Aggregate Planning, Resource Planning and Scheduling

Introduction

Operations systems must translate uncertain market demand into feasible commitments for people, equipment, materials, suppliers and time. Aggregate planning, resource planning and scheduling form a hierarchy for doing so. Aggregate planning determines the broad capacity and workforce pattern over a medium-term horizon. The master production schedule (MPS) converts that plan into specific end-item quantities and timing. Material requirements planning (MRP) translates the MPS into component and purchasing requirements, while enterprise resource planning (ERP) integrates these decisions with finance, procurement, sales, maintenance and human resources. Scheduling then assigns work to specific resources and sequences activities to meet delivery, cost and quality objectives.

These decisions are interdependent. A plan that appears economical at an aggregate level may be impossible because of machine capacity, supplier lead times, labour skills or setup constraints. Conversely, an efficient schedule cannot compensate for inadequate aggregate capacity. Effective operations management therefore combines quantitative models with managerial judgement, data governance and continuous replanning.

Learning Objectives

After studying this chapter, you should be able to:

1. Explain the hierarchy linking aggregate planning, MPS, MRP, ERP and detailed scheduling.
2. Formulate and compare level, chase and hybrid aggregate plans.
3. Calculate workforce, inventory, capacity and relevant planning costs.
4. Construct a basic MPS and MRP record using lead times, lot sizes and scheduled receipts.
5. Evaluate sequencing rules and workforce schedules under operational constraints.
6. Analyse variability, utilization, delivery commitments and plan robustness.
7. Critically assess technology, governance, ethics and implementation risks.

1. The Planning Hierarchy

Planning horizons are commonly grouped as follows:

The hierarchy should be vertically aligned. The aggregate plan usually uses product families and common capacity units, such as labour-hours or machine-hours. The MPS disaggregates families into stock-keeping units (SKUs). MRP uses bills of material (BOMs), inventory records and lead times to calculate planned orders. Scheduling considers the actual jobs, resources, sequence-dependent setups, calendars and employee qualifications.

A useful conceptual relationship is:

Demand forecast → Aggregate plan → MPS → MRP/ERP → Detailed schedule → Execution and feedback

Feedback is essential. Actual demand, absenteeism, supplier delays, quality losses and machine failures alter available capacity. Planning is therefore a rolling process rather than a one-time calculation.

2. Aggregate Planning

2.1 Purpose and inputs

Aggregate planning balances forecast demand and available capacity for a medium-term horizon. It normally uses product families rather than individual products because detailed information is unnecessary at this level. Important inputs include:

• demand forecasts and confirmed orders;
• opening inventory and desired ending inventory;
• regular-time, overtime and subcontracting capacity;
• workforce size, productivity and skill availability;
• hiring, training, layoff and overtime costs;
• inventory holding, shortage and back-order costs;
• contractual delivery promises and service targets.

The core balance for period t is:

where I_t is ending inventory, P_t regular production, S_t subcontracted or externally supplied quantity, D_t demand, and B_t backlog or shortage carried into the next period. The exact treatment of backlog varies by model; if backlog is represented as a signed inventory variable, it should not also be subtracted separately. The equation assumes all quantities use the same units and that production and demand occur within the period according to the adopted convention.

If workforce productivity is p units per worker per period and W_t is the workforce, regular capacity is:

If each unit requires h labour-hours and available regular labour-hours are L_t, then:

These formulas assume stable productivity and no bottleneck other than the stated resource. In practice, capacity must be adjusted for breaks, absenteeism, maintenance, quality losses, changeovers and learning.

2.2 Planning strategies

Level strategy. Production and workforce remain relatively constant while inventory, backlog or subcontracting absorbs demand variation. It supports employment stability and predictable production, but may create high inventory, obsolescence or customer waiting.

Chase strategy. Production follows demand by changing workforce, hours or external supply. It reduces inventory but may incur hiring, training, layoff and quality costs. It is more feasible where labour is flexible and products are not highly specialized.

Hybrid strategy. The organization combines a stable core workforce with overtime, temporary labour, inventory, cross-training or subcontracting. Most real systems use hybrid plans because pure strategies are rarely optimal.

The total relevant cost of a plan can be represented as:

where C_R is regular-time production cost, C_O overtime cost, C_H hiring and training cost, C_L layoff cost, C_I inventory holding cost, C_S subcontracting cost and C_B shortage or backlog cost. The model is useful only when costs are measured consistently and fixed, sunk and irrelevant costs are excluded from comparisons. It also omits strategic effects unless they are explicitly valued.

2.3 Linear programming formulation

For a multi-period plan, decision variables may include workforce W_t, hires H_t, layoffs L_t, regular production P_t, overtime O_t, inventory I_t and backlog B_t. A simplified objective is:

subject to workforce balance:

and demand balance:

Typical constraints include:

The symbols c denote unit costs, D_t demand, p productivity, and O_t^{max} the overtime limit. Integer restrictions may be required for workers, shifts or batches. Linear programming assumes linear costs and relationships; it may need mixed-integer programming when setup decisions, minimum lots or yes/no subcontracting choices matter.

2.4 Worked example: comparing level and chase logic

An illustrative manufacturer forecasts demand of 800, 1,200 and 1,000 units in three successive months. Opening inventory is 200 units, and management requires 200 units at the end of month three. Thus total required production is:

800 + 1,200 + 1,000 + 200 − 200 = 3,000 units.

A level plan produces 1,000 units each month. Inventory evolves as follows:

A chase plan, assuming production can change without cost or capacity limits, produces 600, 1,200 and 1,000 units respectively. Inventory remains at 200 units throughout. The chase plan minimizes inventory variation, but it may require substantial workforce changes or overtime. The level plan is operationally stable, but it holds an average of 266.7 units during the three ending periods. Neither plan is automatically superior; cost, service, labour relations, product perishability and capacity flexibility determine the choice.

3. Capacity, Constraints and Variability

Capacity is not simply the nameplate output of equipment. Effective capacity is the output achievable under normal operating conditions. If a machine is available for 480 minutes, experiences 30 minutes of planned maintenance and has a 10% loss from minor stops and changeovers, effective time is approximately:

The calculation assumes losses are sequentially applied and independent. If losses overlap, they must not be double-counted.

Utilization and efficiency should be distinguished:

A resource operating near 100% utilization may appear efficient but have no protection against variability. Queueing effects generally increase sharply as utilization approaches full capacity. Consequently, managers should protect bottlenecks with time buffers, material availability, preventive maintenance and prioritized work. The theoretical bottleneck capacity is the minimum capacity across required stages, but practical throughput may be lower because of setups, yield losses, blocking, starving and product mix.

Capacity requirements planning (CRP) translates MRP orders into labour- and machine-hour requirements by work centre. It identifies overloads and underloads, but its accuracy depends on routing data, standard times, calendars and realistic queue assumptions. Capacity can be adjusted through overtime, alternate routing, lot splitting, cross-training, preventive maintenance, subcontracting or investment.

4. Master Production Scheduling

The MPS specifies what end items will be completed and when, usually over weekly time buckets. It is not simply a sales forecast. It is a feasible commitment constrained by aggregate capacity, inventory policy, available-to-promise (ATP) quantities and customer priorities.

A basic projected available balance (PAB) is:

where Orders_t represents demand allocated to the period. In some systems, forecast and customer orders are combined using a defined consumption rule. The MPS must also respect time fences: a frozen zone limits changes near-term, a slushy zone permits controlled changes, and a liquid zone permits replanning. Time fences reduce nervousness—the disruptive propagation of small changes through the planning system.

ATP indicates uncommitted supply available for new orders. A common first-period calculation is:

Later ATP quantities are based on the relevant MPS receipt and orders until the next receipt. The exact formula depends on the organization's order-allocation convention; ATP must not be treated as a promise if capacity, quality or supply risk remains unresolved.

5. Material Requirements Planning

MRP is a time-phased planning system for dependent demand. Dependent demand is calculated from the requirements of a parent item, whereas independent demand is forecast or order driven. MRP requires:

1. an MPS;
2. a single-level or multi-level BOM;
3. inventory status, including on-hand and scheduled receipts;
4. lead times and lot-sizing rules;
5. planning policies such as safety stock and scrap allowances.

The standard MRP logic is:

Gross requirements → Projected available balance → Net requirements → Planned order receipts → Planned order releases.

For a period, a simplified net-requirement calculation is:

where NR_t is net requirement, GR_t gross requirement, SS safety stock and Available_t projected supply after considering prior balances and scheduled receipts. A planned receipt is then offset by lead time to determine the planned release. The formula assumes a defined lot-sizing rule and correct timing of receipts.

If one finished product requires three units of component A, and the MPS calls for 100 finished products, gross requirement for A is:

If 80 units are available and 20 units of safety stock must remain, net requirement is 240 units, before considering scheduled receipts. If the component has a two-week lead time, the order release occurs two weeks before the required receipt date. BOM accuracy is critical: a wrong quantity or effective date produces systematic shortages or excess inventory.

MRP has limitations. It plans material timing but does not automatically guarantee finite capacity, supplier reliability or shop-floor execution. Nervousness may result from frequent demand changes, and large batch sizes can create inventory peaks. Techniques such as demand time fences, exception messages, safety time, postponement and finite-capacity checks improve robustness.

6. ERP and Integrated Resource Planning

ERP extends MRP by using a shared database and integrated processes. Typical modules cover sales and operations planning, purchasing, inventory, manufacturing, maintenance, finance, quality, projects and human resources. Integration enables a sales order to affect inventory, production, procurement, revenue recognition and capacity visibility.

ERP benefits include common data, transaction traceability, standardized workflows and faster cross-functional decisions. Risks include poor master data, excessive customization, weak user adoption, cyber threats, implementation disruption and false confidence in system-generated plans. ERP does not replace managerial judgement: an algorithm using inaccurate lead times or obsolete BOMs will produce precise but unreliable recommendations.

Sales and operations planning (S&OP), increasingly called integrated business planning, provides the governance layer between strategy and execution. A typical cycle includes data review, demand review, supply review, reconciliation of alternatives and executive approval. The process should expose assumptions, capacity trade-offs, risks and decisions rather than merely produce a forecast.

7. Scheduling and Sequencing

Scheduling assigns jobs to resources and time periods. It differs from planning because it uses greater detail: individual orders, setup times, routing alternatives, shift calendars, labour qualifications and machine availability.

Important scheduling environments include:

• Single-machine: all jobs use one resource.
• Parallel machines: jobs can use one of several similar resources.
• Flow shop: jobs follow the same sequence of machines.
• Job shop: jobs have different routings.
• Project scheduling: activities have precedence relationships and uncertain durations.

Common performance measures are completion time, flow time, lateness, tardiness, makespan, work-in-process and utilization. If job j is due at d_j and completes at C_j, lateness is:

Tardiness is non-negative lateness:

Average flow time is the mean of completion times measured from a common release time. Makespan is the completion time of the final job. Measures must be selected according to strategy: minimizing average flow time can conflict with minimizing maximum tardiness.

Sequencing rules

No dispatching rule dominates in every environment. SPT is attractive when average flow time is important and release dates are comparable. EDD is often appropriate when due dates are central. Critical-ratio rules are useful when jobs become urgent at different rates. Rules should be supplemented by constraints such as material availability, quality holds, setup families, customer class and maintenance windows.

For two machines in a flow shop, Johnson's rule minimizes makespan under restrictive assumptions: every job visits machine 1 then machine 2, processing times are known and deterministic, all jobs are available at time zero, machines cannot process more than one job at once, and no interruptions occur. The rule repeatedly selects the smallest processing time among all unscheduled jobs; if it belongs to machine 1, place the job as early as possible, and if it belongs to machine 2, place it as late as possible. These assumptions must be checked before applying the rule.

8. Workforce Scheduling

Workforce scheduling matches labour supply with time-varying demand while respecting skills, contracts, fatigue and employee preferences. Inputs include forecast workload, required staffing by interval, employee availability, qualification matrices, maximum hours, rest periods and labour regulations.

A basic coverage constraint is:

where x_es equals 1 if employee e is assigned to shift s, a_es indicates eligibility and availability, and R_s is required staffing. The model assumes binary assignment decisions. Additional constraints may require each employee to work no more than a specified number of shifts, receive minimum rest, cover critical skills and avoid overlapping shifts. Objective functions may minimize labour cost, understaffing penalties, overtime and undesirable schedules, subject to fairness requirements.

Cross-training increases flexibility but has training cost and possible productivity variation. Stable rosters support retention, while excessive overtime can produce fatigue, safety incidents, absenteeism and quality deterioration. Workforce planning must therefore treat health, dignity, equal opportunity and legal compliance as operational constraints, not optional social considerations.

9. Illustrative Case: Meridian Medical Devices

Background. Meridian produces three families of diagnostic cartridges. Demand is seasonal, one sterilization chamber is the bottleneck, and hospitals require high delivery reliability. The firm uses an ERP system, but its BOMs and standard times have not been reviewed for two years.

Problem. A promotional campaign increased forecast demand by 25%. The aggregate plan proposed overtime and subcontracting, while the MPS promised additional hospital orders. The sterilization chamber became overloaded, component shortages appeared in MRP, and planners repeatedly changed near-term orders. Expediting costs rose and on-time delivery fell.

Analysis. A cross-functional team first reconciled actual demand, confirmed orders and forecast consumption. It audited BOM quantities, sterilization routings, yield losses and supplier lead times. Capacity analysis showed that the chamber, not assembly labour, constrained throughput. The team also found that the ERP calendar counted planned maintenance as available time and that safety stock was applied inconsistently.

Approach. Meridian adopted a rolling 12-month S&OP process, a three-week frozen MPS zone and a finite-capacity check for sterilization. It level-loaded the chamber, moved noncritical work to an approved supplier, and introduced a priority rule based on due-date risk and remaining sterilization time. It also created a skills matrix, cross-trained operators and revised standard times using observed data. Hospital orders were confirmed only after capacity and material checks.

Outcome. The plan reduced schedule changes, made the bottleneck visible and improved delivery reliability without simply increasing utilization. The company accepted a small capacity buffer at the chamber because a nominally cheaper full-utilization plan generated excessive queues and expediting.

Learning points. First, aggregate plans must recognize bottlenecks. Second, ERP integration is valuable only when master data are governed. Third, delivery promises should reflect finite capacity and material risk. Finally, resilience may require deliberate spare capacity rather than maximum short-term utilization.

10. Challenges, Governance and Contemporary Developments

Planning systems face forecast error, demand volatility, supplier disruption, engineering changes, labour scarcity, cyber risk and climate-related interruptions. Scenario planning can evaluate demand, capacity and supply alternatives rather than relying on one forecast. Robust plans often include postponement, dual sourcing, qualified substitutes, strategic inventory and capacity options.

AI and advanced analytics can improve demand sensing, anomaly detection, predictive maintenance, schedule optimization and exception prioritization. However, models may reproduce historical bias, obscure trade-offs or make unsafe recommendations when conditions change. Governance should require data lineage, human approval for high-impact decisions, monitoring for drift, explainable constraints and secure access. Employee scheduling algorithms should not systematically assign undesirable shifts to vulnerable groups or use intrusive personal data without legitimate justification.

Best practices include:

• maintain one governed set of calendars, BOMs, routings, lead times and inventory records;
• separate forecast assumptions from confirmed orders;
• use rolling planning with explicit time fences;
• plan the bottleneck first and validate finite capacity;
• measure service, flow time, inventory, cost, schedule stability and employee impact together;
• conduct what-if analysis before changing customer commitments;
• review exceptions rather than blindly replanning every item;
• audit model assumptions, data quality, cybersecurity and access rights;
• involve sales, operations, finance, procurement, engineering and workforce representatives;
• learn from actual performance and update standards systematically.

Chapter Summary

Aggregate planning establishes medium-term decisions about workforce, inventory, overtime, subcontracting and capacity. Level, chase and hybrid strategies represent different ways of absorbing demand variation, and their comparison requires explicit relevant costs and operational constraints. The MPS disaggregates aggregate families into end-item commitments, while MRP converts those commitments into time-phased component requirements using BOMs, inventory records, lot sizes and lead times. ERP integrates these plans with enterprise processes but cannot compensate for poor master data.

Scheduling assigns jobs and people to resources. Sequencing rules such as SPT, EDD and critical ratio should be selected according to performance objectives and applied only within their assumptions. Workforce schedules must address coverage, skills, rest, fairness and legal requirements. Across all levels, bottlenecks, variability, delivery promises and data quality determine whether a plan is executable. Modern analytics and AI can improve responsiveness, but governance, human oversight and ethical safeguards remain essential.

Key Terms

Aggregate planning: Medium-term planning of capacity, workforce, inventory and supply for product families.

Available-to-promise (ATP): Uncommitted supply that can be promised to customers under an established allocation rule.

Backlog: Demand not fulfilled in its originally planned period.

Bill of material (BOM): Structured record of components and quantities required for a parent item.

Bottleneck: Resource whose effective capacity constrains system throughput.

Capacity requirements planning (CRP): Translation of planned orders into work-centre capacity requirements.

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

Dependent demand: Demand calculated from the requirements of another item.

Enterprise resource planning (ERP): Integrated information system linking operational and business processes.

Finite-capacity planning: Planning that does not schedule more work than a resource can perform.

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

Material requirements planning (MRP): Time-phased calculation of component requirements and planned orders.

Nervousness: Unnecessary instability caused by frequent changes in planned orders.

Projected available balance (PAB): Expected inventory position after planned supply and demand.

Sequencing rule: Policy used to determine the order in which jobs are processed.

S&OP: Cross-functional process for reconciling demand, supply and strategic decisions.

Tardiness: Amount by which completion exceeds a due date, never less than zero.

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

Utilization: Proportion of available resource time used for operation.

Review Questions

Short Answer Questions

1. Distinguish aggregate planning from master production scheduling.
2. What are the principal advantages and disadvantages of a level strategy?
3. Define dependent demand and explain why MRP is appropriate for it.
4. Distinguish lateness from tardiness.
5. Why can a bottleneck operating at very high utilization reduce delivery performance?

Long Answer Questions

1. Explain the planning hierarchy from S&OP through detailed scheduling, including the information exchanged at each level.
2. Compare level, chase and hybrid aggregate plans using cost, workforce and service considerations.
3. Explain MRP logic from gross requirements to planned order releases and identify its major data requirements.
4. Evaluate the strengths and limitations of FCFS, SPT, EDD and critical-ratio sequencing rules.
5. Discuss how ERP, master-data governance and finite-capacity planning influence operational performance.

Analytical / Application Questions

1. A firm has monthly demand of 900, 1,400 and 1,100 units, opening inventory of 250 units and a desired final inventory of 150 units. Construct a level-production plan and calculate ending inventory for each month. State any feasibility assumptions.
2. A component has gross requirements of 500 units in week 4, 300 in week 5 and 400 in week 6. On-hand inventory is 250 units, safety stock is 50 units, no scheduled receipts exist, and the lot size is 600 units with a two-week lead time. Develop the planned receipt and release logic, explaining the inventory convention used.
3. A hospital service requires staffing of 4, 6 and 5 qualified employees across three shifts. Propose a workforce-scheduling model that includes coverage, employee availability, rest, fairness and overtime, and explain which objective measures should be monitored.

Multiple Choice Questions with Answers

Question 1

Which planning level normally converts product-family plans into specific end-item quantities and timing?

A. Strategic capacity planning

B. Master production scheduling

C. Supplier relationship management

D. Payroll administration

Correct Answer: B. Master production scheduling

Question 2

A chase strategy primarily absorbs demand variation by changing which factor?

A. The product design

B. The BOM structure

C. Production or workforce levels

D. The accounting period

Correct Answer: C. Production or workforce levels

Question 3

If demand is 700 units, opening inventory is 100 units, production is 650 units and the desired ending inventory is 50 units, what is the resulting surplus or shortage before other adjustments?

A. 50-unit surplus

B. 50-unit shortage

C. 100-unit surplus

D. 100-unit shortage

Correct Answer: A. 50-unit surplus

Question 4

Which rule generally prioritizes the job with the smallest processing time?

A. EDD

B. FCFS

C. SPT

D. Critical ratio

Correct Answer: C. SPT

Question 5

Tardiness for a job completed at time 18 with a due date of 15 is:

A. −3 time units

B. 0 time units

C. 3 time units

D. 33 time units

Correct Answer: C. 3 time units

Question 6

Which item is essential input data for MRP?

A. A bill of material

B. An employee satisfaction survey only

C. A marketing slogan

D. A depreciation policy only

Correct Answer: A. A bill of material

Question 7

A bottleneck is best defined as the resource that:

A. Has the largest floor area

B. Constrains system throughput

C. Has the lowest purchase price

D. Always has the highest utilization

Correct Answer: B. Constrains system throughput

Question 8

If a component requires 2 units per finished product and the MPS calls for 150 finished products, the gross component requirement is:

A. 75 units

B. 150 units

C. 152 units

D. 300 units

Correct Answer: D. 300 units

Question 9

What is the primary purpose of a time fence in an MPS?

A. To eliminate all forecasts

B. To control how freely near-term plans can change

C. To increase every lot size

D. To replace capacity planning

Correct Answer: B. To control how freely near-term plans can change

Question 10

Which statement about ERP is most accurate?

A. ERP guarantees correct plans regardless of data quality

B. ERP integrates processes but depends on governed, accurate master data

C. ERP is used only for financial reporting

D. ERP eliminates the need for managerial judgement

Correct Answer: B. ERP integrates processes but depends on governed, accurate master data