Automotive suppliers operate in an environment where production stability and constant change have to coexist.
OEM call-offs can shift at short notice. Components arrive late. Bottleneck resources constrain output. JIT and JIS requirements leave little room for delay, while sequence changes, setup decisions and customer priorities can affect several production areas at once.
The challenge is therefore not simply to create a production plan. It is to keep that plan executable when reality changes.
For suppliers in Germany, this challenge comes at a time when investment, profitability and production volumes are already under significant pressure. That makes better use of existing materials, capacity and production resources increasingly important.
67%
of companies surveyed by the VDA said investments originally planned for Germany had to be postponed, relocated abroad or cancelled.
Source: VDA, June 2026
54%
of the companies surveyed were reducing their workforce in Germany, while only 3% were adding jobs.
Source: VDA, June 2026
16%
below 2019 levels: German passenger car production after the first eight months of 2026.
Source: VDA, September 2026
76%
of European automotive suppliers expect profitability below 5% in 2026.
Source: CLEPA Pulse Check, March 2026
The pressure is not only cyclical. Deloitte's Supplier Risk Monitor 2025/2026 concludes that fewer than half of the suppliers analysed can currently be considered financially healthy.
In this environment, productivity increasingly depends on making better operational decisions with existing resources rather than simply adding inventory, equipment or headcount.
Automotive supply environments are typically built around highly repetitive production, tight delivery windows and close synchronization with OEM demand.
That creates a very different planning problem from engineer-to-order manufacturing. An automotive supplier may need to deal with:
The planning challenge is therefore not only to calculate demand. It is to translate changing customer requirements into a feasible production plan and then into a realistic operating sequence.
The individual steps are closely connected. A change in an OEM call-off can alter material requirements. That may shift a bottleneck, which in turn changes the optimal production sequence. Once production starts, actual progress determines whether the original schedule still remains realistic.
Lever 1
Short-term demand changes become particularly difficult when planners cannot immediately see whether the required components will actually be available.
A call-off may look feasible from a demand perspective but become impossible once supplier capacity, in-transit material, current stock or work in progress are considered.
Instead of evaluating demand and material availability separately, automotive suppliers need a common view of:
thyssenkrupp Steering provides a practical example. Its planning model incorporates customer call-offs, supplier capacity, supplier material in transit, current inventory, order progress for internally produced parts and packaging information into the same planning process.
This gives planners earlier visibility of whether customer demand can actually be supported by the available material and supply situation.
Lever 2
A detailed schedule cannot compensate for an unrealistic production plan.
Before individual work orders are sequenced, planners need to understand whether demand can be covered by available resources and materials across the relevant planning horizon.
This is where production planning and scheduling need to be clearly distinguished.
Production planning determines what should be produced, in which quantities and within which capacity and supply constraints.
Factory Scheduling then determines how those requirements should be executed on individual machines, lines or resources and in which sequence.
At thyssenkrupp Steering, Resource & Supply Planning supports rolling capacity planning and load balancing across a twelve-month horizon with weekly granularity. The objective is to create a feasible and balanced Main Production Plan before moving into detailed daily scheduling.
That connection matters: if the higher-level plan already exceeds available capacity or assumes unavailable material, the scheduler is left solving a problem that cannot realistically be solved.
Lever 3
Once demand, material and capacity have been balanced, the next question is how production should actually run.
For repetitive automotive production, sequence decisions have a direct impact on usable capacity. Frequent changes between product families or variants can increase setup effort, disrupt production rhythm and reduce the time available for value-adding operations.
A realistic schedule therefore needs to consider more than due dates.
Relevant constraints can include:
thyssenkrupp Steering uses daily scheduling that considers setup matrices, EPEI logic, packaging quantities and dynamic lot-size optimization. Work orders can be bundled while still respecting handling and customer requirements.
The objective is not simply to reduce every setup. It is to create a sequence that uses available capacity effectively while still protecting customer commitments.
Lever 4
Automotive supply networks rarely depend on a single resource.
A production line may have sufficient capacity while a preceding machining operation, supplier or another plant becomes the real constraint. Local optimization can therefore produce a plan that looks efficient in one area but cannot be executed across the full production network.
Cross-plant planning helps answer questions such as:
This is another important element of the thyssenkrupp Steering project. Resource & Supply Planning is used both within individual plants and for cross-plant planning, creating a common view of capacity requirements and dependencies across the network.
The benefit is not maximum utilization everywhere. The aim is to identify constraints early enough to make a controlled decision before they become an operational delivery problem.
Lever 5
A schedule is based on assumptions. Production creates facts.
An operation may take longer than expected. A machine may stop. A quality issue can create rework. A supplier delivery may arrive later than planned. Once these changes occur, the original schedule gradually loses its connection to reality.
This is where MES becomes important.
MES provides actual information from execution such as production progress, quantities, machine status, quality events, downtime and material consumption. Factory Scheduling can use current execution information to determine whether the operating sequence still remains feasible.
The resulting loop is:
thyssenkrupp Steering already applies this principle at scheduling level: re-scheduling uses the same planning rules and model together with current order status from production and continuously updated supply and stock information.
MES can extend this loop further by providing actual shopfloor data directly from production execution.
The same closed-loop principle can also be seen at Richel. By connecting MES functionality with Factory Scheduling, the company connects production monitoring with capacity-based scheduling, creating a more reliable basis for operational planning and faster reactions to deviations.
This is the difference between simply seeing that production has deviated and being able to understand what that deviation means for the next orders and customer commitments.
Lever 6
When a disruption occurs, the fastest reaction is not always the best reaction.
Bringing one OEM order forward may protect one delivery date but delay several others. Moving production to another resource may solve a capacity problem but create additional setups. Building additional safety stock may reduce supply risk but increase working capital.
Before changing the plan, planners should therefore understand the consequences of the available alternatives.
Example: An OEM increases a short-term call-off for a critical product family. Before changing the production sequence, planners can evaluate whether the required material is available, which resource becomes the bottleneck, which existing orders would move and what the effect would be on other delivery commitments.
Scenario-based planning shifts the conversation from “Can we change the plan?” to “Which alternative creates the best overall outcome?”
DDM+ supports this decision layer by connecting demand, supply and capacity scenarios and making trade-offs visible before changes are implemented operationally.
The thyssenkrupp Steering project illustrates why isolated planning functions are not enough.
Its planning approach connects:
The result is an integrated planning philosophy that uses common restrictions and master data from mid-term planning down to short-term scheduling.
That is the central principle automotive suppliers can take from the example: planning stability does not come from freezing the plan. It comes from connecting the decisions that create the plan with the actual conditions under which it has to be executed.
Automotive suppliers do not need another isolated planning layer.
They need a connected process in which OEM demand, supply constraints and available capacity create a feasible plan; detailed scheduling translates that plan into an executable production sequence; and actual production information feeds back into the next decision.
The individual technologies matter, but the greater value comes from connecting them.
When shortages become visible earlier, schedules reflect real constraints and shopfloor deviations return quickly to planning, teams gain more time to make controlled decisions before a problem becomes a missed delivery.