INSIGHT • GROSS-TO-NET

Risky Batches: Looking Beyond the Returns Claims %

Why product-level historical return rates may not tell the entire story when estimating short-dated and expired product reserves.

THE TRADITIONAL APPROACH

Historical claims are useful. But averages can hide risk.

One of the most common approaches to estimating an expired product return reserve is to start with historical claims.

At a high level, an organization may calculate a historical return claims percentage and apply that rate to an appropriate population of current or expected sales.

This can be a reasonable starting point. But historical averages can become less predictive when the underlying business conditions have changed.

A return rate is ultimately a reflection of the environment in which the products were sold, distributed, stocked, and eventually returned.

When that environment changes, the historical percentage may need to be challenged.

SCOPE

What are we measuring?

For this discussion, we're focused on products subject to manufacturer return provisions for short-dated or expired inventory.

In many commercial arrangements, products may become eligible for return during a defined period before expiration—for example, six months prior to expiration—or after expiration, depending on the applicable agreement.

Short-Dated

Product approaching expiration that falls within the applicable return eligibility window.

Expired

Product that has reached or passed its expiration date and may generate a return claim under applicable contractual terms.

Reserve Exposure

The estimated financial obligation associated with expected future return claims.

WHAT CHANGES THE RISK?

The historical rate is only as useful as its relevance.

There are numerous factors that can change the expected return profile of a product.

Some are obvious. Others can be difficult to see when the analysis is performed only at an aggregate product level.

High Return Risk

Certain products, customers, channels, or periods may historically demonstrate materially higher return activity than the broader portfolio.

Shorter Dating

Product manufactured or released with less remaining shelf life can have a different probability of reaching a return-eligible state.

Market Conditions

Changes in market demand, treatment dynamics, competitive activity, or other commercial conditions can alter inventory velocity.

Competitive Landscape

New competitors, additional products, or market oversupply can reduce demand and increase the likelihood that inventory becomes aged.

Customer Loss

Losing a large customer can materially change demand assumptions and leave inventory positioned for a different commercial environment.

Aged & Slow-Moving Inventory

Existing inventory that is already aging or moving slowly may carry a substantially different return risk than the portfolio average.

LOOK CLOSER

Sometimes the product isn't the problem. The batch is.

Performing a return-rate calculation at the product level can be perfectly appropriate in many situations.

But there are circumstances where it is worth going one level deeper and examining the activity by batch or lot.

BATCH & LOT ANALYSIS

The batch can tell a different story.

Consider a newly launched product.

New launches can involve substantial shipments across multiple batches or lots. Because of the uncertainty that often surrounds an approval, launch, and initial distribution cycle, some of those batches may carry shorter-than-typical dating.

If those batches subsequently demonstrate elevated return activity, an aggregate historical return rate may not adequately distinguish the underlying cause.

More importantly, the conditions that created that historical return experience may not be representative of the current or future business.

That is where batch-level analysis can become particularly valuable.

AN ILLUSTRATIVE EXAMPLE

An elevated return rate may have a very specific explanation.

Imagine a product with a historical return rate that appears elevated.

At the product level, the obvious response may be to increase the reserve percentage.

But a deeper analysis could reveal that a disproportionate amount of the historical returns came from a small number of early launch batches with unusually short dating.

Aggregate View

Historical return rate appears elevated and suggests increased reserve requirements.

Batch-Level View

Analysis identifies a concentration of returns within specific early batches.

Forward-Looking Assessment

Current production has normal dating and the conditions that created the earlier risk are no longer present.

RESERVE JUDGMENT

Historical experience should inform the reserve—not automatically dictate it.

The purpose of historical claims analysis is to provide evidence for a reasonable estimate of future obligations.

When circumstances have materially changed, organizations should consider whether the historical experience remains representative.

A meaningful reserve assessment may therefore require a combination of historical claims data, current inventory, product dating, demand expectations, customer behavior, market conditions, and specific risk factors.

Batch and lot-level analysis can provide another layer of evidence when the circumstances warrant it.

BEYOND THE RESERVE

Returns are also a feedback loop.

There is another reason to analyze returns beyond simply estimating the accounting reserve.

Returns represent a full-cycle opportunity for the organization to evaluate how well its commercial and operational processes are working.

Demand Planning

Are forecasts appropriately reflecting actual demand and changes in market conditions?

Volume Allocation

Is inventory being allocated to customers and channels in a way that minimizes unnecessary aging?

Inventory Management

Are slow-moving and aging inventories being identified early enough to allow corrective action?

Commercial Strategy

Are changes in competition, customer behavior, and market supply being incorporated into inventory decisions?

Waste Reduction

Can earlier intervention reduce avoidable product returns, destruction, and associated costs?

Reserve Accuracy

Are reserve assumptions aligned with the actual risk profile of the current inventory population?

A PRACTICAL FRAMEWORK

From historical percentage to risk-based reserve.

A mature approach to expired and short-dated reserves can move beyond simply asking:

"What was our historical return rate?"

Instead, consider asking:

"What is the return risk of the inventory we actually have today?"

That distinction can lead to a more meaningful assessment of reserve adequacy.

QUESTIONS WORTH ASKING

Before relying on the historical rate, look at the underlying population.

What inventory is aging?

Understand the current age and remaining shelf life of the inventory population.

Which batches are driving risk?

Determine whether return exposure is concentrated in particular batches or lots.

Has the business changed?

Consider customers, competitors, market demand, supply, and other commercial changes.

Are historical problems recurring?

Distinguish persistent risk from isolated historical events that may no longer apply.

PROGTN PERSPECTIVE

Sometimes the answer isn't a better percentage. It's a better population.

Historical return rates are an important tool for estimating expired and short-dated product reserves. But the quality of the estimate depends on how well the historical experience represents the inventory and business conditions that exist today.

Looking deeper—down to the batch or lot level when appropriate—can reveal patterns that disappear inside an aggregate product rate.

And perhaps most importantly, returns should not simply be viewed as an accounting expense. They can provide valuable insight into demand planning, inventory allocation, commercial strategy, and opportunities to reduce waste.

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