How does digital transformation help supply chain?
- Automation – Streamlining of work along the supply chain can be done by automating operations and systems. Digital supply chain and supplier management automation can be leveraged to collect and process real-time information automatically, thereby eliminating the slow, time-consuming effort of manually gathering, entering, and updating data. An automobile factory, for example, may employ intelligent automation to speed up production or minimize the chance of human mistake, while a pharmaceutical or life sciences company might use it to save costs and obtain resource efficiencies when repetitive procedures occur.
- Internet of Things(IoT) – The IoT are defined as the network of physical devices and systems that communicate and exchange data, holds real potential for optimizing supply chain operations, especially for collecting data from across many data sources and measuring performance in real time. These devices provide real-time visibility of operations throughout the manufacturing process. Manufacturers can embed IoT sensors in most items moving through their supply chain, gaining unprecedented visibility and traceability of parts for assembly, finished goods, and more.
- Advanced analytics – As IoT data continues to grow at a rapid pace, the data is often unstructured, disorganized, and incomplete. The massive amount of supply chain data collected is of hardly any use if a company can’t quickly and intelligently analyze and leverage it. A major role of advanced analytics is in making supply chain data usable, providing greater insights into processes, products, and people and, in turn, enabling supply chain leaders to make better decisions to improve operations and business.
- Artificial Intelligence – AI and machine learning technologies due to getting exposed to more data learn over time as they are have great potential to transform supply chain processes. Companies are enabled to collect data from a variety of areas and apply self-improving analysis. AI can be used throughout the supply chain to find patterns, forecast future scenarios, identify and correct data errors, surface risks, elevate IoT insights, and improve material planning, order scheduling, and logistics.
- Block chain – Block chain is essentially a digital, decentralized, distributed, and immutable ledger, and it has the potential to be very disruptive. Information once entered into the block chain, the distributed ledger becomes locked and tamper-proof. Smart contracts, traceability, authentication, and other highly decentralized supply chain management functions are considered key candidates for block chain, although most supply chain block chain projects are still pilot projects.
• How to transform supply chain digitally?
- Define a vision – For starters there should be a clear vision for your supply chain digital transformation. Vision should be closely aligned with your enterprise goals. These goals can be related to specific business objectives, such as improved supply chain visibility, better and faster decision-making, automated operations, and integrated customer engagement.
- Access existing systems and resources – Identify what capabilities you’ll need to achieve your transformation goals and determine the gaps. Look for:
- Data collection and analysis: Assess the capability of existing systems to generate, collect, and analyze data. Can the data be accessed easily and used to draw actionable insights?
- Legacy systems: Do existing systems use technology that can support your new goals? Is the technology aligned with business objectives? Identify digital solutions that are best suited to achieve the desired outcomes.
- Workforce skills: Determine if the workforce has the necessary skills to work with and adapt to the new business model.
- Unify data an processes – Unified platform to gain complete, end-to-end visibility of the digital supply chain to be be used. Utilize the enhanced transparency to streamline core functions, including demand forecasting and planning, inventory management, warehouse management and logistics. The key objective here is to enhance visibility for every role and process across the extended supply chain.
- Leverage cloud – based solutions – Shared solutions built by cloud can be accessed by multiple stakeholders in real time. However, you must first assess and identify aspects of the business that can benefit most from the cloud. These can include supply planning, procurement, inventory management, warehousing, transportation and logistics, product lifecycle management, and customer service. Replacing on-premise supply chain management softwarewith cloud-based solutions can boost operational efficiency and significantly improve the ability to collaborate with suppliers and partners.
- Automate the planning process – Automated planning helps you simplify tasks and derive meaning from large volumes of data. Differentiate planning tasks that can be automated from others that are more strategic and need human intervention to arrive at a final decision. Less critical planning processes that can be optimized automatically have to be looked at. These are routine or recurring tasks where best practice solutions can be applied automatically. Processes that involve complex situations or require collaboration between planners shall not be automated.
- Use data and analysis – Supply chain professionals rely on real-time data to make informed decisions in a digital network. Collaboration becomes easier and effective with suppliers, partners, and other functions. Access to real-time data enhances visibility across the supply chain and helps identify potential disruptions. Additionally you can use AI-powered analytical tools to draw actionable insights and improve planning processes.
- Align people with processes – Despite the introduction of advanced technologies, the shift to a digital supply chain would be futile if the workforce is not aligned with the new processes. This shift should integrate digital technologies with people, processes, and management infrastructure. Without such integration, teams may not be able to work efficiently in the new business model and fail to achieve the desired results.
• How does the accuracy of supply chain improve through digitization
- – Some predictions made by the company Gartner on April 20, 2022 are :
- By 2026, 75% of large enterprises will have adopted some form of intralogistics smart robots in their warehouse operations.
In addition to labor availability constraints, rapidly rising labor rates and the residual impacts of COVID-19 will compel most companies to invest more in cyber-physical systems— especially intralogistics smart robots that can be deployed in warehouses and distribution centers. These robots address the need to automate certain processes to supplement the human workforce. Implementation is faster and less expensive than more traditional means of automation, such as conveyor sortation or automated guided vehicles.
- By 2026, more than 75% of commercial supply chain management application vendors will deliver embedded advanced analytics (AA), artificial intelligence (AI) and data science.
Improved decision making through the use of AA and AI is a high priority for supply chain users in all markets and industries. Supply chain application vendors noticed and are reacting accordingly. Many application vendors now offer AA and AI capabilities embedded within their applications and continue to expand these areas. Large mega vendors and supply chain suites vendors have an advantage due to their size, which allows for more investments, but smaller vendors are catching up.
- By 2026, 25% of supply chain execution (SCE) vendors will have rewritten their core application to a micro services architecture, but only 5% of supply chain organizations will have adapted to true composability.
As supply chain complexity and volatility increases, supply chain organizations must become more agile. This means that traditional applications, built around aging architectures, are not fit for the job anymore. One way to future-proof the technological base of the supply chain is to switch to micro services-based and composable application architectures. However, for most organizations, upgrading or implementing a new SCE application is a costly and time-consuming process. Most supply chain leaders constantly balance the risk of not upgrading against the desire to minimize the cost. There will certainly be early adoption of modular, composable services in the supply chain — especially for enterprise-centric applications that can be managed internally. On a multi-enterprise level with different business partners and systems involved, challenges for adoption at scale remain.
- Through 2025, 25% of supply chain decisions will be made across intelligent edge ecosystems.
Edges are physical locations where things, people and data connect — such as operators, machines, sensors and devices that are located across the supply chain network. Edge ecosystems allow decision making to take place close to the original source of information. Edge ecosystems deliver the infrastructure for automated network tools, devices and applications to work in tandem with each other — be it drones, robots or connected vehicles. Advances in data communications services, such as Wi-Fi, Bluetooth and 5G will further support edge ecosystems and complement traditional centralized supply chain solutions. Across many supply chains, edge computing decision making is already occurring, and the focus over the next three years is to identify further use cases where connected, automated and autonomous networks of edge decisions can be enabled.