Image caption: The BOM links every finished product to each component and raw material behind it.
KEY TAKEAWAY: Automated production material planning is only as reliable as the Bill of Materials (BOM) it is built on. An accurate, multi-level, change-controlled BOM that is integrated with inventory and purchasing turns raw material planning from an error-prone manual task into a process that can be calculated, audited and scaled. For executives, the result is more predictable production cost, healthier stock levels and faster procurement decisions.
Many manufacturers still build their material lists from spreadsheets maintained separately by engineering, production and purchasing. As a result, production material requirements are calculated repeatedly under different assumptions, and the gaps only surface when a line stops because a component is missing or when the warehouse fills up with materials nobody needs. A more dependable approach is to treat the BOM as the single source of truth and let the system calculate material requirements automatically from it. This article examines the seven aspects that decide whether that approach succeeds, from structural foundations to cross-functional integration.
BOM Fundamentals: Accuracy and Product Component Structure
A BOM is a structured list of every component, raw material and quantity needed to make one unit of a product. The accuracy of the BOM sets the accuracy of everything calculated on top of it: if a single component is recorded incorrectly, the error is multiplied across every production plan, purchase order and cost calculation.
A sound BOM records at least four elements on every line: a unique component code, a description and specification, the quantity per unit of product with its unit of measure, and a marker showing whether the component is purchased, manufactured in-house or subcontracted. Discipline on these four elements prevents the most common errors, namely inconsistent units (kilograms in one place and grams in another) and the same component recorded under several different codes.
From a management perspective, BOM accuracy is a governance issue rather than an administrative chore. Assign a clear data owner, usually engineering or product development, and verify the BOM periodically by comparing actual consumption on the shop floor with consumption according to the BOM. A consistent variance is a signal that the BOM needs correcting, not that the shop floor needs blaming.
One distinction is often overlooked: the engineering BOM versus the manufacturing BOM. The engineering BOM describes the product as designed, while the manufacturing BOM describes how it is actually assembled in the plant, including consumables and packaging. Reliable material planning must rely on the manufacturing BOM, because that is what determines what must be on the shelf when a production order starts.
Figure 1. An accurate component structure is the joint work of engineering and production.
BOM Complexity: Multi-Level BOM and Product Variants
A multi-level BOM is a tiered structure in which a finished product is built from sub-assemblies, and each sub-assembly has its own BOM. This structure mirrors how a factory actually works, so the system can calculate requirements from the top-level product down to raw materials at the lowest level automatically, a process commonly called BOM explosion.
The advantage of a tiered structure is that a sub-assembly is defined once and used by many products. When a sub-assembly specification changes, the change flows to every product that uses it, without editing dozens of lists separately.
The second challenge is product variants. The same product is often offered in several colors, sizes or configurations. Maintaining a separate BOM for every variant inflates the volume of data and increases the risk of inconsistency. A cleaner approach is to keep one parent BOM holding the components common to all variants, and to flag the components that apply only to specific variants. ERP platforms such as Odoo Manufacturing support this pattern, allowing a BOM line to be limited to certain variants without duplicating the whole structure.
| Aspect | Single-level BOM | Multi-level BOM | Business impact |
|---|---|---|---|
| Structure | Flat list of components | Finished product, sub-assemblies, raw materials | Reflects the real production flow |
| Maintenance | Edit each product one by one | Edit a sub-assembly once | Lower risk of inconsistency |
| Requirement calculation | Manual for derived components | Automatic BOM explosion down to raw materials | Faster, auditable planning |
| Product variants | One BOM per variant | Parent BOM with variant-specific components | Less data, more controlled changes |
Figure 2. One sub-assembly can serve several variants, so a change only needs to be made once.
BOM Efficiency: Material Optimization and Raw Material Requirements Planning
Automated raw material requirements planning works by calculating gross requirements from the BOM and the production plan, subtracting available stock and open orders, and producing the net requirements that must be fulfilled. This logic is known as Material Requirements Planning (MRP) and sits at the core of material planning in most manufacturing ERP systems.
Efficiency comes from three sources. First, consistent calculation eliminates duplicate and late purchases. Second, purchase quantity rounding and lot sizes can be configured so that materials are ordered in sensible multiples. Third, an accurate BOM lets the company see which components consume the most budget, so optimization effort, such as price negotiation or material substitution, is aimed where it has the greatest impact.
One note matters for executives: automation does not fix bad data, it accelerates its consequences. Before switching on automated planning, make sure supplier lead times, units of measure and stock data are trustworthy. Without that, the system will produce recommendations that look precise but are wrong.
For leadership, a useful indicator to monitor regularly is plan adherence: the percentage of production orders that can start on time because all of their components are available. This indicator shows directly whether automated material planning is truly working or is still disrupted by unsynchronized data.
BOM Control: Revisions and Specification Change Management
BOM revision control ensures that every change to a component specification is recorded, approved and applied at the right time. In many plants the problem is not the change itself but the change that was never communicated: production keeps using the old component while purchasing has already ordered the new one, or the other way around.
Recommended practices include explicit BOM versions, effective dates for every revision, an approval workflow before a revision is activated, and an audit trail showing who changed what and when. For high-impact changes, many organizations use a structured process commonly called an Engineering Change Order (ECO), in which a proposed change is reviewed across functions before it takes effect. The product lifecycle modules of some ERP platforms provide this kind of workflow.
The key questions to answer for each change are: what happens to the stock of the old component, to open purchase orders, and to production orders that have already been released? The answers determine whether a revision takes effect immediately, in phases, or only after old stock is depleted.
Another analytical capability that the BOM enables is impact analysis: before replacing a component, a company can trace upward (a where-used inquiry) to see every product affected and then calculate the cost difference. In this way, a savings proposal is judged on comprehensive figures rather than an estimate for a single product.
Figure 3. Cross-functional review ensures every BOM revision is approved before it takes effect.
BOM Financials: Production Cost Estimation
Production cost estimation from the BOM is calculated by multiplying the quantity of each component by its unit cost, summing the results up to the finished product level, and adding operating costs such as labor and machine time when process data is available. The result is a standard cost that serves as a reference for pricing and margin evaluation.
The strategic value of this approach lies in the speed of simulation. When raw material prices rise or a supplier is replaced, leadership can see the effect on product cost without waiting for the books to close. Comparing the BOM standard cost with the actual cost from production is equally valuable; the difference shows where waste, price increases or data errors occur. The table below uses illustrative figures to show the structure.
| Cost component | Calculation basis | Illustrative example per unit |
|---|---|---|
| Direct raw materials | BOM quantity × unit cost | USD 40.00 |
| Sub-assembly components | Rolled-up cost of lower-level BOMs | USD 17.00 |
| Labor and machine time | Operation duration × hourly rate | USD 10.00 |
| Total standard cost | Sum of all cost components | USD 67.00 |
Note: all figures in the table above are illustrations meant to explain the calculation structure and are not real data from any company.
Figure 4. Production cost calculated from the BOM gives leadership a clear basis for pricing and margins.
BOM Operations: By-Products and Scrap
A by-product is a secondary product that is deliberately or unavoidably produced together with the main product, while scrap is waste or leftover material that can no longer be used as a product. Both should be modeled in the BOM so that cost and stock figures reflect what actually happens on the shop floor.
If by-products are not recorded, materials that are actually valuable, such as metal offcuts that can be sold or reused, never enter stock and their value disappears from reports. If scrap is not accounted for, material requirements are calculated too low and the company keeps running short. Modern ERP systems, including Odoo Manufacturing, allow by-products to be defined on the BOM and scrap to be recorded from production orders, so both connect directly to inventory.
From a management standpoint, scrap data is a valuable efficiency indicator. A rising scrap percentage on a particular product or machine points to concrete causes such as material quality, machine calibration or operator skill. With this data, improvements can be prioritized on evidence rather than assumption.
Figure 5. Recording by-products and scrap makes stock and cost figures reflect the shop floor.
BOM Integration: Inventory, Purchasing and Data Standardization
The full value of the BOM is realized only when it is connected to inventory and purchasing in one system. Material requirements calculated from the BOM are compared with available stock, and the shortfall can immediately become a proposed purchase order, or a production order for in-house components. Manual data transfer between functions disappears.
This integration can run only on standardized data. Item codes, units of measure, categories and supplier names must follow the same rules across the organization. Standardization is often dismissed as tedious work, yet it is the foundation that decides whether automation succeeds or simply produces chaos faster.
As a practical guide, begin standardization with the three items that have the greatest impact: unambiguous naming rules and item codes, base units of measure with their conversions, and a clean supplier list without duplicates. All three can be completed relatively quickly and immediately improve the quality of automated calculations.
| Function | Role in material planning | Data that must be standardized |
|---|---|---|
| Engineering | Maintains the BOM and its revisions | Component codes, specifications, versions |
| Production | Runs orders and records scrap | Units of measure, routings, operation times |
| Inventory | Keeps stock and location accurate | Item categories, warehouses, lots or serial numbers |
| Purchasing | Fulfills net requirements from suppliers | Suppliers, lead times, prices, purchase units |
Figure 6. Engineering, production, inventory and purchasing work from the same source of data.
Conclusion: Automated and Controlled Production Material Planning
Planning production material requirements automatically from the BOM is not merely a technology project; it is a governance decision. An accurate BOM foundation, a tidy multi-level structure, disciplined revision control, transparent cost estimation, honest recording of by-products and scrap, and integration with inventory and purchasing together create one trustworthy chain of data from product design to procurement.
A realistic first step for leadership is to audit BOM quality on a few key products, assign data owners and standardization rules, and then enable automated planning in stages. A phased approach lowers risk and proves value with real data before it is extended to the entire product range.
Figure 7. Automated material planning runs on a platform used around the world.
Odoo's Track Record Through 2026
For leaders weighing a system investment, the staying power of the platform provider matters as much as features. Based on Brussels Times reporting of 24 September 2026 and Nalios' recap of Odoo Experience 2026, Odoo's achievements through 2026 are as follows.
| Indicator | Reported figure (2026) | Relevance for production planning |
|---|---|---|
| Users | About 28 million users worldwide, roughly four in five on free plans | A large user base enriches the ecosystem, documentation and implementation talent |
| Global reach | Revenue from more than 180 countries through about 20 subsidiaries and a partner network | Implementation support is available across regions, including for companies with several plants |
| Team | About 7,500 employees, with a target of 10,000 in 2027 | Sustained investment in product development and support |
| Business performance | 2025 revenue of €620 million, about €900 million expected for 2026 (up roughly 45%), and a target of €1 billion in 2027 | A platform provider with strong growth and financial standing |
| Valuation | About €10 billion | A reflection of investor confidence in the product direction |
| Products | Odoo 20 announced at Odoo Experience 2026 (Brussels, 24 to 26 September): an AI agent that can create and update records, an MCP connector for external AI assistants, and 13 new industry packs | Manufacturing, Inventory, Purchase and Accounting apps sit on one platform, alongside community and partner modules |
| Community | Odoo Experience 2026 offered more than 450 conference sessions and over 400 exhibitors | An active community of users and partners |
The figures above are rounded and reported by the media based on company announcements. The 2026 revenue projection and the 2027 target are plans, not final results.
This scale gives manufacturers three assurances: a platform under continuous development, a broad ecosystem of partners and modules for adapting to industry needs, and a very large user base to learn from. Even so, global scale is no guarantee of results. Success in a plant is still determined by accurate process mapping, BOM data discipline, and adoption by users on the shop floor.
Make Material Planning Automatic with Fujicon Japan
Every plant has its own production character. The best first step is therefore not to pick modules, but to understand the control points with the greatest impact on your business: BOM quality, stock accuracy, or procurement timing. The Fujicon Japan team is ready to help you map priorities, plan the implementation stages, and ensure Odoo Manufacturing works in step with your production processes. Contact us to discuss directly:
- WhatsApp: +6281122275222
- Website: www.fujicon-japan.com