- The Foundations of Supply Chain (Lecture 1.1)
- The Quantitative Supply Chain in a Nutshell (Lecture 1.2)
- Product-Oriented Delivery for Supply Chain (Lecture 1.3)
- Programming Paradigms for Supply Chain (Lecture 1.4)
- 21st Century Trends in Supply Chain (Lecture 1.5)
- Quantitative Principles for Supply Chain (Lecture 1.6)
- Bullwhip effect
- Containers
- Copacking
- Cross-docking
- Drop shipping
- Decision-driven optimization
- DDMRP
- Deliverables (Quantitative SCM)
- Economic Drivers (Quantitative SCM)
- Initiative (Quantitative SCM)
- Kanban
- Lean SCM
- Manifesto (Quantitative SCM)
- Micro fulfilment
- Product Life-cycle
- Resilience
- Sales and Operations Planning (S&OP)
- Success (Quantitative SCM)
- Supply Chain Management (SCM)
- Supply Chain Scientist
- Test of Performance
- Third Party Logistics (3PL)
- Backorders
- Bill of Materials (BOM)
- Economic order quantity (EOQ)
- Fill Rate
- Inventory accuracy
- Inventory control
- Inventory costs (carrying costs)
- Inventory Turnover (Inventory Turns)
- Lead demand
- Lead time
- Min/Max inventory method
- Minimum Order Quantity (MOQ)
- Phantom inventory
- Prioritized ordering
- Reorder point
- Replenishment
- Service level
- Service level (optimization)
- Stock-Keeping Unit (SKU)
- Stockout
- Accuracy
- Accuracy (financial impact)
- Accuracy gains (Low Turnover) Formula
- Backtesting
- Continuous Ranked Probability Score (CRPS)
- Cross-entropy
- Forecast Value Added
- Generalization
- Pinball loss function (quantile loss)
- Probabilistic forecasting
- Quantile regression
- Seasonality
- Time-series
- ABC analysis (Inventory)
- ABC XYZ analysis (Inventory)
- Erlang C (call center staffing)
- Time-series forecasting
- Prioritized Inventory Replenishment
- Safety stock
- Supply Chain Antipatterns
- Devil's advocate
- The Non-Euclidian Horror
- The 100% service level
- The Jedi initiation
- Naked forecasts

*By Joannès Vermorel, October 2015*

The fill rate is the fraction of customer demand that is met through immediate stock availability, without backorders or lost sales. The fill rate differs from the service level indicator. The fill rate has a considerable appeal to practitioners because it represents the fraction of the demand that is likely to be recovered or better serviced if the inventory performance was to be improved. The fill rate is measured empirically by averaging the number of correctly serviced requests over the total number of requests.

## Fill rate and service level are distinct

The service level is often mistakenly confused with the fill rate, and vice-versa. Yet, the two indicators are numerically different. While the two indicators are quite correlated, it is possible to find real-world situations were a high service level does not translate into a high fill rate, and the other way around. Such situations tend to arise more frequently when demand is sparse (as for spare parts for example) or when demand is erratic (as in the case of books).

## Formal definition

In order to shed some light on the exact respective definition of the fill rate and the service level, we need to introduce a certain degree of formalism. Let $${X}$$ be a random variable representing the demand over the next cycle. Let $${s}$$ be the stock available, that is, the quantity of stock readily available to service incoming requests.

The service level $${τ_1}$$ is written as:

The fill rate $${τ_2}$$ is written as:

Indeed $${min(X,s)}$$ represents the restriction that the available stock is imposing on the quantities to be serviced without delay. If the actual demand value $${x}$$ is lower than $${s}$$, then $${x}$$ units get served without delay otherwise, only $${s}$$ units get served without delay.