Intelligent Enterprise

CT - IE provides the following out of the box solutions: -Demand Forecasting -Sales Forecasting -Inventory Optimization -Time Fencing -Offer Analytics -Constraint-based optimization -Product to Product Cannibalization Limitation of a legacy supply chain system: -Incapable of doing complex data engineering at scale -Heavy licensing cost -Propriety Software -Limited dashboard capabilities -Less room for modern analytics -Not ready for IoT -Data Orchestration Challenges -Supply chain complexity -Government regulatory compliance -High supply and demand volatility -Legacy systems, processes, and operating models Approach: -Conventional methods, Deep Learning approaches, and modern open-source frameworks like Prophet makes a smart supply chain analytics solutions. -Prediction on the basis of both internal and external factors (weather, market index, competitor's data, POS data, etc.) -Effects of Trade Promotions and Dynamic Pricing are also measured. -Prescriptive and descriptive analytics with real-time dashboards provide more significant KPIs Cloud? -Compute on Demand - Customized Supply Chain Analytics as per the requirements of the customers or scenario -Support for Data Ingestion, Data Orchestration, Wrangling from vast data sources (IoT Databases, Anaplan, SAP), ETL/ELT and automation using Azure Data Factory -Better Data Visualization support with Power BI and Azure Databricks Dashboard -Scheduled Azure Databricks Notebooks with core engine of Spark(Python, SQL) to perform distributed computation and process data in parallel with Machine Learning Library Application (Flint, Moving Average, ARIMA, Regression and Removing seasonalization) -Cloud-based data pipelines to provide end to end solution