By Enzo Comazzi, Supply Chain Practice Director Anaplan – Beyond Plans

Stock planning is still too often managed reactively, driven by emergencies and adjustments. In a context of increasing variability and pressure on cash, this approach is reaching its limits. Structuring the planning model then makes it possible to transform inventory into a real performance lever, balancing service levels, cost control, and anticipation capabilities.

I have often observed that stock planning is limited to a reactive logic. Yet, it is by structuring the model and giving meaning to decisions that it becomes a true performance driver.

In many organizations, stock planning remains largely reactive. Adjustments are made after a stockout. Corrections follow overstock situations. Acceleration or slowdown happens once the problem becomes visible. This way of operating has held up for a long time.

Today, it is reaching its limits. Cycles are shortening and variability is increasing. And one reality stands out: forecasting is imperfect and will remain so.
In CPG as in luxury, between promotions, product launches, market effects, and commercial trade-offs, forecasting is structurally unstable. On the ground, the real issue is not so much accuracy. It is the ability of the planning model to absorb this uncertainty. I have seen organizations where a shifted forecast immediately resulted in immobilized stock in certain markets, stockouts in others, and late reallocations, often costly. Not due to a lack of data, but due to a lack of a management framework.

The Turning Point: Structure Before Optimization

Moving to high-performing planning does not primarily improve forecasting, but rather eliminates overly reactive management, built on inherited stock rules that are rarely revisited, uniform coverage levels regardless of product role, and decisions made in urgency, without a global view.
In this context, even the smallest forecast error turns into an operational issue.
The right question must then be asked: why do we stock this product?

• To secure volume?
• To support a product launch?
• To reinforce a premium strategy or desirability logic?

As long as this answer is not explicit, stock rules remain mechanical and amplify errors rather than absorb them.

What Changes in Structured Planning

Effective planning does not aim to eliminate uncertainty. It enables its management.
And decisions become clearer:

• where to invest in stock?
• where to accept risk?
• how to balance service, cash, and product strategy?

In this type of approach, connected planning tools fully make sense. Not to “automate” decisions, but to structure models, share a single source of data, and quickly simulate the impacts of trade-offs.
This is what platforms like Anaplan enable, when used with a model adapted to business challenges.

Concretely, What Is a Structured Planning Model?

A stock planning model is not limited to defining thresholds or coverage levels. It is a framework that connects several dimensions which, in many organizations, are still handled separately:

• how products are actually segmented (rotation, value, business role, seasonality),
• replenishment rules, built from forecasts but also from service objectives,
• the financial perspective of inventory, particularly its impact on cash and costs,
• and above all, the ability to share these elements across supply, finance, and commercial teams.

What makes the difference is not each component taken individually: it is the overall consistency.

Benefits Observed in the Field

A structured model also changes how performance is monitored. Inventory level or service rate are no longer viewed in isolation. Several indicators are considered together:

• service rate on truly strategic items,
• stock coverage and its evolution over time,
• average inventory level and its impact on working capital requirements,
• product turnover,
• and gaps between planning and execution.

Stock planning then ceases to be a defensive exercise and becomes a lever for overall performance.

Conclusion

Stock planning can no longer be approached as a simple support function. It is a structuring lever to reconcile operational performance and financial objectives.
When it is based on a clear framework, shared across teams and capable of absorbing uncertainty, it enables better anticipation of demand changes and adjustment of decisions in an increasingly unstable environment.