Digital Twinning of Supply Chains

chiefoperatingofficer.blog Sunday, Mar 13, 2022 Subscribe Here! Email Address .. title Subscribe Here! Email Address Subscribe to Supply Chain Game Changer The Digital Supply Chain Road is Full of Potholes, Construction and Accidents! Digital Twinning article and permission to publish here provided by Jenis Sheth. This Digital Twinning of Supply Chains article focuses on transformative ideation of transport & logistics value chains. Current practices of Digitization, e-shopping and industry 4.0 have disrupted the market which is embarking for a revision of managed processes, policies and outcomes that may have once served the business well but are now being challenged at the fundamental level. Any supply chain has complications which creates difficulty in making changes in a piece of the value chain ֠a balance is required in supply chain orchestration through digital transformation. An identified knowledgeable approach, best-fit to the challenges caused in switching from an as-is to to-be model is proposed in Digital Twinning where the roughness of data utilized or gathered is proportionate with the problem statement under study. This orchestration from an As-Is to a To-Be encounters massive data challenges as one moves through several transition phases, each perhaps requiring different modelling methods and progressively finer data tuning in Digital Twinning. The physical supply chain is not easily changeable. In this Digital Twinning white paper, I have used the term digital twinning in the context of the inherent characteristics of the supply chain that are captured in a digital model. However, such a digital twin varies with modelling method, data visualization, to analytical to optimization or simulation. Creating out-of-the-box ideas requires a sandbox in SDLC approach for safe experimentation within the digital twins of transformative ideas. Tools in the sandbox have been carefully picked and open to enhancements as it need to be built with bridges. These tools should organize in such a way to deliver interim milestone results and data collection itself is progressive and matched to identically required in the respective digital twin. I hope that you get more insights from reading this Digital Twinning white paper and that it provides some mapping in your digital supply chain journey. Digital Supply Chain Hitches In todayҳ tech world, DIGITAL is disrupting the way businesses perform across all industries. The mass adoption of digital emerging technologies influences the operations of companiesҠlogistics and supply chain management. Smart and interconnected technologies, such as the Global Positioning System, Radio Frequency Identification, cloud computing and sensor devices have changed how businesses interact with their consumers. Customer-centric strategies, innovativeness, flexibility and responsiveness with higher emphasis on fulfilling consumer expectations are the key drivers in this digital era. Traditional supply chains with linear and long chains may not be sufficient in this digital driven era. Now-a-days businesses need to be dynamic in ratifying the ever-changing trends of consumer demand and shift to a more connected supply network, via digitally interconnected devices and complex platforms to keep pace with digital transformations. Currently digital supply chain needs to have the capabilities for comprehensive data availability, superior collaboration and seamless communication across value chains. Here I portray few disruptions in terms of elements and expectations which drives to the need of digital supply chain: If these disruptive elements not handled properly then it can cause problems and issues in the supply chains, ultimately leading to high operational costs, poor company margins, unacceptable service levels, and low productivity. These elements enjoin with the business problems of todayҳ supply chain which is mentioned in below diagram: Many companies still struggle to make progress with a view to digital supply chain transformation. One of the main reasons for this is that the legacy supply chain and logistics tools/platforms are not able to efficiently address and manage digital supply chain complexities. Therefore, creating a more adaptive and orchestrated platform for assets, business processes, and complex operations has become the imperative. Data Driven Supply Chain Innovation with Digital Twinning Internet of Things, Machine Learning and Big Data are at the heart of supply chain digital transformation. It produces enormous data and information that can be in form of structured data such as delivery transactions and warehouse operational data or unstructured data from external resources and social media such as delivery feedbacks. If it managed properly then this data can help generate smarter supply chain and logistics solutions and improve decision making processes. Hence, many companies are rapidly evolving and investing large amounts of funding and resources in trying to collect and transform data into competitive advantage. However, only collecting (raw data) would not turn the data into business insights. Data processing and analytics, with Artificial Intelligence and Machine Learning technologies are crucial. The raw data needs to be processed into the following steps as shown below: Supply Chain Understanding and Requirement This step involves understanding what supply chain aspects are to be improved or identification of the supply chain problems to be addressed before re-shaping the supply chain network. Bottlenecks need to be clearly identified at this stage. To do that, relevant data such as the current supply chain network, supply-demand flow, KPIs are needed. Data Collection and Acquisition The next step is to gather these data which are identified at earlier step. This step focuses on data availability & accessibility. Relevant data is collected from different sources, like ֠Enterprise Resource Planning (ERP) system, sensors, machine generated, social media and external web services. It can be structured or unstructured data, in the format of text, picture, audio or video. Data Processing The collected data may be duplicate or with errors. E.g., the same data may be inserted multiple time or timestamp of the data does not match with the fulfilment. It needs to be cleaned before subsequent analysis. This process would include matching record, identifying potential data inaccuracies, making computations for missing data, removing outliers, removing duplications, and formatting the data. Data Modelling and Algorithm Designing In this step, mathematical formulas, mathematical / optimization / simulation data models to the supply chain network. It generates insights by identifying relationships among variables, finding patterns from the data, predicting what is likely to happen and optimizing solutions by using what-if scenarios to evaluate transformative strategies for structuring the supply chain network. Data Communication, Visualization and Business Insights Once the data is modelled and analyzed using one or more modelling methods and algorithm designs, data along with insights and results from the model can be reported in many formats for communication with the relevant decision makers. Supply Chain Innovation Based on the data visualization results of the supply chain, the business owners would be able to take action to transform their network design. It may result in new incremental or radical innovations in the supply chain network. This innovation would be derived from the data and the model used. It would be recorded and updated into the system as new knowledge and insights and can be used for further analysis to derive future innovation. Supply Chain Orchestration Platform To address all pain areas of industry by utilizing the extensive supply chain digital twinning orchestration platform. Platform would structure in a way where it equips all parties with proper advocacy in managing changes of goods planning and flow. It integrates supply chain, logistics operations and technologies to strategically shift supply chain resources to create more value and higher returns. The Digital Twinning platform aims to tackle the main challenges of todayҳ supply chain that can be summarized as follows: Supply Chain Transparency: Collaborative data sharing through the whole value chain is still not in usual practice, hence making data available and visible across the supply chain remains as the main challenge. Functional and geographic data silos that do not share information openly, often characterize traditional supply chain. Usually, vast amount of generated data is stored in a complex and unstructured form that are not system-readable. This leads to less effective performance of the supply chain which are influenced by poor demand planning and management, high operating cost due to excessive inventory, high product return rates and poor SKU service levels due to stock-out. Supply chain orchestration platform aims to leverage various cutting-edge technologies (i.e. Internet of Things, Big Data Analytics and Machine Learning Algorithms) to provide seamless integration for all processes and activities in the supply chain with secure data sharing which ensures that all stakeholders have the same view of the database to process real-time information automatically. It will permit a supply chain to respond effectively to increase supply-demand, modal choices and demand volatility. Supply Chain Collaboration: Non-collaborative execution by supply chain stakeholders, particularly in the first and last-mile stage, could result in high costs, low productivity and asset wastage. With limited assets and workforce, supply chain and logistics activities have to be managed in innovative ways to ensure timely order fulfilment. Col...