AI and Data Science: Accelerating supply chain industry
Deccan Chronicle | DC Correspondent
With the help of AI, a variety of tasks can be escalated with limited scope for human error.
Supply chain is perhaps the most data-rich environment in the businesses of today.
A mere mention of Artificial Intelligence would have our heads spinning, thinking about the latest sci-fi movie, robots conspiring to overtake human existence, space travels and whatnot. However, outside the realms of science fiction, the technology has been majorly helping organizations sift through heavy data sets to discover anomalies and best practices. By taking into account enormous data points, organizations can not only envision the future with a certain degree of certainty but also be better prepared for the same.
Supply chain is perhaps the most data-rich environment in the businesses of today. The chain supports an open flow of data from a diverse set of sources. By the same virtue, supply chain verticals stands to gain a lot by deploying automation. With the help of Artificial Intelligence, a variety of tasks can be escalated with limited scope for human error. For instance, AI can effortlessly blend in data from disparate systems, spread across the supply chain verticals, explore any missing data points or bugs and escalate processes.
Besides, machine learning feeds on data; as we go on to feed more data, the system learns on its own and further streamlines the processes. Some of the ways in which Artificial Intelligence & Data Sciences can accelerate the supply chain processes are discussed, as follows:
Optimizing Operations with Historical and Predictive Analytics
Artificial Intelligence & Data Sciences create enough room for faster and accurate decision making.
Companies can now compute major chunk of historical data, in order to weed out the errors and optimize production runs and distribution plans. The technology contributes towards better risk management by extracting data from a multiple sources and hence, identifying patterns and risky behaviours.
The technology platform goes through historical data and figures out the best way forward, when the supply chain mix is confronted with a particular risk or challenge. Thus, the technology also suggests steps that should be taken to mitigate the underlined risks.
Furthermore, with the advent of Predictive Analytics, organizations can also be better prepared to handle whatever is coming their way. For instance, AI can help companies predict how changes in the economic scenario may reflect upon the demand for their product(s) and hence, can adopt a proactive approach towards distribution and sales.
Additionally, customers have no longer remained a conundrum to the enterprises of today deploying advanced analytics. By tracking their behaviour patterns, purchase orders and browsing activities, companies can further gauge demand and the performance of their products.
Better Planning and Inventory Management
With the advent of Internet of Things, the supply chain functions are being radically transformed. By deploying IoT sensors and devices, companies of today can collect information in real-time and hence, plan ahead of time and better manage the inventory. The combination of different technologies in the supply chain mix creates opportunities for products to be stored more effectively, easily tracked and delivered more quickly.
Artificial Intelligence is equipped to handle and resolve singularities occurring in the supply chain plan, more efficiently and quickly, when compared to humans. Offering enough flexibility, AI can be deployed either at the top or in the middle of complex hierarchy of supply chains, as deemed fit by the organization.
Standing amidst such massive tech disruptions, it is only natural for supply chains to evolve. However, when it comes to adopting the accelerating technologies, we seem to have a long way to cover. A study by Accenture discovered that only 17% of the organization has reportedly deployed analytics in one or more aspects of the supply chain. However, the same study also concluded that a majority of enterprises are on the verge of heavily investing in adopting big data and automation.
This is merely the beginning of an era. While organizations of today may find it cumbersome to adopt the transformations, the technocrats are currently involved in making the deployment easier and more user-friendly. Owing to the improvements in the field of Natural Language Processing, the future belongs to Conversational AI, such as Chatbots, where enterprises can converse with the mysterious technology. As per the estimates shared by Gartner, Conversational AI will become part of at nearly 80% of supply chain software applications, enabling enterprises to simply talk to the technology, either verbally or via chat.
—by Prabhakar Chaudhary, MD - HAL Robotics.