologies, or DLT. Prominent among DLT is the blockchain technology. In supply chains, blockchain technology creates an incontrovertible and indelible record of supply chain transactions from the purchase of raw materials through to the sale of the final product. The World Economic Forum reckons that blockchains can slay the paper monster of legacy supply chain systems. Blockchain does this by streamlining and eliminating paperwork, thus facilitating new global trade worth perhaps $1.1 trillion. Blockchains can guarantee the origins and journeys of globally traded goods. For example, blockchains can provide security in certain provenance for global goods such as fair trade coffee, sustainable lumber and fish, and suppliers that meet labor and environmental standards. Generally, the benefits of logistics and supply chain integration are many. Integration will greatly improve the efficiency by providing logistics visibility, faster procurement, smart warehousing, efficient spare parts management, autonomous logistics, prescriptive supply chain analytics, and generally less waste. Logistics and supply chain integration will also greatly improve responsiveness by providing better forecasting, better inventory control, fewer stock outs, reduced over stocking, faster replenishment, bottleneck identification, and predictive maintenance, among many others. In summary, digitalization will starve to integrate logistics and supply chain management. Digitalization is enabled by rapidly evolving digital technologies, and will result in such benefits as better visibility, improved efficiency and faster responsiveness. More efficient and responsive supply chain would await us with logistics digitalization.