1. Inventory Policies and Replenishment

An inventory policy is a repeatable rule for deciding when to replenish and how much to order. A useful policy must fit both the demand pattern and the way suppliers, warehouses, and planning systems actually operate.

The core trade-off is practical: more stock can protect customer service, but it ties up cash and space. Larger or less frequent orders may reduce ordering and transport effort, but can increase average inventory or make shortages more likely. There is no best policy without a service goal, cost picture, and operating constraints.

Start with the inventory position

Before applying a rule, decide which stock measure drives it. On-hand inventory is physically available now. On-order inventory is replenishment already in the pipeline. Backorders are customer commitments that cannot yet be filled.

For a basic replenishment decision, use the inventory position:

$$\\text{Inventory position} = \\text{on hand} + \\text{on order} - \\text{backorders}$$

This differs from the quantity a customer can buy today: an incoming shipment increases the position before it reaches the shelf. Some systems also subtract allocations or include other commitments, so document the exact definition before tuning a policy.

Two policy dimensions determine the replenishment rhythm:

• Review timing: check stock continuously or at set intervals.
• Order quantity: replenish a fixed batch or top up to a target.

Continuous review: $(s,Q)$

Under continuous review, the inventory position is monitored as it changes. When it reaches or falls below the reorder point $s$, place an order for a fixed quantity $Q$.

For example, a rule might be: “When the inventory position is 18 units or less, order 60.” The trigger and batch size are separate: a position of 17 still triggers the same 60-unit order.

Useful when: monitoring is automated or inexpensive, a shortage is costly, and orders can be sent when the trigger is reached. Fixed batches can also match case packs or transport quantities.

Watch for: frequent small orders across many products, supplier order calendars, minimum-order rules, and inaccurate inventory records. A continuous trigger is not workable if the supplier only accepts orders on scheduled days.

Periodic review with an order-up-to target: $(R,S)$

Under periodic review, stock is checked on a fixed schedule, every $R$ time units. At each review, order enough to raise the inventory position to target $S$:

$$\\text{Order quantity} = \\max(0, S - \\text{inventory position})$$

If the position is 42 and the target is 100, the order is 58. If the position is already above 100, the order is zero. The interval is fixed; the order quantity varies.

Useful when: a buyer groups products into one supplier order, orders are accepted on set days, or a planning run happens on a regular cadence.

Watch for: the period between reviews is an exposure window. If stock falls sharply just after a review, the next routine opportunity may be too late. The target should account for demand during both replenishment lead time and the time until the next review, as well as the chosen service goal.

Periodic review with a threshold and fixed batch: $(R,s,Q)$

This rule combines scheduled checks with a fixed order batch. At each review every $R$ time units, compare the inventory position with $s$. If the position is at or below $s$, order $Q$; otherwise, do not order.

Unlike an order-up-to rule, this policy does not calculate a top-up. The batch remains fixed, which can simplify packaging and transport, but the resulting inventory position after ordering can vary.

Useful when: the supplier calendar is fixed and the operation needs standardized batches, such as full cases or pallets.

Watch for: both the review gap and the threshold can delay replenishment. This can require more buffer stock, and the policy needs careful testing against demand and lead-time variability.

Compare the rules

Policy	When is stock checked?	What determines the order?	Typical operational fit
$(s,Q)$	Continuously	Fixed batch $Q$ when position $\\le s$	Responsive ordering; automated monitoring
$(R,S)$	Every $R$	Top up to $S$	Consolidated supplier orders; scheduled planning
$(R,s,Q)$	Every $R$	Fixed batch $Q$ only when position $\\le s$	Scheduled buying with standard pack sizes

The letters are easy to mix up. In this chapter, lowercase $s$ is a trigger threshold, uppercase $S$ is an order-up-to target, $Q$ is a fixed batch, and $R$ is the review interval.

Worked example: one item, three policies

A distributor starts Monday with an inventory position of 40 units. Demand is 5 units per day, and supplier lead time is 3 calendar days. Assume the position is updated after each day's demand, and scheduled reviews happen at the end of every fifth day. Ignore safety-stock tuning for this arithmetic example.

Policy settings	What happens?	Order
$(s,Q)$ with $s=25$, $Q=40$	The position moves from 40 to 35, 30, then 25. Continuous review detects the threshold on Wednesday.	Order 40 on Wednesday; expected arrival is Saturday.
$(R,S)$ with $R=5$ days, $S=55$	At Friday's scheduled review, five days of demand reduce the position to $40 - 5(5) = 15$. The order tops the position up to 55.	Order $55 - 15 = 40$ on Friday; expected arrival is Monday.
$(R,s,Q)$ with $R=5$ days, $s=20$, $Q=24$	At Friday's review, the position is 15, which is at or below 20. The fixed batch is released.	Order 24 on Friday; expected arrival is Monday. The post-order position is 39.

The example isolates the mechanics: continuous review can react as soon as a threshold is reached, while periodic policies wait for their review; an order-up-to policy calculates a top-up, while a fixed-batch policy uses its preset quantity. These parameter choices are illustrative, not optimized. They do not show which policy has lower cost or better service; that comparison needs realistic demand, lead-time variation, and a common service or cost objective.

A policy-selection procedure

Use the constraints first; tune the numerical parameters after the operating rule is feasible:

1. Confirm the stock measure and data quality used by the decision.
2. Check when the supplier accepts orders and whether products need to be consolidated.
3. Decide whether continuous monitoring is possible or reviews must follow a schedule.
4. Choose fixed batches when pack or transport constraints dominate; choose a top-up when a target level is more useful.
5. Set thresholds and targets against demand, replenishment lead time, variability, and the desired service level.
6. Test the rule over realistic demand and lead-time histories; compare shortages, average stock, and ordering workload.

These steps are a starting point, not a substitute for analysis. In particular, a threshold copied from another item or a target chosen without lead-time data can create excess stock or recurring shortages.

Practice: choose and run a policy

Concept check

Quiz

Inventory policy basics

1 / 4

A buyer checks inventory every Monday and orders enough to reach a target level. Which policy describes this rule?

Pick an answer to see if you are right.

Rank the procedure: periodic threshold and fixed batch

Put the steps in the order a planner follows at a scheduled review.

Quiz

Run an (R, s, Q) review

1 / 2

At a scheduled review, apply the periodic threshold-and-batch rule.

OrderDrag the handle to rearrange — top should be first.

1. ⋮⋮1If position is at or below s, release one fixed batch Q; otherwise, place no order.
2. ⋮⋮2Calculate inventory position from on-hand, on-order, and backorders.
3. ⋮⋮3At the scheduled review time, read the current stock records.
4. ⋮⋮4Compare inventory position with the reorder threshold s.

Drag items into the correct order (or use ↑↓), then check.

Key takeaways

• Choose a policy that fits the supplier's order calendar and the buyer's operating constraints.
• Keep the trigger $s$, target $S$, batch $Q$, and review interval $R$ conceptually distinct.
• Calculate policy decisions from a clearly defined inventory position, not on-hand stock alone.
• Periodic review can simplify coordination but exposes the business to risk between reviews.
• Validate candidate settings against service, inventory cost, and workload rather than relying on a label or rule of thumb.

Next: How Much Should I Order? — build a simple cost model and derive an economic order quantity.