Statistical Forecast and Inventory Optimization for Global Airlines MRO Vendor, Singapore

We helped a Singapore-based MRO client with forecasting the demand for maintenance services and optimize inventory for the best SLA and yet minimize investment in inventory.

Business Objective

Singapore based MRO vendor has a presence at 20+ airports around the world to provide maintenance and spare parts leasing services to Airlines. The company operates on a long term service contract model with well defined SLA for quality of parts and services. Under-stocking of parts results in SLA breach and thus attracts penalty while overstocking results in investment in inventory and carrying cost. Our client wants to take this opportunity to build a forecasting model and optimize the tradeoff between SLA and inventory CAPEX + OPEX.


  1. Forecasting on industry-standard methodologies resulted in an inaccurate forecast and financial loss.
  2. Historical data of service transactions was unstructured and too sparse for standard ML models.  
  3. Forecast accuracy is critical because of the large inventory CAPEX and SLA breach penalty.

Solution Methodology

We modeled both demand and TAT of the Client’s repair service using statistical models. This allowed us to derive the optimal balance between SLA and inventory Cost.

  1. We collected  the transaction data and simulated the service processes of the past three years. 
  2. Several demand models were considered. The one we selected accounted for high variability of the repair services. 

Inputs from stakeholders, process owners and output from forecast was used to build the cost optimization model.


The forecasting and Optimization model achieved :

  1. 98% adherence to SLA as per current signed contracts with airlines.
  2. 9% total savings in annual investment, inventory carrying cost, and penalty combined.

Impact in Numbers

No items found.
Download Full Case Study

Want to know more ?

Drop us a message and one of our team members will get in touch with you.
Get in Touch
Please fill the form to download the case study
Thank you for the submission, download the file below.
Download the File
Oops! Something went wrong while submitting the form.