The Limitations of Modelling when Assessing Reinstatement Costs

While modelling and analytics can be valuable tools for assessing reinstatement costs for buildings or machinery, there are several potential weaknesses and challenges associated with these approaches. 

It’s vital for those relying on the outputs of these models to be aware of these limitations to ensure that a model-based analysis produces the required comprehensive and accurate assessment. 

Some common weaknesses include:

1. Assumption Sensitivity:

Modelling often relies on generic assumptions on certain elements, such as construction type, base materials, building heights, site and soil conditions and construction labour markets. Small changes in these assumptions can lead to significant variations in the estimated rebuild costs.

2. Data Accuracy and Availability:

The accuracy of results produced by a model depends on the quality and reliability of the input data used. If the data is outdated, incomplete, or inaccurate, it can compromise the accuracy of the rebuild cost estimate. Getting accurate details on floor areas, equipment/contents and even site boundaries is usually not as straightforward as expected.

3. Complexity of Risk Factors:

Modelling and analytical approaches may struggle to incorporate all relevant factors, such as site topography, local building codes, site access constraints, conservation area regulations, environmental considerations, and potential economic changes. These complexities can significantly alter reinstatement costs and may not be captured in a modelled assessment.

4. Dynamic Market Conditions:

Fluctuations in local prices of construction materials and labour costs, as well as changes in market conditions, can affect the accuracy of rebuild cost estimates. Many creators of models use historic unit rate cost data from third party sources. The fact that this data is based on tenders or procurement agreements from 2 or 3 years ago can mean that these costs are not indicative of current costs.

5. Specialised or Unique Assets:

For machinery, or buildings with unique features or specialised functions, it can be challenging to find accurate benchmark data for modelling. Standard models based on averages cannot capture the intricacies or challenges of such assets.

6. Underestimation of Soft Costs:

Models may focus on tangible costs such as construction materials and labour, but they can often underestimate soft costs like design fees, permits, legal fees, and other associated expenses.

7. Inclusions and Exclusions:

How has a model accounted for inclusions and exclusions. For example with leased property, the terms and obligations in a lease in terms of responsibility for insurance and the definition of insurable assets can differ, and can change if a lease is renewed. Does a modelled value include for tenant’s improvements or fixtures such as mezzanine flooring, internal partitioning, HVAC systems etc. 

8. Dependence on Historical Data:

Models often rely on historical data to make predictions about future costs. However, this approach may not fully account for changes in technology, construction methods, or other factors that can impact costs over time.

9. Human Error and Bias:

Errors in modelling assumptions or biases in the selection of underlying data can introduce inaccuracies. It’s essential to critically evaluate the modelling process to minimise the impact of human error.

10. Lack of Local Expertise:

 Models may not fully capture the nuances of local conditions, regulations, or construction practices. Local expertise and site inspection led assessments are therefore often crucial for ensuring accurate assessments.

To mitigate these weaknesses, it’s advisable to use modelling and analytics as one component of a comprehensive approach that includes inspections, validation of underlying data, and a thorough process for evaluating the assumptions in the models used. 

Regular reviews and updates of models based on real-world data and experiences can also help improve their accuracy over time. If you’d like support with assessing reinstatement costs, see our insurance services for information on how our specialist team can help create a robust approach.