Aggregate Planning: Level, Chase or a Mixed Strategy?

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Estimated reading time: 11 minutes

Aggregate planning sets production volumes, capacity commitments and expected inventory or backlog for product families over the medium term, commonly around 3–18 months. It answers a practical question: when demand rises and falls, should you keep production steady, change output to follow demand, or combine the two?

The variation has to go somewhere. A steady production rate can build stock before a peak. Matching output to demand avoids that buildup but requires capacity you can actually increase and reduce. A mixed strategy shares the burden between inventory and flexible production.

The right choice protects deliveries without paying for stock you cannot use or capacity you cannot provide. SkyPlanner helps carry that choice into production: its scheduling AI, Arcturus, coordinates the orders behind the plan with your workstations, shifts, operators and priorities. You spend less time reconciling a monthly volume target with separate machine queues.

What an aggregate plan decides

An aggregate plan works above the individual job. Instead of assigning Tuesday’s operations to machines, it sets the production and resource policy for a family of products: how much to make in each period, what stock to carry and when extra capacity will be needed.

Group products whose production requirements make a useful comparison. Units can work for a family of similar products. Where sizes or routes differ substantially, use a meaningful common measure such as standard hours on the relevant resource. Adding a small component and a complex assembly as two interchangeable pieces can conceal the capacity problem.

Monthly periods are useful for seeing seasonal changes, but the horizon should cover the decisions you need to make. Training people, securing supplier capacity and preparing material for a peak require more notice than changing tomorrow’s job sequence.

Aggregate planning also connects several planning activities:

• S&OP brings demand, supply and financial decisions into an agreed business plan. The aggregate production policy can be developed and approved through that process.
• The master production schedule (MPS) translates the broader direction into selected-product quantities and availability dates.
• Rough-cut capacity planning (RCCP) checks whether critical resources can support the proposed master schedule.
• Detailed scheduling assigns the resulting operations to available resource time.

The levels inform each other. If the order schedule repeatedly needs more overtime than the aggregate plan allowed, revisit the policy rather than asking the shop to absorb the difference indefinitely.

Level, chase and mixed aggregate planning strategies

The main difference is what you allow to change when demand changes.

Strategy	What stays relatively stable	What absorbs demand variation	Main trade-off
Level	Production rate	Inventory, or explicitly accepted backlog	Stable operations versus stock cost and demand risk
Chase	Production closely matches each period’s demand	Working hours, staffing or other usable capacity	Less stock versus the cost and difficulty of changing capacity
Mixed	A chosen base of production, with controlled changes	A combination of inventory and capacity flexibility	A more tailored response, with several limits to coordinate

Level strategy: make ahead of the peak

A level strategy keeps the production rate steady while demand varies. During quieter periods, output above demand becomes inventory; during the peak, that inventory supplements current production.

This can suit repeatable products with dependable demand, manageable storage costs and a workforce whose skills are valuable to retain. It gives purchasing and production a more stable workload and reduces the need to expand capacity sharply for a short season.

The price is earlier spending and inventory risk. Material, labor and storage are committed before the sale. If demand falls or a specification changes, the stock may no longer be useful. Perishable products and highly customized orders leave much less room for this approach.

Where early production is impossible, a steady rate may instead create a backlog during peaks. That is a service decision requiring acceptable lead times, not a free substitute for inventory. Also distinguish a stable workforce from a constant output rate: changing overtime changes output even if the number of employees stays the same.

Chase strategy: adjust output to demand

A chase strategy raises and lowers production to meet demand in each period. Capacity adjustments can include overtime, additional shifts, temporary staff or subcontracting. Hiring and layoffs are possible levers, but they are not the only way to chase demand.

The attraction is lower inventory exposure. You avoid making large quantities solely because a later forecast says they will sell. This matters when products cannot be stocked economically or customer specifications are not known far ahead.

The difficulty is providing the extra output when needed. Skilled operators may take months to recruit or train. An additional shift needs people, machines, materials and support functions, not just a higher number in the capacity plan. Suppliers may face the same seasonal peak as you.

Treat flexibility as a resource with a limit and a lead time. A chase plan that requires unavailable overtime is not a low-inventory solution; it is an unfulfilled demand plan.

Mixed strategy: decide how much each buffer should do

A mixed strategy combines a stable production base with selected changes in output. You might build some stock before a peak, then cover the remaining increase with approved overtime or subcontracting.

It is useful when neither extreme fits. Storage may be limited, while the workforce cannot expand enough to meet the whole peak. The decision becomes more specific: how much inventory is worth carrying, and how much additional production can you reliably arrange?

Mixed does not automatically mean cheapest. It means you can compare a more suitable combination against the same demand, service expectations and ending-stock target as the alternatives.

Aggregate planning example: where does the peak go?

Imagine a manufacturer planning a family of standard housings. Demand is 800 units in Period 1, 1,200 in Period 2 and 1,600 in Period 3. The periods have equal working time, and regular capacity is 1,200 units per period.

Assume zero starting inventory, no scrap, no backlog and a zero ending-inventory target after Period 3. The products can be stored. Each period’s production is assumed available in time for the demand it covers; this simplified comparison does not establish daily delivery dates.

All three policies produce the same total of 3,600 units:

Policy	Production in Periods 1 / 2 / 3	Ending inventory in Periods 1 / 2 / 3	What must be provided
Level	1,200 / 1,200 / 1,200	400 / 400 / 0	Storage and funding for the prebuilt stock
Chase	800 / 1,200 / 1,600	0 / 0 / 0	Capacity for 400 units above regular output in Period 3
Mixed	1,000 / 1,200 / 1,400	200 / 200 / 0	Some inventory plus capacity for 200 extra units in Period 3

The inventory calculation is:

Ending inventory = beginning inventory + production − demand.

For the level policy, Period 1 ends with 0 + 1,200 − 800 = 400 units. Period 2 leaves that balance unchanged. In Period 3, the 400 stored units supplement 1,200 newly produced units to meet demand of 1,600.

The mixed policy builds a 200-unit buffer instead. In Period 3, that stock plus production of 1,400 meets the same demand. It halves both the maximum period-end inventory and the peak extra-output requirement compared with the respective pure alternatives.

Now suppose management permits no more than 200 units of period-end stock, and production can provide only 200 units of additional output in Period 3. The level option exceeds the inventory limit; the chase option exceeds the extra-capacity limit. The mixed option fits both limits in this model.

That makes it a feasible candidate, not a proven cost optimum. You still need to price the alternatives and check the actual product mix and timing. If the peak disappears, even the mixed policy leaves stock exposure. If demand arrives early in Period 3, the extra production must be ready early enough.

How to choose a workable policy

Start with one consistent demand and stock baseline. Reconcile firm orders with the remaining forecast so the same requirement is not counted twice. Record usable starting stock, existing production commitments and the ending inventory or backlog you will accept.

Then compare feasible alternatives rather than three attractive totals:

1. Establish the limits first. Check shelf life, storage, working capital, approved overtime, available skills, supplier lead times and customer tolerance for waiting. Exclude options that rely on resources you cannot secure.

2. Compare the full relevant cost. Include regular production, paid idle time, overtime, inventory carrying costs, hiring or training, subcontracting and any accepted late-delivery consequences. Use the same cost basis across options; do not count base wages twice when an overtime rate already includes them.

3. Test a different demand outcome. Ask what happens if the peak is lower, higher or earlier. A plan that is slightly cheaper under one forecast may leave much more unsold stock or an unmanageable capacity shortage when demand changes.

4. Approve actions, not just quantities. Name who will secure the extra shift, buy material or reserve supplier capacity, and by when. Review the plan against actual demand and output, with clear triggers for changing it.

For make-to-order production, the useful aggregate measure may be workload and order backlog rather than finished stock. You can plan capacity before knowing every final item, but you cannot prebuild customer-specific products whose requirements are still unknown.

Choose the least costly workable response consistent with your service commitments and risk tolerance. Then check that its jobs can run in the sequence those commitments require.

Turn the chosen policy into scheduled work with SkyPlanner

The mixed example calls for 200 extra units in Period 3. That number becomes useful only when the extra output has a route through the factory. More machining hours will not help if finishing is already full or material arrives after the needed production window.

Use SkyPlanner APS to connect the approved production policy with that work. Keep demand forecasting and the family-level inventory and capacity decision in your planning process; supply SkyPlanner with the production orders that implement it. This is a scheduling handoff, not an automatic conversion of a family forecast into orders.

Product process steps, durations, eligible workstations, materials and bills of materials are configured once. Each order item inherits its product’s route; its quantity and delivery date define the new requirement. Arcturus schedules the orders together, so one family’s peak does not remain isolated from the other work competing for its resources.

For the mixed policy, represent the approved extra working time in the relevant shifts and operator availability, alongside the existing orders. With material-aware scheduling enabled, recorded material availability also affects when work can start. Recalculate and follow the resulting operations through the Gantt timeline.

You can then assess the question the aggregate table cannot answer: do the housings finish when needed, and what happens to the other orders? If a constraint prevents the target, decide whether to change priorities, provide different capacity or revise the production commitment. Arcturus handles the scheduling calculation while you control those decisions.

SkyPlanner integrates with any ERP or MES through its open REST API. Your existing business system can remain in place while SkyPlanner reduces the manual work of fitting the approved volumes into production and keeping the schedule aligned when circumstances change.

What shift visibility changed at Fredman Operations

Fredman Operations, a Finnish manufacturer of kitchen and packaging products, needed clearer shift-by-shift capacity visibility as order volumes grew. Previously, work cards moved manually between systems, and the planner prioritized jobs without precise visibility into machine availability.

Its SkyPlanner implementation connected L7 and LTR and brought machines, free and booked capacity, and job progress into a shared Gantt view. Fredman reports less need for overtime and faster responses to schedule changes.

That visibility gives production a stronger basis for responding to a demand peak: review the work and capacity together before treating more overtime as the only answer.

Bring your next demand peak into the plan

Before approving the next seasonal target, ask where the variation will go. If the answer is inventory, check that the products are worth making early. If it is extra capacity, secure the people and resources. If it is both, make the limits explicit.

Then use SkyPlanner to connect those decisions to the orders your team must complete. Book a demo with one product family’s demand profile, its approved production quantities and the shifts intended to deliver them. That gives you a concrete basis for seeing how Arcturus and the Gantt schedule can reduce the work between the monthly plan and the factory floor. To explore the scheduling workflow first, start a trial with demo data.