The subsequent disruptions, triggered by the COVID-19 pandemic, have created a host of challenges and, significantly increased the complexity of the supply chain management process., including labor and equipment shortages, poor IT infrastructure, climate unpredictability, economic downturn, and geopolitical crises. Additionally, customer buying behavior has changed, with an increased demand for sustainable purchases.
Hence, automated solutions have become necessary to effectively manage the value network amidst these challenges. This requires a connected, agile, and resilient framework that can efficiently manage all activities, from procuring raw materials to delivering finished goods or services to end-users. By implementing such solutions, businesses can easily overcome challenges and maintain a competitive edge in an ever-changing marketplace. This is where, an agile supply chain network that’s more responsive to market disruptions is the need of the hour.
An efficient supply chain management process lays a solid foundation for the economic growth of a region or country. It bridges the gap between material processors, manufacturers, vendors, warehouses, transportation companies, distribution centers, and retailers. To ensure the proper functioning of each of these segments, a reliable information system is needed to provide appropriate management of supply chains via scheduling, sourcing, supplier management, and data analytics.
A tech-enabled data-driven platform for the supply chain can easily break the existing siloes, enabling easy accessibility of real-time data that improves decision-making throughout the network. Data and analytics also help build a resilient and responsive network, benefitting stakeholders in the following ways:
Given its far-reaching impact, businesses today have started prioritizing an efficient supply chain management process as it enables companies to have a resilient network where all the functions are fully optimized, driving revenue and growth and fostering loyalty and competitive advantage for owners. Furthermore, a well-executed supply chain can help align demand with adequate supply, reducing unnecessary waste.
An automated solution can help address supply chains’ current challenges and elevate their responsiveness to market changes. Supply chain automation, therefore, refers to using technology solutions to streamline supply chain processes and executing workflows with minimal human involvement.
It leverages extended capabilities of Artificial Intelligence, like Machine Learning and other digital solutions that automate and scale up each process, ensuring timely and efficient deliveries. It optimizes the whole network for higher efficiency and competitiveness. A few examples of automation in the supply chain management process would be:
Automation of manual tasks: Processing invoices, logistics bills, and other documents is manually time-consuming and causes process bottlenecks. With the power of automation, manual tasks are eliminated, saving time and costs for the owners while ensuring a smooth flow of resources in the supply chain. In addition, this allows employees to focus more on productive tasks like prospecting and building customer relationships.
Improvement in network visibility: Visibility and transparency of operations allow employees across different departments and locations to remain on the same page. It prevents chances of missed orders or delivery errors. With shipping automation, customers can easily track the progress of their orders with updated Information.
Enhancement of data accuracy: Automating the supply chain management process helps eliminate data silos and ensures quick access to reliable and accurate data. Data availability in real-time prompts informed decision-making about demand planning and allows the generation of dynamic and shareable reports for future strategy-building.
Betterment of customer service: Automation ensures faster delivery service with competitive fees and updated order information shared with end users. Since customers today are more demanding than earlier, exceeding their expectations has become the key to thriving in the market.
Elimination of human errors: While manually executing tasks, errors caused can ultimately prove costly for the organization, impair the brand’s reputation and remove loyal customers from the business. Thus, automation in the supply chain eliminates human dependency and manual work, thereby arresting plausible risks and averting costly mistakes like order duplication, incorrect entry from inventory or order details, inaccurate entry of customer information, picking or packing wrong items for customer orders, and so on are vital areas for automation in supply chain management.
Many CPG companies are turning to demand planning, which involves forecasting customer demand for a product or service over a period. For illustration, this case study discusses how Consumer Packaged Goods (CPG) companies have successfully implemented demand planning to forecast customer demand, manage costs, and maximize profits. It highlights examples of their strategies, challenges, and results.
Download case study on CPG companies successfully implementing demand planning.
The supply chain management process comprises five segments: planning, sourcing, inventory, logistics, and returning. And the segments together execute a list of primary goals s mentioned below:
Like the consumer market, the technology market is constantly evolving, with new cutting-edge solutions presenting intelligent ways of fulfilling buyers’ daily and extravagant needs. Automation, Artificial Intelligence, Machine Learning, and IoT are a few such examples that have extensively contributed to how companies conduct their businesses in the digital world. There is a list of others being implemented to revamp the supply chain management process:
Automated sorting and retrieval system: This technology is implemented in warehouses to traditional methods of sorting items around and retrieving them automatically. It automates the warehouse management system to replace the conventional approach with a more streamlined and linear process.
Procurement intelligence: A software solution for sourcing and supplier management enables the availability of the right components in the correct quantity to ensure the continuity of the production and delivery process. Procurement intelligence, including updated market insights, pricing, lead times, and regional and raw material trends, allows owners to make informed decisions pertaining to demand planning, sourcing, storage, and delivery of finished items.
IoT for tracking items: IoT-based tracking devices, as mentioned, are increasingly used to provide a real-time view of items moving along the supply chain network. This improves the visibility of the value network, helps identify bottlenecks in the system, and provides remedies for improvement.
Digital twins: A supply chain digital twin is simply a replication model of the value network created digitally to determine the impact of any physical change of the current reality and predict the outcomes in the real world. This simulation helps businesses to estimate market demand as nearly as possible. In addition, it optimizes supply chain planning and can be tested for impact by evaluating multiple supply chain scenarios.
Now, any new invention is not devoid of limitations and presents numerous challenges for end-users. Automation in a supply chain management process has its fair share.
Automation in the supply chain management process can drive tremendous value for organizations, their stakeholders, and customers. Market experts believe automation initiatives will eventually lead to supply chain autonomy in 10+ years. Unfortunately, many initial automation projects have failed to keep up with user expectations. Poor planning and implementation strategy can be cited as one of the major reasons for such outcomes. Therefore, adopting a few best practices like the ones mentioned below could help improve the overall performance of a supply chain management process and benefit all connected to the same network.
A collaborative value network bridges the communication gap between components and enables easy accessibility of crucial market insights in real-time. Information accessibility safeguards stakeholders from sudden market disruptions and assists them in preparing aforehand for an unforeseeable future.
Simply automating key management processes without thorough network analysis might give birth to further challenges and bottlenecks. Hence, a proper implementation strategy should be in place to enjoy the full potential of a modern software solution and quickly scale it across the network as and when needed.
A thorough analysis of existing processes within the supply chain network should be an integral part of automation implementation strategies. It is impossible to decide on the right automation solution without identifying areas of concern or how each method works. Since a one-size-fits-all approach doesn’t work for every industry, an automation program should align with respective business objectives and network requirements. For example, an automation program for warehouse management in the CPG sector would differ from the apparel industry.
It is imperative to maintain a team of experts who are well-adept with the new software solution and ensure its seamless performance during task execution. However, hiring software experts is not a cost-effective approach. Instead, owners can focus on training sessions to upskill their existing resources and help them become familiar with the fundamentals.
Any machine, robot, or software solution needs a continuous monitoring and maintenance framework to ensure smooth functioning. Investments in supply chain management automation do not go easy on the budget. Hence, proper monitoring of the platform and its timely maintenance should ensure higher returns from the investment.
New-age technology solutions are considered the primary source of competitive advantage by 61% of supply chain leaders and are means to address their digital transformation needs. Tech-enabled platforms that focus on elevating human decisions, managing assets, updating legacy systems, and unifying the value network are most desired to improve the supply chain management process. Therefore, emerging technologies like automation, AI, deep learning, and IoT have become critical investment areas. Market experts predict that in the next three years, the world will witness an increase in the adoption of digital supply chain technologies like intralogistics intelligent robots in warehouse operations, embedded advanced analytics, and data science in commercial supply chain management. Again, as per predictions, by 2025, nearly 25% of supply chain decisions will be made using an intelligent edge ecosystem.
Automation in a supply chain management process has assisted businesses in improving their supply chain efficiency through streamlined operations and connected networks. This has reduced unnecessary labor, warehousing, and other overhead costs for organizations and their stakeholders. In addition, automation, AI, and their extended capabilities are the means for their survival in the face of rising competition and increasing market disruptions.