Real Time Analytics in Supply Chain
Paradigm shift
Over a decade, we have witnessed a paradigm shift in the way information is generated and handled in society. The change is driven by various factors: our vastly increasing ability to store and perform computation over very large sets of data; and most importantly the introduction of Internet of Things. The amounts of data available when making decisions or keeping an overview is enormous and is produced at ever increasing rates and the characteristics of that data produced by those heterogeneous and dynamic sources is very different from the structured data traditionally used. The overall trend says the world is becoming more information centric but the capacity to handle, process, analyses and read value out mammoth data is absolutely critical for industries as well as society. …show more content…
The amount and types of data that can be used to manage the supply chain has grown enormously. Supply chain specific data such as shipments, orders and inventory levels from both manufacturer as well as retailers provide a rich set of demand signals about products across the value chain — from raw materials to consumer purchases.
Production and distribution networks can be made more efficient by using powerful data-processing and analysis capabilities. It enables companies to share data with their partners across the supply chain which eventually results in improved demand forecasting accuracy and discovery of new demand patterns. In addition to this they can even increase asset uptime and expand throughput, enable preventive maintenance of assets and resource optimization along with conducting near real-time supply planning using dynamic data feeds from production
Paradigm shift
Over a decade, we have witnessed a paradigm shift in the way information is generated and handled in society. The change is driven by various factors: our vastly increasing ability to store and perform computation over very large sets of data; and most importantly the introduction of Internet of Things. The amounts of data available when making decisions or keeping an overview is enormous and is produced at ever increasing rates and the characteristics of that data produced by those heterogeneous and dynamic sources is very different from the structured data traditionally used. The overall trend says the world is becoming more information centric but the capacity to handle, process, analyses and read value out mammoth data is absolutely critical for industries as well as society. …show more content…
The amount and types of data that can be used to manage the supply chain has grown enormously. Supply chain specific data such as shipments, orders and inventory levels from both manufacturer as well as retailers provide a rich set of demand signals about products across the value chain — from raw materials to consumer purchases.
Production and distribution networks can be made more efficient by using powerful data-processing and analysis capabilities. It enables companies to share data with their partners across the supply chain which eventually results in improved demand forecasting accuracy and discovery of new demand patterns. In addition to this they can even increase asset uptime and expand throughput, enable preventive maintenance of assets and resource optimization along with conducting near real-time supply planning using dynamic data feeds from production