Enterprise AI for Inventory Optimization Hero
Case Study

Enterprise AI for Inventory Optimization


Baker Hughes, an energy technology company, set a strategic goal to help their customers improve efficiency, increase worker health and safety, and reduce carbon emissions leveraging next-generation digital technologies. C3 AI is the world’s leading technology provider of Enterprise AI digital transformation software. C3 AI provides a cross-industry AI-application Platform as a Service (PaaS) as well as pre-built Software as a Service (SaaS) applications that help large enterprises unlock economic value from AI and machine learning technologies.

Baker Hughes and C3 AI embarked on a strategic partnership to develop and deploy Enterprise AI applications to the oil and gas industry under the brand name (BHC3). Together, Baker Hughes and C3 AI provide wide-ranging AI-based applications for oil and gas companies, including optimizing artificial lift systems operations, selecting drilling targets, and optimizing production operations. This strategic relationship combines Baker Hughes’ deep oil and gas expertise with C3 AI’s industry-leading software platform for developing and operating enterprise-scale AI applications.

In addition to delivering enterprise AI applications to its customers through this alliance, Baker Hughes also adopted BHC3TM products to accelerate its own digital transformation. Baker Hughes and C3 AI established a joint Center of Excellence (CoE) at Baker Hughes to develop and deploy a range of internal AI products that improve Baker Hughes’ productivity and efficiency.


Baker Hughes Enterprise AI Digital Transformation – Key Milestones


AI Digital Transformation Key Milestones

A high-priority AI use case involved the optimization of Baker Hughes’ inventory. The project addressed a substantial economic value and could be delivered by leveraging BHC3 Inventory Optimization, a pre-built AI-based SaaS product that is also provided by Baker Hughes and C3 AI to oil and gas customers. The CoE configured, augmented and deployed BHC3 Inventory Optimization within a portion of the Digital Solutions product company to help manage its oil and gas inventory, with future expansions planned for other business units at Baker Hughes. Baker Hughes expects the BHC3 Inventory Optimization application to reduce approximately 5 percent of inventory while improving overall service levels at the locations deployed.

The BHC3 Inventory Optimization deployment is just the beginning for deploying BHC3 technology across Baker Hughes. The CoE is working continuously to identify, qualify, and implement additional internal AI use cases across Baker Hughes, while delivering cutting-edge Enterprise AI applications to its customers across the energy value chain.


About Baker Hughes
  • Annual Revenues: $24B in 2019
  • Employees: 68,000
  • Industry: Energy technology
  • Locations: 1,500+ locations
    in 120+ countries
  • Inventory: 1,000,000+ parts and $4B+ net inventory
  • Founded: 1907


Baker Hughes and C3 AI embarked on a comprehensive, multi-year effort to improve productivity and efficiency by embedding AI in Baker Hughes’ energy business processes. As part of this vision, Baker Hughes and C3 AI established a CoE in order to support the identification, prioritization, development, deployment and operation of AI-based solutions. The team, consisting of developers, data scientists, subject matter experts and business unit leaders, defined governance and processes required to identify opportunities and qualify AI use cases with full executive support from Baker Hughes and C3 AI leadership.

Projects identified by Baker Hughes for the CoE fall into two categories. The first is comprised of internal application deployments to improve efficiencies and boost productivity across Baker Hughes. The second is comprised of new product development for Baker Hughes customers aiming to improve the safety and efficiency of the oil and gas industry. Projects in both categories will be supported by the CoE, leveraging the unique capabilities of the BHC3 AI Suite.

After reviewing a pipeline of potential projects, the team selected inventory optimization of oil and gas inventory as its first use case. CoE developers and data scientists began supporting the augmentation and configuration of the BHC3 Inventory Optimization application in late 2019, with the goal of deploying to production in 2020.

BHC3 Inventory Optimization is the first BHC3 application deployed at Baker Hughes. As part of configuration and deployment, the CoE team supported the ingestion of more than 340 million ERP data elements spanning the past eight years—including equipment and parts inventory data, material movement data, and purchase orders—into a unified, federated data image on the BHC3 AI Suite. The CoE then supported the use of this unified data image to train more than 59,000 unique machine learning models to help optimize inventory.

The BHC3 Inventory Optimization application is capable of selecting high-performing models for production use, resulting in recommendations that will help enable buyers to minimize inventory while maintaining desired service levels.


Project Highlights
  • Potential inventory reduction opportunity of up to 5 percent
  • 8 years of historic data ingested from ERP systems
  • 59,000 machine learning models developed for Release 1



project ideas; three qualified for development


Baker Hughes resources trained on the BHC3 AI Suite


data elements unified on the BHC3 AI Suite


potential inventory reduction opportunity

Solution Architecture

BHC3 AI Suite Solution Architecture Graphic

Proven results in weeks, not years

Proven Results Timeline

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