Sales and Operations Planning, Aggregate Planning and Scheduling

Introduction

Production and operations management is concerned not only with producing efficiently, but with producing the right output, at the right time, in the right quantity, and at an economically justified cost. Demand is usually expressed in market terms—orders, forecasts, service promises and revenue targets—whereas supply is constrained by labour, equipment, materials, technology, cash and time. Sales and operations planning (S&OP), aggregate planning and scheduling provide an integrated hierarchy for reconciling these perspectives.

S&OP connects commercial strategy with operational capability. Aggregate planning translates this agreement into medium-term decisions concerning production rates, workforce levels, inventory, overtime, subcontracting and backlogs. The master production schedule (MPS) then disaggregates aggregate plans into specific end items and time periods. Detailed scheduling assigns jobs to machines and people, determines sequence and loading, and manages finite capacity. Yield and revenue management add a market-facing dimension by deciding which demand to accept when capacity is scarce.

These decisions are interdependent. A sales promise that ignores capacity creates expediting, poor service and employee stress. A production plan that ignores market priorities creates excess inventory or missed opportunities. Effective operations therefore require a coordinated planning system rather than isolated departmental forecasts.

Learning Objectives

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

1. Explain the purpose, process and governance of S&OP.
2. Develop and evaluate aggregate plans using workforce, inventory, overtime, backlog and outsourcing alternatives.
3. Distinguish aggregate planning from master scheduling and detailed scheduling.
4. Apply loading, sequencing and finite-capacity concepts to operational decisions.
5. Explain yield and revenue management in capacity-constrained environments.
6. Evaluate the strategic, ethical and technological implications of integrated planning.

1. The Hierarchy of Operations Planning

Planning horizons are commonly divided into three levels:

The exact horizons vary by industry. An airline may schedule seats months ahead but adjust assignments daily; a process manufacturer may plan continuously because production is relatively stable. The essential principle is hierarchical consistency: detailed plans should be feasible under tactical plans, and tactical plans should support strategic objectives.

S&OP is a cross-functional decision process. Sales and marketing contribute demand information, product launches and promotions. Operations contributes capacity, lead times and constraints. Finance tests profitability and cash implications. Procurement, logistics, engineering and human resources identify dependencies. Senior management resolves conflicts and approves a single operating plan.

The S&OP cycle

A mature monthly S&OP cycle generally includes:

1. Data and statistical review: actual demand, forecast accuracy, inventory, orders, capacity and supply performance are assembled.
2. Demand review: the commercial team prepares an unconstrained demand plan, including promotions, new products, customer intelligence and risks.
3. Supply review: operations tests whether the demand plan can be met with available capacity, materials, labour and suppliers.
4. Reconciliation: alternative scenarios are evaluated, such as overtime, inventory build, outsourcing, price changes or demand shaping.
5. Executive review: senior managers select a plan, assign accountability and approve exceptions.
6. Execution and learning: the plan is communicated, performance is tracked and assumptions are updated in the next cycle.

S&OP is not merely a forecasting meeting. It is a decision-rights system. It establishes one set of numbers, explicit assumptions and a disciplined method for resolving trade-offs.

Demand and supply plans

A demand plan represents expected requirements, while a supply plan represents feasible output. A basic inventory balance is:

where I_t is ending inventory in period t, P_t is internal production, R_t is receipts from suppliers or subcontractors, D_t is demand fulfilled in the period, and B_t represents units removed from inventory for backlog fulfilment or other approved commitments. In a simpler formulation where all demand is fulfilled immediately, B_t is omitted. Units must be consistent, such as units per month. The relationship assumes that shrinkage, spoilage and quality losses are either negligible or incorporated into the relevant terms.

A planning gap can be expressed as:

where G_t is the shortfall in period t, D_t is required demand and C_t is feasible supply capacity. A positive gap requires action; a negative value indicates potential idle capacity or inventory accumulation. This identity is descriptive, not a decision rule: management must determine how the gap should be addressed.

2. Aggregate Planning

Aggregate planning determines medium-term production and resource levels for product families rather than individual stock-keeping units. A product family shares facilities, labour or materials sufficiently for planning purposes. The plan may be expressed in tonnes, standard hours, cases, machine hours or monetary value.

The central choices are:

• regular-time production;
• overtime or additional shifts;
• hiring and layoffs;
• inventory accumulation or depletion;
• backorders or planned backlog;
• temporary labour;
• subcontracting or outsourcing;
• lost sales or demand shaping.

The best plan is not necessarily the one with the lowest direct manufacturing cost. It must also consider service, resilience, quality, workforce stability, cash, risk and strategic capability.

Chase and level strategies

A chase strategy varies production or workforce to follow demand. It can minimize inventory, but frequent hiring, layoffs, training and schedule changes may reduce morale and productivity.

A level strategy maintains a relatively stable production rate and uses inventory or backlog to absorb demand variation. It supports workforce stability but may create carrying costs, obsolescence, stockouts or excessive backlogs.

Most organizations use a mixed strategy, combining stable core capacity with overtime, temporary labour, inventory, subcontracting and limited backlog. The appropriate mix depends on demand volatility, product perishability, labour-market conditions, customer tolerance and capacity flexibility.

Aggregate planning cost model

A commonly used planning objective is:

Here, T is the number of planning periods; P_t^r, P_t^o and P_t^s are regular-time, overtime and subcontracted production; I_t^+ is positive ending inventory; B_t^+ is positive backlog; H_t and L_t are hires and layoffs; and f_t represents fixed or other period costs. The coefficients c, h, p, k and l are unit costs. The model is applicable when costs and capacities can reasonably be represented in a linear or piecewise-linear form.

The objective must be accompanied by constraints. A typical workforce relationship is:

where W_t is the workforce at the end of period t. Production capacity may be represented as:

where a_t is regular-time output per worker in period t. If workers provide hours rather than units, a_t should be calculated from available hours, productive efficiency and standard time per unit. Capacity constraints should also include machines, materials and supplier limits; labour alone is rarely sufficient.

A service requirement may be written as:

where B^max is the maximum permitted backlog. For perishable products, inventory may require an upper bound or an age-based model rather than a simple aggregate balance.

Worked example: comparing two aggregate plans

Illustrative example. A firm faces monthly demand of 800, 1,200 and 1,000 units over three months. Initial inventory is 100 units and the desired ending inventory is zero. One worker produces 100 units per month. The firm begins with 10 workers. Regular production costs CU 20 per unit, inventory carrying cost is CU 2 per unit per month, hiring costs CU 500 per worker and layoff costs CU 700 per worker. Ignore overtime, subcontracting and backorders.

Under a chase plan, available units after initial inventory are 700, 1,200 and 1,000. A feasible workforce sequence is 7, 12 and 10 workers. The workforce changes are: lay off 3 workers, hire 5, then lay off 2. Regular production is 700, 1,200 and 1,000 units, totalling 2,900 units. Production cost is:

2,900 × CU 20 = CU 58,000.

Adjustment cost is:

3 × CU 700 + 5 × CU 500 + 2 × CU 700 = CU 6,400.

Total estimated cost is CU 64,400, assuming no ending inventory and no inventory charge.

Under a level plan, 10 workers produce 1,000 units each month. Inventory evolves as follows:

Total production remains 3,000 units, costing 3,000 × CU 20 = CU 60,000. If inventory is charged at CU 2 per unit per month on ending inventory, the carrying cost is (300 + 100 + 100) × CU 2 = CU 1,000. No workforce adjustment is required, so total cost is CU 61,000. In this simplified case the level plan is cheaper by CU 3,400 and leaves 100 units of ending inventory. If the desired ending inventory must be zero, the final month’s production can be reduced to 900 units, subject to the workforce and minimum-run assumptions.

The example illustrates why a cost-minimizing answer is conditional. It excludes training effects, quality risks, labour laws, overtime, demand uncertainty and the opportunity cost of inventory. A manager should therefore use the model for structured comparison, not as a substitute for judgement.

3. Workforce, Inventory and Outsourcing Decisions

Workforce flexibility

Hiring and layoffs provide capacity flexibility but have economic and social consequences. Relevant costs include recruitment, screening, training, severance, productivity loss during learning, legal compliance and reputational effects. A firm may protect a core workforce and use temporary or cross-trained employees for variability. Cross-training increases flexibility, although it can reduce specialization and may require certification.

Overtime and shifts

Overtime is useful for temporary peaks but can create fatigue, accidents, absenteeism, maintenance problems and quality deterioration. It should not be treated as unlimited capacity. A proper plan specifies maximum overtime hours, premium rates, rest requirements and skill constraints.

Inventory and backlog

Inventory decouples production from demand and protects service against uncertainty. Its costs include capital, storage, insurance, handling, damage, obsolescence and shrinkage. Backlogs may be acceptable in engineer-to-order or industrial markets, but they can cause cancellations and damage customer trust in consumer markets.

Outsourcing and subcontracting

Outsourcing can provide capacity, specialist expertise and geographic flexibility. However, a comparison based only on supplier price is incomplete. The relevant total cost may include transport, inspection, supplier development, transaction costs, intellectual-property exposure, minimum order quantities, switching costs and failure risk. Strategic capabilities, critical technologies and safety-sensitive activities may warrant internal control even when external unit cost is lower.

A make-or-buy decision should evaluate total landed cost and risk over the relevant horizon. It should also consider whether the internal capacity released by outsourcing can be used productively; otherwise, an avoidable fixed cost may remain.

4. Master Production Scheduling and Material Coordination

The MPS converts an aggregate family plan into a time-phased statement of specific end items. It answers: which product, how many units and in which period? It is not the same as a customer order list. The MPS considers forecast demand, confirmed orders, inventory, safety stock, lot sizes, lead times, production capacity and available-to-promise commitments.

A simplified projected available balance is:

where PAB_t is projected available balance, MPS_t is scheduled receipt from the master schedule and D_t is demand during the period. If safety stock S is required, the plan should maintain PAB_t ≥ S unless an approved exception exists. The simplified formula assumes no scheduled receipts other than the MPS and no lead-time or allocation complexities.

Available-to-promise quantity for a future period is the uncommitted supply that can be promised to customers. It should not be calculated by simply subtracting current orders from total annual production; timing, material availability and capacity must be respected.

The MPS feeds material requirements planning (MRP). MRP explodes the bill of materials, offsets requirements by lead times and proposes planned orders. Errors in the MPS propagate through every component level, so schedule stability and data accuracy are essential.

5. Scheduling: Loading, Sequencing and Dispatching

Scheduling allocates scarce resources over time. It differs from planning in its shorter horizon and greater detail. A schedule identifies jobs, resources, start times, completion times and priorities.

Loading

Loading assigns work to resources. It may be expressed in units, standard hours or machine time. A basic load for resource r in period t is:

where q_j is the quantity of job j and s_j,r is the standard processing time per unit of that job on resource r. If Load_r,t exceeds available capacity, the schedule is infeasible unless work is moved, overtime is approved, processing is split or capacity is added.

Sequencing rules

Common priority rules include:

• First-come, first-served (FCFS): perceived as fair and simple.
• Shortest processing time (SPT): often reduces average flow time, but may delay long jobs.
• Earliest due date (EDD): prioritizes the nearest due date and is useful for lateness control.
• Critical ratio:

where d_j is the due date of job j, t is the current time and p_j is remaining processing time. A lower ratio indicates greater urgency. The ratio assumes comparable time units and is meaningful only when due dates and processing estimates are reasonably reliable.

No rule dominates in every setting. SPT can improve average flow time while harming strategically important orders. EDD can reduce maximum lateness under appropriate single-machine assumptions, but setup times, release dates, rework and multiple resources complicate the result. Priority rules should therefore be aligned with customer commitments and strategic value.

Flow time and lateness

For job j, flow time is:

where C_j is completion time and r_j is release time. Lateness is:

where d_j is due date. Tardiness is the non-negative part:

These measures must not be confused. A job completed early has negative lateness but zero tardiness. Average flow time, maximum lateness, number of tardy jobs, weighted tardiness and utilization may lead to different scheduling choices.

Finite-capacity scheduling

Infinite-capacity planning assumes that required work can be placed in any period. Finite-capacity scheduling explicitly respects machine hours, labour skills, tooling, maintenance, material availability, calendars and precedence relationships. It may use constraint programming, mixed-integer optimization, simulation, dispatching heuristics or specialized scheduling systems.

A finite-capacity schedule should identify the bottleneck. In a multi-stage flow, increasing non-bottleneck capacity may not improve throughput. The theory of constraints emphasizes five actions: identify the constraint, exploit it, subordinate other activities, elevate its capacity and repeat when the constraint moves. This logic must be combined with quality and safety requirements; maximizing bottleneck utilization with defective or unsafe output is not effective performance.

6. Yield and Revenue Management

Yield management allocates limited, perishable capacity among demand segments to maximize expected contribution. It is prominent in airlines, hotels, car rental, event venues and some healthcare services. Revenue management adds pricing, booking controls and demand forecasting to this allocation problem.

The central conditions are:

1. capacity is relatively fixed in the short run;
2. demand varies by time and customer segment;
3. inventory is perishable or costly to carry;
4. customers differ in willingness to pay or booking flexibility;
5. demand can be segmented without unacceptable discrimination.

A simple two-segment decision compares a protected high-value booking with a lower-value booking. If one unit of capacity remains and a high-value customer may arrive with probability p, accepting a low-value booking at contribution r_L gives certain contribution but eliminates the high-value opportunity. A simplified protection rule accepts the low-value request only when:

where r_H is high-value contribution. This is a one-period expected-value comparison. Real revenue-management models include multiple periods, capacity classes, cancellations, no-shows, overbooking risk and network effects.

Overbooking can compensate for predictable no-shows, but it creates ethical and financial exposure if realized attendance exceeds capacity. Controls should include reliable show-up models, transparent terms, compensation policies, legal compliance and limits for safety-critical capacity.

7. Integrated Case: Meridian Appliances

Illustrative case. Meridian Appliances manufactures a family of commercial refrigeration units. Demand is seasonal, with a major hotel-equipment promotion in the second quarter. Sales proposes 4,800 units over the next six months, while the plant’s stable workforce can produce 3,900 units. The shortfall is concentrated in two promotional months. The plant has limited finished-goods storage, a bottleneck testing cell and a supplier capable of producing 600 units under subcontract.

Problem

The sales plan promises rapid delivery, but operations estimates that accepting all orders with regular time would overload testing capacity and require excessive overtime. Finance is concerned about subcontracting cost and inventory cash. Human resources opposes layoffs because skilled technicians are difficult to replace.

Analysis

The S&OP team constructs three scenarios:

The team identifies testing as the constraint rather than final assembly. Therefore, adding assembly labour alone will not deliver the promised output. It evaluates supplier capability using process audits, first-article inspection and a contractual quality agreement. It also shifts some low-complexity units to the supplier while retaining high-customization models internally.

The MPS is revised to build a controlled inventory before the promotion, with a maximum storage limit. The finite-capacity schedule reserves testing slots for high-contribution and contractually urgent orders. Sales receives an available-to-promise table rather than a blanket promise. A revenue-management rule protects bottleneck capacity for customers with stronger contribution and strategic service obligations, while avoiding arbitrary customer discrimination.

Outcome

The hybrid plan meets the commercially approved demand, maintains the skilled core workforce and prevents the testing cell from being overloaded. Its success depends on supplier quality, disciplined order promising and daily monitoring during the promotion. The plan is not automatically superior: if subcontractor defect rates rise or demand falls sharply, its apparent advantage may disappear.

Learning points

1. The true constraint must be identified before capacity is added.
2. S&OP makes trade-offs visible across functions.
3. Aggregate plans require operational disaggregation through the MPS.
4. A feasible finite-capacity schedule is more credible than an unconstrained promise.
5. Outsourcing should protect strategic capabilities and include quality governance.
6. Revenue management is an allocation mechanism, not permission to ignore fairness or contractual obligations.

8. Technology, Governance and Contemporary Issues

Enterprise resource planning systems integrate orders, inventory, bills of material, capacity and purchasing. Advanced planning and scheduling systems use optimization, heuristics and simulation to create feasible alternatives. Artificial intelligence can improve demand sensing, anomaly detection, lead-time prediction and scenario generation. However, AI forecasts can amplify biased data, hide uncertainty or recommend actions that violate labour, safety or service constraints.

Good governance requires:

• clear ownership of master data and planning assumptions;
• version control for forecasts and approved scenarios;
• human review of exceptional or high-impact recommendations;
• audit trails for overrides and customer allocations;
• cybersecurity and access control;
• explainable service and pricing policies;
• monitoring for forecast bias and systematic customer disadvantage.

Contemporary planning increasingly incorporates resilience and sustainability. Firms may evaluate dual sourcing, strategic buffers, nearshoring, carbon intensity, energy availability and disruption scenarios. A plan with minimum cost but extreme dependence on one supplier may be economically fragile. Similarly, frequent expediting may increase emissions and undermine sustainability claims.

Planning metrics should be balanced. Useful measures include forecast bias, forecast accuracy, schedule adherence, capacity utilization, on-time-in-full delivery, inventory turns, backlog age, overtime, employee turnover, supplier quality, contribution margin and carbon emissions. No single metric should be maximized in isolation. High utilization can increase waiting time and reduce responsiveness; high inventory turns can conceal stockouts; and high schedule adherence can indicate that the schedule was set unrealistically.

Challenges and Limitations

Aggregate and scheduling models simplify reality. Demand forecasts are uncertain, processing times vary, machine failures occur and human performance is not constant. Linear cost models may omit nonlinear effects such as learning curves, minimum batch sizes and congestion. Data may be inconsistent across sales, finance and operations. Plans can also fail because managers treat them as fixed commitments rather than assumptions requiring revision.

Organizational behaviour is equally important. Sales may inflate forecasts to secure capacity, operations may understate capability to protect utilization, and finance may reject resilience investments because their benefits are uncertain. Effective S&OP therefore requires transparency, shared incentives and escalation rules.

Ethically, workforce changes must comply with employment law and respect dignity. Customer prioritization should be based on transparent commercial and service principles, not protected characteristics or hidden exclusion. Capacity allocation in healthcare and other essential services requires public-interest criteria rather than simple willingness to pay. Sustainability claims should include relevant supply-chain impacts rather than only factory emissions.

Best-Practice Guidelines

1. Use one reconciled demand and supply plan.
2. Separate statistical forecasts from commercial judgement and document overrides.
3. Plan at the product-family level, then disaggregate carefully through the MPS.
4. Include material, labour, equipment, supplier and calendar constraints.
5. Compare total cost, service, risk, quality and workforce consequences.
6. Identify bottlenecks before investing in non-bottleneck capacity.
7. Use finite-capacity checks before making customer promises.
8. Treat overtime and outsourcing as constrained resources, not unlimited remedies.
9. Monitor both leading indicators and outcomes.
10. Review assumptions after major demand, supply or technology changes.

Chapter Summary

S&OP integrates demand, supply, finance and strategic priorities through a recurring cross-functional process. Aggregate planning converts this agreement into medium-term decisions about production, workforce, inventory, backlog, overtime and outsourcing. Chase, level and mixed strategies represent different approaches to absorbing demand variability, and their evaluation requires both quantitative cost analysis and managerial judgement.

The MPS disaggregates aggregate plans into specific products and periods, while MRP coordinates component requirements. Detailed scheduling then loads resources, sequences jobs and tests feasibility under finite capacity. Measures such as flow time, lateness and tardiness help evaluate schedule performance, but no priority rule is universally optimal. Yield and revenue management allocate scarce, perishable capacity across customer segments and periods, subject to ethical and regulatory constraints.

Effective systems combine models with reliable data, cross-functional governance, bottleneck awareness, scenario analysis and human judgement. Technology and AI can strengthen planning, but they require transparency, controls and accountability. The ultimate objective is not merely low cost; it is a resilient, feasible and strategically coherent balance among service, profitability, capability, people and sustainability.

Key Terms

Aggregate planning: Medium-term planning of production and resources for product families.

Available-to-promise: Uncommitted supply that can legitimately be promised to customers.

Backlog: Demand accepted but not yet fulfilled.

Chase strategy: A plan that varies production or workforce to follow demand.

Critical ratio: Remaining time until due date divided by remaining processing time.

Finite-capacity scheduling: Scheduling that explicitly respects available resource capacity.

Flow time: Time from job release to job completion.

Loading: Assigning work to resources and time periods.

Master production schedule: Time-phased schedule of specific finished products.

Mixed strategy: Aggregate plan combining level and chase mechanisms.

MRP: Material requirements planning based on the MPS, bills of material and lead times.

On-time-in-full: Delivery performance measured by both timing and quantity completeness.

Revenue management: Pricing and capacity-allocation decisions intended to maximize contribution from variable demand.

S&OP: Cross-functional process for reconciling demand and feasible supply.

Sequencing: Determining the order in which jobs are processed.

SPT: Shortest-processing-time priority rule.

Subcontracting: Obtaining production or services from an external provider.

Tardiness: Positive lateness; the amount by which a job exceeds its due date.

Yield management: Allocation of fixed, perishable capacity among demand opportunities.

Review Questions

Short Answer Questions

1. What is the purpose of an executive S&OP process?
2. Distinguish a chase strategy from a level strategy.
3. What information does an MPS provide?
4. Define finite-capacity scheduling.
5. Why can high capacity utilization reduce responsiveness?

Long Answer Questions

1. Explain the S&OP cycle and the roles of sales, operations, finance and senior management.
2. Compare workforce adjustment, inventory, overtime, backlog and outsourcing as aggregate-planning alternatives.
3. Explain how an aggregate plan is translated into an MPS and subsequently into material and capacity requirements.
4. Compare FCFS, SPT, EDD and critical-ratio sequencing rules, including their advantages and limitations.
5. Discuss the strategic, ethical and governance issues associated with yield and revenue management.

Analytical / Application Questions

1. A manufacturer faces monthly demand of 900, 1,400 and 1,100 units, begins with 100 units of inventory and has a stable capacity of 1,100 units per month. Develop the inventory balance under a level plan and identify any backlog or ending inventory.
2. A resource has 160 available hours in a week. Three jobs require 50, 70 and 60 hours and have due dates in 4, 3 and 2 days respectively. Calculate total load, determine whether the schedule is feasible, and explain which managerial action is appropriate.
3. A hotel has one remaining room. A low-rate booking contributes CU 120 with certainty. A premium customer may arrive with probability 0.7 and would contribute CU 250. Using the simplified expected-contribution rule, should the hotel accept the low-rate booking? State the assumptions and explain limitations of the decision.

Multiple Choice Questions with Answers

Question 1

Which activity normally belongs to the executive S&OP review?

A. Selecting the exact cutting sequence for individual machine jobs

B. Approving a reconciled demand and supply plan

C. Exploding every bill of material into purchase requisitions

D. Recording individual operator attendance

Correct Answer: B. Approving a reconciled demand and supply plan

Question 2

A level strategy primarily absorbs demand variation through which mechanism?

A. Frequent workforce changes

B. Stable production combined with inventory or backlog

C. Elimination of all safety stock

D. Permanent outsourcing of all production

Correct Answer: B. Stable production combined with inventory or backlog

Question 3

If beginning inventory is 200 units, production is 900 units and demand is 1,000 units, ending inventory is:

A. 0 units

B. 100 units

C. 200 units

D. 1,100 units

Correct Answer: B. 100 units

Question 4

Which document specifies specific finished products and quantities by time period?

A. Master production schedule

B. Supplier code of conduct

C. Aggregate wage agreement

D. Facility layout

Correct Answer: A. Master production schedule

Question 5

Under the shortest-processing-time rule, which job is normally scheduled first?

A. The job with the latest due date

B. The job with the longest processing time

C. The job with the shortest processing time

D. The job with the highest material cost

Correct Answer: C. The job with the shortest processing time

Question 6

A job has a due date 12 hours from now and requires 4 hours of processing. Its critical ratio is:

A. 0.33

B. 3

C. 8

D. 16

Correct Answer: B. 3

Question 7

Finite-capacity scheduling differs from infinite-capacity planning because it:

A. Ignores machine calendars

B. Assumes unlimited labour

C. Explicitly respects available resource capacity

D. Uses only annual forecasts

Correct Answer: C. Explicitly respects available resource capacity

Question 8

In the simplified yield-management rule, a low-value booking with contribution CU 100 should be accepted over a possible high-value booking contributing CU 200 when the high-value arrival probability is:

A. 0.25

B. 0.50

C. 0.60

D. 0.75

Correct Answer: A. 0.25

Question 9

Which is a potential disadvantage of excessive overtime?

A. Guaranteed improvement in quality

B. Fatigue and increased error risk

C. Elimination of all capacity constraints

D. Removal of all labour costs

Correct Answer: B. Fatigue and increased error risk

Question 10

Why should a bottleneck be identified before adding capacity elsewhere?

A. Non-bottleneck capacity always reduces demand

B. Additional non-bottleneck capacity may not increase system throughput

C. Bottlenecks are unrelated to scheduling

D. Bottleneck resources never require maintenance

Correct Answer: B. Additional non-bottleneck capacity may not increase system throughput