Stock Replenishment (Supply Chain)
- 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
In supply chain, the stock replenishment is an operation that consists in ordering more stocks in order to fulfill the customer demand. Replenishment is typically initiated either by an inventory policy such as the Min/Max inventory method or by a backorder triggered by a client order that could not be fulfilled by the stock on hand.
Replenishment rules
In order to increase productivity, most ERP and inventory management systems implement replenishment rules to automate operations to some extent. Replenishment is typically triggered when the inventory level hits the reorder point (also called reorder trigger level), a setting from the system.
When the reorder point is hit, an order matching the economic order quantity (EOQ) is produced. Again, ERPs typically provide some support for the calculation of the EOQ.
The complexity of replenishment operations greatly depends on the position of the ordering agent within the supply chain.
For stores part of a retail network that relies on centralized warehouses, replenishment are typically numerous, simple and largely automated. Indeed, at the store level - grocery stores being the archetype here - there are typically a rather large numbers of small orders to be passed on a daily basis. Hence, store managers cannot afford a system either too complex or too demanding in term of manpower.
For warehouses, replenishment’s from producers are typically larger and of longer order cycle (the week rather than the day). Then, the order itself is typically more complex because lead time can vary a lot (from next day delivery for local producers to several months for overseas manufacturers) and because other factors such as volume discounts impact the economic order quantity.
Lokad’s gotcha
We are routinely encountering companies that seemingly don’t do any demand planning. Yet, frequently in those situations, forecasts are implicitly defined through replenishment rules. Indeed, defining a reorder point is roughly equivalent to producing a demand forecast: from the report point, it’s possible - to some extent - to compute the underlying implicit demand forecast. We believe that it’s best practice to explicitly isolate, within the replenishment rules, where demand forecasts come into play.