Balancing Demand and Supply: Coordinating Demand Planning and Supply Planning Processes

In brief: When demand planning and supply planning are run by different teams, the sales plan and the production plan often rest on neither the same figures nor the same assumptions. This is especially visible for seasonal products: for durable goods such as air conditioners, white goods, garden products, and heaters, demand fluctuates with the season and with campaigns, and in peak periods exceeds the factory's normal capacity. This article covers how the two processes are coordinated in establishing the demand-supply balance. It explains, with a simple quarterly example, how factors such as seasonality and campaigns are reflected in the plan on the demand side, and how demand fulfillment, production leveling, and hybrid methods are designed on the supply side. For the general framework of S&OP, the What Is Sales and Operations Planning (S&OP)? page can be consulted.

Why Should Demand and Supply Planning Be Coordinated?

The demand plan answers the question "what can be sold?" without taking the capacity constraint into account. The supply plan shows how much of this demand can be met with current capacity, materials, and inventory targets. The difference between the two plans, that is, the gap between demand and achievable supply, is the subject of S&OP decisions. When the two processes do not work with the same assumptions, this gap appears different from what it really is; the sales side notifies production of the campaign calendar late, while the production side does not reflect capacity limits in the demand plan.

The purpose of coordination is to make both processes work from the same figures. For this, demand planning puts campaign, price, seasonality, and new product assumptions in writing; supply planning presents with what resource and at what cost it will meet this demand, together with its options. The decision is then taken in the monthly S&OP cycle, in a way where who decides what in each meeting is defined in advance (see Which Decision in Which Meeting in the S&OP Cycle? Calendar, Decision Logic, and Scenarios).

Demand Side: Seasonality, Campaigns, and Other Factors

In durable goods, the demand plan does not consist of a single forecast figure; it is read as the sum of several components. Monitoring the components separately allows the supply side to see which part is permanent and which part is temporary.

• Baseline demand: The usual sales level of the product family once season and campaign effects are removed.
• Seasonality: Demand that rises in summer months for air conditioners and coolers and in winter months for heaters; the calendar and weather conditions can change the timing and intensity of the season. Calendar effects such as holidays and vacation periods are handled separately.
• Campaigns and promotions: Price discounts, installment plans, and dealer campaigns pull demand forward and can cause a dip in the weeks after the campaign. How the campaign effect is separated is covered in the article How to Forecast Promotion Impact: Campaign Types and Uplift Calculation.
• Channel stocks: Pre-season loadings to dealers occur before consumer demand; shipments and consumer sales (sell-out) should be monitored separately.
• New products and economic conditions: Model changes, launch calendars, price increases, and consumer confidence can shift the level of seasonal demand.

Demand planning combines these components to present the unconstrained demand plan and a reasonable uncertainty range. Stating the range explicitly is important; supply planning should make capacity and inventory decisions not on a single figure but on the likely demand range.

Supply Side: Demand Fulfillment, Production Leveling, and Hybrid Methods

When peak demand exceeds normal capacity, supply planning has three basic approaches available. All three answer the same question, namely with which resource, at what time, and at what cost demand will be met, in a different way.

Demand Fulfillment (Chasing Demand)

In this approach, each period's production is set equal to that period's demand. Inventory stays low, but capacity must be changed continuously. In peak periods, additional shifts, overtime, temporary labor, or subcontracted production are brought in; when demand falls, these resources are withdrawn. It is applicable when the peak is narrow and short; as the peak lengthens, the cost of side effects such as hiring, training, quality fluctuation, and subcontractor dependence rises.

Production Leveling (Level Production)

The factory runs at a constant rate throughout the year; the surplus produced in low-demand periods is put into stock, and sales are made from this stock in the peak quarters. A stable workforce, a predictable shift pattern, and low unit cost are its strengths. Its cost is high inventory; in addition to storage and insurance costs, inventory ties up cash and carries obsolescence risk in situations such as model changes or the end of the season.

Hybrid Approach

Base production is kept level, limited additional capacity (overtime or an additional shift) is used in the peak quarters, and a certain amount of pre-build stock is created. Its strength is providing a balance among costs; its cost is that it requires planning discipline. Which products will be pre-built, within what limit overtime will be kept, and when subcontracting will be brought in must be determined in advance.

In comparing the three approaches, not only production cost but also inventory carrying cost, overtime premium, subcontracting cost, cash requirement, and service level are evaluated together. The lowest total-cost option varies with the product family and the length of the season.

Numerical Example: Quarterly Demand and Supply Plan

In the example, a product family's annual demand is 440 thousand units and normal production capacity is 110 thousand units per quarter. All figures are in thousands of units and are for illustration purposes. First, the demand plan is broken down into its components.

Demand in the second and third quarters is above normal capacity (110). Supply planning addresses this demand with three approaches.

In the demand fulfillment approach, production follows demand one for one. 150 thousand units must be produced in the second quarter and 140 thousand units in the third quarter; this is 40 and 30 thousand units above normal capacity respectively and requires an additional shift, temporary labor, or subcontracting. In the first and fourth quarters, on the other hand, capacity goes unused. Inventory is low, but capacity cost and operational risk increase.

In the production leveling approach, 110 thousand units are produced every quarter. No overtime is needed; ending inventories run at 80, 40, 10, and 40 thousand units and average 42.5 thousand units. Its cost is the inventory carried throughout the year, which reaches 80 thousand units before the peak.

In the hybrid approach, production is raised to 120 thousand units with overtime in the peak quarters (the second and third quarters) and reduced to 90 thousand units in the fourth quarter because demand falls. Ending inventories are 60, 30, 10, and 20 thousand units; average inventory is 30 thousand units, which is about 30% lower than with level production. The hybrid approach reduces inventory cost by accepting the overtime cost.

Which approach is preferred is determined by comparing the sum of the overtime premium and inventory carrying cost: if the sum of the hybrid approach's overtime and inventory cost is lower than the inventory cost of level production, the hybrid approach is chosen. The calculation must be made with the actual costs of the product family and repeated with at least two scenarios, optimistic and pessimistic, for the demand range.

The real decision in seasonal products concerns the timing of production;
this decision is a trade-off among demand uncertainty, inventory, capacity, and cash.

How Is Coordination Achieved in the S&OP Cycle?

These decisions are not made in a single monthly meeting; they are spread across the 12-18 month S&OP horizon. The stages of the cycle carry coordination as follows:

• Demand review: Seasonality, campaign, price, and new product assumptions are approved; the campaign calendar is communicated to the supply side at this stage.
• Supply review: It is determined which part of the demand plan can be met with current capacity, materials, and inventory targets; demand fulfillment, production leveling, and hybrid scenarios are prepared together with cost, inventory value, cash requirement, and service level.
• Pre-S&OP: Gaps within the authority limit, such as overtime within policy, are closed; issues exceeding the limit are prepared for management as a decision proposal with at most two or three options.
• Management S&OP: The pre-build quantity, the limits for overtime and subcontracting, and, if necessary, postponing a campaign or allocation between customers are approved.

The process does not end when the season starts. As demand deviates from the plan, production for the remaining months and channel allocation are revisited in the monthly cycle; by monitoring separately which component (baseline demand, seasonality, campaign) the deviation comes from, it is fed back into the demand assumptions (see How to Measure and Interpret Forecast Error: Bias and Percentage Error Metrics).

Pre-Build Stock and End-of-Season Risk

• With the most predictable products: Pre-peak stock is built with high-volume core models that have low forecast error.
• With common components: Where the variant decision can be postponed, semi-finished goods or common components are stocked instead of finished goods.
• Not with new models: For products approaching a model change or with high demand uncertainty, pre-build stock carries obsolescence risk.
• Taking channel stocks into account: Pre-season loading of dealers takes place before consumer demand; dealer stocks must be monitored separately.

When the season closes, the remaining stock is either carried over to the next season or cleared with discounts; both options are costly. For this reason, it is recommended that in the second half of the season production be adjusted according to the actual sales rate rather than the pre-build plan. The end-of-season stock target and discount decisions must also be on the S&OP agenda.

Technology and Digitalization: Integrated Demand and Supply Planning

When the demand plan and the supply plan are kept in separate files and systems, most of the coordination meetings are spent reconciling figures. Current planning systems combine the two plans in a common data model, calculate capacity-constrained multi-period scenarios before the meeting, and allow meeting time to be devoted to evaluating options.

Enterprise Resource Planning (ERP) is the enterprise transaction system that records orders, inventory, purchasing, production, and finance transactions in a common database; it is the master data and transaction source for planning. It provides sales, inventory, capacity, and cost actuals and is the source of the cost parameters for the demand fulfillment, production leveling, and hybrid methods.

Advanced Planning and Scheduling (APS) is a planning system based on optimization and heuristic methods that produces feasible plans and schedules by considering capacity, material, and priority constraints at the same time. It combines demand, supply, and capacity plans in a common data model; it calculates the cost of the demand fulfillment, production leveling, and hybrid scenarios in the same model and presents them comparatively to the meeting.

Artificial Intelligence (AI) and Machine Learning (ML) are methods that learn patterns from data to produce forecasts, classifications, and recommendations; machine learning is the sub-field of artificial intelligence that learns from data. By modeling seasonality, campaign, price, weather, and calendar effects together, they separate baseline demand from the campaign effect and narrow the likely range of seasonal demand.

Digital Twin is a virtual model of a factory, line, or supply network that is updated with data; it allows scenarios to be tested without affecting the physical system. It makes it possible to test shift, overtime, subcontracting, and warehouse capacity options on the virtual model.

Internet of Things (IoT) is the infrastructure in which sensors on machines, vehicles, warehouses, and products transmit data automatically over a network; location, temperature, status, and consumption data are collected without human input. Usage data from connected products in the field serves as a leading indicator of seasonal demand and renewal demand.

Business Intelligence (BI) is the analytics layer that combines data from different sources and presents it to decision makers through dashboards and reports. It provides the dashboard that monitors the plan-versus-actual gap, channel stocks, and inventory build-up throughout the season.

The division of tasks must be clearly defined. The system separates baseline demand from the campaign effect, calculates scenarios, flags risks, and prepares summaries. Approving the campaign calendar, the pre-build quantity, the limits for overtime and subcontracting, and the choice among options is the decision of the demand and supply planning teams and management. Artificial intelligence cannot know with certainty how weather conditions and the market will evolve over the medium-term S&OP horizon; for this reason, instead of relying on a single forecast, it is recommended to test optimistic and pessimistic scenarios separately on the APS or digital twin.

What the season will bring cannot be known with certainty;
but which step will be taken in which scenario can be determined in advance.

Implementation: Checklist

• Break the 12-18 month demand plan down by product family into baseline demand, seasonality, and campaign components.
• Approve the campaign calendar in the demand review and communicate it to supply planning in the same meeting.
• Clarify the limits and costs of normal capacity, overtime, and subcontracting.
• Cost the demand fulfillment, production leveling, and hybrid scenarios with the same template.
• Determine the product and component list for pre-build according to forecast error and obsolescence risk.
• Monitor dealer and channel stocks separately throughout the season; in the second half of the season, update production monthly according to the actual sales rate.
• Combine demand and supply plans in a common data model; prepare scenario calculations before the meeting with the planning system.

Related Articles

• Which Decision in Which Meeting in the S&OP Cycle? Calendar, Decision Logic, and Scenarios
• Demand Planning and S&OP in Fast-Moving Consumer Goods (FMCG): 5 Critical Topics
• How to Forecast Promotion Impact: Campaign Types and Uplift Calculation

Frequently Asked Questions

Why are the demand plan and the supply plan prepared separately?

The demand plan answers "what can be sold?" without taking the capacity constraint into account; the supply plan takes capacity, material, and inventory constraints into account. Preparing them separately prevents constraints from hiding demand and makes the gap visible. On the other hand, assumptions and figures should be kept in a single data source and the two plans combined in the monthly S&OP cycle.

Is level production, chasing demand, or the hybrid approach cheaper?

There is no single correct answer to this question. When inventory carrying cost is low and demand is predictable, level production stands out. When capacity flexibility is cheap and obsolescence risk is high, chasing demand is advantageous. In most companies, the lowest total cost is achieved with the hybrid approach; the decision rests on calculating the overtime premium, subcontracting, inventory carrying cost, and service level together.

When should the campaign calendar be communicated to supply planning?

It is recommended that the campaign calendar be prepared at least as far ahead as the S&OP horizon and approved in the demand review meeting. In periods with capacity or material constraints, the timing of the campaign is evaluated as an option in the supply review; shifting a campaign by a few weeks is often less costly than overtime or subcontracting.

When should pre-building start?

The start date is calculated backward from the peak. The latest date by which the capacity gap at the peak can be closed with idle capacity beforehand is taken as the starting point. Components with long lead times, however, need to be planned even before this date.

What do artificial intelligence and digital planning contribute to demand and supply coordination?

Artificial intelligence models seasonality, campaign, price, and weather effects together, separating baseline demand from the campaign effect and narrowing the demand range. An integrated planning system, in turn, combines the two plans in a common data model and calculates scenarios before the meeting. Approving the campaign calendar, the pre-build and overtime limits, and the choice among options remain the decision of the demand and supply planning teams and management.

References

• Wallace, T. F., & Stahl, R. A. (2008). Sales & Operations Planning: The How-To Handbook (3rd ed.). T. F. Wallace & Company.
• Nahmias, S., & Olsen, T. L. (2015). Production and Operations Analysis (7th ed.). Waveland Press.
• Chopra, S., & Meindl, P. (2019). Supply Chain Management: Strategy, Planning, and Operation (7th ed.). Pearson.

Related Optimum Planlama Trainings

Institutions We Work With in Durable Goods

Some of the institutions to which we provide training and/or consulting services in the durable goods sector are listed below. For all sectors, you can visit our References page.

ABB Elektrik, 2011

Agt, 2021

Akplas Plastik, 2010

Aksu Tost, 2021

Alarko-Carrier, 2011, 2012

Alfemo, 2017

Artema, 2016

Bahariye Halı, 2012

Besa, 2012

Bonna, 2021, 2022

Boytaş Mobilya, 2010

BSH Ev Aletleri, 2012, 2019

Chicco, 2012

Copreci, 2015

Cross Jeans, 2017

Çamsan Ordu, 2023

Çilek Mobilya, 2012–2021

Çimstone, 2011

Çokyaşar Holding, 2024

Daikin, 2020

Deceuninck, 2013

E.c.a., 2021, 2023

Elsel, 2016

Erciyes Anadolu Holding, 2021

EssilorLuxottica, 2022, 2023

Family Group, 2014

Foxconn TR, 2017

İstikbal Mobilya, 2012

Kale Musluk, 2013, 2018

Kastamonu Entegre, 2010–2018

Kilim Mobilya, 2013, 2014

Klimasan, 2011

LAV-Gürallar, 2020

Lazzoni Mobilya, 2014, 2016

Mavili Elektronik, 2014, 2017

Neşe Plastik, 2011

Panasonic Electric Works, 2022, 2023

Penti, 2011

Pina, 2015

Rengarenk Mobilya, 2017

Robert Bosch Bursa, 2015

Samet Kalıp, 2010, 2011

Silter, 2014

Tense Elektronik, 2023

Turkuaz Seramik, 2017, 2025

Türk Demirdöküm, 2011

Ukinox, 2016

Vestel, 2024

Vezirköprü, 2019

Vitra, 2016

Yatsan, 2023

Comments

“The training was a useful and comprehensive training with the end-to-end integration of the S&OP process into the supply chain, explaining each step and explaining the roles and responsibilities in these steps.”

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