Production Allocation in Chemistry and Pharmaceuticals
Why Excel Reaches Its Limits in Multi-Site Planning
The bottleneck often begins unspectacularly. At location A, a line is tied up by an ongoing campaign. Location B would still have free capacity, but some systems would need to be maintained and released again. At the same time, an important order is pending, a raw material is delayed, and a quality release is still outstanding. Everything is visible. And yet, the central question remains: which location should produce what, in what order, and under what conditions?
Especially in chemistry and pharmaceuticals, cross-site production planning is not just a coordination problem. As soon as multiple plants are involved, simply shifting quantities is not sufficient. Every transfer also changes cleaning effort, capacity utilization, material flows, releases, delivery capability, and costs. Excel can document such interdependencies in production planning. However, it cannot reliably evaluate them simultaneously.
„Free capacity is not yet a good decision.“
An additional location doesn't automatically create more leeway.
Multiple production sites seem like a safety net at first glance. If one plant gets overwhelmed, 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 based on spare capacity. Quantity is often only the most visible, but not the decisive factor.
The real effort lies in the changes.
Many problems arise not during stable production, but at the transitions. When is a change of location worthwhile? Which sequence reduces cleaning and setup effort? Which additional batch shifts next week's schedule?
Especially in batch and campaign environments, not only the quantity but also the sequence determines a good plan. 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.
„In pharma, supply security counts; in chemistry, campaign stability.“
In pharma, it's not just capacity that counts, but also the release logic.
In the pharmaceutical industry, a production plan is only reliable when it is not only capacity-wise but also quality-wise sensible. A batch that could theoretically be produced is not yet a reliably available contribution to supply. Quality control, release processes, and site-specific requirements significantly alter the operational logic.
Multi-site planning in pharma is therefore more than just volume distribution. It manages a system in which supply security, regulatory requirements, and production reality are closely intertwined.
In chemistry, campaigns and costs intensify the decision.
In chemistry, the mechanism looks different, but the consequence is similar. Here, campaigns, product sequences, cleaning effort, energy consumption, and stable plant utilization shape the planning. A site with free capacity is not automatically the more economical answer if it leads to additional changeovers or unfavorable campaign lengths. High energy and feedstock costs intensify this pressure.
The real challenge, therefore, lies in deciding across locations which assignment is better under real-world constraints. And that is precisely where Excel's strength as a planning tool ends: many things become visible, but the overall system can only be reliably evaluated to a limited extent.
„Optimization changes not just the plan, but the decision logic.“
The change in perspective begins with the network
Mathematical optimization does not replace the experience of planners. It changes the structure of decision-making. Instead of examining location by location to see which plant could still absorb something, it evaluates the production network as a connected system. Capacities, product sequences, releases, material availability, and conflicting goals are considered together.
This means decisions are no longer made from a series of local compromises, but from a consistent evaluation of the overall system.
Goal conflicts are explicit
In practice, the real questions are rarely just: "Where is there still capacity?" More relevant are: "Should a batch be relocated even if additional changeovers are incurred there?" "Is a stable campaign more important than short-term flexibility?" "How much reserve makes sense when costs and delivery capability are under pressure at the same time?"
Optimization makes such conflicting objectives visible. It translates priorities into a robust decision-making logic and shows which levers actually have an effect.
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Re-planning is also becoming more structured
The real value often becomes apparent during changes. A raw material is delayed. A line fails. A release takes longer. In many Excel setups, this then marks the beginning of a new round of manual interpretation.
With an optimization approach, the decision logic in cross-location production planning remains stable even when inputs change. This makes replanning more understandable, faster, and more consistent, especially in environments where late insights cause high operational follow-up costs.
Why specialized software is necessary for this
The basic idea is simple: decision options, restrictions, and goals are evaluated together. Industrial reality is more difficult, with different locations, data qualities, special cases, and campaign-dependent interactions.
That's why specialized software is needed not as a replacement for expertise, but as a reliable framework for complex decisions.
„When restrictions interact, planning needs more than transparency.“
OPTANO translates restrictions into robust planning logic
OPTANO helps companies think about production allocation and cross-site production planning not in isolation per plant, but across the entire network. For chemistry and pharmaceuticals, this means: Capacities are not considered detached 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 person-specific compromises, more reproducible decisions
In complex production networks, Excel planning often relies on experienced individuals who implicitly consider rules. While this is valuable, it's also risky. If crucial compromises exist only in the minds of individual planners, the planning becomes vulnerable to time pressure, handovers, and inconsistent scenarios.
OPTANO helps to institutionalize this logic. Decisions become more reproducible, scenarios easier to compare, and impacts more transparent.
Especially relevant when multiple restrictions apply simultaneously
The added value arises where Excel is expected to do too much at once: matching capacity, respecting campaigns, minimizing changes, considering approvals, ensuring supply, and keeping costs in view. This is precisely where it becomes clear why transparency cannot replace consistent valuation logic.
Better decisions don't come from more spreadsheets
Those who distribute production volumes across multiple sites in the chemical and pharmaceutical industries never make decisions based solely on volume. Every decision has consequences that extend far beyond the actual allocation. As long as such dependencies are resolved step-by-step and manually, the plan remains prone to error. Therefore, the decisive progress lies not in more spreadsheets, but in better decision-making logic.
If you want to check where your production allocation in chemicals or pharmaceuticals is reaching its limits, it's worth taking a look at the decision 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 at which points does the local view of individual plants prevent better overall decisions?
OPTANO helps companies answer precisely these questions in a structured manner. If you would like, we can take a look together at what a robust planning approach for your location network could look like.
Key Takeaways
- In Chemistry and Pharmaceuticals, multi-site planning is more than just distributing quantities across available capacity.
- In pharmaceuticals, approvals, regulatory requirements, and supply security are crucial.
- In chemistry, campaign logic, cleaning effort, energy consumption, and stable plant occupancy shape the decision.
- Excel creates transparency but only offers limited simultaneous evaluation of complex interactions.
- Mathematical optimization helps to explicitly manage conflicting goals and make replanning more consistent.