Advanced Analytics is the autonomous of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations. Advanced analytic techniques include those such as data/text mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, sentiment analysis, network and cluster analysis, multivariate statistics, graph analysis, simulation, complex event processing, neural networks. We comply with ISO 19731:2017 – Digital analytics and web analyses.
As a supply chain leader, you increasingly find yourself pulled into making IT recommendations and decisions. Thanks to rapid moves toward Industry 4.0, technology and data have come to play an integral part of supply chain management. The ability to collect and respond to data has become especially important, and it’s not uncommon for supply chain managers to struggle with how to handle the sheer volume of data, let alone leverage it effectively. The key is to integrate advanced analytics throughout the supply chain, an approach that has multiple key benefits.
5 Key Benefits of Advanced Analytics
- Capacity for True E2E Supply Chain Visibility.
- Ability to Optimize Manual vs. Automatic Decision-Making and Execution.
- Increased Speed to Market
- Support for a Hybrid “Agile-Lean” Model.
- Lower Inventory Costs and Higher Revenue.