Obsolescence management in the supply chain: how to anticipate it and minimise its financial impact

Obsolescence management in the supply chain has become one of the biggest silent challenges for many organisations. It often does not show up as a priority until the financial impact is already clear: inventory that does not move, unexpected write-offs and direct pressure on margin. At that point, decisions tend to be reactive and expensive.

However, obsolescence is not inevitable nor is it a warehouse-only problem. It is the outcome of planning decisions made much earlier relating to forecasting, purchasing policies, manufacturing and product lifecycle management. In this article, we look at why obsolescence is one of the biggest hidden costs in supply chain, how to anticipate it with predictive models and which operational adjustments help reduce its financial impact sustainably.

Why obsolescence is one of the biggest hidden costs in supply chain

Obsolescence is rarely managed as a strategic issue despite its direct impact on results. In many cases, it is detected late and treated as an unavoidable consequence of business when it is a symptom of structural planning failures.

Obsolescence vs excess stock: two different issues with the same financial impact

Although they are often confused, obsolescence and excess stock are not the same. Excess stock means holding more inventory than needed that still has potential demand. Obsolescence refers to inventory with a very low or zero likelihood of being consumed in future. Both tie up capital, but obsolescence has a more severe impact because it directly reduces the value of the asset.

From a financial perspective, both create similar pressure on the balance sheet and cash flow. However, obsolescence often goes unnoticed for longer because it materialises gradually until an accounting adjustment becomes unavoidable.

Tied-up capital, write-offs and margin erosion

Obsolete inventory represents tied-up capital that generates no return. On top of that come storage and handling costs and, in many cases, disposal or clearance at prices well below cost. The final impact is not only operational. It is directly financial.

Obsolescence write-offs affect margin and distort the interpretation of results. In addition, they often appear in concentrated spikes, creating negative peaks that make financial planning harder and undermine confidence in internal forecasts.

Why many businesses detect obsolescence when it is already too late

In most organisations, obsolescence is detected when inventory has already aged too far. This happens because traditional indicators look backwards (historical turns, current stock) rather than at expected future consumption.

Without a forward view, the problem only becomes visible when the options for action are limited. At that point, decisions tend to be defensive: aggressive promotions, clearance or accounting adjustments that could have been avoided with earlier detection.

Understanding obsolescence as a planning issue not a warehouse issue

One of the most common mistakes is treating obsolescence as a local operational problem. In reality, it originates in planning decisions made long before the product reaches the warehouse.

Where obsolescence really starts in the supply chain

Obsolescence is created in demand planning, in the definition of purchasing policies and in manufacturing decisions. Poorly calibrated forecasts, excessive supplier commitments or rigid production plans create inventory that does not reflect real demand.

The warehouse only makes the problem visible. It does not create it. Tackling obsolescence through execution without reviewing planning is treating symptoms rather than the cause.

The role of forecasting, product mix and lifecycle

Changes in product mix and lifecycle are among the main sources of obsolescence. Products moving into maturity or decline require a different planning approach from products in growth.

A forecast that does not account for these transitions tends to overestimate future consumption. This drives purchasing and production that do not match market reality, increasing the risk of obsolete inventory.

Defensive decisions that make the problem worse (buying “just in case”)

In the face of uncertainty, many organisations make defensive decisions: increasing cover, buying larger batches or bringing production forward “just in case”. While these decisions aim to protect service levels, they often create the opposite effect in the medium term.

This approach shifts risk from service to inventory. A lack of anticipation is compensated with excess stock, increasing both the likelihood of obsolescence and the associated financial impact.

How to anticipate obsolescence with predictive models

Anticipation is the main lever for reducing obsolescence. To achieve it, you need to go beyond historical metrics and use models that project future consumption more accurately.

Identifying patterns of slowdown and declining consumption

Obsolescence rarely appears abruptly. It is usually preceded by slowdown signals: lower consumption frequency, progressive volume reductions or increasing intermittency.

Predictive models can detect these patterns before inventory builds up. Spotting a downward trend early enables gradual adjustments in purchasing and production, reducing risk without creating disruption.

Distinguishing seasonality, intermittency and true end of lifecycle

Not every drop in consumption means obsolescence. Distinguishing between seasonality, intermittent demand and end of lifecycle is essential to avoid wrong decisions. Mistaking a seasonal pause for a structural decline can create unnecessary stockouts.

Advanced models help separate these behaviours and assess the real likelihood of future consumption. This differentiation improves decision quality and prevents excessive adjustments.

Using scenarios and simulations to anticipate future impact

Scenario simulation is a fundamental tool for anticipating obsolescence. It helps answer key questions: what if demand drops by 20%? What impact will a mix change have? What inventory will be at risk?

These simulations help quantify risk before it materialises. This shifts planning from reactive responses to proactive financial risk management.

The role of AI in predictive obsolescence management

Today’s supply chains are too complex to manage obsolescence with static rules or manual analysis. The combination of large portfolios, ever shorter lifecycles and non-linear demand patterns calls for an approach supported by advanced models and predictive capabilities. This is where artificial intelligence makes a real difference.

AI can analyse large volumes of historical data and current signals to identify slowdown patterns, structural shifts in consumption and emerging obsolescence risks that traditional indicators do not reveal. Instead of reacting when stock has already lost value, planning can anticipate likely scenarios and assess their economic impact in advance.

From static rules to models that learn from real behaviour

Traditional approaches often rely on fixed thresholds: days without movement, historical turns or stock age. While useful as basic signals, these criteria do not capture the real complexity of consumption or how it evolves over time.

AI-based models incorporate continuous learning, adapting to changes in demand, product mix or customer behaviour. This makes it possible to distinguish a temporary slowdown from a true end-of-life and to adjust purchasing, production and clearance decisions far more precisely.

Anticipating obsolescence before it becomes visible in inventory

One of the biggest advantages of applying AI to planning is its ability to flag risks before they physically show up in the warehouse. By combining forecast data, actual consumption, future cover and operational constraints, predictive models can highlight products with a high probability of becoming obsolete weeks or months in advance.

This early visibility increases your room for manoeuvre. It enables progressive adjustments, reduced commitments, policy changes or commercial actions while the economic impact is still controllable, avoiding late and costly decisions.

Key KPIs to detect and manage obsolescence risk

Measuring well is essential but not all KPIs deliver the same value. With obsolescence, indicators should support decisions not just reporting.

At-risk inventory vs healthy inventory

Distinguishing between healthy inventory and at-risk inventory is one of the first steps. At-risk inventory is stock where expected future consumption does not justify the available quantity.

This classification helps prioritise actions and focus effort where potential impact is greatest rather than treating all inventory in the same way.

Stock age, future cover and expected consumption

Stock age on its own does not define obsolescence. You need to combine it with future cover and expected consumption. Old stock can still be valid if future demand supports it.

Cross-referencing these indicators provides a much more accurate view of real risk and supports sound decisions, avoiding rushed action.

Why inventory turns alone do not detect obsolescence

Inventory turns are retrospective. They measure what has already happened not what will happen. A product may have turned well in the past and still be at risk of obsolescence.

That is why relying only on turns creates a false sense of control. Anticipation requires a forward view not just historical analysis.

Adjusting purchasing and manufacturing policies to reduce obsolescence

Anticipation only creates value when it is translated into concrete operational decisions. This is where planning connects with execution.

Adapting MOQs, frequencies and batch sizes for at-risk products

Products at risk of obsolescence require different purchasing policies. Reducing MOQs, increasing order frequency or renegotiating terms helps limit unnecessary commitments.

This approach reduces financial exposure without compromising service, especially in the final phases of the lifecycle.

Flexible manufacturing and reduced commitments in the final phases

In production environments, flexibility is critical. Reducing batch sizes, delaying final configurations or using postponement strategies helps minimise product-specific inventory.

These practices allow better alignment with real demand and reduce the risk of making products that will not sell.

Trade-offs between service level, cost and financial risk

Reducing obsolescence means accepting trade-offs. It is not always possible to maximise service while minimising risk at the same time. The key is to make conscious, quantified choices.

Assessing these trade-offs end to end helps protect margin without unnecessarily damaging customer experience.

From managing inventory to governing business decisions

Obsolescence management delivers its greatest value when it stops being treated as an operational issue and becomes part of the executive decision agenda. At this level, the objective is not only to reduce obsolete stock. It is to protect margin, stability and the organisation’s ability to respond. To achieve this, you need to translate operational risk into economic impact and align all functions around a shared forward view.

Translating obsolescence risk into economic impact

Quantifying obsolescence risk in financial terms is what elevates the discussion to the leadership team. Talking in units or SKUs rarely drives action. Talking about tied-up capital, potential write-offs, margin impact or cash flow risk does. This translation turns obsolescence into a variable that can be compared with other investment and prioritisation decisions.

When risk is expressed in pounds and financial scenarios, decisions become clearer: which products to protect, where to reduce commitments and which actions justify the risk being taken. Obsolescence stops being a “warehouse problem” and becomes fully integrated into the business’s economic management.

Aligning demand, procurement, operations and finance

Anticipation only works when all involved functions work from a shared view of risk and the future. If demand, procurement, operations and finance make decisions based on different assumptions, obsolescence multiplies. Each function optimises locally but overall performance worsens.

Aligning these functions means sharing scenarios, agreeing priorities and assessing trade-offs together. When every area understands the financial impact of its decisions on inventory and obsolescence, planning becomes more coherent and contradictory choices that create unnecessary stock are reduced.

From reactive decisions to proactive planning

The real shift is moving from reacting to obsolescence to governing it through anticipation. Reactive decisions are made late with limited alternatives and high cost. Proactive planning allows action while there is still room to manoeuvre.

This approach offers more options: adjust purchasing, redefine production plans, launch commercial actions or review commitments before inventory loses value. Over time, it reduces firefighting, stabilises operations and protects profitability. Obsolescence stops being an unexpected event and becomes a consciously managed, strategic risk.

Anticipating obsolescence protects margin and stability

Obsolescence cannot be eliminated entirely but it can be managed proactively. Treating it as a planning issue rather than only an inventory issue reduces its financial impact and improves supply chain stability. Organisations that anticipate make better decisions and avoid disruptive adjustments.

At Imperia, we help organisations integrate obsolescence management into a connected, decision-oriented advanced planning model. Our Supply Chain Planning software enables you to anticipate risk, adjust policies and align demand, operations and finance on a reliable data foundation. If you would like to see how to protect margin and stability in your organisation, we invite you to request a free advisory session with our experts.