In chemical plants, equipment replacement and capital projects occur regularly. That means budget estimates must be accurate enough to gain internal approval. Saying “It’s my first time, so mistakes are inevitable” won’t satisfy management.
Owner’s engineers often rely on historical data to prepare budgets. While this is a practical approach, it can easily backfire if certain hidden factors are overlooked. In this article, we highlight the most common reasons why estimates based on past data can deviate from actual costs—and what engineers should keep in mind when preparing budgets.
Why Past Data and Actual Costs Don’t Match
Using past data to estimate costs is standard practice. Yet when projects move into execution, budget overruns are surprisingly common. Here are the typical reasons why.
1. Applying Scaling Factors Without Considering Design Differences
Many engineers use the Lang factor method with scaling exponents (e.g., 0.6 power rule) to estimate equipment costs. However, this method assumes the same design type.
For example, scaling from a 1 m³ tank to a 100 m³ tank using the 0.6 rule may underestimate costs. Larger tanks may require outdoor fabrication, scaffolding, heavy lifting, and higher transport costs.
Similarly, with centrifugal pumps, a capacity increase may require an entirely different pump model. Catalog data often doesn’t make this clear, leading to unexpected cost jumps.
2. Single Purchase vs. Bulk Purchase
Even when buying the same equipment type, costs can differ if the past purchase involved bulk orders while the current one is for a single unit.
Bulk discounts often go unnoticed in historical databases, especially if only model and price are recorded. Without quantity details, engineers may assume a lower “per-unit” price applies to single-item purchases—leading to underestimation.
3. Supplier Workload and Plant Capacity
Suppliers’ workloads fluctuate. A past purchase may have been cheaper because the vendor had spare capacity. In contrast, if they are currently overloaded with orders, prices can rise.
Predicting supplier capacity is almost impossible. While early reservations can help, they carry risks: cancellations damage credibility, scope changes make early orders obsolete, and delays in design can push purchases past reserved slots.
4. Escalation (Market Price Inflation)
Price escalation is one of the clearest reasons for cost increases. Since around 2020, it has been easier to explain internally, as inflation affects daily life as well as industrial purchases.
However, quantifying escalation is challenging. Should tanks be assumed to rise 5% annually, while pumps increase 10%? Collecting such data is time-consuming, and few suppliers provide quick preliminary quotes. The result: delayed investment decisions and budget overruns.
5. Special or One-Time Discounts
Past purchases may have been made at special introductory prices or with hidden discounts. If those numbers enter the database without clear notes, they can mislead future estimates.
This creates a false expectation that such prices are standard, leading to significant underestimation.
Building Realistic Budgets
Using past data is practical, but modern projects contain many uncertainties. The best approach is to include a reasonable contingency—large enough to absorb surprises but small enough to remain credible.
Equally important is transparency: define your estimation method, list assumptions, and agree internally that certain unforeseen factors will require separate review. This builds trust and reduces the risk of disputes when costs inevitably change.
Conclusion
Budget estimation for chemical plant equipment is never straightforward. Historical data is useful but must be interpreted carefully. Factors like scaling rules, purchase quantities, supplier capacity, escalation, and special pricing all create hidden risks.
Owner’s engineers should build estimates with clear assumptions, modest contingencies, and transparent communication. By doing so, they can reduce internal conflicts and make investment decisions more reliable.
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