Aggregate Planning, S&OP, and Resource Coordination

Introduction

Capacity planning is not an isolated decision about machines, labor, or floor space. In practice, an organization must coordinate its available resources with uncertain demand, inventory policies, workforce decisions, materials, production schedules, and commercial commitments. Aggregate planning provides the medium-term bridge between strategic capacity decisions and detailed operational schedules. Sales and operations planning (S&OP) provides the cross-functional governance process through which this bridge is built and maintained.

The central managerial problem is one of balance. Excess capacity creates idle resources and financial burden; insufficient capacity causes late deliveries, overtime, expediting, lost sales, and employee stress. Inventory can absorb demand variation, but it ties up capital and may become obsolete. Workforce flexibility can reduce inventory, but hiring, training, layoffs, subcontracting, and temporary labor involve cost and ethical considerations. A sound planning system therefore coordinates several levers rather than optimizing any single function in isolation.

This chapter examines aggregate planning, S&OP, workforce and inventory coordination, master production scheduling (MPS), material requirements planning (MRP), and resource feasibility. It also considers quantitative planning models, implementation challenges, digital tools, and managerial governance.

Learning Objectives

By the end of this chapter, the reader should be able to:

1. Explain the role of aggregate planning within the hierarchy of operations planning.
2. Distinguish level, chase, and hybrid aggregate-planning strategies.
3. Formulate and interpret a basic aggregate-planning model.
4. Explain how S&OP integrates sales, operations, finance, procurement, and capacity decisions.
5. Coordinate workforce, inventory, MPS, MRP, and rough-cut capacity planning.
6. Evaluate planning alternatives using cost, service, risk, and strategic criteria.
7. Diagnose common sources of planning instability and recommend governance practices.

1. The Planning Hierarchy

Operations planning is normally organized across time horizons. Strategic planning addresses facilities, technology, sourcing architecture, and long-term capacity. Tactical planning addresses aggregate output, workforce levels, inventory targets, and supplier commitments over approximately 3–24 months. Operational planning translates those decisions into product-family schedules, material orders, sequencing, and dispatching.

A simplified hierarchy is:

Figure: The planning hierarchy links strategic capacity with detailed execution.

The hierarchy is not strictly one-way. Detailed constraints can invalidate an aggregate plan, and actual sales, supplier performance, and production yields feed back into the next S&OP cycle. The hierarchy is therefore best understood as a coordinated feedback system.

Aggregate versus detailed planning

Aggregate planning uses product families, labor-hours, machine-hours, or standard units rather than individual stock-keeping units (SKUs). Its purpose is to determine feasible overall production and resource patterns. The MPS then disaggregates the plan into specific end items and time buckets. MRP converts the MPS into component requirements, planned orders, and purchase or production releases.

The aggregate plan should be sufficiently detailed to expose capacity and financial consequences, but sufficiently aggregated to remain stable and manageable. Planning at SKU level too early often creates nervousness: minor forecast changes cause frequent rescheduling, material changes, and labor disruption.

2. Aggregate Planning Concepts and Strategies

An aggregate plan typically covers a monthly or weekly horizon. Inputs include forecast demand, opening inventory, current workforce, production rates, labor and subcontracting costs, inventory costs, backlog penalties, capacity limits, and policy constraints.

A plan uses several decision levers:

• Production rate: regular-time output, overtime, or subcontracted output.
• Workforce level: hiring, training, reassignment, temporary labor, and separation.
• Inventory: building stock in advance or using safety stock.
• Backlog or lost sales: postponing fulfillment, subject to service policy.
• Capacity timing: adding shifts, equipment, or external supply.

Level strategy

A level strategy keeps workforce and production relatively stable while inventory or backlog absorbs demand variation. It supports stable employment and predictable operations, but may produce high inventory, obsolescence, or customer waiting.

Chase strategy

A chase strategy adjusts production or workforce to follow demand. It reduces finished-goods inventory but may generate hiring, training, overtime, layoff, quality, and morale costs. It is more feasible where labor is flexible, products are standardized, and capacity can be changed quickly.

Hybrid strategy

Most organizations use a hybrid strategy. They may maintain a core workforce, use overtime within limits, hold strategic inventory, employ temporary labor, and subcontract selected operations. The best choice depends not only on nominal cost but also on flexibility, resilience, quality, regulatory obligations, and strategic capability.

Relevant cost categories

A planning comparison commonly includes:

• regular production cost;
• overtime cost;
• hiring and training cost;
• separation cost;
• subcontracting cost;
• inventory holding cost;
• shortage, backorder, or lost-margin cost;
• setup and changeover cost;
• transportation and expediting cost.

Fixed corporate overhead should not automatically be included in a tactical comparison if it does not change with the decision. Conversely, capacity acquisition, employee benefits, quality failures, and working-capital effects should not be omitted merely because they are inconvenient to quantify.

3. A Basic Aggregate-Planning Model

Let periods be indexed by t = 1, 2, ..., T. A linear planning model can be written as follows.

Here:

• Pₜ = regular-time production in period t;
• Oₜ = overtime production;
• Sₜ = subcontracted production;
• Iₜ = ending inventory;
• Bₜ = ending backlog;
• Hireₜ and Fireₜ = workers hired and separated;
• cₜ, oₜ, sₜ, hₜ, bₜ, Hₜ, Fₜ = corresponding unit costs;
• Z = total relevant planning cost.

The inventory-flow balance is:

where Dₜ is demand in period t. This equation assumes that production and demand are expressed in common units and that inventory and backlog are measured at the same point in the period. It permits either inventory or backlog, but not both simultaneously, if an additional logical restriction is imposed. Without that restriction, the model could mathematically carry positive inventory and backlog at the same time, which is usually operationally nonsensical.

If each worker produces r units per period and Wₜ workers are available, regular capacity can be represented by:

Workforce balance is:

If overtime is limited to \bar{Oₜ} units, then 0 ≤ Oₜ ≤ \bar{Oₜ}. Non-negativity constraints apply to production, inventory, backlog, hiring, and separation variables. Additional constraints may represent minimum workforce, labor agreements, warehouse capacity, supplier limits, safety-stock requirements, or minimum production runs.

This model is a useful decision aid, not a complete representation of reality. Linear costs imply constant unit rates, while actual operations often exhibit setup costs, breakpoints, learning effects, nonlinear overtime, and sequence-dependent capacity. Mixed-integer programming, simulation, robust optimization, or stochastic programming may therefore be required for complex environments.

Worked example: comparing two policies

An illustrative manufacturer faces demand of 800, 1,200, and 1,000 units in three months. Opening inventory is 200 units. A stable workforce can produce 1,000 units per month. Regular production costs $10 per unit, overtime costs $14, and inventory holding costs $2 per unit per month. Assume no shortages and unlimited overtime for this simple comparison.

Under a level plan, regular production is 1,000 units each month. Ending inventory is calculated from the flow balance:

• Month 1: 200 + 1,000 − 800 = 400 units.
• Month 2: 400 + 1,000 − 1,200 = 200 units.
• Month 3: 200 + 1,000 − 1,000 = 200 units.

Regular production cost is 3,000 × $10 = $30,000. If holding cost is charged on ending inventory for each month, holding cost is (400 + 200 + 200) × $2 = $1,600. Total relevant cost is therefore $31,600.

A no-inventory plan produces exactly demand net of opening inventory: 600 units in month 1, 1,200 in month 2, and 1,000 in month 3. Relative to regular capacity, month 1 uses 600 regular units and month 2 requires 200 overtime units; total production remains 2,800 units. Regular cost is 2,600 × $10 = $26,000 and overtime cost is 200 × $14 = $2,800, for a total of $28,800. In this simplified case, the chase-like plan is cheaper because the assumed inventory cost is high relative to overtime. A manager should still test quality, employee fatigue, overtime limits, and forecast error before selecting it.

4. Sales and Operations Planning

S&OP is a recurring, cross-functional process for reconciling market demand with operational supply and financial objectives. It is not merely a forecasting meeting and not merely a production meeting. Effective S&OP produces one agreed plan, with explicit assumptions, ownership, exceptions, and escalation rules.

A typical monthly cycle contains the following stages:

1. Data gathering and measure review: actual sales, forecast error, inventory, capacity, supplier performance, and financial variance are assembled.
2. Demand review: sales and marketing develop an unconstrained demand view, including promotions, new products, cannibalization, and market intelligence.
3. Supply review: operations, procurement, engineering, and logistics test capacity, labor, materials, lead times, and risks.
4. Pre-S&OP reconciliation: alternative scenarios are costed and evaluated against service, revenue, margin, and risk objectives.
5. Executive S&OP: senior leaders approve a feasible plan, resolve cross-functional trade-offs, and authorize exceptional actions.
6. Execution and feedback: the plan is translated into MPS, purchasing, staffing, and customer commitments; results feed the next cycle.

Demand and supply plans should be separated conceptually before being reconciled. A demand plan describes what customers may require; a supply plan describes what the organization can provide under stated constraints. Concealing constraints inside the forecast creates false confidence, while treating every sales estimate as a production obligation creates instability.

S&OP outputs

Useful outputs include a consensus demand plan, aggregate production plan, inventory policy, capacity gap list, supplier action plan, financial reconciliation, scenario decisions, and documented assumptions. Each output should identify the time horizon, level of aggregation, owner, revision date, and confidence level.

Governance principles

S&OP works best when:

• one numerical plan is used across functions;
• decisions are made at product-family and resource level before SKU detail;
• exceptions receive attention rather than every item receiving equal debate;
• assumptions and trade-offs are documented;
• the frozen zone and change rules are explicit;
• measures do not reward one function for damaging total system performance.

5. Coordinating Workforce, Inventory, MPS, and MRP

Workforce planning

Workforce plans must consider more than headcount. Relevant variables include skill availability, certification, shift patterns, absenteeism, learning curves, cross-training, labor law, union agreements, ergonomic limits, and succession risk. Effective capacity is often lower than theoretical capacity because breaks, maintenance, meetings, training, quality losses, and changeovers consume time.

A useful capacity measure is:

The factors must be defined carefully. If utilization allowance represents the proportion of scheduled time made available for production and efficiency represents actual performance relative to standard, both should be dimensionless proportions between 0 and 1. The product gives expected output capacity under the stated conditions; it is not a universal law and should be calibrated with historical data.

Cross-training increases flexibility but can reduce short-term productivity during learning. Workforce decisions should therefore evaluate total cost, resilience, safety, and retention rather than treating labor as a perfectly adjustable variable.

Inventory coordination

Inventory has several functions: cycle stock supports lot-sizing, safety stock protects against uncertainty, anticipation stock supports seasonal demand, decoupling stock separates processes, and pipeline inventory is in transit. Aggregate planning should specify which function is intended; otherwise inventory may increase without improving service.

For a simple continuous-review model with independent demand and replenishment lead time, a commonly used safety-stock expression is:

where SS is safety stock in units, z is the standard-normal service factor, and σ_L is the standard deviation of demand during lead time. This expression assumes that demand during lead time is approximately normal, the lead time is fixed or its variability has already been incorporated into σ_L, and the desired service measure is compatible with the chosen z. If both demand and lead time vary, a more complete variance model is required; using the simple expression without adjustment can materially understate risk.

Inventory policy must be aligned with product postponement, shelf life, replenishment time, and customer promise. High aggregate inventory can coexist with poor service if stock is in the wrong location or consists of the wrong SKUs.

Master production scheduling

The MPS converts the aggregate plan into end-item quantities by period. It uses the forecast, customer orders, opening inventory, lot sizes, lead times, safety stock, and available capacity. The MPS should be feasible for critical work centers and should respect the organization’s planning time fences.

Available-to-promise (ATP) identifies uncommitted supply that can be promised to customers. In a simplified first-period calculation:

The exact calculation depends on the organization’s ATP convention, time buckets, scheduled receipts, and whether future MPS receipts are included. ATP is therefore a promise-control mechanism, not a substitute for capacity analysis.

Material requirements planning

MRP explodes the MPS through the bill of materials, offsets requirements by lead time, and proposes planned orders. Its basic logic is deterministic and depends on accurate records. It requires reliable bills of material, inventory balances, scheduled receipts, lead times, lot-sizing rules, and engineering-change control.

MRP does not prove that labor, tooling, supplier capacity, or warehouse space is feasible. Capacity requirements planning and supplier review must validate its proposals. Poor data quality produces technically correct calculations based on false premises.

6. Resource Coordination and Capacity Feasibility

Resource coordination links demand commitments to bottlenecks. A plan may appear feasible in total hours but fail at a particular machine, skill group, supplier, or time period. Rough-cut capacity planning (RCCP) tests the MPS against key resources before detailed MRP releases are made.

For resource r in period t:

If available hours are A_r,t, the load ratio is:

A ratio above 1 indicates overload under the stated assumptions. A ratio below 1 does not guarantee feasibility because variability, sequence-dependent setups, yield losses, and material shortages may still prevent execution.

When overload occurs, managers can alter the MPS, shift production, use overtime, subcontract, cross-train, reduce setup time, add equipment, change product design, or renegotiate customer dates. The appropriate response depends on whether the overload is temporary, structural, predictable, or caused by inaccurate standards.

The theory of constraints emphasizes that system output is governed by its constraint. Increasing output at non-bottleneck resources may merely increase work-in-process. Coordination therefore requires identifying the binding constraint, subordinating other activities to it, elevating its capacity when justified, and reassessing after the constraint moves.

7. Performance Measurement and Decision Quality

A balanced performance system should include cost, service, flow, capacity, quality, people, and risk. Examples include:

• forecast error and bias;
• schedule adherence;
• on-time-in-full delivery;
• inventory turns and days of supply;
• backlog age;
• capacity utilization and bottleneck load;
• overtime and temporary labor;
• changeover time;
• supplier promise adherence;
• first-pass yield and rework;
• employee turnover and safety incidents.

The common inventory-turns measure is:

Both numerator and denominator must use compatible valuation bases. High turns are not automatically desirable if they produce stockouts, expediting, or excessive setup cost. Similarly, high utilization can conceal long queues and poor responsiveness. Measures must be interpreted as a system, not as isolated targets.

Planning quality also depends on forecast bias. Mean absolute deviation, for example, is:

where Dₜ is actual demand, Fₜ is forecast demand, and n is the number of observations. MAD measures average absolute error but does not reveal whether forecasts are consistently too high or too low; bias should therefore be monitored separately.

8. Illustrative Case: Northstar Appliances

Background

Northstar Appliances, an illustrative mid-sized manufacturer, produces three refrigerator families. Demand is seasonal, rising sharply before summer. The company uses a monthly S&OP cycle, but sales frequently inserts promotions after the supply review. The result has been overtime, late deliveries, and excessive inventory of unpopular models.

Problem

The aggregate plan showed sufficient annual capacity, yet the finishing line was overloaded in April and May. MRP released component orders based on an unstable MPS. At the same time, procurement reported shortages of a specialized compressor. Finance criticized inventory growth, while sales argued that service failures were damaging strategic accounts.

Analysis

A cross-functional team separated demand from supply. It found that:

• the unconstrained promotion forecast exceeded historical demand by 18%;
• the finishing line was the true bottleneck, not total factory hours;
• changeovers consumed 14% of available bottleneck time;
• the compressor supplier had a 10-week lead time and a 92% promise reliability;
• finished-goods inventory was high, but the required high-volume models were understocked;
• sales incentives rewarded revenue bookings rather than profitable, feasible demand.

RCCP showed that the proposed MPS required 9,600 bottleneck hours in May against 8,700 available hours, a load ratio of 1.103. The plan therefore required 900 additional hours or a reduction in scheduled demand. Because the bottleneck could safely support only 500 overtime hours, the remaining 400 hours had to be addressed through earlier production, subcontracting, promotion adjustment, or customer-date negotiation.

Approach and solution

Northstar introduced a three-scenario S&OP review: unconstrained demand, feasible supply, and financially preferred supply. The executive team approved the following actions:

1. Move selected standard models into March and April, using controlled anticipation inventory.
2. Reduce low-margin promotion volume during the bottleneck months.
3. Reserve 350 overtime hours for strategic accounts and subcontract 300 hours of a standardized operation.
4. Freeze the MPS for two weeks and require executive approval for changes inside the frozen zone.
5. Establish a compressor allocation rule based on contribution margin, customer commitment, and service risk.
6. Cross-train operators and launch a setup-reduction project on the finishing line.
7. Change sales incentives to include on-time delivery, margin, and forecast quality.

Outcome

In the next planning cycle, the May bottleneck load fell below available capacity after promotion changes and schedule smoothing. Finished-goods inventory declined in aggregate, while service for strategic models improved. The company did not eliminate uncertainty; it made assumptions visible and created a governed process for resolving trade-offs.

Learning points

The case demonstrates that annual capacity can be adequate while monthly or resource-specific capacity is inadequate. It also shows why inventory totals alone are weak evidence of performance, why MRP cannot repair an infeasible MPS, and why incentives and decision rights are part of operations planning. S&OP creates value when it changes decisions, not when it merely produces another report.

9. Challenges, Technology, and Governance

Aggregate planning is limited by uncertain demand, changing product mix, inaccurate standards, incomplete cost data, and political behavior. Forecasts are not commitments, and optimization results are not automatically managerial recommendations. A mathematically optimal plan may be unacceptable because it increases safety risk, violates labor agreements, damages supplier relationships, or undermines long-term capability.

Digital planning platforms increasingly combine ERP data, demand sensing, scenario modeling, constraint-based scheduling, and workflow approval. Machine-learning models can detect demand patterns, estimate lead-time risk, and identify anomalous capacity data. However, AI-generated forecasts and recommendations require governance: data lineage, version control, explainability appropriate to the decision, human approval, bias monitoring, cybersecurity, and clear accountability. Automation should not silently change customer promises or employment decisions.

Contemporary practice also emphasizes resilience and sustainability. Plans may include dual sourcing, strategic buffers, regional capacity, energy constraints, carbon accounting, and circular flows. These considerations can change the apparent cost ranking of level, chase, and hybrid strategies. A narrow unit-cost objective may be inferior to a slightly more expensive plan with lower disruption exposure and better environmental performance.

Best practices include:

• plan at the right level of aggregation;
• use one reconciled set of numbers;
• validate bottlenecks and suppliers, not only total capacity;
• distinguish forecast, order, allocation, and promise;
• use time fences and formal change control;
• model scenarios rather than relying on a single forecast;
• include relevant financial, service, quality, people, and risk effects;
• audit master data and planning parameters;
• review forecast bias and capacity assumptions;
• assign decision rights and escalation thresholds;
• connect S&OP outputs to MPS, MRP, procurement, and execution;
• treat employee safety, fairness, and customer transparency as planning constraints.

Chapter Summary

Aggregate planning coordinates medium-term demand, production, workforce, inventory, subcontracting, and backlog decisions. Level, chase, and hybrid strategies offer different cost, service, flexibility, and workforce consequences. A basic linear model represents production, inventory, backlog, workforce, and relevant costs, but real systems may require integer, stochastic, or simulation methods.

S&OP is the cross-functional governance process that reconciles an unconstrained demand view with feasible supply and financial objectives. Its outputs must flow into the MPS, RCCP, MRP, procurement, and execution. Workforce plans require attention to skills, learning, safety, and labor constraints. Inventory must be classified by purpose and positioned where it protects service. MPS and MRP are interdependent but do not independently guarantee resource feasibility. Bottlenecks, supplier reliability, changeovers, and time fences must be explicitly managed.

High-quality planning uses balanced measures, scenario analysis, accurate data, disciplined governance, and ethical judgment. Technology and AI can improve sensing and analysis, but accountability remains with managers. The central lesson is that capacity, demand, materials, people, and finance form one system; decisions that optimize one element can damage the whole.

Key Terms

Aggregate planning: Medium-term planning of production, workforce, inventory, and capacity at a product-family level.

Available-to-promise (ATP): Uncommitted supply that may be promised to customers under defined calculation rules.

Backlog: Customer demand accepted but not yet fulfilled.

Bottleneck: Resource whose limited capacity constrains system output.

Chase strategy: Policy that adjusts production or workforce to follow demand.

Consensus demand plan: Cross-functional agreement on expected demand and assumptions.

Frozen zone: Near-term schedule interval in which changes require special authorization.

Hybrid strategy: Aggregate-planning policy combining level, chase, inventory, overtime, or subcontracting levers.

Level strategy: Policy that maintains relatively stable production or workforce while inventory or backlog absorbs variation.

Master production schedule (MPS): Time-phased plan for producing specific end items.

Material requirements planning (MRP): System that derives component requirements and planned orders from the MPS and product structure.

Rough-cut capacity planning (RCCP): Early capacity test of an MPS against critical resources.

Safety stock: Inventory held to protect against uncertainty in demand, supply, or lead time.

Sales and operations planning (S&OP): Recurring process that reconciles demand, supply, financial, and strategic plans.

Time fence: Boundary defining how freely a schedule may be changed.

Utilization: Proportion of available or scheduled resource time used for productive work.

Workforce flexibility: Ability to vary skills, hours, staffing, or assignments in response to demand.

Review Questions

Short Answer Questions

1. What is the purpose of aggregate planning in the operations-planning hierarchy?
2. Distinguish a level strategy from a chase strategy.
3. Why can high total inventory coexist with poor customer service?
4. What is the role of RCCP in relation to the MPS?
5. Why should demand and supply plans be developed separately before reconciliation?

Long Answer Questions

1. Explain the S&OP cycle and discuss the responsibilities of sales, operations, finance, procurement, and executive management.
2. Formulate a basic aggregate-planning model, define its variables, and explain its principal assumptions and limitations.
3. Compare level, chase, and hybrid strategies using cost, service, workforce, resilience, and ethical criteria.
4. Explain how aggregate planning, MPS, MRP, and capacity planning are connected and identify where infeasibility may arise.
5. Critically evaluate the use of AI-enabled planning systems, including data quality, explainability, cybersecurity, and accountability.

Analytical / Application Questions

1. A plant has monthly demand of 900, 1,400, and 1,100 units, opening inventory of 100 units, and regular capacity of 1,100 units per month. Develop a feasible no-shortage production plan and calculate ending inventory by month. State any overtime or subcontracting requirement.
2. An MPS requires 7,200 hours at a bottleneck in a month, while regular available capacity is 6,600 hours and permitted overtime is 400 hours. Calculate the remaining capacity gap and recommend at least two operational responses.
3. A company has high aggregate inventory but frequent stockouts of premium products. Diagnose at least four possible planning causes and design an S&OP intervention that addresses demand, supply, inventory positioning, and performance measurement.

Multiple Choice Questions with Answers

Question 1

Which planning process primarily reconciles demand, supply, financial objectives, and cross-functional commitments?

A. Material requirements planning

B. Sales and operations planning

C. Dispatching

D. Preventive maintenance

Correct Answer: B. Sales and operations planning

Question 2

A level strategy generally absorbs demand variation primarily through which mechanism?

A. Inventory or backlog changes

B. Continuous workforce layoffs

C. Elimination of all safety stock

D. Immediate supplier replacement

Correct Answer: A. Inventory or backlog changes

Question 3

If demand is 1,200 units, opening inventory is 300 units, and production is 1,000 units, what is ending inventory assuming no backlog?

A. 100 units

B. 300 units

C. 500 units

D. 1,500 units

Correct Answer: B. 300 units

Question 4

What does a load ratio greater than 1 at a resource indicate?

A. The resource has unused capacity

B. The resource is overloaded under the stated assumptions

C. Inventory is necessarily obsolete

D. Demand is lower than forecast

Correct Answer: B. The resource is overloaded under the stated assumptions

Question 5

Which system explodes an end-item schedule into component requirements?

A. MRP

B. S&OP

C. RCCP

D. ABC analysis

Correct Answer: A. MRP

Question 6

In the simple safety-stock expression SS = zσ_L, what does z represent?

A. The production rate

B. The standard-normal service factor

C. The replenishment quantity

D. The number of suppliers

Correct Answer: B. The standard-normal service factor

Question 7

A major limitation of MRP is that it does not by itself prove feasibility of which factor?

A. The bill of materials structure

B. The existence of a forecast

C. Labor, tooling, supplier, or work-center capacity

D. The time-phased nature of requirements

Correct Answer: C. Labor, tooling, supplier, or work-center capacity

Question 8

A bottleneck is best defined as a resource that:

A. Has the lowest purchase price

B. Constrains system output because of limited capacity

C. Always has the highest utilization in every period

D. Stores finished goods

Correct Answer: B. Constrains system output because of limited capacity

Question 9

If regular capacity is 6,600 hours, overtime is limited to 400 hours, and required load is 7,200 hours, what gap remains after using all permitted overtime?

A. 200 hours

B. 400 hours

C. 600 hours

D. 1,000 hours

Correct Answer: A. 200 hours

Question 10

Why are time fences used in production planning?

A. To define how freely near-term schedules may be changed

B. To eliminate all demand uncertainty

C. To convert inventory into cash

D. To guarantee supplier quality

Correct Answer: A. To define how freely near-term schedules may be changed