About Bear Bit Bear Bit develops NVMI smart cabinet solutions that help manufacturers improve material visibility, inventory control and replenishment coordination. Our approach connects smart hardware, software and material management workflow...
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NVMI SKU selection is one of the most important decisions in the early stage of an intelligent inventory project. A manufacturer does not need to move every fastener, C-part, MRO consumable, tool, and production material into a new replenishment process on day one. A more practical approach is to identify a controlled group of SKUs whose consumption patterns, replenishment workload, shortage exposure, and storage characteristics make them suitable for an initial NVMI pilot.
The purpose of the first SKU group is not to prove that every material in the factory should use the same inventory method. It is to create a manageable operating scope where the buyer, supplier, warehouse team, and production users can validate inventory visibility, material-issue recording, replenishment signals, responsibilities, and exception handling before expanding the program.
The best first SKUs for an NVMI program are usually materials with repeatable consumption, frequent replenishment activity, clear specifications, reliable supplier relationships, and a real operational reason for improving inventory visibility. High-frequency fasteners and C-parts are often strong candidates because their individual unit value may be relatively low while the administrative effort required to count, request, replenish, and track them can be significant.
However, frequency alone is not enough. A good pilot should also consider material criticality, historical usage, supplier lead time, packaging quantity, point-of-use location, access-control requirements, storage dimensions, data quality, and the consequences of a shortage. The objective is to select SKUs that are representative enough to test the process but controlled enough to troubleshoot during the pilot.
An NVMI implementation changes more than the physical storage location of a component. It changes how inventory quantities are observed, how consumption is recorded, how replenishment conditions are identified, and who is expected to respond. Trying to introduce those changes across thousands of different materials simultaneously makes it difficult to determine whether a problem comes from the technology, material master data, supplier response, inventory parameters, or user behavior.
A controlled pilot reduces that complexity. The project team can validate a smaller group of materials, establish data definitions, confirm the replenishment workflow, and identify exceptions before expanding the operating model.
This also helps prevent the common mistake of assuming that all inventory deserves the same control method. A frequently consumed washer, a calibrated tool, an expensive electronic module, and an emergency maintenance spare have very different usage patterns and control requirements. The first NVMI pilot should focus on materials that fit the intended workflow rather than forcing unrelated items into one process.
A strong candidate usually has several characteristics that make its behavior understandable and its replenishment process repeatable.
The best pilot portfolio normally contains enough activity to test the system. A SKU that moves once every several months may not generate sufficient transactions to evaluate inventory monitoring or replenishment logic during a practical pilot period.
High frequency SKUs can create operational workload that is not obvious when procurement looks only at unit price or annual purchase value. A low-cost component may be collected from a storage location many times, replenished repeatedly, counted manually, and included in numerous small purchasing or warehouse transactions.
This is why transaction frequency should be included in the selection process. Inventory classification can use different criteria depending on the management objective. For example, inventory systems can classify materials according to historical transaction count, historical usage quantity, current inventory value, or other selected criteria.
For an NVMI pilot, historical transaction count and usage quantity can be especially useful because they help reveal which materials generate repeated physical and administrative activity.
Annual inventory value should still be considered, but it should not be the only ranking method. A plant may discover that some inexpensive components create more manual material-handling activity than more expensive items that move infrequently.
C-parts selection is a logical starting point for many manufacturing NVMI projects because standardized fasteners and similar components often combine relatively low unit value with high transaction frequency.
Examples can include bolts, nuts, washers, screws, clips, fittings, and other regularly consumed production or maintenance materials. Whether a specific component belongs in the first pilot should still be determined from actual plant data rather than from its product category alone.
A practical fastener inventory analysis should examine several dimensions:
| Selection Factor | Question to Ask |
|---|---|
| Consumption frequency | How often is the SKU physically withdrawn? |
| Usage quantity | How much is consumed during a normal operating period? |
| Specification stability | Is the material specification stable and clearly identified? |
| Supplier stability | Is there a defined supplier and repeatable replenishment route? |
| Shortage exposure | What happens when the item is unavailable at the point of use? |
| Manual workload | How much counting, recording, ordering, or internal movement does it create? |
| Storage fit | Does the size and weight fit the intended inventory unit? |
| Demand variability | Is consumption sufficiently repeatable for a pilot? |
Fasteners with stable specifications and recurring consumption can make the pilot easier to interpret. If an item repeatedly changes specification or is tied to temporary engineering projects, demand changes may make it difficult to separate inventory-process performance from product-change effects.
Material criticality needs careful treatment. Critical components can provide a strong reason for improving inventory visibility, but the first pilot should not create unnecessary production risk.
One approach is to select materials that matter operationally but still have manageable contingency options during the pilot. This gives the project team a meaningful test without making the success of an unproven process the only protection against a serious production interruption.
For each candidate, classify the consequence of a shortage. A simple structure can separate materials into categories such as low operational impact, moderate production impact, and high production-criticality. The exact categories should follow the manufacturer's own risk-management process.
Criticality should then be considered together with consumption frequency. A high-frequency component with meaningful shortage impact may deserve close attention, while a high-criticality item with extremely irregular demand may require a different inventory strategy during the initial phase.
Traditional ABC classification is useful for understanding relative inventory importance, but NVMI pilot selection should normally use more than inventory value alone. Inventory-management systems can rank items using criteria including current on-hand value, historical transaction frequency, historical usage quantity, historical usage value, and other measures.
For the first NVMI pilot, combine several dimensions. A component may have low annual spend but high transaction frequency and high production importance. Another may have high inventory value but almost no regular movement. These two materials should not automatically receive the same pilot priority.
A practical segmentation can consider:
This creates a more useful picture of the material's operational behavior.
An SKU can look ideal from a consumption perspective and still be a poor initial candidate if the supplier cannot support the intended replenishment workflow.
Before moving an item into the pilot, confirm who will monitor the material, how inventory or consumption data will be shared, what replenishment parameters apply, how packaging quantities affect refill decisions, and how exceptions will be escalated.
Supplier-managed replenishment generally depends on the buyer identifying the materials included in the program and sharing relevant inventory and demand information. Minimum and maximum inventory conditions can then provide part of the framework used by the supplier to determine when replenishment is required.
Supplier readiness questions should include:
These questions should be answered before the first SKU is activated.
The first pilot should make the process easier to evaluate. Some materials can introduce unnecessary complexity and may be better added after the basic workflow has been validated.
Poorly identified materials should normally be corrected first. If multiple item codes refer to the same physical component, or one code refers to several specifications, automated inventory data can amplify the master-data problem.
Obsolete or end-of-life items are usually weak pilot candidates because their consumption does not represent the future process.
Extremely irregular project materials can also be difficult to evaluate because historical consumption provides little guidance about the next requirement.
Frequently changing engineering items may create complexity if specifications, substitutes, or approved sources change during the test.
Materials without supplier ownership of the replenishment process should not be presented as supplier-managed items until responsibilities are actually agreed.
Items with unresolved inventory discrepancies should be physically and digitally reconciled before they become part of an automated replenishment process.
A scorecard can make selection discussions more objective. The exact weighting should be customized by the manufacturer, but the following structure provides a useful starting framework.
| Criterion | Low-Priority Signal | Strong Pilot Signal |
|---|---|---|
| Transaction frequency | Rare movement | Frequent repeated withdrawals |
| Demand pattern | Highly irregular | Relatively repeatable |
| SKU definition | Unclear or duplicated | Clean and standardized |
| Replenishment workload | Little manual activity | Repeated counting or refill activity |
| Supplier readiness | Responsibilities unclear | Supplier process defined |
| Storage fit | Difficult to accommodate | Fits available inventory unit |
| Shortage relevance | Little operational effect | Availability matters to operations |
| Data availability | Limited transaction history | Usable inventory and consumption history |
The team can rank candidate materials using a simple internal score and then review the highest-ranked items manually. The score should support engineering and supply-chain judgment rather than replace it.
SKU selection and equipment selection should be performed together. The physical characteristics and control requirements of the material determine how it should be stored and accessed.
The NVMI intelligent inventory approach combines smart inventory equipment with SaaS-based material management, providing functions such as real-time inventory updates, material usage records, shortage reminders, and replenishment information.
NVMI-H provides an open-access configuration suited to applications where convenient material collection is important, including warehouse and production-line material management. This can make it relevant for frequently consumed C-parts where rapid access is required.
NVMI-D uses an enclosed structure and supports authorization and access monitoring, making it more suitable where the material requires stronger control or traceability. Current configuration information can be reviewed on the NVMI-D smart inventory cabinet page.
NVMI-X is a mobile configuration intended for production environments where material inventory may need to move according to workstation or production-layout requirements. It can be considered when a fixed storage point does not match the actual material flow.
Manufacturers planning broader digital warehouse processes can also review the smart warehouse technology resources when mapping storage locations, material flows, and replenishment responsibilities.
There is no universal number that applies to every factory. The correct pilot size depends on the number of storage locations, users, suppliers, material categories, data interfaces, and replenishment workflows being tested.
The scope should be large enough to generate meaningful operational activity but small enough that exceptions can still be investigated individually. A pilot containing many thousands of SKUs can make root-cause analysis difficult, while a pilot containing only a few rarely used items may not generate enough data to evaluate the system.
Instead of starting from an arbitrary SKU quantity, define the processes that need to be tested:
Then select enough representative SKUs to exercise each process repeatedly.
A pilot does not need to contain only one material type. A balanced portfolio can provide more information about how the process performs under different conditions.
For example, the project may include a group of high-frequency fasteners, several medium-frequency C-parts, and a limited number of materials requiring controlled access. This allows the team to compare different inventory behaviors without turning the pilot into a full-site rollout.
However, avoid adding complexity simply for variety. Every additional material type, supplier, cabinet architecture, integration, or commercial workflow increases the number of variables the team must manage.
During the first phase, process clarity is more important than scope.
Before finalizing the candidate list, collect a basic dataset for each material. This should provide enough information for the team to understand both consumption and replenishment behavior.
If these data fields are unavailable or unreliable, the pilot preparation phase should include data cleanup. Automated replenishment depends on trusted material and inventory information.
Once the first NVMI pilot items are activated, the team should not immediately expand the program simply because the hardware is functioning. The operating process needs to be reviewed.
Check whether digital inventory reflects physical inventory, whether shortage signals occur at appropriate conditions, whether suppliers understand the replenishment workflow, and whether users can collect materials according to the intended process.
Also review exceptions. Which items repeatedly fall below the desired level? Which remain above the intended range? Are packaging quantities creating unnecessary stock? Are some materials being used differently from the historical pattern?
The answers should be used to adjust inventory parameters and determine which material groups are suitable for the next rollout phase.
Start with materials that have clear specifications, recurring consumption, meaningful replenishment workload, reliable suppliers, and suitable storage characteristics. High-frequency C-parts and fasteners are common candidates, but actual factory data should determine the final selection.
Not necessarily. Inventory value is only one factor. Historical transaction frequency, usage quantity, shortage impact, supplier readiness, and manual handling effort can be equally important when selecting an NVMI pilot.
They can be. Frequently consumed fasteners may generate repeated counting and replenishment activity even when individual unit values are low. Stable specifications and recurring usage can also make their behavior easier to evaluate during a pilot.
They should be evaluated carefully. Operationally relevant materials provide a meaningful test, but the manufacturer should avoid creating unnecessary production risk during an early implementation. Material criticality and contingency options should be reviewed before inclusion.
There is no universal number. Select enough SKUs to generate repeated material and replenishment transactions while keeping the scope manageable enough to investigate exceptions and validate the workflow.
Expand after the pilot demonstrates that inventory records, user workflows, shortage signals, supplier replenishment, and exception handling operate as intended. The next SKU group should be selected using the lessons and data collected during the first phase.
NVMI SKU selection should balance operational value with implementation control. The best first materials are not automatically the most expensive items or the largest inventory categories. Strong candidates typically combine repeatable consumption, frequent material activity, clean master data, manageable demand variability, supplier readiness, and a clear reason for improving replenishment visibility.
C-parts and fasteners can provide an effective starting point because they often create substantial recurring inventory activity. However, every candidate should still be evaluated for criticality, physical storage fit, supplier capability, and data quality.
The first pilot should be used to learn. It should show whether physical consumption is captured correctly, whether replenishment signals reflect actual requirements, whether suppliers can respond according to the agreed workflow, and whether users can adopt the new material process. Those lessons can then guide the selection of the next SKU group.
To prepare an NVMI pilot, share your material categories, candidate SKU list, monthly usage, transaction frequency, current storage method, stockout pain points, supplier model, item size and weight range, user count, access-control requirements, deployment locations, integration scope, and target KPIs. These inputs provide the foundation for selecting a practical first group of materials and designing the corresponding smart inventory workflow.