Hyper-automation in Supply Chain
Manufacturers all over the world constantly invest time and money to enable the efficient and effective utilization of their resources. Chief among their concerns is the supply chain, which uses data and financial as well as other resources to get products to customers. Traditionally, the supply chain has been riddled with inefficiencies and redundancies due to involvement of multiple people, processes, and handoffs. Manufacturers are, therefore, turning to RPA (Robotic Process Automation) and AI (Artificial Intelligence) to engender intelligent automation. Intelligent automation capabilities are instrumental in not only enhancing supply chain efficiency, but also in providing much-needed transparency and control. In an industry where ensuring and exceeding customer satisfaction is paramount, intelligent automation can prove to be a boon.
Challenges in Automating Supply Chains Organization such as Uber Eats and Amazon are using next-gen supply chain technologies that are constantly engendering superior customer experiences by meeting their need for speed and convenience. If traditionally-managed supply chain companies want to remain relevant, they should follow suit.
This, however, is easier said than done. Several challenges make it difficult for organizations to upgrade their supply chain. Some of these include:
• Delays caused by information silos, resulting in poor response times
• Poor planning due to the lack of visibility throughout the supply chain
• Legacy systems and frameworks that are incapable of supporting multiple channels in an integrated marketplace
• Prevalence of outdated technologies that are rigid in their functioning and expensive to maintain
• The lack of new technologies that enable greater speed and efficiency
• Shortage of talented workforce
• Inconsistent priorities
Creating an intelligent supply chain entails constant product, service, and process innovation. This allows organizations to comprehend and deliver in accordance with customer expectations, thereby unlocking opportunities for business growth.
Role of Intelligent Automation in Logistics
Logistics is a vital aspect of the supply chain. It links buyers and suppliers to enable production that helps meet customer demand. The ever-evolving demand and the undying need of organizations to retain customer loyalty have forced them to optimize their supply chains.
So far, logistics personnel have been deploying basic manual tools to plan and manage deliveries. Predicting shipment-related risks, such as bad weather and infrastructure failure, in real-time is a challenge. It is also difficult to accurately determine estimated time of arrival (ETA) or know about on time and in full (OTIF) commitments, and other conditions that can help ensure that loads are delivered as expected.
Intelligent automation benefits logistics by significantly reducing manual effort and enhancing efficiency. More can be accomplished with fewer resources, resulting in lowered overhead costs and maintaining competitive price points. Human workers are able to centralize scattered data and use it to connect the dots, ultimately gaining the required insights within minutes.
This data also enables smarter decision-making. Intelligent technologies like scenario modeling and recommendation engines empower organizations to resolve their more complex problems. AI-based smart workflows automate critical processes, allowing supply chain personnel to focus on enriching customer experiences, innovation, and revenue-generating tasks.
What Does Intelligent Automation in Supply Chains Involve?
1. Self-Learning Algorithms for Predicting Demand
Organizations frequently detect demand fluctuations due to changing customer requirements. Since inaccuracies in forecasts can negatively impact planning, inventorying, and order fulfilment, it is crucial to know about true demand. This may different from forecasted demand, which might be traditionally calculated based on historical data. In modern times, however, organizations are increasingly leveraging self-learning algorithms to derive true demand, by using real-time demand signals. These algorithms analyze data from multiple sources, such as points of sale (POS), economic indicators, weather conditions and reams of other data to deliver insights. Using real-time signals to predict demand reduces errors to a great extent as it makes predictions based on the current market scenario rather than historical data.
2. Cognitive Analytics
Each development in the supply chain creates enormous amount of structured as well as unstructured data. This data provides critical insights that drive operational excellence and advanced operating models. However, because the majority of the data is unstructured, it can be difficult to analyze it using conventional IT methods that do not recognize natural language and elements in images. This is where cognitive analytics comes into the picture. Without cognitive abilities, organizations are forced to rely only on structured data, which may prove insufficient to gain insights into current market conditions and evolving customer behaviors. This makes it impossible for manufacturers and logistics providers to upgrade operating models and stay competitive. When it comes to supply chains, predictability is a key differentiator. Predictive analytics analyzes multiple variables and makes forecasts will greater accuracy. Cognitive abilities enable the interpretation of data correlations, while employing advanced algorithms to gain insights from unstructured data. Manufacturing companies are also using cognitive analytics, which harnesses data from various sources and channels to analyze patterns, understand consumer demand, and provide customized services. This, in turn, improves return on investment (ROI). Logistics companies are now using GPS (Global Positioning System)-based smart containers, tracking devices, and sensors to trace the movement of packages. These technologies have enabled enhanced container utilization, leading to better package-handling and higher return on assets (ROA). Logistics providers are deploying cognitive analytics to facilitate data collection, aggregation, as well as its management to gain insights at speed. This is also being done for scaling and visualization for more accurate decision-making and resolving persistent issues. An increasing number of manufacturers are embracing digital transformation to touch new heights in operational excellence. Logistics providers are harnessing emerging technologies, like advanced robotics, analytics, AI, and ML. Long-term value enhancement is being ensured through the adoption of new business models that encourage the use of smart factories, products and packaging, as well as smart supply chains and well-linked field services.
3. Autonomous Order Fulfilment
While technologies such as radio-frequency identification (RFID) and GPS have been used in supply chains for a while now, the advent of AI is proving to be a game changer. A prime example of this is being provided by Amazon. The e-commerce giant is already using robots in its fulfilment warehouses, while drones are being tested for deliveries. Self-driving vehicles are being tested all over the world with several logistics companies planning to incorporate them in their transportation fleets. Navigation is being enabled via preinstalled radars, cameras, and data-emitting sensors. AI-powered systems are being leveraged to process and analyze data. Crashes and accidents caused to due to human error and fatigue are being minimized. Autonomous fulfilment and deliveries have, therefore, made processes more effective, efficient, and environment-friendly. The combination of GPS and Internet of Things (IoT) has been instrumental in improving lead times, while the use of autonomous vehicles is helping usher in a new era of enhanced mobility. These factors are all set to revolutionize supply chain and logistics in B2B as well as B2C markets.
Benefits of Automating Supply Chains
Using intelligent process automation enables manufactures to automate logistics and order management functions, and enhance customer experiences to a great extent. Manufacturers are increasingly leveraging AI-powered intelligent bots to gather crucial data from unstructured orders being placed through various channels, like emails and fax. These bots are adept at entering this data into relevant systems without the need for human intervention of any kind. Intelligent systems are able to learn from past and current data, thus enabling enhanced decision-making and more accurate forecasting.
For instance, orders that display certain characteristics are directed towards different workflows. Orders from reliable vendors are processed faster and simple orders are routed to fulfilment rapidly. Orders that raise concerns are ticketed and sent to a human employee for closer investigation. Supply chain processes are embedded with advanced technologies, like intelligent analytics and ML, to lower the overall processing time. This arrangement can be extrapolated to bigger volumes to accelerate operations, freeing up the human workforce to focus on more strategic tasks.
Overall, by automating even a single area of the supply chain, manufacturers can look forward to:
• Reduced costs
• Minimized errors
• Accelerated processes
• Informed decision-making based on accurate forecasting and intelligent insights
• Faster shipment and deliveries
• Enhanced customer experiences and customer relationships
How Hyper-Botz Can Help You
At Hyper-Botz, we believe in providing superior automation services that transform your supply chains. We achieve this objective by leveraging intelligent technologies, skills, processes, as well as visualization that help us build solutions tailored to your organization’s unique needs.
We are adept at fusing business processes with sophisticated cloud-based solutions that are centered around analytical insights, benchmarking, change management, and more. From planning to delivery, we have you covered every step of the way.
Our experts will equip you with a comprehensive collaborative platform that allows real-time visibility across all supply chain operations. Our algorithm-based demand prediction services will enable more accurate forecasting, while cognitive analytics will empower you to gather and centralize more and more data. All this and more will enable insight-based decision-making, improve efficiency and effectiveness, and bring you the competitive edge to become an industry leader.