Decision intelligence library
Production Planning: how to make the decision well
Production planning decides what to make, when each operation should run, and which capacity should perform it while respecting orders, routes, and delivery commitments.
Written and reviewed by Optivise. Published and updated 2026-08-14.
Why this decision is hard
Manual production plans break when multiple orders share machines, jobs need to move through workshops in sequence, and due dates compete for the same capacity. A useful method distinguishes rules that cannot be broken from preferences that can be traded off. It also records the objective before comparing alternatives, so a team can explain the result rather than defend a black box.
Worked example
Inputs: Use the rows below as a small decision set. Manual baseline: A planner manually staggers jobs by expected dates, often missing machine conflicts or downstream workshop waits. Improved result: Smart Planner returns operation start dates, machine assignments, finish dates, delay days, and a solve summary that planners can inspect. Trade-off: A plan that improves the stated objective may still leave lower-priority work unassigned or delayed; surface those exceptions for review.
| Order | Product | Qty | Workshop route | Planned start | Due date |
|---|---|---|---|---|---|
| 001-W33 | Power supply | 200 | SMT > Assembly > Packaging | 2022-08-03 | 2022-08-11 |
| 002-W31 | Power supply | 500 | SMT > Assembly > Packaging | 2022-07-15 | 2022-07-25 |
| 003-W32 | Speaker | 1000 | Assembly > Packaging | 2022-07-20 | 2022-08-04 |
Method comparison
Manual ordering is quick but misses interacting constraints. Scoring compares preferences but does not guarantee feasibility. Optimization evaluates feasible choices against an explicit objective.
Implementation workflow
- 1. Put master orders and detailed operation rows into the template.
- 2. Open Smart Planner from the Google Sheets sidebar.
- 3. Ask Smart Planner to read the workbook and build a production schedule.
- 4. Review constraints, objective, and machine assumptions before solving.
- 5. Run optimization and write the schedule and solve summary back into Sheets.
Evaluate the result
Check feasibility first, then measure the objective, inspect exceptions, compare key scenarios, and confirm that the inputs and assumptions are still current.
Where it applies
- Manufacturing
Plan production, jobs, capacity, and delivery commitments across constrained operations.
Choose how to use Optivise
Use the same decision intelligence through an AI agent, a familiar work tool, or a shared enterprise workflow.
Agent Optimization Engine
Use Optivise through the AI agent you already work with.
Explore Agent EngineSmart Planner
Start from a familiar spreadsheet and the operational data you already maintain.
Explore Smart PlannerOptivise Platform
Build persistent, shared, and governed decision workflows for your team.
Explore Optivise PlatformQuestions people ask
Can I optimize a production schedule directly in Google Sheets?
Yes. Smart Planner reads the active sheet, identifies orders, operations, machines, constraints, and objectives, then writes the optimized schedule back to output tabs.
What constraints should a production planning spreadsheet include?
Start with order due dates, operation durations, workshop route, machine capacity, precedence rules, and any release dates or priority weights.
Sources and method
This guide describes a general decision framework. It does not claim a quantified result. Source context: APICS Dictionary: production planning .