Dependent Demand and Materials Planning

Introduction and Context

Inventory decisions differ fundamentally according to the source of demand. Independent demand arises from external customers and must usually be forecast—for example, demand for finished refrigerators. Dependent demand is derived from the demand for another item. If each refrigerator requires one compressor, the demand for compressors depends on the production plan for refrigerators rather than on a separate market forecast.

This distinction is central to materials planning. Forecasting is appropriate for finished goods and service parts, whereas components and raw materials can often be planned by translating a known or forecast production schedule through a bill of materials (BOM). Materials requirements planning (MRP) performs this translation over time. Distribution requirements planning (DRP) applies similar logic to replenishment across warehouses, regional distribution centres and retail locations.

Modern planning is not limited to calculating quantities. It must also consider lead times, lot sizes, capacity, supplier reliability, engineering changes, inventory policies, transportation constraints and the operating philosophy of the organisation. Push systems, pull systems, just-in-time (JIT), Kanban, lean management and the theory of constraints (TOC) offer different ways of coordinating material and production flows. Effective logistics managers therefore treat MRP as a decision-support system embedded in a broader operating model, not as an automatic substitute for judgement.

Learning Objectives

After studying this chapter, the reader should be able to:

1. Distinguish independent from dependent demand and explain their planning implications.
2. Construct and interpret a multi-level bill of materials.
3. Perform time-phased MRP calculations, including gross requirements, projected available balance, net requirements, planned receipts and planned order releases.
4. Explain lot-sizing methods and evaluate their operational consequences.
5. Relate MRP to capacity requirements planning, supplier schedules and DRP.
6. Compare push, pull, JIT, Kanban, lean and TOC approaches.
7. Diagnose implementation risks and design appropriate managerial controls.

1. Dependent Demand as a Planning Logic

Dependent demand is calculated from a parent item’s planned production or usage. Its principal advantages are:

• the quantity relationship is explicit;
• the timing relationship can be derived from lead times;
• safety stock can often be reduced because requirements are calculated rather than independently forecast;
• engineering and product-structure changes can be incorporated systematically.

The logic is not perfect. A production schedule may be wrong, scrap may occur, usage may vary, and components may be shared by several products. Consequently, dependent-demand planning requires accurate master data and feedback from operations.

A basic gross-requirement relationship for a component is:

where GR_i,t is the gross requirement for component i in period t, PORel_j,t is the planned order release for parent item j in that period, and q_ij is the quantity of component i required per unit of parent j. The summation is necessary when a component is used in several parent items. This relationship assumes that the BOM quantity is known and that component usage is proportional to parent production.

Independent demand remains important. Finished goods, replacement parts and consumables may require forecasts, safety stock and service-level policies. A product can therefore contain both demand types: its finished-goods demand is independent, while its components’ demand is dependent.

2. Bills of Materials

A bill of materials is a structured representation of the parts, subassemblies, materials and quantities required to make one unit of a parent item. It is both an engineering document and a planning master-data object.

A BOM normally records:

• item number and description;
• unit of measure;
• quantity per parent;
• level or indentation;
• effectivity dates;
• revision status;
• scrap or yield factors;
• substitutes and approved alternatives;
• phantom assemblies, where relevant.

2.1 Product structure

Consider a finished product P. Each unit requires two units of A and one unit of B. Each A requires three units of C. Each B requires two units of C and one unit of D.

Figure: A multi-level product structure. Quantities in parentheses are usage quantities per immediate parent.

For one unit of P, the total requirement for C is eight units: six through A and two through B. The distinction between single-level usage and cumulative usage is important. MRP explodes requirements level by level, but planners must ultimately ensure that all lower-level requirements are captured.

BOM accuracy is a governance issue. Incorrect quantities, obsolete revisions, missing effectivity dates or unrecorded substitutes can cause shortages, excess stock and production disruption. Engineering, procurement, manufacturing and finance should share formal change-control procedures.

3. Materials Requirements Planning

MRP is a time-phased planning technique that converts a master production schedule into requirements for components and materials. Its principal inputs are:

1. Master production schedule (MPS): what finished products or major assemblies are to be completed, and when.
2. BOM: how each parent is made.
3. Inventory and open-order records: on-hand stock, scheduled receipts, allocations, scrap and order status.
4. Planning parameters: lead times, lot-sizing rules, safety stock, order policies and calendar constraints.

Its principal outputs are planned order receipts and planned order releases, together with exception messages such as expedite, defer, cancel or reschedule.

3.1 MRP record logic

For each item and period, MRP commonly calculates:

where PAB_t is projected available balance at the end of period t, SR_t is the scheduled receipt due in period t, PORc_t is the planned order receipt in that period, and GR_t is gross requirement. The opening balance is PAB₀. All terms must use the same unit and time bucket.

If the projected balance would fall below the required safety stock, the net requirement is:

where NR_t is net requirement and SS_t is the safety-stock target in period t. This expression assumes that current-period scheduled receipts are available to satisfy the requirement. If receipt timing differs, the record must use the organisation’s defined availability convention.

A lot-sizing rule converts the net requirement into a planned receipt. Under lot-for-lot (L4L):

Under a fixed order quantity Q, a positive net requirement is rounded upward:

The planned release is offset by the item’s lead time. With a deterministic lead time of L periods:

These formulas assume discrete planning periods, known lead times and no capacity limitation. Real systems may use calendars, overlap operations, variable lead times and finite-capacity scheduling.

3.2 Worked MRP example

Suppose an item X has the following data:

• opening projected balance: 30 units;
• safety stock: 10 units;
• scheduled receipt: 20 units in period 2;
• lead time: 1 period;
• lot-for-lot ordering;
• gross requirements: 20, 35, 40 and 15 units in periods 1–4.

The calculations are as follows.

For period 1, the balance is 30 − 20 = 10, exactly the safety stock. In period 2, without a planned receipt, the balance would be 10 + 20 − 35 = −5. To finish with 10 units, the net requirement is 15 units, received in period 2 and released in period 1. The same logic produces 40 and 15 unit receipts in periods 3 and 4. This example illustrates why MRP distinguishes a planned receipt from a planned release.

3.3 MRP nervousness

Small changes in the MPS can generate frequent changes in lower-level planned orders. This phenomenon, often called MRP nervousness, can increase purchase-order amendments, supplier instability and shop-floor confusion. Common controls include planning time fences, frozen zones, firm planned orders, order modifiers, safety lead time and exception-based review. These controls deliberately sacrifice some theoretical responsiveness to obtain operational stability.

4. Lot-Sizing Decisions

Lot sizing determines how much to order or produce when a net requirement occurs. The choice influences setup cost, carrying cost, obsolescence, working capital, transport efficiency and production flexibility.

For independent replenishment with constant demand, fixed order cost and linear holding cost, the classical EOQ benchmark is:

where Q^* is economic order quantity in units per order, D is annual demand in units per year, S is ordering or setup cost per order, and H is annual holding cost per unit per year. The model assumes known constant demand, instantaneous replenishment, no shortages, constant unit price and independent replenishment decisions. These assumptions often do not hold exactly in MRP environments; therefore, EOQ should be treated as a benchmark rather than an unquestionable answer.

If annual demand is 12,000 units, order cost is £50 per order and annual holding cost is £2 per unit, then:

Q^* = √(2×12,000×50÷2) = √600,000 ≈ 775 units.

The result should be checked against supplier minimums, truck capacity, shelf life, production setup constraints and service requirements.

4.1 Lot-sizing trade-offs

Large lots reduce the number of orders and setups, but they increase cycle stock, storage requirements and exposure to obsolescence. Small lots support flow and reduce inventory, but they demand reliable suppliers, short setups, stable processes and accurate transactions. In postgraduate practice, the correct question is not “Which method is best?” but “Which cost, risk and flow objective is being prioritised under which constraints?”

5. Capacity-Linked Materials Planning

MRP answers whether material is needed and when, but a material plan is infeasible if labour, machines, tooling, warehouse space, transport or suppliers cannot support it. Capacity requirements planning (CRP) translates planned or released orders into workload by work centre.

For a work centre, a basic load calculation is:

where Load_w,t is required capacity time at work centre w in period t, Q_i,t is the quantity of item i processed, s_i is setup time per batch or order, and r_i is run time per unit. Time must be expressed consistently, such as machine-hours.

Available capacity can be represented as:

where N_w is the number of available resources, H_t is scheduled hours per resource, U_w,t is planned utilisation and E_w,t is efficiency. Utilisation and efficiency should not be multiplied casually unless their definitions are distinct and non-overlapping.

A capacity-load ratio is:

A value above 1 indicates overload under the stated assumptions. It does not automatically prove that production will fail: overtime, alternate routings, subcontracting, backlog, yield improvement or schedule changes may alter the outcome.

The usual closed-loop process is MRP → CRP → capacity adjustment → revised MPS/MRP. Capacity planning can be rough-cut at the MPS level and detailed after order releases. Managers should examine bottlenecks, queue time and finite-capacity sequencing rather than relying solely on aggregate ratios.

6. Distribution Requirements Planning

DRP applies time-phased planning to distribution networks. A distribution centre calculates its gross requirement from planned shipments, forecasts, dependent requirements or replenishment policies. The central or supplying location then sees the distribution centre’s planned order release as a demand signal.

A typical DRP record includes forecast or demand, scheduled receipts, projected available balance, safety stock, planned replenishment receipts and planned shipment releases. The logic resembles MRP, but the BOM is replaced by a distribution structure and the lead time includes order processing, transport and receiving.

DRP supports coordinated deployment, but it can also transmit poor forecasts upstream. Multi-echelon inventory planning improves the analysis by recognising that stock at one echelon affects service and inventory at other echelons. Governance should define which location owns safety stock, how allocation is prioritised during shortages and how transport constraints are represented.

7. Push, Pull, JIT, Kanban, Lean and TOC

7.1 Push and pull

A push system releases work according to a forecast, plan or schedule. MRP is principally a push planning mechanism: requirements are calculated and orders are released before the downstream operation consumes them. Push systems are valuable when demand is forecastable, product structures are complex, lead times are long and coordination across many levels is necessary.

A pull system authorises replenishment in response to actual downstream consumption. Pull reduces the risk of producing material merely because a forecast exists, but it requires stable processes, visible signals and disciplined replenishment rules. Most practical systems are hybrid: MRP plans long-horizon supply and capacity, while Kanban controls repetitive short-horizon replenishment.

7.2 Just-in-time and lean

JIT seeks to provide the right item, quantity and quality at the required time, with minimal waste. Lean management extends this logic into a broader system of value identification, flow, customer pull and continuous improvement. Typical wastes include overproduction, waiting, transport, excess processing, inventory, motion and defects.

JIT is not simply “low inventory.” Low inventory without process capability may expose defects and create shortages. Successful JIT depends on quick setups, preventive maintenance, quality at source, reliable suppliers, standard work, visual control and problem-solving discipline.

7.3 Kanban

Kanban is a visual or electronic authorisation mechanism. A downstream process takes material from a supermarket or controlled buffer, and that consumption authorises replenishment. A simplified container formula is:

where n is the number of kanban containers, D is average demand per time unit, L is replenishment lead time in the same time unit, α is an agreed protection factor, and C is container capacity. The formula assumes relatively stable demand and lead time and a defined protection factor. It is a policy approximation, not a guarantee of service.

For example, demand is 40 units per hour, replenishment takes 0.5 hour, protection is 10%, and each container holds 10 units:

n = ceil(40×0.5×1.10÷10) = ceil(2.2) = 3 containers.

Kanban is most effective for repetitive items with reasonably stable consumption. It is less suitable for highly intermittent demand, major engineering changes or products requiring unique project-based planning.

7.4 Theory of constraints

TOC argues that system performance is governed by constraints. Its five focusing steps are:

1. Identify the constraint.
2. Exploit it using existing resources and better priorities.
3. Subordinate other activities to the constraint’s needs.
4. Elevate the constraint through additional capacity or redesign.
5. When the constraint moves, repeat the process.

The drum-buffer-rope concept schedules the constraint (the drum), protects it with a time or material buffer, and limits upstream release (the rope) so that work does not accumulate unnecessarily. TOC differs from local efficiency thinking: maximising every department’s utilisation can increase work-in-process and delay if it overloads the system’s constraint.

8. Integrated Planning Architecture

An effective planning architecture links strategic, tactical and operational horizons. Sales and operations planning balances demand and aggregate supply. The MPS converts that agreement into end-item schedules. MRP explodes requirements for materials and components. CRP checks feasibility. DRP coordinates network replenishment. Execution systems report receipts, production, quality and shipment events back to planning.

Technology may include enterprise resource planning (ERP), advanced planning and scheduling, warehouse-management systems, supplier portals, barcode or RFID transactions, and analytics. Artificial intelligence can assist with demand sensing, anomaly detection, supplier-risk prediction and parameter recommendations. However, AI does not repair an incorrect BOM, missing inventory transactions or ambiguous ownership. Models require clean data, explainable decision rules, human oversight and controls against automated amplification of planning errors.

Important performance measures include schedule adherence, forecast error for independent demand, inventory record accuracy, supplier on-time delivery, planned-order stability, stockouts, inventory turns, order fulfilment, capacity utilisation and constraint throughput. Metrics should be balanced: reducing inventory while increasing expedites and customer shortages is not genuine improvement.

9. Illustrative Case: Northstar Medical Devices

Background

Northstar Medical Devices assembles diagnostic units at one plant and distributes finished units through two regional distribution centres. Its product contains a reusable sensor module, a control board and several purchased components. Demand for finished units is seasonal, while some components have long supplier lead times.

Problem

The company’s ERP generated frequent purchase-order changes. Production supervisors reported shortages of connectors even though total inventory was rising. The organisation had accurate end-item forecasts but inconsistent BOM revisions and no formal capacity review for the board-testing operation.

Analysis

A cross-functional audit found three causes. First, an obsolete BOM revision remained active for one product family, causing incorrect connector requirements. Second, planners used fixed large lots for low-value components, creating excess stock that did not protect against shortages of the correct revision. Third, the testing work centre was a constraint; MRP releases created queues that extended actual lead times beyond the master-data values.

Approach and solution

Northstar established engineering change control with effectivity dates and a single approved BOM owner. It introduced lot-for-lot ordering for high-value, revision-sensitive components and retained economic supplier quantities for stable consumables. A rolling capacity check was added for testing, and the MPS was frozen inside a two-week time fence. For repetitive connector kits, the plant introduced a supermarket and electronic Kanban after supplier lead-time variability had been reduced. The testing work centre became the TOC focus: work was prioritised by constraint throughput, and non-urgent orders were prevented from consuming scarce testing time.

Outcome

After three planning cycles, schedule changes declined, connector shortages fell and excess inventory was reduced. The improvement did not result from MRP alone. It came from accurate product data, disciplined change governance, capacity-linked release rules and a selective combination of push and pull controls.

Learning points

1. Dependent-demand calculations are only as reliable as BOM and inventory data.
2. Large lots can hide planning weaknesses while increasing total inventory.
3. Actual capacity and bottleneck behaviour must be reflected in lead-time assumptions.
4. Hybrid systems are usually more practical than ideological commitment to either push or pull.
5. Process ownership and exception management are as important as software functionality.

10. Challenges, Limitations and Governance

MRP can produce technically correct recommendations that are operationally poor. Common limitations include uncertain demand, inaccurate stock records, variable lead times, supplier minimums, capacity overload, scrap, rework, common components and rapidly changing designs. Planning periods that are too long conceal sequencing problems; periods that are too short create excessive administrative activity.

Governance should address data ownership, revision control, authorisation of manual overrides, audit trails, segregation of duties and cybersecurity. A planner should be able to override a recommendation, but the reason and expected expiry should be recorded. Supplier collaboration must protect confidential information while sharing the forecasts and schedules necessary for reliable replenishment. In regulated industries, traceability, approved substitutions and revision history may be legal as well as operational requirements.

Ethically, planners should not manipulate demand or inventory records to improve local performance measures. Expedites, premium freight and supplier pressure may transfer cost and risk elsewhere in the network. Balanced scorecards and transparent escalation are therefore preferable to targets based only on local utilisation or inventory reduction.

Best-Practice Checklist

• Maintain one controlled, effectivity-dated BOM.
• Audit inventory accuracy and transaction discipline.
• Separate forecasted independent demand from calculated dependent demand.
• Review lead times using actual performance and capacity conditions.
• Select lot-sizing rules by item characteristics, not convenience.
• Use time fences and exception messages to control MRP nervousness.
• Link MRP releases to CRP and supplier capacity.
• Apply Kanban only where consumption and replenishment are sufficiently stable.
• Protect bottlenecks and subordinate non-constraints to system throughput.
• Use technology to improve visibility and decisions, not to conceal weak processes.

Chapter Summary

Dependent demand is derived from the requirements of a parent item and is planned through product structure, schedules and inventory records rather than through an independent forecast alone. The BOM provides the structural relationship; the MPS provides the time-phased parent demand; and MRP converts these inputs into gross requirements, net requirements, planned receipts and planned releases. Correct timing requires lead-time offsetting, while practical decisions require suitable lot-sizing rules and safety-stock policies.

MRP must be linked to capacity requirements planning because material availability does not guarantee labour, equipment or supplier feasibility. DRP extends similar time-phased logic through distribution networks. Push systems coordinate complex, forecast-driven requirements, whereas pull and Kanban respond to actual consumption. JIT and lean seek flow and waste reduction, while TOC focuses managerial attention on the system constraint. In practice, organisations combine these approaches.

The central managerial lesson is that planning performance depends on data quality, capacity realism, process discipline and governance. ERP and AI tools can improve visibility and analysis, but they cannot compensate for defective BOMs, unreliable transactions or unmanaged constraints.

Key Terms

Dependent demand: Demand calculated from the planned use or production of another item.

Independent demand: Demand originating from external customers or markets.

Bill of materials (BOM): Structured list of components and quantities required to make a parent item.

Master production schedule (MPS): Time-phased schedule for producing finished goods or major assemblies.

Materials requirements planning (MRP): Systematic calculation of time-phased material requirements and planned orders.

Gross requirement: Total demand for an item before considering inventory and scheduled receipts.

Net requirement: Additional quantity needed after available inventory and receipts are considered.

Projected available balance: Expected inventory remaining at the end of a planning period.

Planned order receipt: Quantity scheduled to become available in a specified period.

Planned order release: Order authorisation timed to allow a planned receipt after lead time.

Lot sizing: Determination of the quantity released in an order or production batch.

Capacity requirements planning (CRP): Evaluation of workload against available resource capacity.

Distribution requirements planning (DRP): Time-phased replenishment planning across a distribution network.

Push system: System that releases work according to a plan, forecast or schedule.

Pull system: System that authorises replenishment in response to downstream consumption.

Just-in-time (JIT): Operating philosophy seeking timely provision with minimal waste and inventory.

Kanban: Visual or electronic signal authorising replenishment or production.

Lean management: Systematic pursuit of customer value, flow, pull and waste reduction.

Theory of constraints (TOC): Management approach that focuses improvement on the system’s limiting constraint.

MRP nervousness: Instability caused by frequent changes to planned orders after small schedule changes.

Review Questions

5 Short Answer Questions

1. What is the difference between independent and dependent demand?
2. Identify the principal inputs to an MRP system.
3. Distinguish a planned order receipt from a planned order release.
4. Why can an inaccurate BOM create both shortages and excess inventory?
5. State the five focusing steps of the theory of constraints.

5 Long Answer Questions

1. Explain how an MPS, BOM and inventory record interact to produce an MRP plan.
2. Compare lot-for-lot, fixed order quantity and period-order quantity methods, including their operational trade-offs.
3. Explain why MRP should be integrated with capacity requirements planning.
4. Compare push, pull, JIT and Kanban systems and identify conditions favouring each.
5. Discuss the role of governance, data quality and change control in materials planning.

3 Analytical / Application Questions

1. An item has an opening balance of 25 units, safety stock of 5 units, no scheduled receipts and gross requirements of 10, 20 and 15 units in periods 1–3. Using lot-for-lot ordering and a one-period lead time, calculate the planned receipts and releases.
2. A plant has a testing constraint with 2 machines, 7 scheduled hours per machine per day, utilisation of 85% and efficiency of 90%. If the planned workload is 12 hours, calculate available capacity and the capacity-load ratio. Interpret the result.
3. A distribution centre experiences highly variable demand and supplier lead times, while a nearby assembly cell has stable repetitive consumption. Recommend where MRP, DRP, Kanban and safety stock should be used, and justify the combination.

Multiple Choice Questions with Answers

Question 1

Which statement best describes dependent demand?

A. Demand generated directly by retail customers

B. Demand calculated from the planned requirements of a parent item

C. Demand that is always constant over time

D. Demand that cannot be influenced by production schedules

Correct Answer: B. Demand calculated from the planned requirements of a parent item

Question 2

In an MRP record, what is the purpose of lead-time offsetting?

A. To increase the finished-goods forecast

B. To move a planned receipt earlier so the order is released in time

C. To eliminate safety stock

D. To convert independent demand into capacity

Correct Answer: B. To move a planned receipt earlier so the order is released in time

Question 3

An item has an opening balance of 30 units, a gross requirement of 25 units, and no scheduled or planned receipts. If safety stock is 5 units, what is the net requirement?

A. 0 units

B. 5 units

C. 25 units

D. 30 units

Correct Answer: A. 0 units

Question 4

Which MRP lot-sizing rule orders exactly the calculated net requirement?

A. Fixed order quantity

B. Economic order quantity

C. Lot-for-lot

D. Period-order quantity

Correct Answer: C. Lot-for-lot

Question 5

What does a capacity-load ratio greater than 1 generally indicate?

A. Available capacity exceeds required load

B. Required load exceeds stated available capacity

C. Inventory records are automatically accurate

D. The item has independent demand

Correct Answer: B. Required load exceeds stated available capacity

Question 6

Which condition most strongly supports the use of Kanban?

A. Highly unique project demand and frequent design changes

B. Stable repetitive consumption and reliable replenishment

C. No defined container quantity

D. Uncontrolled supplier lead times

Correct Answer: B. Stable repetitive consumption and reliable replenishment

Question 7

What is the primary focus of the theory of constraints?

A. Maximising the utilisation of every department independently

B. Reducing all purchase prices simultaneously

C. Identifying and managing the system’s limiting constraint

D. Replacing all forecasts with safety stock

Correct Answer: C. Identifying and managing the system’s limiting constraint

Question 8

Which document specifies the component quantity required per unit of a parent item?

A. Bill of materials

B. Cash-flow statement

C. Routing exception report

D. Warehouse picking wave

Correct Answer: A. Bill of materials

Question 9

Using the classical EOQ formula, if annual demand is 8,000 units, ordering cost is £20 per order and annual holding cost is £2 per unit, the approximate EOQ is:

A. 283 units

B. 400 units

C. 566 units

D. 800 units

Correct Answer: C. 566 units

Question 10

Which statement best characterises a hybrid planning system?

A. It uses only forecast-driven production

B. It uses only customer-triggered replenishment

C. It may use MRP for longer-horizon coordination and Kanban for repetitive short-horizon flow

D. It excludes capacity planning

Correct Answer: C. It may use MRP for longer-horizon coordination and Kanban for repetitive short-horizon flow