Stock Orderpoint Safety Stock (stock_orderpoint_safety_stock)

This module enhances inventory management by introducing service-level–based, stochastic control using a continuous review replenishment system. Instead of relying solely on fixed min/max stock levels, the module estimates your typical (mean) and variable (variance) daily demand from historical data and factors in lead time. These calculations generate a statistically sound safety stock, which is included in your reorder threshold (the “min”). The “max” is set so your inventory will cover expected demand during the entire replenishment cycle.

Now, you can set replenishment rules (orderpoints) based on the **Cycle Service Level (CSL)**, which reflects the probability of meeting all demand during a replenishment cycle without running out of stock. This provides a practical alternative to manually setting minimum and maximum stock thresholds.

With CSL enabled, safety stock is automatically calculated using your historical daily sales data (both average and standard deviation), gathered over a period you define, plus the orderpoint’s lead time. The system then keeps your reordering rule's min and max levels up-to-date.

Prefer manual control? You can always switch back to the “Manual” mode to specify min and max directly.

## Theory

The backbone of this approach is the Cycle Service Level (CSL), a widely used supply chain metric:

- **CSL Definition:** The chance that your inventory will fully cover demand during a restocking cycle.
- **Example:** A CSL of 95% means that only 5% of cycles will risk a stockout.

This system assumes demand is random (not fixed), so it uses statistical methods:

- **Average daily demand** (μ)
- **Standard deviation of daily demand** (σ)

Because demand can fluctuate during the lead time, safety stock acts as a buffer to reduce the risk of running out of stock.

**Safety stock formula:**

`safety_stock = σ_L × z × g`

Where:

- **σ_L:** Standard deviation of demand over the lead time
- **z:** Z-score for your desired CSL (e.g., 1.65 for 95% CSL)
- **g:** Growth factor (optional, lets you add a margin)

**Three zones are needed to define how min and max are derived:**

- **Red zone = safety stock:**
- This zone should never be touched. It acts as the buffer for unexpected variation.
- Refer to the safety stock formula above.
- **Yellow zone = expected demand during the lead time:**
- This zone represents the expected stock consumption from the moment you click on replenish, until the moment you receive your purchase order.
- Formula: `average daily demand × lead time in days`
- **Green zone = expected demand during the cycle:**
- Represents the stock consumption during the desired reordering cycle (the time between two replenishments)
- Formula: `average daily demand × cycle days`

Where:

- **lead time:** The time it takes to receive the order.
- **cycle days:** The desired number of days between orders.

From these three zones, the min and max quantities are derived as follows:
- **Minimum (min):** Red + Yellow
- **Maximum (max):** Red + Yellow + Green

**Why does it work?**

- Odoo triggers replenishment whenever stock falls below the min, which should be enough to cover variance (safety stock) and lead time demand.
- The max level is set high enough to cover all expected demand until the next restock, plus a buffer to cover the desired cycle days.

This makes inventory management both more data-driven and easier to maintain.

![cycle-graph](../static/description/cycle-graph.png)

Code Analysis ⓘ

Views touched (6)

XML ID	Model	Type	Status
`res_config_settings_view_form`	res.config.settings	form	Inherits stock.res_config_settings_view_form
`stock_reorder_report_search`	stock.warehouse.orderpoint	search	Inherits stock.stock_reorder_report_search
`view_stock_cycle_service_level_list`	stock.cycle.service.level	list	New
`view_stock_replenishment_info`	stock.replenishment.info		Inherits stock.view_stock_replenishment_info
`view_stock_warehouse_orderpoint_tree_editable`	stock.warehouse.orderpoint	tree	Inherits stock.view_warehouse_orderpoint_tree_editable
`view_warehouse_orderpoint_form`	stock.warehouse.orderpoint	form	Inherits stock.view_warehouse_orderpoint_form

HTTP endpoints (0)

No HTTP endpoints found for this module.

Models touched (6)

New fields (0)

No new fields.

Public methods (0)

No public methods.

New fields (1)

demand_history_days Integer
default=365 help='The number of days in the past to use to compute the safety stock.'

Public methods (0)

No public methods.

New fields (1)

demand_history_days Integer
readonly=False related='company_id.demand_history_days'

Public methods (0)

No public methods.

New fields (4)

csl Float
digits=(2, 2) help='The probability that demand during the replenishment lead time is fully covered without a stockout.\nThis value defines how reliable the stock should be during each replenishment cycle. A higher target increases safety stock to reduce the risk of stockouts; a lower target reduces inventory at the cost of more frequent shortages.\nTypical values range from 0.90 to 0.99 (e.g., 0.95 = 95% of cycles without stockouts).' string='Cycle Service Level'
orderpoint_count Integer
compute='_compute_orderpoint_count' string='Orderpoints Count'
orderpoint_ids One2many → stock.warehouse.orderpoint
string='Orderpoints' args: 'stock.warehouse.orderpoint', 'cycle_service_level_id'
z_score Float
compute='_compute_z_score' digits=(16, 4) help='Statistical factor derived from the target cycle service level.\n\nThe z-score represents how many standard deviations of demand variability are covered by the safety stock.\nA higher z-score corresponds to a higher service level and results in more safety stock.' store=True string='Z-Score'

Public methods (1)

action_open_orderpoints(self)

New fields (10)

cycle_days Integer
readonly=False related='orderpoint_id.cycle_days'
cycle_service_level_id Many2one
readonly=False related='orderpoint_id.cycle_service_level_id'
demand_avg_qty Float
related='orderpoint_id.demand_avg_qty'
demand_history_days Integer
related='orderpoint_id.demand_history_days'
demand_lt_std_dev Float
related='orderpoint_id.demand_lt_std_dev'
demand_std_dev Float
related='orderpoint_id.demand_std_dev'
growth_factor Float
readonly=False related='orderpoint_id.growth_factor'
safety_stock Float
related='orderpoint_id.safety_stock'
safety_stock_method Selection
readonly=False related='orderpoint_id.safety_stock_method'
z_score Float
depends=['orderpoint_id.cycle_service_level_id'] related='orderpoint_id.z_score'

Public methods (0)

No public methods.

New fields (12)

csl Float
related='cycle_service_level_id.csl' string='Cycle Service Level Target'
cycle_days Integer
help='The desired number of days between orders.\nUsed to size the gap between the min and max quantities, to cover the expected demand during the desired reordering cycle.\n\nproduct_max_qty = product_min_qty + (demand_avg_qty * cycle_days)'
cycle_service_level_id Many2one → stock.cycle.service.level
ondelete='restrict' string='Cycle Service Level' args: 'stock.cycle.service.level'
demand_avg_qty Float
compute='_compute_daily_demand' digits='Product Unit' help='The average daily outgoing quantity on this warehouse.' string='Average Daily Demand'
demand_history_days Integer
related='company_id.demand_history_days' string='Demand History Days'
demand_lt_std_dev Float
compute='_compute_demand_lt_std_dev' digits='Product Unit' help='The standard deviation of the daily outgoing quantity on this warehouse over the lead time.' string='Standard Deviation of Daily Demand over Lead Time'
demand_std_dev Float
compute='_compute_daily_demand' digits='Product Unit' help='The standard deviation of the daily outgoing quantity on this warehouse.' string='Standard Deviation of Daily Demand'
growth_factor Float
default=0.0 digits=(2, 2) help='A multiplier to apply to the safety stock and the resulting min and max quantities. Used to account for expected growth or decrease in demand.'
safety_stock Float
compute='_compute_safety_stock' digits='Product Unit' help='The safety stock is the amount of stock to keep on this warehouse to cover for the variability in demand during the lead time.\nIt is computed as the product of the standard deviation of the daily outgoing quantity over the lead time, the z-score (statistical factor derived from the target cycle service level) and the growth factor.\n\nsafety_stock = demand_lt_std_dev * z_score * (1.0 + growth_factor)'
safety_stock_method Selection
default='manual' help="The method to use to set the product's min and max quantities.\n* Manual: The product's min and max quantities are set manually.\n* Cycle Service Level: The product's min and max quantities are computed based on the target cycle service level and the growth factor.\n" selection=[('manual', 'Manual'), ('csl', 'Cycle Service Level')]
safety_stock_update_date Datetime
readonly=True string='Last modification date of Min and Max quantities from Safety Stock'
z_score Float
related='cycle_service_level_id.z_score'

Public methods (1)

action_apply_safety_stock(self)
Apply the safety stock to the orderpoint min and max quantities

Code Analysis ⓘ

Views touched (6)

HTTP endpoints (0)

Models touched (6)

product.product Extends Model 0 fields 0 methods ProductProduct · inherits product.product

res.company Extends Model 1 field 0 methods ResCompany · inherits res.company

res.config.settings Extends TransientModel 1 field 0 methods ResConfigSettings · inherits res.config.settings

stock.cycle.service.level New model Model 4 fields 1 method StockCycleServiceLevel · Cycle Service Level

stock.replenishment.info Extends TransientModel 10 fields 0 methods StockReplenishmentInfo · inherits stock.replenishment.info

stock.warehouse.orderpoint Extends Model 12 fields 1 method StockWarehouseOrderpoint · inherits stock.warehouse.orderpoint