The Client
Global Oil and Gas Organization (up-stream/down-stream)
The Challenge
This major oil and gas organization like other organization had very little insight into the depreciation and failure rates of individual assets, and rarely incorporated the understanding into planning spare parts inventory. Delays in the arrival of pipes, casing, tubing, and other accessories, can result in extensive rig downtime and consequently high operating costs.
The Solution
The client utilized advanced analytics and was able to automate decision making on restocking strategies by considering purchase price, transport cost, storage cost, order cost, risk of obsolescence, and scrap value.
- Automated inventory level-setting with fully quantified operating characteristics of expected cost and probability of stocking out
- Increased availability of spare parts for servicing and repairing of drilling and rigging machinery, pipeline, refineries, filtration units
- Reduced cost of maintaining inventory
The Approach
- Gathered data from supply chain history for drilling, rigging, pipeline materials, other inputs, part failure and part usage history, lead time history (for reorders), history of disruptions to supply chain, planned and actual history of ramping of capacity
- Established a financial cost model that measures costs and risks in common currency
- Characterized statistical properties (distributions and correlations) in parts demand and lead times
- Accounted for historical disruptions
- Linked data sources with analytics engine
- Utilized current state of inventory and chosen economic scenario, automatically set optimal inventory levels for all parts