Advanced Promotional Demand Management: Practical Techniques to Forecast Peaks and Avoid Stockouts

Promotional demand is one of the biggest challenges for any organisation running intensive commercial campaigns, especially in sectors such as retail, FMCG, food or fashion. From the outset, managing promotional demand puts the supply chain’s ability to anticipate consumption peaks, absorb volatility and maintain service levels to the test, all without ending up with overstocks that are hard to justify.

In this article, we look at why promotions break traditional forecasting approaches and which techniques allow their impact to be anticipated more reliably. We will cover how to model promotional effects correctly, how to integrate planning across procurement, inventory and capacity, and which indicators help assess whether a campaign has truly been a success, not only in terms of sales, but also operational efficiency and profitability.

Why Promotional Demand Breaks Any Traditional Forecast

Promotions deliberately alter normal consumer behaviour. Unlike regular demand, which tends to follow relatively stable patterns, promotional demand responds to artificial stimuli that create sharp peaks and behavioural changes that are difficult to extrapolate from historical data.

What Makes Promotions Unpredictable: Elasticity, Peaks and Category Shifts

One of the main sources of complexity is price elasticity. For certain products, a temporary price reduction can multiply demand within a matter of days. These peaks are usually concentrated in very short time windows and with an intensity that is difficult to absorb unless planned in advance.

In addition, many promotions do not generate true additional consumption, but rather demand shifts within the category. Customers bring purchases forward, switch formats or substitute one product for a promoted alternative. If this effect is not identified, the forecast tends to overestimate total consumption, leading to inefficient inventory decisions.

Differences Between Base, Incremental and Shifted Demand

To manage a promotion properly, it is essential to distinguish between three components:

• Base demand, which represents expected consumption without a promotion.
• Incremental demand, attributable exclusively to the promotional stimulus.
• Shifted demand, corresponding to purchases brought forward or cannibalised from other products or periods.

Treating all promotional sales as incremental is one of the most common mistakes. This approach leads to over-procurement, artificial inventory peaks and a false sense of commercial success that later turns into leftovers and hidden costs.

Impact on Forecast Accuracy, Inventory and Service Level

When promotional demand is not modelled correctly, the impact is immediately reflected in key indicators. Forecast accuracy deteriorates, BIAS becomes systematically positive and inventory grows as a defensive mechanism. However, this excess coverage does not always prevent stockouts, as poor stock allocation still causes shortages at high-rotation locations.

How to Anticipate Promotional Demand with Advanced Models

The key is not to react faster, but to forecast better. This requires moving away from approaches based solely on historical averages and adopting models that separate the promotional effect from normal demand behaviour.

Building Uplift: How to Measure the Real Promotional Effect

Promotional uplift represents the increase in sales attributable to the campaign. Estimating it requires comparing observed behaviour with a counterfactual scenario: what would have happened without the promotion.

This analysis can be based on historical comparisons, control windows or similar non-promoted products. The goal is not to find an exact figure, but to define a realistic range that enables lower-risk planning and greater operational coherence.

Using External Regressors: Price, Discount, Visibility and Competition

Promotional demand depends on multiple factors. Discount depth, campaign duration, in-store visibility and competitive pressure all directly influence the final outcome.

Advanced models incorporate these elements as external regressors, allowing forecasts to be adjusted based on the true intensity of the promotion. This approach is particularly effective in multi-channel campaigns or highly competitive environments.

Methods for Intermittent, Recurring and Combined Promotions

Not all promotions behave in the same way. One-off campaigns require models capable of handling irregularity, while recurring promotions allow patterns to be learned and uplift to be adjusted progressively.

In both cases, continuous recalibration is essential. Each campaign generates valuable information that should be fed back into the model to improve accuracy in future initiatives.

Integrating Promotional Planning into Procurement, Inventory and Capacity

An isolated promotional forecast delivers little value if it does not translate into coherent operational decisions. Integration with procurement, inventory and capacity planning is what turns the forecast into real results.

Dynamic Stock Policies Based on Promotional Aggressiveness

Promotions should not be managed using the same stock policies as regular demand. Promotional aggressiveness determines the level of risk that can be assumed and, therefore, the required coverage.

In high-impact campaigns, it is common to apply temporary policies that increase safety stock only during the promotional window. For moderate or recurring promotions, adjustments can be more selective, focusing on critical SKUs.

Operational Adjustments: MOQs, Supplier Constraints and Variable Lead Times

Promotional planning also requires a review of MOQs, actual lead times and supplier constraints. If these parameters are not adjusted before launching the campaign, even the best forecast loses effectiveness.

Anticipating these changes enables better supplier negotiations, order consolidation and a reduction in last-minute urgencies that drive up logistics costs and erode promotional margins.

Scenario Simulation to Avoid Stockouts and Excess Coverage

Scenario simulation makes it possible to assess different uplift levels, supply delays or changes in campaign duration. This approach does not eliminate uncertainty, but it does allow it to be managed consciously, prioritising service for key SKUs while limiting the impact of extreme scenarios.

Organisational Connectivity: Sales, Marketing and Supply Chain Sharing the Same Forecast

Promotional demand is a cross-functional phenomenon. Without alignment between teams, the risk of over-optimism and inconsistent decisions increases significantly. How can organisations align their teams to improve decision-making?

Validating Commercial Inputs and the Cost of Over-Optimism

Commercial inputs are valuable, but they must be validated. Excessive optimism often results in overstocks and margin erosion. Challenging these forecasts against historical data and alternative scenarios helps balance commercial ambition with operational feasibility.

Defining a Promotional S&OP Process

Integrating promotions into the S&OP process makes it possible to assess their impact on demand, capacity and finances before launch. This approach supports aligned decision-making and reduces surprises during execution.

Continuous Review and Learning for Future Campaigns

Each promotion should be reviewed once it ends. Comparing forecasts with actual results allows models to be refined, assumptions to be improved and accuracy to increase in future campaigns.

Essential KPIs to Control Promotional Demand

Measuring performance correctly is key to learning and continuous improvement. That’s why the following KPIs should be closely monitored.

Uplift Accuracy, Promo-BIAS and Incremental Error

These indicators help assess whether the model has correctly captured the promotional effect and whether there is any systematic bias in the forecast.

Promotional Service Level (On Time In Full)

OTIF during the promotion is one of the most relevant indicators, as it reflects the supply chain’s real ability to absorb peaks without failing the customer.

Remaining Inventory and the Cost of Excess Coverage

Leftover stock after the campaign is one of the main hidden costs. Analysing it helps refine policies and avoid repeating the same mistakes.

Forecasting Promotional Demand Means Managing Risk, Profitability and Service

Promotional demand is not a one-off issue, but a structural risk that must be managed through method, data and collaboration. Organisations that model it correctly reduce errors, protect service levels and avoid reactive decisions that damage margins.

At Imperia, we help companies anticipate promotional demand by integrating it consistently into demand, inventory and capacity planning. Our software enables scenario modelling, validation of commercial inputs and data-driven decision-making.

If you’d like to learn how we can help you improve the management of your campaigns, request a free consultation with our experts.