In energy projects, precise estimating is the cornerstone of successful planning and execution. Benchmarking offers a strategic advantage by comparing current estimates with historical data and industry standards to validate assumptions, identify risks, and enhance decision-making. This approach not only improves estimate accuracy but also instills confidence among stakeholders and supports better resource allocation. By leveraging the benchmarking advantage, project teams can elevate success and navigate the complexities of industrial estimating with clarity and precision.
This article explores the concept of benchmarking in the context of project estimating, the benefits it offers, and how to implement it effectively.
What is Benchmarking in Project Estimating?
Benchmarking is the process of comparing a project’s costs, resources, and performance metrics against historical data or industry standards. In the context of project estimating, it involves using past project data or external benchmarks to validate and refine cost and schedule estimates.
There are two primary types of benchmarking in estimating:
- Internal Benchmarking: Comparing current estimates to historical data from similar past projects within the same organization.
- External Benchmarking: Comparing estimates to industry standards, published cost indices, or data from other organizations.
By leveraging benchmarking, estimators can identify gaps, validate assumptions, and adjust estimates to better align with real-world conditions.
Benefits of Benchmarking in Estimating
- Improved Accuracy
Benchmarking provides a reality check for estimates by aligning them with historical performance and industry standards. This reduces the risk of underestimating or overestimating project costs and durations.
- Enhanced Decision-Making
Accurate estimates derived from benchmarking enable project managers and stakeholders to make more informed decisions about budgeting, resource allocation, and risk management.
- Risk Mitigation
By highlighting potential discrepancies or outliers, benchmarking helps identify areas where assumptions may be overly optimistic or conservative, allowing teams to address risks proactively.
- Greater Stakeholder Confidence
Estimates backed by benchmarking data are more credible, fostering trust and confidence among clients, contractors, and project teams.
- Continuous Improvement
Benchmarking encourages organizations to maintain comprehensive project databases, creating a feedback loop for refining estimating practices over time.
Steps to Implement Benchmarking in Estimating
Collect and Organize Data
The first step in benchmarking is building a robust database of historical project data. This includes:
- Cost Data: Labor, materials, equipment, indirect costs, and contingencies.
- Schedule Data: Timeframes for key milestones, phases, and overall project completion.
- Performance Metrics: Productivity rates, efficiency metrics, and key performance indicators (KPIs).
Best Practices:
- Standardize data collection methods across projects to ensure consistency.
- Include detailed project descriptions (e.g., scope, size, location) to enable meaningful comparisons.
Select Appropriate Benchmarks
Determine whether internal or external benchmarks (or both) are most relevant for the project. Factors to consider include:
- Project Similarity: Choose benchmarks from projects with comparable scope, scale, and complexity.
- Geographic Context: Ensure benchmarks account for regional variations in labor rates, material costs, and regulations.
- Timeframe: Adjust historical data for inflation or market changes to ensure accuracy.
Best Practices:
- Use published cost indices (e.g., ENR Construction Cost Index) for external benchmarking.
- Collaborate with industry associations or benchmarking groups to access broader datasets.
Analyze and Compare
Compare the current estimate against selected benchmarks to identify deviations or trends. Key steps include:
- Cost Comparisons: Examine how line items (e.g., materials, labor) align with benchmarks.
- Schedule Comparisons: Assess whether planned durations for phases or tasks are realistic based on historical data.
- Performance Metrics: Evaluate productivity assumptions against actual performance from past projects.
Best Practices:
- Use statistical tools, such as variance analysis, to quantify deviations.
- Identify root causes of discrepancies to refine assumptions.
Adjust and Refine Estimates
Incorporate insights from benchmarking into the estimate by adjusting assumptions, contingencies, or resource allocations. For example:
- Optimistic Estimates: If the current estimate is consistently lower than benchmarks, consider increasing contingencies or reviewing scope assumptions.
- Conservative Estimates: If the estimate is higher than benchmarks, explore opportunities for cost savings or efficiency improvements.
Best Practices:
- Validate adjustments with subject matter experts to ensure they are justified.
- Document all changes and their rationale for future reference.
Monitor and Update Benchmarks
Benchmarking is not a one-time activity; it requires ongoing maintenance to remain relevant. Regularly update benchmarks to reflect:
- New project data.
- Changes in market conditions.
- Advances in technology or construction methods.
Best Practices:
- Conduct post-project reviews to capture lessons learned and update databases.
- Engage in industry forums or benchmarking groups to stay current with trends and standards.
Benchmarking Examples
Cost Estimating Benchmarks
Scenario: A company is preparing an estimate for a new natural gas processing plant.
- Benchmarking Application: Compare cost per unit of processing capacity ($/MMBtu or $/bpd) against similar completed projects.
- Example: Recent projects average $2,500 per bpd capacity. The current estimate is $2,700 per bpd.
- Outcome: This comparison highlights areas of potential cost savings, such as renegotiating material procurement or optimizing labor schedules.
Schedule Estimating Benchmarks
Scenario: A renewable energy company is developing an estimate for the construction timeline of a 100 MW solar farm.
- Benchmarking Application: Use historical data to compare estimated construction durations.
- Example: Similar projects in the region took an average of 18 months, but the current estimate assumes 20 months.
- Outcome: Investigating the discrepancy may reveal inefficiencies in supply chain planning or permitting processes, leading to a more competitive schedule.
Quantity-Based Benchmarks
Scenario: During the estimating phase for a wind farm, the team benchmarks the quantities of materials needed.
- Benchmarking Application: Compare the steel tonnage per MW installed against industry averages.
- Example: Industry benchmarks suggest 200 tons of steel per MW. The current estimate is 230 tons per MW.
- Outcome: This variance can guide value engineering efforts to optimize material usage and reduce costs.
Indirect Cost Estimating Benchmarks
Scenario: A refinery expansion project requires estimating indirect costs like insurance and site overhead.
- Benchmarking Application: Compare indirect costs as a percentage of direct costs.
- Example: Industry benchmarks indicate indirect costs are 25-30% of direct costs. The current estimate is 35%.
- Outcome: This comparison suggests revisiting overhead and administrative costs to identify inefficiencies.
Labor Productivity Benchmarks
Scenario: A nuclear power plant project is estimating labor hours for installation activities.
- Benchmarking Application: Compare labor productivity rates with industry averages.
- Example: Industry data suggests 50 labor hours per ton of steel installed, but the estimate assumes 60 labor hours.
- Outcome: Identifying gaps in productivity estimates may lead to workforce training or schedule adjustments to improve efficiency.
Equipment Utilization Benchmarks
Scenario: An offshore wind project is estimating costs for crane usage.
- Benchmarking Application: Compare crane rental durations and costs with similar projects.
- Example: Benchmark data indicates 1,000 hours of crane usage for a comparable project. The estimate assumes 1,200 hours.
- Outcome: Reevaluating equipment needs may identify opportunities for cost reduction or alternative utilization strategies.
Contingency Benchmarks
Scenario: An energy storage facility project is estimating the contingency needed for unexpected costs.
- Benchmarking Application: Compare contingency as a percentage of total project cost with industry standards.
- Example: Industry benchmarks suggest 10-15% contingency. The current estimate includes 20%.
- Outcome: Benchmarking provides confidence to adjust contingency levels based on project complexity and risk profile.
Challenges in Benchmarking for Estimating
- Data Quality and Availability
Inaccurate or incomplete data can undermine the effectiveness of benchmarking. Organizations must invest in robust data collection and management systems.
- Project Complexity
Highly unique or complex projects may lack comparable benchmarks, limiting the applicability of benchmarking.
- Time and Resource Constraints
Collecting, organizing, and analyzing benchmarking data requires time and expertise, which may be challenging for resource-constrained organizations.
- Adjusting for Context
Benchmarks must be carefully adjusted for factors like inflation, geographic location, and project-specific conditions, which can introduce additional complexity.
Tools and Techniques for Benchmarking
- Benchmarking Software
Modern tools like Cleopatra Enterprise, AACE’s Cost Management Framework, and Prism Estimating provide integrated platforms for benchmarking and estimating.
- Cost Indices
Publications like the ENR Construction Cost Index, RSMeans data, and regional cost guides offer valuable external benchmarks.
- Statistical Analysis Tools
Software like Excel, SPSS, or R can be used to perform variance analysis, trend analysis, and other statistical evaluations.
- Collaboration Platforms
Platforms like Procore or Primavera enable teams to share and analyze benchmarking data collaboratively.
Case Study: Benchmarking in Action
Project: Construction of a 200-MW solar power plant.
Step 1: Data Collection The organization gathered historical data from five similar solar projects completed in the past five years, including costs for modules, inverters, racking systems, and labor.
Step 2: Selecting Benchmarks Internal benchmarks from the past projects were used, adjusted for inflation and regional cost differences.
Step 3: Analyzing and Comparing The initial estimate was 10% lower than the benchmarked cost for racking systems. Analysis revealed an overly optimistic productivity assumption for the installation crew.
Step 4: Adjusting Estimates The labor costs for racking installation were adjusted upward, and a contingency was added for potential delays.
Step 5: Monitoring Benchmarks As the project progressed, actual costs and productivity rates were tracked against benchmarks, providing feedback for future projects.
Conclusion
Benchmarking is a critical tool for improving estimate accuracy in energy projects. By comparing current estimates to historical data and industry standards, project teams can validate assumptions, identify risks, and make more informed decisions. While benchmarking requires effort and expertise, the benefits, improved accuracy, risk mitigation, and stakeholder confidence, make it an essential practice for organizations aiming to deliver projects on time and within budget.
For organizations looking to implement benchmarking effectively, the key lies in maintaining robust data, leveraging modern tools, and fostering a culture of continuous improvement. By doing so, they can turn benchmarking into a competitive advantage in the high-stakes world of energy project execution.
Disclaimer
The information provided in this post is for reference purposes only and is intended to serve as a guide to highlight key topics, considerations, and best practices. It does not constitute professional advice or a substitute for consulting regarding specific projects or circumstances. Readers are encouraged to evaluate their unique project needs and seek tailored advice where necessary. Please Contact Us to discuss your particular project.
