When the production plan tips over
Why new planning in pharma and chemicals needs more than Excel
Monday morning, 8:15 am. A line is not available as planned, a preliminary product arrives later than announced, and at the same time demand for an important product picks up noticeably. The production plan is therefore not worthless. But it becomes uncertain at precisely the moment when decisions need to be made quickly. In such situations, many companies still react with spreadsheets, empirical knowledge and a series of manual adjustments. This works as long as individual parameters can be shifted in isolation. In the reality of production planning, however, this logic falls short. This is because demand, capacities, material availability, sequences and priorities do not change one after the other, but simultaneously.
In pharmaceuticals and chemicals in particular, this becomes a serious planning problem. One industry is characterized by high regulatory and quality-related requirements, the other by tight profitability limits, volatile costs and complex production relationships. In both cases, if you only react to changes locally, you lose time at the very time when reliable new planning is most important.
„If one parameter changes, the logic of the entire plan often has to be re-examined.“
When something changes, it's not just a value that slips
A production plan can easily be read as an overview of quantities and deadlines. It becomes more difficult when the underlying conditions change. Then it is no longer just a matter of updating individual figures. A new decision must be made as to which orders have priority, which capacities are to be used differently, which postponements are still acceptable and what consequences this will have elsewhere.
This is precisely where the limits of Excel-based planning become apparent. Tables can make many things visible. What they cannot reliably achieve is the consistent re-evaluation of interlinked decisions under several restrictions at the same time. Those who make manual adjustments therefore often solve a local problem first and postpone the next difficulty to the following period, to another line or to another product.
„Even a single failure can shift priorities, quantities and availability across the entire plan.“
In pharma, a deviation quickly becomes a problem for supply
This dynamic is particularly pronounced in the pharmaceutical industry. Production problems, quality deviations, raw material bottlenecks or jumps in demand often have a direct impact on availability and supply. Added to this are release times, material-specific restrictions, fixed process steps and the need to remain within reliable framework conditions even under time pressure.
New planning is therefore not simply a question of higher computing speed. It must result in decisions that are operationally realistic, can be prioritized and can actually be implemented under the given conditions. If a batch fails or a line is not available at short notice, it is not enough to redistribute quantities. The real question is which alternative makes the most sense overall under the remaining restrictions.
„A modified plan is only good if it also holds up in terms of capacity utilization, conversion and costs.“
In the chemical industry, new planning often determines both stability and profitability
Even in the chemical industry, the situation is rarely stable enough for rigid planning. Weak demand, high energy costs, economical batch sizes, campaign-dependent production sequences and limited flexibility of individual plants mean that short-term changes can be expensive. A shift that looks sensible at first glance can result in high conversion costs, poorer capacity utilization or additional inventory risks elsewhere.
The challenge is therefore different from that in pharmaceuticals, but no less so. While the focus there is on security of supply and permissible reactivity, in the chemical industry it is often more a question of how a changed plan can be restructured in an economically and operationally viable way without losing the stability of production. Particularly in campaign-driven production, the value of a new plan is often determined by whether additional changeovers, energy use and capacity utilization can be evaluated together instead of one after the other.
„The difference lies not in faster calculation, but in a better comparison of options for action.“
Good new planning not only replaces figures, but also reassesses options for action
The decisive difference lies in the method. Good replanning does not simply replace an old figure with a new one. When demand, capacity or material availability change, it is not just quantities that need to be adjusted. A new decision must be made as to which orders have priority, which systems are used and how, and what consequences this has for service, costs and stability.
This sounds technical at first, but is very concrete in operational terms. The decisive factor is how a change affects priorities, line occupancy, sequences, capacity utilization and service. Only when these interrelationships are considered together can a plan be created that is not only quickly adapted, but also sustainable.
Hectic corrections become a comprehensible consideration
This is precisely where the strength of mathematical optimization lies. It does not provide arbitrary suggestions, but evaluates options for action along clear objectives and restrictions. This makes it clear which decision creates the best balance between competing requirements.
Such conflicting objectives are the rule in production planning. Serving a prioritized product faster can trigger additional changeovers. A capacity shift can improve service but increase costs. Alternative procurement can stabilize supply, but at the same time burden margins or complexity. Systematic replanning not only makes these conflicting objectives more transparent, but also puts them into a form that is repeatable and comprehensible.
Further interesting content
Example:
What happens if a bottleneck is not treated in isolation
Suppose a critical active ingredient arrives late, while demand for an important product increases at the same time. A chain of local corrections then often begins in Excel: quantities are shifted, slots are reallocated, priorities are reassigned. But the crucial question often remains unanswered: What are the overall consequences of this reaction for the rest of the production plan?
Instead, a model that systematically evaluates planning alternatives examines which combination of postponement, reprioritization, capacity utilization and possible alternatives results in the most viable plan under the given conditions. This is not a theoretical luxury. It is the difference between hectic readjustment and a resilient decision under time pressure.
„Value is created when changes can be incorporated quickly, alternatives compared and decisions clearly justified.“
When replanning becomes part of production control
The benefit of a specialized planning system lies not only in faster calculations. It is crucial that changes in demand, capacity or procurement options can be adopted as new planning requirements, that alternatives can be compared consistently and that decisions can be justified in a comprehensible and repeatable manner.
This is particularly valuable for pharmaceuticals, where decisions often have to be made under great time pressure and within tight operational constraints. For chemicals, the advantage is strong where the economic impact of changes to plans should not only become apparent after the fact, but must be taken into account when selecting the alternative. In projects, we have already achieved savings of up to 5 % and more This is seen as an advantage when companies reorganize their production planning in a more structured and consistent manner in response to changing conditions.
From personal table logic to resilient planning
Another advantage lies in the reproducibility. In many companies, planning knowledge has grown historically in individual files, abbreviations and personal experience rules. This can work in day-to-day business. However, it becomes fragile as soon as scenarios need to be compared quickly, decisions need to be justified or different stakeholders need to be brought into line with a common view.
OPTANO addresses precisely this point: not with the promise of a simple standard answer, but with the ability to evaluate complex production decisions in a consistent and repeatable manner. This is particularly relevant when the situation is unstable and the quality of new planning determines delivery capability, cost-effectiveness or the operational burden.
An initial plan is important. However, production planning becomes really crucial at the moment when the original plan no longer fits the current conditions. This is when a quick reaction is separated from a resilient decision.
Planning that can quickly run through and properly evaluate various developments is therefore not an extra for exceptional cases. Especially in pharmaceuticals, but also in chemistry, this creates a clear advantage: away from local table maintenance and towards comprehensible decisions under real restrictions.
If you want to check how your team can make reliable production decisions more quickly in the event of changes in demand, bottlenecks or capacity shortfalls, it is worth taking a closer look at the rules that are used today to prioritize and reschedule. OPTANO supports companies in transforming this logic into a form in which scenarios not only become visible, but also lead to reliable decisions.
Key Takeaways
- Rescheduling becomes relevant when production conditions change faster than manual planning can cleanly follow.
- In pharma, the benefits are particularly high because quality, release and supply risks are closely linked to decisions.
- In the chemical industry, added value is created above all where modified plans have to be economically and operationally viable at the same time.
- Excel can map planning information, but has structural limits when it comes to linked decisions.
- Mathematical optimization helps to systematically and reproducibly evaluate conflicting objectives under restrictions.
- The real progress lies not in faster computing, but in better decisions under changed conditions.