Lesson 4 of 6
Supply planning and S&OP
10 min
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Once demand is agreed, supply planning answers whether and how the network can meet it: which plant builds how much, which components to buy, what moves to Toledo, and where capacity runs short. In IBP this is time-series supply planning; it runs in buckets across the network and feeds the monthly S&OP decision. It is not MRP: it works at an aggregate level and leaves exact orders to S/4HANA.
Three supply planning methods
| Method | What it does | When to use it |
|---|---|---|
| Supply planning heuristic (infinite) | Propagates demand through the network without regard to capacity or material limits; shows the gaps | Capacity checks: where will we overload? |
| Finite heuristic (priority-based) | Meets demand in priority order from the available supply and capacity | Allocation when supply is short; which customers get served first |
| Supply planning optimizer | Builds a finite plan that minimizes total cost or maximizes profit under constraints | Network trade-offs: make in Detroit or Chicago, build ahead or lose sales |
Time-series supply planning options as SAP's learning material describes them; check your license for the optimizer.
SAP's training notes that the older supply propagation heuristic is no longer offered to new customers. Contoso's APO SNP used heuristics, so Jonas starts with the infinite heuristic for capacity visibility and plans to test the optimizer for the Detroit / Chicago sourcing choice later.
Worked example: Detroit capacity
Illustrative course data: ASSY-10 can assemble 4,600 alternators a month on two shifts. Consensus demand sourced from Detroit for May is 4,400 CMC-ALT-100 plus 500 CMC-ALT-240. The infinite heuristic plans 4,900 units, 107% of capacity. The capacity key figure shows the overload; the heuristic does not solve it. Jonas has three options for the supply review: shift 300 units of CMC-ALT-100 to Chicago (standard cost $156 instead of $150, so about $1,800 more cost), build 300 ahead in April when ASSY-10 runs at 88%, or add a Saturday shift. The S&OP meeting chooses; IBP shows the consequences of each option as scenarios.
| Option | Effect on May load | Cost or risk |
|---|---|---|
| Shift 300 to Chicago | 4,600 (100%) | About $1,800 more standard cost (300 × $6) |
| Pre-build 300 in April | 4,600 (100%) | Inventory carrying cost, stock in 171B |
| Saturday shift | Capacity rises to about 5,000 | Overtime cost; labor agreement |
Illustrative course data for the May supply review.
The monthly S&OP cycle
S&OP is a monthly management process, not a calculation. IBP supports it with planning views, scenarios, dashboards and process management that tracks steps and owners. The common five-step cycle runs: product review (new and phased-out products), demand review (consensus), supply review (constraints and options), pre-S&OP or reconciliation (financial view, open decisions) and executive S&OP (decisions and approval).
- Work day 1–2History and forecastMonth-end loads, forecast jobs, alerts
- Work day 3–6Demand reviewSunita leads; sales and marketing adjust
- Work day 7–10Supply reviewJonas presents capacity scenarios
- Work day 11–13ReconciliationFinance adds revenue and margin view; Dan joins
- Work day 14Executive S&OPCOO decides; decisions logged
Finance in the S&OP plan
S&OP becomes integrated business planning when the volume plan is valued. IBP multiplies quantities by prices and costs held as key figures or attributes, so the reconciliation step can show revenue, cost and margin per product family. For Contoso, the plan values CMC-ALT-100 at the 240.00 USD list price and the standard cost of 150.00 USD in Detroit (156.00 USD in Chicago). A May plan of 4,400 Detroit units is worth 1,056,000.00 USD of revenue at list price and 660,000.00 USD of standard cost. Dan, the finance process owner, checks that these values come from the current standards and price list, not last year's.
| S&OP input | Owner at Contoso | Source |
|---|---|---|
| Consensus demand | Sunita | IBP demand review |
| Capacity and supply options | Jonas | IBP supply planning scenarios |
| Prices and standard costs | Dan | S/4HANA, loaded each month |
| New and phased-out products | Product management | Product review |
| Decisions and approvals | COO in executive S&OP | Decision log with planning notes |
Who brings what to the S&OP table.
What to test in supply planning
- Network: every location product in scope has a source (production, lane or supplier); an orphan shows as unmet demand.
- Capacity: resource capacity per month matches the agreed shift model for ASSY-10 and Chicago assembly.
- Heuristic result: on a controlled data set of two products and two plants, the propagated requirements equal a hand calculation.
- Constraints: with the finite heuristic, demand priorities decide who is short; check the customer order of priority with Maria, the O2C key user.
- Scenarios: each S&OP option is a scenario with its own capacity and cost view, and the chosen one is promoted.
What would you do?
In the executive S&OP, the COO approves the "shift 300 to Chicago" scenario. Two days later, Chicago's MRP shows no extra requirements. What is the most likely gap?
- Infinite heuristic shows overloads; finite heuristic allocates by priority; the optimizer minimizes cost under constraints.
- IBP supply planning is aggregate; S/4HANA MRP and PP/DS create the exact orders.
- S&OP is a monthly decision process: product, demand, supply, reconciliation, executive review.
- Approved scenarios must reach the baseline before release.
Check your understanding · not graded
Lesson check
1. What does the infinite supply planning heuristic show?
2. Which method minimizes cost under constraints?
3. Which step comes directly before executive S&OP?
4. Shifting 300 alternators from Detroit to Chicago adds about how much standard cost?