Dynamic Min/Max recommendations in Recurrency are designed to provide optimal inventory levels based on key demand and supply inputs. By leveraging dynamic calculations, Recurrency automatically adjusts minimum and maximum inventory levels to suit changing demand patterns, ensuring stock is available when needed while avoiding excess.
Calculations Overview
Effective inventory management is crucial for distributors aiming to optimize their operations and ensure customer satisfaction. A key component of this process is setting accurate minimum and maximum inventory levels for each item at each location. This involves understanding and calculating demand over lead time, order cycle, and safety stock days.
The Dynamic Min and Dynamic Order Point are set using the below formula, and the inputs are provided for each item within the Planning tool.
Forecast Over Lead Time: Lead Time Demand * Lead Time
Order Cycle Demand: Order Cycle Demand * Order Cycle
Safety Stock Qty: Safety Stock Demand * Safety Stock
The Dynamic Max is calculated using the below formula, and the inputs are provided for each item within the Planning tool.
Forecast Over Lead Time: Lead Time Demand * Lead Time
Safety Stock Qty: Safety Stock Demand * Safety Stock
Economic Order Qty: Yearly Demand, Replenishment Cost, Holding Cost, and Unit Cost.
To learn more, Review Understanding EOQ
Min/Max Input Definitions
Lead Time Demand | The quantity of a product or service that is expected to be demanded |
Order Cycle Demand | The total quantity of a product or service that is expected to be |
Safety Stock Demand | The quantity of inventory held as a buffer against unexpected |
Economic Order Quantity (EOQ) | Determines the optimal order quantity a business should purchase to minimize total inventory costs. These costs include holding costs (the cost of storing unsold goods) and ordering costs (the costs associated with placing and receiving orders) |
Lead Time | Takes into account the time required to receive stock after placing an order, ensuring that inventory is replenished before running out. |
Months with Demand | Considers the number of months with recorded demand over the past year to ensure the recommendation reflects recent consumption patterns. |
Average Monthly Demand | Calculates the average quantity sold per month based on available historical data. |
Input Calculations
This section explains the importance of essential inputs and how they interrelate to form robust min/max inventory recommendations. By mastering these calculations, you can minimize stockouts, reduce excess inventory, and ultimately enhance your overall supply chain efficiency.
Calculating Average Daily Demand
Consider the following scenario for reviewing a specific min/max recommendation:
Today's date is in mid-July.
The lead time for the item at the specific location is 104 days.
The order cycle is 45 days.
The safety stock is 30 days.
To calculate the total demand over these periods, we need to account for the average demand within each time frame.
Lead Time: This period starts from the current moment and looks at the average demand from now until the end of the lead time. It always starts by using the current month of forecasted demand.
Safety Stock: Uses the same average daily demand value as lead time but with the number of days is generally different, which results in a different value
Order Cycle: This period starts after the lead time period, ensuring timely replenishment and preventing stockouts by aligning inventory arrivals with actual usage patterns.
To calculate the average daily demand within a given period, we use the following:
💡 We always use at least one month of demand in these calculations. If any period is less than a month, then this calculation uses the average daily demand for a singular month.
The Average Daily Demand equation is the same for all periods, but the actual monthly demand values, and the number of months considered is different for each period.
To get the forecast demand over the given period, you multiply the Average Daily Demand by the number of days in the given period:
Detailed Example
From the image above, here are our monthly forecast values starting in July and going until the end of the different periods we are considering.
July: 28.99 units
August: 23.59 units
September: 28.58 units
October: 30 units
November: 29.87 units
December: 23.26 units
Lead Time Demand
To calculate the lead time demand, we take the average daily demand over the lead time period. This is done by averaging the forecasted demand for each month included in the lead time and multiplying by the number of days in the lead time.
In this case, the lead time is 104 days, which is rounded to 4 months to calculate the daily demand. This calculation will average the demand across the first 4 months of forecasted usage (July, August, September, October).
Safety Stock Quantity
Safety stock is the extra buffer to keep on hand in case of supplier lead time issues or unusual demand while waiting for inventory to come in. Safety Stock uses the Lead Time Daily Demand but for a different number of days which results in a different final output.
Order Cycle Demand
The order cycle demand is calculated similarly but starts after the lead time period. We take the forecasted demand for the months immediately following the lead time period and calculate the average daily demand. We then take the average daily demand for the order cycle period and multiply it by the number of days in the order cycle. Order Cycle in this case is 45 days, which we round to 2 months when calculating the daily demand.
Given that Lead Time was 4 months, Order Cycle will start at the next forecasted demand period and take months 5 and 6 (November and December).
By breaking down and summing the demands as described, we ensure that our inventory recommendations are precise and reflective of the actual needs over the specified periods. This method helps distributors maintain optimal inventory levels, reducing the risk of stockouts and excess inventory.
Economic Order Quantity
Economic Order Quantity (EOQ) is a concept used in inventory management and represents the optimal order quantity a company should purchase to minimize its total inventory costs. These costs typically include order costs (like setup or ordering costs) and holding costs (such as storage, insurance, and potential obsolescence).
The formula we use for calculating EOQ is:
Where:
D: Yearly demand (units / year)
S: Replenishment cost per order ($ / order )
H: Holding cost per unit per year ($ / year)
C: Unit cost of the item ($ / unit )
The derived EOQ value indicates the ideal order size that minimizes the combined ordering and holding costs.
As your yearly demand and replenishment cost go up, you should buy more (to reduce the number of times you pay the fixed cost to replenish the item). Likewise, as your holding cost and unit cost go up, the total EOQ should go down. If something is very expensive to purchase, you are less willing to over purchase.
To learn more about EOQ, check out this article.
Items where Min = Max
If you’re working with items where Min = Max, Recurrency offers an optional setting to automatically create separation between these levels:
When enabled, Recurrency will add the EOQ (Economic Order Quantity) to your Min and use the sum as your Max.
If a Minimum Order Quantity (MOQ) exists, it will take precedence.
This does not change the behavior of sparse demand items.
This feature is especially useful if you’re using native ERP purchasing, as it avoids situations where you’re prompted to replenish one unit every time you sell one.
Learn more about how to manage items where min = max in this article. To skip right to the section regarding this setting, check out this article.