How Seasonality and Growth Trends Affect a Business Interruption Loss Model

Seasonality is usually assessed using historical financial and operational information rather than a single accounting period.

Depending on the nature of the business, an expert may examine:

The objective is not simply to find a recurring percentage change and apply it mechanically.

The expert must consider whether the historical pattern is representative of the business during the period being analyzed.

A seasonal pattern may have changed because of a new location, acquisition, product launch, major customer, pricing change, capacity expansion, or other event. Historical data therefore needs to be interpreted in its commercial context.

Growth assumptions should be supported by evidence relevant to the business and the period under analysis.

An expert may consider:

The strength of each indicator depends on the circumstances of the particular business.

For example, a signed contract that was scheduled to begin during the loss period may provide different evidence from an internal sales target that had not yet been supported by customer commitments.

Likewise, historical growth may not be a reliable predictor if the business had reached a capacity constraint or was entering a materially different market.

The expert's role is to determine which evidence provides a reasonable basis for reconstructing the expected trading position.

A common analytical risk is assuming that historical growth would have continued indefinitely.

Suppose a business grew by 15% in each of the three years before an interruption. That history may support an argument that the business was on an upward trajectory. It does not, by itself, establish that a 15% growth rate should automatically be applied throughout the entire loss period.

The expert may need to determine:

The longer the projection extends, the more important these questions can become.

A defensible model should distinguish demonstrated historical performance from assumptions about future performance.

Another important issue is that a business may not have a constant growth rate.

A model that applies one annual percentage increase across the entire projected period may not reflect the actual development of the business.

For example, a company may have experienced rapid growth following a new product launch, followed by a period of stabilization. Alternatively, a business may have been expanding gradually before entering a period where capacity limitations restricted further growth.

A business interruption expert may therefore consider whether the evidence supports:

The appropriate approach depends on the facts, the available evidence, and the requirements of the applicable policy and dispute.

Some businesses do not have a long or consistent trading history.

This can occur with:

In those circumstances, the expert may need to place greater weight on other evidence.

Potential sources can include: comparable operations; existing contracts; customer commitments; pre-loss order information; budgets prepared before the interruption; operational capacity; industry benchmarks; management forecasts; actual trading information from comparable locations or business units.

Such evidence should be assessed carefully. A forecast prepared after the interruption may be affected by knowledge of the loss and therefore may require different scrutiny from a contemporaneous forecast prepared before the event.

In a contested business interruption claim, the central issue may not be whether the business suffered a revenue decline.

The more difficult question can be how much of that decline is attributable to the insured interruption rather than conditions that would have affected the business anyway.

Seasonality and growth assumptions can therefore become important points of disagreement between opposing experts.

Counsel may need to understand:

These questions can be particularly important when the projected loss is substantial or when relatively small changes in the revenue assumption produce significant changes in the claimed business income loss.

For broader litigation support, see the site's Federal Rule of Evidence 702 Expert Reports & Joint Statements, which addresses instructions, materials reviewed, assumptions, limitations, alternative assumptions, and areas of expert disagreement.

Seasonality and growth can have a material effect on the projected revenue used in a business interruption loss calculation.

A reliable analysis should explain why the selected comparison periods are appropriate, how recurring seasonal patterns were identified, what evidence supports the growth assumptions, and whether unusual circumstances could distort the historical data.

The objective is not to produce the highest possible projection or the lowest possible claim. It is to reconstruct a reasonable financial position using evidence that can be explained, tested, and, where necessary, challenged.

For attorneys and insurers dealing with a disputed BI claim, a qualified business interruption expert can help separate historical fact from projection, identify assumptions that require further support, and present the resulting quantum analysis in a transparent manner.

For additional information on the broader methodology, see the Business Interruption Expert Witness Services and the US Business Income Policy Forms & Loss Calculation guide.

This article is provided for general informational purposes only. It does not constitute legal, accounting, insurance coverage, or other professional advice. The treatment of business interruption losses depends on the applicable policy wording, facts, jurisdiction, and available evidence. A qualified professional should be consulted regarding a specific claim or dispute.