Combining Operational + HR Automation is the Key to Optimizing Human Capital in Oil and Gas
Diversification aside, boom and bust are woven into the oil and gas business’s fabric. Consider the past few months alone. Brent crude was at $69 a barrel on February 4, $114 on May 4, and back down to $72 on July 4.
Hiring sprees and RIFs have historically followed price curves. Efficiency gains have smoothed that out somewhat, but also sent the overall industry employment trajectory lower. The oil and gas business employs 20 percent fewer workers today than it did a decade ago, and the number of jobs required to produce a barrel of oil has fallen by half in that same span.
That can’t go on forever, and many factors are contributing to a tougher environment on the people side of the business. To name three:
People intelligence assistants provide workforce insights and reporting, inform headcount planning, do skill-gap analysis, and attrition and retention forecasting.
- Baby boomers are retiring in droves, taking their and the industry’s intellectual capital with them.
- The technology and clean energy industries, utilities, data center builders, and others are scooping up talent of all sorts to the detriment of energy producers.
- Spending weeks out in the Bakken Formation, the Permian Basin or on an offshore platform is becoming a harder sell to a younger generation that prioritizes lifestyle and flexibility.
Those and other factors have left a shortage of talent ranging from roughnecks to automation engineers, control systems specialists, data scientists, cybersecurity pros, PLC and SCADA experts, electricians, welders – and beyond. The energy industry is recognizing that two types of AI-supported automation will be central to hiring, retaining, and training the people needed to keep the products flowing and the profits going: automation in asset management and automation in the human resource function itself.
Asset Management Automation to Lighten Workers’ Load
AI in asset management has made human capital more productive for a while now. What’s new is autonomous robotics capable of extending AI’s reach into the physical world. The most exciting AI applications in oil and gas asset management involve smart robots.
They monitor and inspect assets continuously with sensors that can spot anomalies based on visual, chemical, acoustic, and thermal signals; send data directly to field service management systems; have those systems assign work orders (or suggest teeing up work orders for human decision makers); and propagate the impacts of the work to business systems (operations, procurement, finance, and so on). That gives the organization an immediate understanding of the operational status and the business impacts associated with it.
A couple of examples:
- Percepto’s autonomous drones are enabling emission detection of storage tanks, liquid leak detection of pipelines, and thermal analysis to detect heat loss and deteriorated insulation. Upstream companies are integrating these drones with operational AI in remote operations centers.
- ANYbotics four-legged robots are automating inspections in ATEX/IECEx zones for continuous asset monitoring in places your people generally don’t want to be. Offshore, they’re working in process and storage areas, jetties, and topside structures, and being dispatched for corrosion and gas detection and localization. Onshore, companies are using them in corrosive, gaseous, and high-temperature environments.
Combining autonomous or human-controlled robots with remote operations centers capable of monitoring hundreds of wells, pipelines, compressors, and production facilities also lets specialists stay closer to the urban centers they tend to prefer, improving work satisfaction and quality of life. Those operations centers also enable automated drilling parameter optimization, pressure control, and AI-assisted hydraulic fracturing that let intelligent software continuously optimize operations rather than having onsite crews manually adjusting equipment.
HR Automation to Sharpen all Aspects of Human Capital Management
Of course, technologies such as automated drilling systems, digital well monitoring, and the IT systems that enable them (cloud software, networking, AI…) demand new and evolving skill sets that must be brought in, tracked and, often, developed in-house. AI assistants, each of which relies on a collaboration of AI agents, can help oil and gas companies track and individualize the human resource details across massive workforces.
Workforce upskilling assistants provide adaptive learning that delivers micro-lessons for just-in-time upskilling and reinforce skills continuously in the flow of work. They’re comprised of microlearning agents that generate concepts, quizzes, flashcards, and microlearning experiences using enterprise content; knowledge management agents that connect to enterprise learning sources and other assets; and adaptive learning journey agents that focus on skill-aware learning pathways, reinforcement, and personalized learning progression, among other agents.
Recruiting assistants harness recruiting Q&A agents, interview agents, candidate relationship management agents, and candidate reverse-matching agents – the last of which recommends best-fit roles to candidates based on their profiles and preferences.
People intelligence assistants provide workforce insights and reporting, inform headcount planning, do skill-gap analysis, and attrition and retention forecasting. They’re built on reasoning and recommendation agents that monitor workforce KPIs, keep skill profiles current, and provide financial and ROI views of talent decisions.
Those are just a sampling of HR-focused AI assistants that also include onboarding assistants, compensation assistants, payroll assistants, and compensation assistants, among others.
Automation to Sharpen Contingent Workforce Management
Contingent workforce management is another area in which oil and gas companies are reaping the benefits of automation. AI lets workforce scheduling systems and contingent workforce management systems get specific on the individual level and provides more timely and accurate reporting for a big-picture understanding of the overall human capital picture.
Integrating demand planning with workforce scheduling and/or contingent workforce management systems lets you model workforce needs based on ebbs and flows of demand. Contingent workforce systems help select the best sourcing channels and worker classifications and recommend preferred managed service providers with configurable distribution and tiered positioning. These systems can benchmark external-workforce metrics based on cost, worker quality, hiring cycle time, and other factors.
Add to that pay rate optimization, qualification verification, and the use of generative AI as a natural-language interface in general and to handle such things as the creation of job listings in multiple languages. These systems let HR staff focus on strategic personnel-related work, and improve staff/contractor utilization and retention.
Oil and gas may always be boom and bust. But emerging AI-driven automation on the asset management and HR fronts could finally give the industry the tools it needs to decouple the inherently cyclical nature of the business with the human capital aspects of it.
Brent Potts is Senior Director of Global Marketing for oil, gas and energy, chemicals, and AI marketing lead for industries at SAP.