Production allocation in chemicals and pharmaceuticals
Why Excel reaches its limits in multi-site planning
The bottleneck often begins unspectacularly. At location A, a line is tied up due to an ongoing campaign. Site B would still have free capacity, but some lines would have to be serviced and released again. At the same time, an important order is waiting, a raw material is late and a quality release is still pending. Everything is visible. And yet the central question remains: which site should produce what, in what order and under what conditions?
Particularly in the chemical and pharmaceutical industries, cross-site production planning is not just a coordination problem. As soon as several plants are involved, it is not enough to simply shift quantities. Every relocation also changes cleaning effort, capacity utilization, material flows, releases, delivery capability and costs. Excel can document such correlations in production planning. However, it cannot reliably evaluate them at the same time.
„Free capacity is not yet a good decision.“
An additional location does not automatically create more scope
Several production sites initially act as a safety net. If there is a shortage at one plant, another is supposed to step in. However, this logic only works to a limited extent in the chemical and pharmaceutical industries. Not every plant is suitable for every product. Not every line is quickly available again. And not every decision can be made solely on the basis of free capacity. Quantity is often only the most visible factor, but not the decisive one.
The real effort is in the changes
Many problems do not arise during stable production, but at the transitions. When is a change of location worthwhile? Which sequence reduces cleaning and changeover costs? Which additional batch shifts next week's schedule?
In batch and campaign environments in particular, it is not only the quantity that determines a good plan, but also the sequence. An additional changeover can be more expensive than a supposedly less favorable location. This is precisely why table logics often fall short: they show quantities and dates, but not reliably the consequences of a change.
„Security of supply counts in pharma, campaign stability in chemistry.“
In pharma, it's not just capacity that counts, but also release logic
In the pharmaceutical industry, a production plan is only resilient if it makes sense not only in terms of capacity, but also in terms of quality. A batch that could theoretically be produced is not yet a reliably available contribution to supply. Quality testing, approval processes and site-specific requirements significantly change the operational logic.
Multi-site planning in pharma is therefore more than just quantity distribution. It controls a system in which security of supply, regulatory requirements and production reality are closely linked.
In the chemical industry, campaigns and costs make the decision more difficult
The mechanism is different in the chemical industry, but the consequences are similar. Here, campaigns, product sequences, cleaning effort, energy consumption and stable plant occupancy characterize the planning. A site with free capacity is not automatically the better economic answer if this results in additional changes or unfavorable campaign lengths. High energy and feedstock costs increase this pressure.
The real challenge therefore lies in deciding across all locations which occupancy is better under real restrictions. And this is where Excel's strength as a planning tool comes to an end: a lot becomes visible, but the overall system can only be reliably evaluated to a limited extent.
„Optimization not only changes the plan, but also the decision-making logic.“
The change of perspective starts with the network
Mathematical optimization does not replace the experience of planners. It changes the structure of the decision. Instead of checking site by site which plant could still accommodate something, it evaluates the production network as an interconnected system. Capacities, product sequences, releases, material availability and conflicting objectives are considered together.
This means that decisions no longer result from a series of local compromises, but from a consistent assessment of the overall system
Conflicting objectives are explicitly
In practice, the actual questions are rarely just: Where is there still capacity? More relevant is: Should a batch be relocated even though additional changes are required? Is a stable campaign more important than short-term flexibility? How much reserve makes sense when costs and delivery capacity are under pressure at the same time?
Optimization makes such conflicting goals visible. It translates priorities into a reliable decision-making logic and shows which levers really work.
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Replanning is also becoming more structured
The actual value is often revealed when changes occur. A raw material is delayed. A line fails. A release takes longer. In many Excel setups, a new round of manual interpretation then begins.
With an optimization approach, the decision-making logic in cross-location production planning remains stable, even if inputs change. This makes replanning more comprehensible, faster and more consistent, especially in environments where late findings cause high operational follow-up costs.
Why specialized software is needed for this
The basic idea is simple: decision options, restrictions and objectives are evaluated together. The industrial reality with different locations, data quality, special cases and campaign-dependent interactions is more difficult.
This is why specialized software is not needed as a substitute for specialist knowledge, but as a reliable framework for complex decisions.
„When restrictions interact, planning needs more than transparency.“
OPTANO translates restrictions into resilient planning logic
OPTANO helps companies to think about production allocation and cross-location production planning not in isolation per plant, but in terms of the entire network. For chemicals and pharmaceuticals, this means that capacities are not viewed in isolation from product sequences, campaigns, material restrictions or release conditions, but in their actual context.
This not only improves the quality of individual decisions. The planning work itself also becomes more robust.
Fewer personal compromises, more reproducible decisions
In complex production networks, Excel planning often relies on experienced people who think along with implicit rules. This is valuable, but also risky. If crucial compromises only exist in the minds of individual planners, planning becomes susceptible to time pressure, handovers and inconsistent scenarios.
OPTANO helps to institutionalize this logic. Decisions become more reproducible, scenarios more comparable and effects more transparent.
Particularly relevant if several restrictions apply at the same time
The added value arises where Excel has to do too much at the same time: Balancing capacity, respecting campaigns, minimizing changes, considering approvals, securing supply and keeping an eye on costs. This is precisely where it becomes clear why transparency is no substitute for consistent evaluation logic.
Better decisions do not come from more tables
Anyone who distributes production volumes in chemicals and pharmaceuticals across several sites never just decides on volumes. Every decision has consequences that go far beyond the actual allocation. As long as such dependencies are resolved step by step and manually, the plan will remain susceptible to disruption. The decisive progress therefore lies not in more tables, but in better decision-making logic.
If you want to check where your production allocation in chemicals or pharmaceuticals is reaching its limits, it is worth taking a look at the decision-making mechanics of your site network: Which restrictions are only implicitly mapped today? Where do changes, approvals or replanning already cost unnecessary time and stability? And where does the local view of individual plants prevent a better overall decision?
OPTANO helps companies to answer precisely these questions in a structured way. If you wish, we can look together at what a resilient planning approach for your site network might look like.
Key Takeaways
- In the chemical and pharmaceutical industries, multi-site planning is more than just distributing quantities to free capacity.
- In pharma, what counts are approvals, regulatory requirements and security of supply.
- In the chemical industry, campaign logic, cleaning effort, energy consumption and stable plant occupancy determine the decision.
- Excel creates transparency, but only evaluates complex interactions simultaneously to a limited extent.
- Mathematical optimization helps to explicitly control conflicting goals and make replanning more consistent.