Mitigate risks in supply chain for manufacturer of agricultural equipment

Client

 US-based multi-business firm that is a global leader in design, manufacture, and distribution of a wide range of agricultural equipment

OPPORTUNITY

The client wanted to mitigate internal risks and vulnerable links in the supply chain. The client wanted to focus on top suppliers of agricultural sub-appliances. The client faced challenges in automating the data capture process and minimizing manual efforts.

SOLUTION

SG Analytics data analytics team created a model for risk estimation associated with each component delivery based on the need to maintain the flow of supply chain and to avoid surplus/shortage:

• The SG Analytics team gathered data for various components of a given product type to be used as a demand value and in risk prediction in the supply chain
  The SG Analytics team developed the demand value of  these components and the risk associated with their delivery
  The team used attributes such as country, logistical, performance, supplier, and supply quantity as predictors
  SG Analytics monitored the estimated value error continuously and improvised models for better results
  The team used techniques such as artificial neural network, linear regression, and support vector machine to estimate demand value, and predict risk probability as well as risk severity (High, Medium, Low)