- JD Solomon
- Dec 16, 2025
Asset criticality and risk are essential for prioritizing projects, but they are not relevant when validating asset data for a capital plan. The initial plan development should focus on the accuracy, completeness, and consistency of asset records—not on ranking which projects should come first.
Why Are Asset Criticality and Risk Not Important in Validating Asset Data for the Capital Plan?
When organizations embark on developing a capital improvement plan (CIP), one of the first hurdles they face is ensuring that their asset data is reliable. Without accurate inventories, condition scores, and replacement values, the plan itself risks being built on shaky foundations. A deliberate choice is to exclude criticality and risk scoring from the discussion of data validation. This intentional omission allows you to focus on the core data.
Data Validation vs. Project Prioritization
Data validation is the process of confirming that the information in your asset management system is correct, consistent, and usable. It asks questions like:
Do we have the right number of assets in the inventory?
Are condition scores applied consistently across asset classes?
Is replacement asset value (RAV) calculated using a defensible method?
By contrast, criticality and risk scoring are tools for prioritization. They help decision makers determine which projects should be funded first, based on the potential consequences of failure, service impacts, or safety concerns. These are vital for investment decisions, but they do not tell us whether the underlying data is accurate.
Why Criticality Doesn’t Validate Data
Criticality measures how important an asset is to system performance or organizational objectives. For example, a water treatment plant may be deemed more critical than a small pump station. But this ranking does not confirm whether the pump station’s install date is correct, whether its condition score is reliable, or whether its replacement cost is accurate.
In other words, criticality is a lens for prioritization, not a test of accuracy. A highly critical asset can still have poor or incomplete data. Conversely, a low-criticality asset may have pristine records. Validation must focus on the quality of the data itself, not the importance of the asset.
Why Risk Scoring Doesn’t Validate Data
Risk scoring typically combines condition, criticality, and consequence of failure into a matrix that guides investment decisions. While powerful for prioritization, risk scoring assumes that the underlying data is already valid. If condition scores are inconsistent or replacement values are inflated, the risk matrix will produce misleading results.
This is why my approach emphasizes condition and asset replacement value as the key dimensions for data validation. These are measurable, verifiable, and directly tied to the accuracy of asset records. Risk scoring, by contrast, is a derivative process—it depends on validated data to function properly.
The Danger of Mixing Validation with Prioritization
Organizations sometimes conflate validation with prioritization, believing that if they can rank projects, their data must be sound. This is a dangerous assumption. A risk matrix built on flawed data can create a false sense of confidence, leading to misallocated funds and missed opportunities.
By separating the two processes, planners can ensure that:
Validation establishes a trustworthy foundation of asset data.
Prioritization applies criticality and risk scoring to the validated data to guide investment decisions.
Practical Implications for Capital Planning
For practitioners, the takeaway is clear:
Focus validation efforts on condition and value. These are the most direct indicators of data quality.
Use criticality and risk only after validation. They are powerful tools for prioritization, but criticality and risk cannot be a substitute for accurate data.
Communicate the distinction to stakeholders. Decision makers often conflate these concepts; clarifying the distinction builds trust and ensures better outcomes.
Validating Asset Data through the Capital Plan
Leaving out criticality and risk from asset data collection and validation highlights the key difference between validating data and prioritizing projects. For a sound capital plan, focus validation on asset lists, condition, and value; use criticality and risk only in prioritization.
JD Solomon is the founder of JD Solomon, Inc., the creator of the FINESSE Fishbone Diagram®, and the co-creator of the SOAP criticality method©. He is the author of Communicating Reliability, Risk & Resiliency to Decision Makers: How to Get Your Boss’s Boss to Understand and Facilitating with FINESSE: A Guide to Successful Business Solutions.
JD Solomon Inc. provides solutions for program development, asset management, and facilitation at the nexus of facilities, infrastructure, and the environment. Visit our Asset Management page for more information related to reliability, risk management, data analytics, and other asset management services.
