A New Approach to Energy Labor Market Intelligence: Moving from Job Titles to Job Indicators

1. The Problem with Interpreting Traditional Labor Market Data

For decades, labor market intelligence (LMI) has relied heavily on static, occupation-based classification systems such as those from the Bureau of Labor Statistics. While useful for high-level macroeconomic analysis, this approach is fundamentally flawed for understanding the dynamics of a rapidly evolving sector like the energy industry. The core challenge lies in the over-reliance on job titles.

A job title, such as “Energy Auditor”, can be misleading. Responsibilities once centralized under a single title are now distributed across a wider range of roles. Today, an energy audit may be performed by a Building Performance Analyst, a Facilities Engineer, or a Sustainability Consultant. Relying solely on “Energy Auditor” would underestimate demand for these critical skills, leading to flawed workforce planning.

Traditional LMI also struggles with emerging roles. Titles like “Grid Modernization Analyst” may not exist in standardized systems, yet represent real and growing functions. Without flexibility, these jobs are often overlooked or misclassified.

2. The Solution: A Job Indicator Approach

To overcome these limitations, we developed a new approach centered on Job Indicators. A Job Indicator is not a single job title, but a curated combination of elements that together provide a high-signal proxy for demand in a specific function.

A Job Indicator combines:

• Job Titles: Relevant, common, and adjacent titles (e.g., “Energy Auditor,” “Building Analyst”).
• Skills: Specific hard and soft skills (e.g., “HVAC System Design,” “Data Analysis,” “Client Communication”).
• Certifications: Industry-recognized credentials (e.g., BPI Building Analyst, CEM, LEED Green Associate).
• Keywords & Phrases: Language from postings and profiles (e.g., “energy retrofits,” “utility rebate programs,” “ASHRAE standards”).

By combining these dimensions, we create a more accurate, robust measure of demand that goes beyond job titles and reflects real-world functions as they evolve.

3. The Process: Iterative and Expert-Driven

Our Job Indicator approach is iterative and collaborative, grounded in data and industry expertise:

1. Hypothesis Generation: Using advanced analytics, we identify clusters of skills, certifications, and keywords across job postings.
2. Expert Validation: Industry SMEs review and refine clusters, ensuring they represent cohesive, real job functions.
3. Indicator Refinement: Final indicators are validated and kept flexible, adapting as new technologies and certifications emerge.

This feedback loop ensures indicators are both statistically rigorous and practically relevant, supporting accurate workforce insights in a changing industry.

By focusing on flexible, expert-validated Job Indicators, we provide the energy sector with precise, actionable intelligence to identify talent gaps, strengthen the workforce, and prepare for future shifts.