Choosing between custom and standard benchmarking depends on what you need to measure. Custom benchmarking uses your company’s historical data to track specific project performance over time. Standard benchmarking compares your performance to broader industry trends using external data. Each method serves a distinct purpose, and the choice often depends on your project’s complexity, available data, and goals.
Key Takeaways:
- Custom Benchmarking: Tailored to your own data; ideal for tracking detailed, project-specific insights.
- Standard Benchmarking: Based on industry averages; useful for planning and comparing to market norms.
- Main Differences:
- Custom focuses on internal performance; standard provides external comparisons.
- Custom offers detailed insights; standard is more generalized.
- Custom requires more effort to implement; standard is quicker but may lack precision.
Quick Comparison:
| Feature | Custom Benchmarking | Standard Benchmarking |
|---|---|---|
| Purpose | Internal performance tracking | Industry trend comparison |
| Data Source | Company’s historical data | External reports (e.g., BLS) |
| Granularity | High (project-specific) | Low (generalized) |
| Effort | High (data preparation needed) | Moderate (data access required) |
| Best For | Complex projects, risk scenarios | Budgeting, market positioning |
Using tools like ABLEMKR simplifies both approaches by providing real-time workforce data and standardized metrics, helping you make informed decisions. The best strategy often combines both methods, leveraging the strengths of each for optimal results.
Custom vs. Standard Benchmarking: Side-by-Side Comparison
Different types of benchmarking: Examples And Easy Explanations
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Defining the Two Benchmarking Approaches
Let’s break down each benchmarking method to understand their distinct purposes.
Custom Benchmarking Frameworks
Custom benchmarking focuses on comparing your current performance against your own historical data. This method evaluates similar tasks, crew sizes, and locations, providing a tailored look at how you’re progressing over time.
Here’s how it works: A contractor organizes field activities using a concise set of 6 to 15 labor codes that reflect actual on-site tasks. Time and cost codes are logged in real time to maintain accuracy. This "field-first" strategy ensures the data remains clean, making it easier to establish dependable benchmarks.
Tracking earned hours versus burned hours on a weekly basis is key. It allows managers to spot potential problems early – long before the project wraps up.
"Specialty contractors who measure only the cost side of the equation tend to find out about productivity problems after the fact… By then nothing can be done."
In contrast, standard benchmarking involves external data, offering a broader industry perspective.
Standard Industry Benchmarks
Standard benchmarks are built using data from external sources like the Bureau of Labor Statistics (BLS), the Construction Industry Institute (CII), and established standards such as ASTM E2691 (Standard Practice for Job Productivity Measurement), which was developed with input from NIST.
These benchmarks serve a different role compared to custom frameworks. They provide leadership with a snapshot of how their company compares to the wider industry, aiding in strategic and financial decision-making.
"Industry-level metrics… serve a different purpose than project-level or task-level metrics. They tell a contractor where the industry sits, not where the contractor sits relative to its own historical performance."
For instance, knowing that the average rework costs across the industry amount to about 9% of the project value offers leadership a useful benchmark. However, this figure doesn’t help a foreman determine if their team is lagging on conduit installation this week. Each approach has its place, depending on the level of insight needed.
Key Differences Between Custom and Standard Benchmarking
The main difference lies in the focus and data source. Custom benchmarking relies on your own historical records, helping you evaluate and improve internal performance over time. Standard benchmarking, on the other hand, compares your metrics to broader industry trends using data from sources like SHRM or the BLS.
Comparison Table: Custom vs. Standard Benchmarking
| Dimension | Custom Benchmarking | Standard Benchmarking |
|---|---|---|
| Primary Purpose | Pinpoint internal gaps and refine specific processes | Assess market position and set goals |
| Data Sources | Internal HRIS, payroll, and project data | Industry reports (e.g., SHRM, BLS), vendor surveys |
| Granularity | High – detailed to specific job sites or managers | Low – generalized across industries or regions |
| Implementation Effort | High – requires thorough data preparation | Moderate – requires budget for data access |
| Data Recency | Real-time or near-real-time | Often delayed by 6–18 months |
| Best Fit For | Ongoing project management or high-risk scenarios | Initial planning and market rate comparisons |
One major drawback of standard benchmarks is their age. In fast-changing industries like oil & gas or heavy construction, a lag of 6–18 months can make the data less relevant. This is especially critical when over 53% of workers expect pay adjustments to match inflation. These differences clarify when to use tailored metrics versus industry-standard ones, depending on your project needs.
When Custom Benchmarking Works Best
Custom benchmarking shines when detailed, project-specific insights are essential. By analyzing your own historical data, you can uncover performance trends that broader industry metrics might miss. This approach is particularly valuable for managing complex, multi-trade projects, such as remote pipeline repairs, multi-phase mining operations, or emergency plant shutdowns. These scenarios often involve varied crew compositions, certifications, and local labor conditions, making precise data crucial.
Custom benchmarking is ideal when:
- You’re overseeing a complex project with unique labor dynamics.
- You need to measure the impact of specific operational changes, like a new safety protocol or onboarding process.
- You want to identify high-performing crews, managers, or job sites.
"A gap that reflects a conscious strategic choice is very different from one that reflects a process breakdown." – SoftwareFinder
This level of insight is only possible when you compare against your own baseline instead of relying on industry averages.
When Standard Benchmarking Is Enough
Standard benchmarks are most useful during the planning phase. For tasks like budgeting a new project, setting pay ranges, or aligning staffing decisions with market norms, external data provides a solid foundation without the complexity of building a custom system.
For instance, industry averages for cost-per-hire and wage rates can help you create accurate bids and staffing plans. SHRM’s 2025 benchmarking reports alone offer 88 distinct data sets organized by industry, sector, organization size, and region. This level of detail is often sufficient for high-level planning, though it’s important to remember that standard benchmarks establish the baseline – not the ultimate performance goal.
Using Technology Platforms to Support Benchmarking
Deciding between custom and standard benchmarking is only part of the equation. The other part? Accessing reliable, up-to-date data to make those benchmarks meaningful. This is where workforce deployment platforms come into play – not to replace decision-making but to enhance data accuracy, timeliness, and comparability.
Real-Time Workforce Data for Benchmarking
Using outdated data can throw benchmarks off course. Platforms like ABLEMKR solve this by aggregating live mobile data and verified timecards, offering real-time insights into crew locations, certifications, and compliance across all active sites. In industries like oil and gas or heavy construction, where project schedules are worth millions, even a few hours of delay in workforce data can skew critical metrics like crew mobilization times, average hours worked per shift, or safety incident rates.
ABLEMKR also collects detailed worker attributes, including OSHA 10/30 certifications, MSHA credentials, fit-for-duty status, drug test results, and site-specific onboarding completion. This level of detail allows for benchmarks such as average time to mobilize a fully compliant crew or incident rates by certification level, replacing guesswork with precision. Having access to this real-time data strengthens the foundation for creating highly accurate custom benchmarks.
Building Custom Benchmarks with Detailed Data
The quality of custom benchmarks depends entirely on the data feeding into them. With ABLEMKR’s integrated payroll and timekeeping records – covering hourly rates in USD, overtime multipliers, per diem, clock-in/clock-out times, and shift lengths – contractors can calculate detailed cost and productivity metrics.
Take, for instance, a contractor managing a multi-phase pipeline project. They could use this data to track the average labor cost per linear foot of pipeline installed, broken down by crew composition and geographic region. As new payroll and hours data are continuously added, these benchmarks become sharper. This allows project managers to compare active jobs to historical performance, identifying and addressing cost overruns early.
"The app made managing timecards and payroll simple during a complex multi-week shutdown." – Project Manager, Energy Services Company
When layered with job site performance data – such as output rates, rework incidents, and safety near-misses – the insights become even richer. Linking this data to variables like crew certifications, shift patterns, temperature (°F), or site elevation enables benchmarks like rework cost per $1,000 of labor or daily throughput per foreman. These types of detailed metrics go far beyond what external reports can typically provide, paving the way for more meaningful comparisons.
Applying Standard Benchmarks with Normalized Data
Custom benchmarks are great for project-specific insights, but standardized benchmarks are equally valuable when comparing performance against industry norms. However, standardized benchmarks rely on uniform data, which can be tricky to achieve internally. Job codes, time bases, and role classifications often vary widely across projects, making direct comparisons difficult.
ABLEMKR addresses this by standardizing metric definitions across projects and mapping internal roles to recognized occupational categories. This ensures that organizations can directly compare metrics like Total Recordable Incident Rate (TRIR), lost-time rates, or average hourly wages against published U.S. benchmarks for construction, energy, or mining. Pre-configured dashboards make it easy to spot where performance deviates from industry standards, turning what used to be a tedious quarterly task into a seamless part of daily operations management.
Conclusion: Choosing the Right Benchmarking Approach
The best benchmarking strategy hinges on your goals, the scope of what you’re measuring, and how much data you have on hand. By using these strategies, you can avoid unnecessary costs while making informed decisions throughout your project’s lifecycle.
A Decision Checklist for Benchmarking
Here are some critical factors to consider:
- Project complexity: For intricate projects, custom benchmarks are essential. On the other hand, standard benchmarks work well for repetitive, high-volume tasks.
- Risk level: High-risk industries – like oil and gas shutdowns, underground mining, or live electrical work – require precise custom benchmarks to account for factors like team compatibility and field reliability.
- Data availability: If your internal data is limited, start with standard benchmarks. You can transition to custom models as your data improves.
- Compliance requirements: Standard benchmarks help ensure adherence to OSHA certifications, state licensing, and union regulations, which are essential legal standards.
- Hiring intent: For permanent or long-term roles, custom benchmarks provide a deeper understanding of how candidates will perform in real-world conditions – something no resume can fully capture.
By weighing these considerations, you can create a balanced approach, blending the benefits of both standard and custom benchmarking methods.
Combining Both Approaches: Hybrid Benchmarking
A hybrid strategy merges compliance-focused standard benchmarks with the tailored insights of custom benchmarks. A great example is the "Flex to Hire" model. This method evaluates workers against internal performance standards during live projects before offering them full-time roles. ABLEMKR’s version of this model even eliminates buyout costs after a worker completes 1,000 hours, making it a low-risk way to test custom benchmarks before committing to permanent hires.
Patrick Wallain, CEO of ABLEMKR, sums it up well:
"The labor shortage isn’t coming. It’s already here… The companies winning today are the ones building workforce ecosystems: faster matching, better retention, verified skills, real career mobility, and technology that actually supports the trades." – Patrick Wallain, CEO, ABLEMKR
This hybrid approach – using standard benchmarks for compliance and custom benchmarks for optimization – is quickly becoming an industry standard in sectors where both speed and precision are critical.
Key Takeaways
Standard benchmarks ensure compliance, while custom benchmarks help optimize projects. Together, they form a powerful hybrid strategy, supported by ABLEMKR’s real-time data insights. This balanced approach offers a clear path to deploying an effective and efficient workforce.
FAQs
How do I know if I need custom benchmarks or standard ones?
Deciding between custom and standard benchmarks often comes down to the specifics of your project. Standard benchmarks offer a broad view of performance across industries, giving you a reliable baseline to measure against. On the other hand, custom benchmarks are tailored to fit unique project needs, whether it’s meeting certifications, managing specific cost structures, or adhering to strict safety requirements.
With ABLEMKR, you have the flexibility to define your own criteria right from the start – whether it’s based on geo-location, skill sets, or other specific factors. This way, you can ensure you’re tracking and compensating workers who align perfectly with your project’s objectives.
What internal data is needed to create reliable custom benchmarks?
To create dependable custom benchmarks, focus on gathering and organizing these core data categories:
- Worker profiles: Include details like skills, certifications, safety training, and performance records.
- Job site conditions: Document safety requirements and equipment specifics.
- Project schedules: Track milestones, resource needs, and timelines.
- Cost data: Account for wages, taxes, benefits, overhead, and overtime expenses.
ABLEMKR simplifies this process by centralizing all this information, ensuring reliable and consistent data for benchmarking.
How can I combine both approaches without getting conflicting results?
To merge custom and standard benchmarking effectively, start by bringing all fragmented data into a single, centralized cloud platform. This step ensures that information remains consistent and accurate across all systems. By adopting standardized data formats and leveraging API-based tools, you can integrate systems seamlessly, allowing for smooth data exchange. This approach reduces manual errors and avoids inconsistencies in reporting, providing a dependable base for both standard and custom metrics.
