Leverage machine learning analytics to predict outcomes and optimize operations


Big-box stores are always concerned with having enough stock on hand during holiday shopping time. They can’t always depend on last year’s results since there are other factors, such as the current economy, which affects what shoppers decide to do this year. A key characteristic of an intelligent supply chain is having the ability to leverage machine learning-based advanced analytics to predict outcomes, optimize and automate business operations, and take informed actions. Developers can help their companies compete by pulling data generated from a federated set of systems to create predictive machine-learning models and predict future market needs. Using IBM Sterling Supply Chain Insights in conjunction with Watson™ Studio enables developers to do just that – get visibility into the data and mitigate disruptions and risks.


In this developer code pattern, you can use IBM Sterling Supply Insights and Watson Studio to predict and adjust the defined “Below Safety Stock” (required inventory) external value as a result of supply and demand variances. The data will come from multiple data sources, such as IBM Sterling Supply Chain Insights and third parties, and Watson Studio will analyze this data and generate predictions, resulting in few stock replenishments needed.



  1. Pull supply chain data from IBM Sterling Supply Chain Insights into Watson Studio, which is included as part of IBM Cloud Pak™ for Data.
  2. Inject data from systems outside of IBM Sterling Supply Chain Insights into Watson Studio.
  3. Train and deploy machine learning model.
  4. Use Watson Studio to predict purchasing outcomes.


Please see the README for detailed instructions on how to set up and run this pattern. Steps include:

  1. Uploading the data set
  2. Building, testing, and deploying model in IBM Cloud Pak for Data
  3. Integrating Sterling Supply Chain Business Assistant with Cloud Pak for Data to predict new safety stock
  4. Recalculating new safety stock using new back-end asset in Node.js
  5. Integrating Sterling Supply Chain Business Assistant with Sterling Supply Chain Insights to update item