Client is leading Healthcare Hospital Group targeted for better forecasting and managing the Supply Chain effectively. The client is largest hospital chain in SEA with more than 5,000+ employees.
Lack of Demand Planning of each SKU & Days of Inventory (DOI) to manage existing Supply Chain.
Data residing in SILOS and lack of in-time data availability
Decision Support Systems (DSS) and Real-Time Data Modelling is near to impossible
Technology Enabled Business Solution
Data Science Models like Multi Variate Time Series (Vector Auto Regression), Deep Learning Techniques like LSTM (Recurrent Neural Networks) and Advanced AI Techniques of ARIMA
Drive KPI(s) and ROI via Forecast and Machine Learning Models
Sanitize and Integrate data from various Heterogeneous Systems into Large Volumes of Structured, Semi-Structured, Unstructured data stored in “NoSQL storage” like Graph DB, Columnar DB, Key-Value DB and Document DB.
Effective Data Transformation using Python.
Develop tools in GBQ using SQL
Reduction of excessive Stocked SKU and Days of Inventory (DOI) were achieved