Demand Planning for Distributed Manufacturing Demand planning is the process of estimating what products customers or users will require, in what quantities, at which locations, and at what times. In distributed manufacturing, demand planning does more than create a sales forecast. It helps determine: -
Which facilities should produce each product -
Where capacity should be available -
Which materials should be positioned -
How much inventory should be held -
When suppliers should prepare for increased volume -
Which regions may require additional support -
When backup or surge capacity should be activated -
How production should respond to uncertainty Demand planning connects expected market requirements with manufacturing capacity, inventory, sourcing, logistics, and production allocation. A strong demand plan helps the manufacturing network prepare before orders become urgent. Why Demand Planning Matters Distributed manufacturing creates more production options, but it also creates more planning complexity. Demand may vary by: -
Product -
Customer -
Region -
Season -
Configuration -
Service requirement -
Sales channel -
Regulatory market -
Delivery priority If demand is poorly understood, the network may place the wrong capacity, materials, or inventory in the wrong locations. Possible consequences include: Demand planning provides the foundation for coordinated decisions across the network. Demand Planning Is Not the Same as Forecasting Forecasting estimates future demand. Demand planning uses forecasts together with business knowledge, customer information, product strategy, risk, and operational constraints to create an actionable demand view. A statistical forecast may indicate that 10,000 units are likely to be needed next quarter. The demand plan should also determine: -
Which products and configurations are included -
Which customers or regions will require them -
How confident the estimate is -
Which demand is contractually committed -
Which demand is promotional or speculative -
Which manufacturing resources will be affected -
Which risks may cause demand to change Forecasting produces an estimate. Demand planning turns that estimate into a coordinated operational input. Demand Planning Is Not Production Scheduling Demand planning estimates what the network is likely to need. Production scheduling determines when specific work will be performed. Demand planning usually covers a broader and longer period. Scheduling converts the approved demand plan and actual orders into detailed instructions for: -
Facilities -
Machines -
Workers -
Materials -
Tooling -
Inspection Demand planning guides capacity and resource preparation. Scheduling controls execution. Begin with the Demand Requirement A useful demand plan should identify more than total unit volume. It should include: -
Product number -
Product family -
Configuration -
Quantity -
Required period -
Customer -
Delivery location -
Priority -
Probability -
Service level -
Source of demand -
Planning assumptions A forecast of 50,000 total units may be inadequate if those units include many products with different processes, materials, and regional requirements. Sources of Demand Demand information may come from: Each source has different levels of reliability. Confirmed orders should not be treated the same as early sales opportunities. Demand Categories Demand should be segmented according to its characteristics. Confirmed Demand Confirmed demand is supported by: It usually carries the highest planning priority. Forecast Demand Forecast demand is expected but not yet confirmed through a firm order. It may be based on: -
Historical patterns -
Customer estimates -
Market analysis -
Sales projections Dependent Demand Dependent demand results from the requirement for another product. For example, demand for a finished assembly creates demand for: -
Components -
Raw materials -
Packaging -
Replacement tooling Independent Demand Independent demand comes directly from customers or the market and is not calculated from another production requirement. Service Demand Service demand includes: -
Replacement parts -
Repairs -
Maintenance -
Warranty support -
Product upgrades Service demand may be low in volume but highly urgent. Emergency Demand Emergency demand may arise from: -
Disasters -
Infrastructure failures -
Public-health events -
Material shortages -
Equipment breakdowns -
Supply disruption Emergency demand is difficult to forecast precisely and may require planned capacity or inventory buffers. Promotional Demand Promotional demand results from: -
Marketing campaigns -
Discounts -
Product launches -
Seasonal programs -
Customer incentives Promotional plans should be incorporated before production and inventory commitments are made. Speculative Demand Speculative demand is based on opportunities that are uncertain. It may include: -
Unconfirmed projects -
Early-stage sales opportunities -
Possible government contracts -
Potential market expansion Speculative demand should be assigned a probability or treated as a scenario rather than as a firm commitment. Demand Segmentation by Product Products may be grouped according to: -
Volume -
Variability -
Value -
Profitability -
Lead time -
Criticality -
Product lifecycle -
Customization -
Service urgency Different product groups may require different forecasting and planning methods. High-Volume Stable Products Stable products may be forecast using historical patterns and customer commitments. They may support: Variable-Demand Products Products with uneven demand may require: Customized Products Customized products may require planning at two levels: The common components may be forecast, while final configuration is delayed until customer requirements are known. Replacement Parts Replacement-part demand may be based on: -
Installed-base size -
Product age -
Failure rate -
Maintenance schedule -
Regional service history -
Equipment criticality Traditional sales forecasting may not accurately predict replacement-part needs. New Products New products have limited historical demand data. Planning may rely on: -
Comparable products -
Customer commitments -
market research -
sales pipelines -
launch plans -
production pilots Forecast uncertainty should be higher during product introduction. Product Lifecycle and Demand Demand patterns change over the product lifecycle. Introduction Demand is uncertain and may change rapidly. Growth Demand may exceed available capacity if expansion is not planned early. Maturity Demand may become more stable and predictable. Decline Demand may decrease overall but remain important for selected customers. Service Replacement-part and repair demand may continue long after normal production ends. The manufacturing network should adjust capacity, inventory, and facility roles as the product progresses through these stages. Geographic Demand Planning Distributed manufacturing requires demand to be understood geographically. The plan may need to show demand by: -
Country -
Region -
State or province -
Metropolitan area -
Distribution center -
Customer site -
Service territory Geographic planning helps determine: Total global demand may hide major regional imbalances. Customer-Level Demand Planning Some customers may require separate planning because of: Customer-level planning can improve service but may increase complexity. Channel Demand Products may be sold through several channels, including: Each channel may have different: -
Order patterns -
Forecast reliability -
Lead-time expectations -
Return rates -
Inventory practices Demand should not be combined without understanding these differences. Demand Granularity Demand planning should use the level of detail required for operational decisions. Possible levels include: -
Product family -
Product -
Configuration -
Component -
Region -
Customer -
Week -
Month -
Quarter Too little detail makes the plan unusable. Too much detail can create false precision and excessive administrative work. The appropriate level depends on: -
Product complexity -
Lead time -
capacity constraints -
material commonality -
customer requirements -
planning horizon Planning Horizons Demand planning operates across several time horizons. Short-Term Demand Planning Short-term planning may cover days or weeks. It focuses on: -
Firm orders -
Immediate shortages -
order changes -
delivery priorities -
current capacity -
material availability Medium-Term Demand Planning Medium-term planning may cover several months. It supports: -
Supplier commitments -
Workforce planning -
Inventory targets -
Capacity reservations -
Seasonal preparation -
Maintenance scheduling Long-Term Demand Planning Long-term planning may cover one or more years. It supports: -
Facility investment -
Major equipment -
Regional expansion -
Long-term contracts -
Strategic sourcing -
Workforce development -
Network redesign Forecast accuracy generally decreases as the horizon extends. Long-term plans should therefore use ranges and scenarios. Forecasting Methods Different products and demand patterns require different forecasting methods. Historical Time-Series Forecasting Historical methods use previous demand patterns to estimate future requirements. They may consider: -
Trends -
Seasonality -
Cycles -
Recent demand Historical methods are most useful when the future is expected to resemble the past. Moving Average A moving average uses demand from a selected number of previous periods. It can smooth short-term variation. It may respond slowly to significant changes. Exponential Smoothing Exponential smoothing gives greater weight to recent demand. It can be useful for products with relatively stable patterns. Trend Forecasting Trend forecasting estimates continuing growth or decline. It should be used carefully when market conditions may change. Seasonal Forecasting Seasonal methods account for recurring demand patterns associated with: -
Weather -
Holidays -
Agricultural cycles -
Construction seasons -
School calendars -
Budget periods Causal Forecasting Causal methods estimate demand based on variables such as: -
Price -
Promotion -
Economic activity -
Installed base -
Customer usage -
Weather -
Market growth Customer Collaborative Forecasting Customers may provide expected requirements directly. Customer forecasts can improve visibility but should be evaluated against: -
Historical accuracy -
Contractual commitment -
Market conditions -
customer inventory -
ordering behavior Sales-Pipeline Forecasting Sales opportunities may be weighted according to: -
Probability -
Expected quantity -
Expected order date -
Customer readiness -
Project stage Pipeline forecasts should not be treated as confirmed orders. Judgmental Forecasting Experienced employees may adjust statistical forecasts based on information not contained in historical data. This may include: -
Customer changes -
Competitor activity -
Product launches -
regulation -
supply shortages -
economic conditions Judgment should be documented to reduce hidden bias. Composite Forecasting Many organizations combine several methods. For example: -
Statistical forecast -
Customer forecast -
Sales input -
Service demand -
Promotional plan The final demand plan should explain how these inputs were reconciled. Forecast Accuracy Forecast accuracy measures how closely expected demand matched actual demand. Common errors include: -
Overforecasting -
Underforecasting -
Timing error -
Product-mix error -
Geographic error A forecast may be accurate in total while being wrong by product or region. That error can still cause serious manufacturing problems. Forecast Bias Forecast bias is the consistent tendency to forecast too high or too low. Persistent overforecasting may create: -
Excess inventory -
unused capacity -
supplier overcommitment -
obsolete materials Persistent underforecasting may create: -
Shortages -
overtime -
late delivery -
expedited freight -
customer dissatisfaction Bias should be monitored separately from average forecast error. Common Forecast Measures Organizations may use measures such as: No single measure is ideal for every product. Low-volume items and intermittent demand may require different methods. Intermittent Demand Some products have many periods with no demand followed by occasional orders. Examples include: Conventional average-based methods may perform poorly. Planning may rely more on: -
Installed-base analysis -
Failure probability -
Strategic inventory -
On-demand capacity -
Digital inventory Demand Variability Variability should be measured and planned. Sources may include: -
Customer behavior -
seasonality -
promotions -
product mix -
project timing -
market disruption -
regulation -
competitive activity Products with high variability may require: -
Greater capacity cushion -
More safety stock -
Shorter planning cycles -
Flexible suppliers -
Postponement -
Dynamic allocation Demand Uncertainty Uncertainty reflects the limits of what the organization knows. A demand plan should identify: -
Forecast range -
Probability -
Confidence -
Key assumptions -
Trigger events -
downside scenario -
upside scenario A forecast of exactly 12,500 units may be less useful than a range of 10,000 to 15,000 with defined assumptions. Scenario Planning Scenario planning prepares the network for several possible demand outcomes. Common scenarios include: -
Base demand -
High demand -
Low demand -
Delayed launch -
Accelerated growth -
Regional shift -
Supply disruption -
Emergency demand Each scenario should identify the effect on: -
Capacity -
Materials -
Workforce -
Inventory -
Suppliers -
Logistics -
Cost Demand Sensing Demand sensing uses recent information to detect changes sooner than traditional forecast cycles. Data may include: -
Current orders -
Point-of-sale activity -
Customer usage -
inventory movement -
service requests -
web activity -
market events Demand sensing can improve short-term responsiveness. It should not replace long-term capacity planning. Demand Shaping Demand shaping involves influencing demand to better align with available supply. Methods may include: -
Pricing -
Promotions -
Lead-time commitments -
Product substitution -
Order prioritization -
Customer communication -
Delivery scheduling Demand shaping should be coordinated with sales and customer-service teams. Demand Prioritization When demand exceeds supply, the organization may need priority rules. Priority may consider: -
Safety -
contractual obligations -
customer criticality -
equipment downtime -
emergency need -
regulatory requirements -
revenue -
penalty exposure -
fairness Priority rules should be defined before shortages occur. Demand and Capacity Alignment The demand plan should be compared with qualified network capacity. This comparison should identify: The organization should not assume that aggregate capacity can support every product. Demand and Production Allocation Demand planning provides an input to production allocation. The plan helps determine: -
Which facilities should prepare for demand -
How volume should be divided -
Which regions need production support -
When backup sources should receive work -
Where capacity reservations are needed Production allocation converts the demand plan into facility assignments. Demand and Supplier Planning Suppliers need sufficient visibility to prepare: -
Materials -
Workforce -
Equipment -
Tooling -
Capacity -
Subcontractors The organization should communicate demand according to defined categories such as: -
Firm order -
committed forecast -
planning forecast -
upside scenario Suppliers should understand which quantities are binding. Forecast Commitments A customer forecast is not automatically a purchase commitment. Supplier agreements should define: Unclear forecast commitments can create commercial disputes. Frozen, Flexible, and Forecast Zones A demand plan may use time fences. Frozen Zone Near-term requirements are fixed except under approved exception. Flexible Zone Changes are allowed within defined limits. Forecast Zone Longer-term quantities are planning estimates rather than firm commitments. Time fences help suppliers and facilities make appropriate decisions. Demand and Inventory Inventory can protect against demand uncertainty. The demand plan should support decisions concerning: -
Raw materials -
Common components -
Work in process -
Finished goods -
Regional inventory -
Service parts -
Safety stock Inventory should be positioned according to: -
Demand variability -
Lead time -
Product value -
Obsolescence -
service requirements -
production flexibility Safety Stock Safety stock protects against uncertainty in demand and supply. The required amount may depend on: -
Forecast error -
Lead-time variability -
service target -
supplier reliability -
product criticality -
demand pattern Safety stock should not be used to hide poor planning or unreliable production. Postponement Postponement delays final product differentiation until demand becomes clearer. A common platform may be produced in advance. Regional or local facilities may later complete: -
Configuration -
Packaging -
labeling -
software loading -
accessories -
final assembly Postponement can reduce forecast error at the finished-product level. Demand and Digital Inventory Digital inventory may support products with: The demand plan should still account for: -
Materials -
qualified capacity -
tooling -
production lead time -
delivery Digital files alone do not satisfy demand. Demand and Logistics Demand location affects: -
Inventory placement -
warehouse capacity -
production region -
carrier requirements -
delivery time -
customs Geographic demand planning should be coordinated with logistics. Demand and Product Configuration Many products exist in numerous configurations. Forecasting every final configuration may be difficult. The organization may plan: This reduces the risk of producing the wrong variation. Demand and Common Components Products may share common: -
Materials -
components -
subassemblies -
tooling -
capacity The demand plan should identify aggregate requirements for shared resources. This can improve purchasing leverage and reduce shortages. Demand and Material Requirements Planning The approved demand plan may feed material requirements planning. MRP converts expected production into requirements for: -
Raw materials -
Components -
Purchase orders -
Production orders -
Timing Poor demand data will create poor material plans. Demand and Sales and Operations Planning Sales and operations planning aligns: -
Demand -
Supply -
Capacity -
Inventory -
Finance -
customer commitments Demand planning is a major input to S&OP. In distributed manufacturing, S&OP may also include: -
Regional facilities -
Contract manufacturers -
Critical suppliers -
logistics providers -
backup capacity Demand and Integrated Business Planning Integrated business planning extends demand and supply coordination into broader financial and strategic planning. It may connect: -
Revenue -
Margin -
Working capital -
Capital investment -
Capacity -
Inventory -
Risk -
Product strategy Cross-Functional Demand Planning Demand planning should not be owned by sales alone. Useful participants may include: -
Sales -
Marketing -
Operations -
Supply chain -
Procurement -
Finance -
Product management -
Customer service -
Engineering -
Service and maintenance Each function provides different information. Demand-Planning Ownership The organization should define who is responsible for: -
Creating the baseline forecast -
Collecting customer input -
Reviewing promotions -
Approving overrides -
Measuring accuracy -
Publishing the final plan -
Communicating with suppliers -
Managing exceptions Ownership should be clear even when the process is collaborative. Consensus Demand Planning A consensus process combines functional inputs into one approved plan. The objective is not to average every opinion. The objective is to resolve differences using: -
Evidence -
assumptions -
risks -
financial impact -
customer knowledge The final plan should have one approved version. Forecast Overrides Manual changes to forecasts may be necessary. Each override should document: -
Original forecast -
Revised forecast -
Reason -
Owner -
Assumption -
Expected duration -
Approval Tracking overrides helps determine whether they improve accuracy. Baseline Forecast A baseline forecast is generated before manual adjustments. Comparing the baseline with the final plan helps evaluate: Exception-Based Planning Large networks may contain too many products for equal manual attention. Exception-based planning focuses on items with: -
Large forecast error -
High value -
High criticality -
Capacity risk -
Material constraints -
unusual demand change -
customer urgency This allows planners to concentrate on the most important issues. Demand Classification Products may be classified according to value and variability. One approach may distinguish: Each category can use different: -
Forecast methods -
Review frequency -
Service levels -
Inventory policies -
Capacity strategies Demand Data Quality Demand planning depends on reliable data. Common data problems include: -
Duplicate orders -
Incorrect product identifiers -
Missing customer locations -
Cancelled orders remaining open -
Unrecorded promotions -
Incorrect historical demand -
Returns counted as demand -
Stock transfers counted as customer sales Data should have: -
Defined ownership -
validation rules -
correction procedures -
update schedules -
consistent definitions Lost Sales and Unconstrained Demand Historical shipments may understate actual demand when products were unavailable. The organization should distinguish among: -
Orders received -
Orders shipped -
Orders cancelled -
Lost sales -
Backorders -
Customer substitutions Demand history based only on shipments may repeat past shortages. Returns and Demand Returns may distort demand records. The organization should separate: -
New demand -
Replacement demand -
Returns -
Warranty replacements -
Rework -
Inventory transfers Demand Signals Across the Network Different participants may see different demand signals. For example: -
Retailers see consumer purchases. -
Distributors see replenishment orders. -
Manufacturers see distributor orders. -
Suppliers see production releases. Information delays can amplify demand variation. The Bullwhip Effect The bullwhip effect occurs when small changes in customer demand create larger order swings upstream. It may result from: Distributed networks can reduce the effect through better information sharing and coordinated planning. They can also amplify it if each participant creates separate forecasts. Collaborative Planning Collaborative planning allows manufacturers, suppliers, customers, and logistics providers to share relevant demand information. Potential benefits include: Shared data should be: -
Accurate -
appropriately protected -
clearly classified -
updated regularly Demand Confidentiality Demand information may reveal: -
Product launches -
Customer relationships -
Sales volumes -
Market strategy -
Commercial forecasts Access should be restricted according to role and need. Suppliers may need product-level forecasts without receiving broader customer or market information. Demand Planning and Cybersecurity Demand systems may be targets for: -
Data theft -
manipulation -
ransomware -
service interruption A corrupted forecast can affect: -
Purchasing -
capacity -
inventory -
production -
finance Controls may include: -
Access management -
approval workflows -
backups -
audit logs -
validation -
incident response Demand Planning Systems Relevant systems may include: -
Enterprise resource planning -
Customer relationship management -
Demand-planning software -
Advanced planning systems -
Business intelligence platforms -
Supplier portals -
Service-management systems The systems should support one controlled and explainable demand plan. Artificial Intelligence in Demand Planning Artificial intelligence may support: -
Pattern recognition -
Forecasting -
anomaly detection -
customer segmentation -
demand sensing -
scenario generation AI can process large amounts of data. It may still fail when: Human review remains necessary. Forecast Explainability Planners should understand why a forecast changed. An explainable process may identify: -
Historical trend -
seasonal effect -
customer forecast -
promotion -
market assumption -
manual override Unexplained model output can reduce trust and make errors difficult to correct. Demand Planning During Disruption Disruption may change both demand and supply. Examples include: The organization may need to: -
Reforecast rapidly -
prioritize critical customers -
activate alternate facilities -
release strategic inventory -
revise allocation -
communicate constraints -
create emergency scenarios Demand Planning During Shortage When demand exceeds available supply, the organization should use controlled allocation rules. Possible considerations include: -
Safety -
essential services -
contractual commitments -
customer criticality -
fairness -
regulatory requirements -
long-term relationships Sales should not promise volume that the network cannot deliver. Demand Planning for Emergency Manufacturing Emergency demand planning should identify: -
Critical products -
likely scenarios -
required response time -
minimum quantities -
priority users -
acceptable substitutes -
qualified facilities -
material availability Exact demand may be unknown. The objective is to establish reasonable preparedness. Demand Planning for Replacement Parts Replacement-part planning may use: Part criticality may matter more than forecast volume. A low-volume part can cause major customer downtime. Demand Planning for Repair and Remanufacturing Demand may be driven by returned products rather than customer orders alone. Planning should consider: -
Return rate -
Product condition -
repairability -
recovery yield -
component availability -
turnaround target -
regional return flow Demand Planning for New Product Introduction New product plans should include: Capacity should not be based only on an optimistic launch forecast. Demand Planning for Product Retirement When a product is discontinued, the organization should estimate future: -
Service demand -
replacement-part demand -
warranty requirements -
regulatory obligations -
customer commitments Final production quantities should balance: Demand and Financial Planning The demand plan affects: -
Revenue -
Gross margin -
Working capital -
Inventory -
Purchasing -
Overtime -
Capital investment Finance should understand both the expected demand and the uncertainty surrounding it. Demand Planning Metrics Useful measures may include: Metrics should support improvement rather than punishment. Punitive use of forecast metrics may encourage manipulation. Measuring Forecast Value An advanced demand-planning process may evaluate whether each adjustment improved the baseline forecast. This helps determine whether: -
Sales input adds value -
Customer forecasts are reliable -
Promotions are estimated accurately -
Statistical models are appropriate -
Manual overrides improve results Review Frequency Demand plans may be reviewed: -
Daily for urgent products -
Weekly for short-term changes -
Monthly for standard planning -
Quarterly for long-term strategy -
Immediately after major disruption Review frequency should reflect: -
Demand volatility -
Product criticality -
Lead time -
network flexibility Demand Planning Governance Governance should define: -
Data sources -
Forecast methods -
Approval authority -
Override rules -
planning calendar -
time fences -
supplier communication -
performance measures -
exception handling The organization should maintain one approved demand plan. Common Demand-Planning Mistakes Treating Sales Targets as Demand Forecasts A goal is not evidence of customer demand. Using One Forecast Number Ranges and scenarios better represent uncertainty. Forecasting Only Total Volume Product, regional, and timing errors can still create shortages. Using Shipments as the Only Demand History Past shortages may hide unmet demand. Ignoring Product Mix Products may consume different materials and capacity. Ignoring Regional Differences Global totals may conceal local shortages and excess inventory. Treating Customer Forecasts as Firm Orders Customers may change plans without contractual commitment. Failing to Track Bias Consistent over- or underforecasting creates avoidable cost. Overriding Forecasts Without Documentation Uncontrolled judgment makes improvement difficult. Planning Without Capacity Feedback An unconstrained demand plan must still be reconciled with supply capability. Sharing Forecasts Without Clear Commitment Rules Suppliers may overinvest or underprepare. Failing to Update the Plan Demand information becomes outdated quickly. Demand-Planning Questions Organizations should ask: -
What products are likely to be required? -
In what quantities? -
When will they be needed? -
Where will demand occur? -
Which demand is confirmed? -
Which demand is forecast? -
How accurate has the forecast been? -
Is there persistent bias? -
Which products have intermittent demand? -
Which customers require special treatment? -
How will demand affect capacity? -
How will it affect materials and inventory? -
Which suppliers need visibility? -
Which scenarios should be prepared? -
How will shortages be prioritized? -
Who owns the final demand plan? -
How often will the plan be reviewed? A Practical Demand-Planning Process 1. Collect Demand Data Gather orders, forecasts, sales plans, service records, market information, and customer input. 2. Clean and Classify the Data Remove duplicates, correct identifiers, separate returns, and classify demand by certainty and source. 3. Segment Products and Customers Group demand according to volume, variability, value, criticality, lifecycle, region, and customer requirements. 4. Create a Baseline Forecast Use appropriate statistical, causal, or installed-base methods. 5. Add Business Intelligence Incorporate customer changes, promotions, launches, service needs, and market events. 6. Develop Scenarios Create base, low, high, delayed, disruption, and emergency cases where relevant. 7. Build the Consensus Plan Resolve differences among sales, operations, finance, service, and product teams. 8. Compare Demand with Supply Evaluate capacity, materials, inventory, suppliers, logistics, and constraints. 9. Resolve Gaps Adjust capacity, inventory, allocation, customer commitments, or demand-shaping actions. 10. Approve and Publish the Plan Create one controlled version for internal and external use. 11. Monitor Actual Demand Track orders, consumption, cancellations, returns, and regional shifts. 12. Measure and Improve Review accuracy, bias, overrides, assumptions, and planning outcomes. Minimum Demand-Planning Requirements A distributed manufacturing demand plan should include: -
Defined products and configurations -
Quantities -
Timing -
Geographic location -
Demand source -
Confidence or probability -
Confirmed and forecast demand separation -
Product and customer segmentation -
Forecast assumptions -
Scenario ranges -
Capacity comparison -
Material implications -
Inventory implications -
Supplier communication rules -
Priority rules -
Approval ownership -
Review cadence -
Forecast-performance measures A Working Definition DistributedManufacturing.info defines demand planning as: The structured process of estimating, classifying, reviewing, and communicating future product requirements by quantity, timing, configuration, customer, and location so that manufacturing capacity, suppliers, materials, inventory, logistics, and production allocation can be prepared and coordinated across the network. Demand planning does not eliminate uncertainty. It makes uncertainty visible enough for the manufacturing network to prepare, respond, and make better decisions. | 