The 6 Supply Chain Planning processes
SCP is organized into six processes that feed one another. Integration matters more than order: the output of one is the input of the next.
The literature varies — and varies even more depending on whether you look through a conceptual or a technological lens. Some material focuses on S&OP and IBP, some on demand planning, some on operations. One reference that synthesizes these perspectives well is Gerald Feigin, PhD in applied mathematics from Harvard and consultant to large manufacturers: he splits SCP into three broad areas — demand planning, sales and operations planning (S&OP), and inventory and supply planning. Breaking down the last one — which in practice carries quite distinct functions and technologies, as Gartner itself notes — and with a touch of consulting license, we arrive at the six processes we use day to day in projects.
1. Demand Planning
Forecasting future demand is only half the job: the process also manages variability, accuracy and forecast bias — and, from a management standpoint, treating the root cause of errors is worth more than chasing zero error, because uncertainty is intrinsic to the process. It involves cleansing the demand history (removing noise from known events such as promotions and stockouts), statistical methods with automatic per-product selection and, increasingly, AI-assisted forecasting.
Key outputs: demand forecast and variability (mean and standard deviation), accuracy and bias — wMAPE, mMAPE and mMPE.
2. S&OP e IBP
S&OP (Sales & Operations Planning) seeks consensus across sales, operations, marketing, logistics and finance around a single number: what the company expects to sell, produce and fulfill in each horizon, balancing service, revenue and cost. IBP (Integrated Business Planning) is its evolution: it adds portfolio management and financial integration (FP&A) to the cycle — data gathering, demand planning, supply planning, scenario review and the executive meeting.
Key outputs: sales, production and purchasing plan + revenue, cost, margin and plant-utilization expectations.
3. Inventory Planning
Inventory connects service level and cost: it is what absorbs demand and supply variability. The process defines strategies by item segment (ABC, PQR, XYZ curves), policies such as safety stock and standard lot sizes, and at which link to hold stock — raw material, work-in-process or finished goods. Methodologies such as DDMRP support dynamic, responsive sizing, and simulating volumes, lead times, service level and cost per scenario is the heart of the decision.
Key outputs: inventory policies and targets by item and segment, projected coverage and financial impact per scenario.
4. Production Planning (MPS)
Defines what will be produced in each period to meet the inventory plan and the order book — from the annual budget to the Master Production Schedule (MPS), revised in weekly S&OE (Sales & Operations Execution) cycles. This is where companies struggle most: the aggregate S&OP plan does not reveal the real mix, and production constraints — finite capacity, setups, materials — are rarely handled by the spreadsheets that dominate this stage.
Key outputs: finite-capacity MPS per period, integrated with inventory and the order book.
5. Supply Planning
Starts from S&OP and the MPS to calculate material requirements, balancing shortage risk, replenishment lead times and cost. Agility is vital here: when demand or a supplier changes, you must quickly see which materials are affected, in what quantity and by when — without that, stockouts and overstock end up coexisting in the same operation.
Key outputs: purchasing plan (MRP) connected to a finite-capacity MPS and responsive to demand, as DDMRP advocates.
6. Distribution Planning
Closes the cycle by defining the logistics network: where distribution centers sit, what volumes stay at each site and with which transport strategy. DRP and DRP II methods organize distribution connected to the production and inventory plans; strategies such as milk run, cross-docking and route optimization make transport efficient — and the environmental impact of transport is increasingly part of the objective function.
Key outputs: distribution plan per DC and transport requirements, integrated with inventory and production.
The S&OP / IBP cycle
The traditional stages of the process. In yellow, the ones that exist only in IBP.
01 · IBP
Portfolio management
05
Scenario review (pre-S&OP)
06 · IBP
Financial integration
You will notice that some stages also appear in other SCP processes. The difference here is the focus: in S&OP and IBP, what is at stake is collaboration and consensus across functions — not the calculation itself.
Gartner also positions Order Promising (ATP/CTP — promising delivery dates based on the plan, not guesswork) and Production Scheduling as SCP — detailed production scheduling, the very reason Siemens Opcenter APS (formerly Preactor) exists, the world leader in the category. Advanced analytics, AI and the digital supply chain twin round out the package, recommended for more mature operations.
