CN113177763A - Replenishment suggestion generation method and system and computer readable storage medium - Google Patents
Replenishment suggestion generation method and system and computer readable storage medium Download PDFInfo
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Abstract
The application discloses a replenishment suggestion generation method and system and a computer-readable storage medium, wherein the method comprises the following steps: acquiring daily sales data in a preset time; acquiring inventory data in preset time; acquiring the duration of stock preparation; generating a replenishment suggestion based on the daily sales data, the inventory data and the stock duration; according to the scheme, the replenishment suggestion can be intelligently generated according to the sales data, the inventory data and the stock preparation duration of the user in preset time, so that the saturation of the inventory can be ensured, and the risk of goods breakage can be avoided in time.
Description
Technical Field
The present disclosure relates to the field of logistics replenishment, and more particularly, to a replenishment suggestion generation method and system, and a computer-readable storage medium.
Background
At present, in order to provide better and better logistics service for buyers and improve the competitiveness of stores of sellers, sellers need to put purchased commodities into a warehouse in advance so as to avoid the occurrence of a broken commodity (the process is called 'replenishment' for short). When the stock of the warehouse is insufficient, the time and the amount of the stock are related. How to timely and accurately replenish goods directly relates to the performance and the profit of the shop, therefore, how to accurately and efficiently provide replenishment suggestions is a problem to be solved urgently.
Disclosure of Invention
The method and the device aim to intelligently generate the replenishment suggestions and reduce the risk of goods failure.
The technical purpose of the application is realized by the following technical scheme: a replenishment suggestion generation method comprises the following steps:
acquiring daily sales data in a preset time;
acquiring inventory data in preset time;
acquiring the duration of stock preparation;
and generating a replenishment suggestion based on the daily sales data, the inventory data and the stock preparation duration.
According to the scheme, by acquiring daily sales data and inventory data, according to the daily sales data and the inventory data, a sale date which can be met by the inventory data can be obtained, and then according to the duration of stock preparation, the replenishment can be correspondingly obtained, so that the replenishment quantity and the time of stock preparation are pertinently selected, the replenishment suggestion is generated, through the data, the replenishment suggestion can be intelligently generated, the stock stability of a user is ensured, and the risk of failure is reduced.
Optionally, the replenishment suggestion generation method includes:
acquiring historical sales data;
acquiring a preset sales rule;
and calculating daily sales data in a preset time based on the historical sales data and the sales rule.
According to the scheme, the daily sales data in the preset time are obtained by obtaining historical sales data and calculating the daily sales data in a certain time period in the future according to the sales rules preset by the user, and the accuracy of data simulation can be improved based on the historical sales data.
Optionally, the replenishment suggestion generation method includes:
acquiring local existing inventory;
acquiring purchasing in-transit data;
local inventory data is calculated for a predetermined time based on the local inventory-on-hand and the procurement en-route data.
According to the scheme, the inventory data in the preset time is obtained, the local existing inventory and the data of purchased and not-in-stock are obtained, and the accuracy of the inventory data is guaranteed by combining and calculating the local inventory data in a certain period of time in the future.
Optionally, the method for generating a replenishment suggestion includes:
and acquiring the FBA inventory and the European shared inventory, removing duplication of the European shared inventory, and combining local inventory data to obtain final inventory data.
According to the scheme, the inventory data further comprises FBA inventory and European shared inventory, data duplication is removed for the European shared inventory, and the local inventory data is combined, so that final inventory data is obtained, and the accuracy of the inventory data is further guaranteed.
Optionally, the method for generating a replenishment suggestion includes the following steps:
the daily sales data is updated based on the FBA inventory and the european shared inventory.
According to the scheme, the daily sales data are updated by acquiring the FBA inventory and the European shared inventory, and the accuracy of the daily sales data in a certain period of time in the future is further improved.
Optionally, the replenishment suggestion generation method, wherein the method of obtaining the stock preparation duration includes:
acquiring a purchase delivery period;
obtaining quality inspection time;
acquiring the number of saleable days after expected replenishment;
and calculating the stock duration based on the purchase delivery period, the quality inspection time and the number of saleable days after the expected replenishment.
According to the scheme, the stock preparation time mainly comprises the purchase delivery period, the quality inspection time and the number of days available for sale after the expected replenishment, and the data accuracy of the stock preparation time is guaranteed by considering multiple parameters, so that the accuracy of the generated replenishment suggestion is guaranteed.
Optionally, the replenishment suggestion generating method includes, based on daily sales data, inventory data and stock duration, generating a replenishment suggestion:
calculating whether goods are broken or not in preset time and the time of the goods breaking based on daily sales data, inventory data and the time of the goods stock;
and calculating the purchasing amount and the purchasing time based on the outage time to generate a replenishment suggestion.
According to the scheme, the generation of the replenishment suggestions is based on daily sales data, inventory data and the length of stock preparation time, whether the goods failure risk exists in a certain period of time in the future or not and the number of the goods failure days are judged, the goods failure is avoided or the number of the goods failure days is reduced through comprehensive consideration, the optimal replenishment suggestions are intelligently generated and provided for users, and therefore the goods failure risk is reduced.
Optionally, the replenishment suggestion generation method includes:
acquiring logistics timeliness and cost;
and screening to obtain a matched logistics mode based on the purchasing time, the purchasing quantity, the logistics timeliness and the cost.
According to the scheme, the logistics mode is selected in the replenishment suggestion, and the logistics mode with the least cost can be selected according to time in the generated replenishment suggestion by acquiring the logistics timeliness and the cost, so that the cost is saved.
The application also discloses a replenishment suggestion generation system, wherein, includes:
the daily sales data acquisition module is used for acquiring daily sales data in preset time;
the inventory data acquisition module is used for acquiring inventory data in preset time;
the stock duration acquisition module is used for acquiring stock duration;
and the replenishment suggestion module is used for generating replenishment suggestions based on the daily sales data, the inventory data and the stock preparation duration.
According to the scheme, by acquiring daily sales data and inventory data, according to the daily sales data and the inventory data, a sale date which can be met by the inventory data can be obtained, and then according to the duration of stock preparation, the replenishment can be correspondingly obtained, so that the replenishment quantity and the time of stock preparation are pertinently selected, the replenishment suggestion is generated, through the data, the replenishment suggestion can be intelligently generated, the stock stability of a user is ensured, and the risk of failure is reduced.
The application also discloses a computer readable storage medium, wherein the computer readable storage medium is loaded by a processor and executes the replenishment suggestion generation method.
In summary, the present application discloses a replenishment suggestion generation method and system and a computer-readable storage medium, wherein the method includes: acquiring daily sales data in a preset time; acquiring inventory data in preset time; acquiring the duration of stock preparation; generating a replenishment suggestion based on the daily sales data, the inventory data and the stock duration; according to the scheme, the replenishment suggestion can be intelligently generated according to the sales data, the inventory data and the stock preparation duration of the user in preset time, so that the saturation of the inventory can be ensured, and the risk of goods breakage can be avoided in time.
Drawings
FIG. 1 is a flow chart of steps of a replenishment proposal generation method described in the present application.
Fig. 2 is an operation flowchart of a first embodiment of a replenishment proposal generation method described in the present application.
Fig. 3 is an operational flow diagram of a second embodiment of a replenishment proposal generation method described in the present application.
Fig. 4 is a block diagram of a replenishment proposal generation system according to the present application.
Detailed Description
The present application is described in further detail below with reference to figures 1-4.
The embodiment of the application discloses a replenishment suggestion generation method, which can intelligently generate a replenishment suggestion for reference of a user aiming at the existing commodity sales, ensure the inventory stability of the user and avoid the risk of goods failure, and specifically, referring to fig. 1, is a step flow chart of the method, and the method comprises the following steps:
s1, acquiring daily sales data in preset time;
s2, acquiring inventory data in a preset time;
s3, acquiring the duration of stock keeping;
and S4, generating a replenishment suggestion based on the daily sales data, the inventory data and the stock preparation duration.
In the embodiment of the application, by acquiring daily sales data, inventory data and stock duration in a predetermined time, a replenishment suggestion is generated intelligently, wherein the sequence of steps S1, S2 and S3 is adjustable, the order of the acquired data is not limited, the predetermined time can be selected by a user, in the embodiment of the application, the predetermined time is set to 60 days, that is, the replenishment suggestion is generated based on sixty days in the future, the daily sales data of sixty days is acquired, the sales of sixty days in the future can be known, the inventory data of sixty days can be obtained, the inventory data of each day can be known, for example, the daily sales of the first day is 20 pieces, then the inventory of the first day is subtracted by 20, and so on, according to the inventory data, it can be correspondingly obtained which day the existing inventory is not enough to support the daily sales of the current day, and then the risk of outage exists on the current day, that is, replenishment is needed before the day to avoid the outage, the duration of stock preparation is obtained to obtain the time required for replenishing the stock, for example, the duration of stock preparation is fifteen days, and then fifteen days are carried forward in the day of outage to avoid the deadline of outage, the stock preparation can avoid the outage before the day, and the risk of outage exists after the day.
In the foregoing solution, it is mentioned that multiple data need to be acquired, and then a replenishment suggestion is generated intelligently based on the acquired data, where the replenishment suggestion includes acquiring daily sales data in a predetermined time, and in this embodiment of the present application, a method for acquiring daily sales data in a predetermined time is specifically disclosed, where the method includes:
acquiring historical sales data;
acquiring a preset sales rule;
and calculating daily sales data in a preset time based on the historical sales data and the sales rule.
The sequence of obtaining the historical sales data and obtaining the preset sales rule is not limited.
In the embodiment of the present application, the daily sales data in the predetermined time are obtained, mainly by obtaining historical sales data, and according to a sales rule preset by a user, the daily sales data in the predetermined time are calculated, that is, according to the sales data before a current time node, the sales data in a certain time period in the future can be simulated, and in order to make the daily sales data in the certain time period in the future more accurate, data correction can be performed according to the preset sales rule, in the specific embodiment of the present application, the sales rule is divided into two types: a dynamic pin count and a fixed pin count;
dynamic sales volume: and accumulating and calculating according to the daily average sales weighted value of each time span (rounding up the decimal after accumulation). If the daily average accounts for 50% in 7 days, 32% in 14 days, 8% in 30 days, 5% in 60 days and 5% in 90 days, the daily average sales are dynamic values, and statistics is carried out according to actual platform orders;
for example, 10 are all used in 7 days, 20 are all used in 14 days, 25 are all used in 30 days, 40 are all used in 60 days, and 50 are all used in 90 days. The calculated daily average sales is: 10 × 50% +20 × 32% +25 × 8% +40 × 5% +50 × 5% =5+6.4+2+ 2.5=17.9, and the decimal is rounded up to 18, and the daily sales are calculated as 18.
Fixing pin quantity: specified daily sales, such as 25 per day;
on this basis, the daily sales for a certain period of time may be specified, e.g. 2021-02-01 to 2021-02-05, which is specified to be 50 daily, the daily sales for this period of time would cover the above-defined 25 daily calculations of 50 daily. The daily fixed sales amount can be determined according to the stock quantity, for example, the stock quantity is saturated, the daily fixed sales amount can be slightly higher, and if the stock quantity is in a tension state, the daily fixed sales amount is not too high, so that the risk of goods break is avoided.
In the embodiment of the present application, based on the sales volume rule, daily sales volume data within a certain time in the future can be simulated, for example, taking 60 days as an example, the predicted sales volume per day is calculated according to the sales volume rule, and then sales volume per day within nearly 60 days is simulated according to time, so as to obtain sales volume data within nearly 60 days, for example, 15 sales are sold under No. 2021-02-01, and 20 sales are sold under No. 2021-02-02, which is a data structure.
In the foregoing solution, in addition to obtaining daily sales data in a predetermined time, it is also necessary to obtain inventory data in the predetermined time, and in this embodiment, the method for obtaining inventory data in the predetermined time includes:
acquiring local existing inventory;
acquiring purchasing in-transit data;
local inventory data is calculated for a predetermined time based on the local inventory-on-hand and the procurement en-route data.
The sequence of obtaining the local inventory and obtaining the procurement in-transit data is not limited.
In the embodiment of the present application, the local inventory data in the predetermined time is calculated based on the existing inventory and the procurement in-transit data, for example, the daily sales amount is fixed, 15 per day and 300 existing inventory data are specific to only merchants of the local inventory, so that sales for 20 days can be satisfied according to the existing inventory, but 300 goods are purchased, but the time for reaching the inventory needs 4 days, and no other factors such as quality inspection are considered, so that the inventory for the first day is 285, the inventory for the second day is 270, the inventory for the third day is 255, the inventory for the fourth day is 540, but quality inspection of the goods may be performed after reaching the inventory, in the embodiment of the present application, the default quality inspection rate is 100%, specifically, after the goods reach the inventory, the specific operation flow based on the local inventory is manually adjusted, and is shown in fig. 2.
In the foregoing solution, it is mentioned that, for a merchant with only local inventory, but in this embodiment of the present application, for amazon merchants, there may be FBA inventory and european shared inventory, and therefore, inventory data needs to be merged and calculated, in this embodiment of the present application, the replenishment proposal generation method is described, where the method for obtaining inventory data within a predetermined time further includes:
and acquiring the FBA inventory and the European shared inventory, removing duplication of the European shared inventory, and combining local inventory data to obtain final inventory data.
In the embodiment of the present application, amazon is taken as an example, and is currently applied to a seller selling goods in amazon [ mark a ], as shown in fig. 3, in order to provide better and better logistics service for buyers and improve competitiveness of own stores, the seller needs to transport goods purchased in China to an amazon FBA warehouse [ mark B ] (this process is simply referred to as "replenishment") in batches in advance.
FBA shared inventory: the full name is FEN (European network distribution of European film Networks). That is, the stock is stored in any FBA warehouse in Europe, and Amazon is responsible for stock scheduling between warehouses when the goods are put on shelves or sold. The seller need only manage the european shared inventory and need not manage warehouse inventory at a specific site (country) in europe.
If the seller opens a store in germany and french and opens the shared inventory service. Since the inventory between sites is confusing, the seller sees an inventory of, for example, 100 in europe in either the france or german stations. For the European shared inventory, the two inventory report data can not be simply processed, and the duplicate removal processing is needed, and actually the total number of the commodities in the European two sites is 100, but the two sites are not 100 respectively.
Therefore, after considering the above factors, the final inventory data may change, and the european shared inventory needs to be deduplicated and combined with the local inventory to obtain the final inventory data.
In the foregoing solution of the present application, it is mentioned that, in the method for acquiring daily sales data in a predetermined time, according to a preset sales rule, including a dynamic sales and a fixed sales, a local inventory is fixed, but in addition to the local inventory, if there is an FBA inventory, the fixed sales can be adaptively adjusted according to an inventory saturation, and therefore, in this embodiment, the method for acquiring daily sales data in a predetermined time further includes: the daily sales data is updated based on the FBA inventory and the european shared inventory. The daily sales data are updated through the final inventory data, and the accuracy of the daily sales data is guaranteed.
The scheme of the application discloses how to obtain daily sales data in the preset time and inventory data in the preset time, but similarly, the stock-in duration needs to be obtained, and the replenishment suggestion is generated by combining the previous data according to the stock-in duration, so that the embodiment of the application also discloses a specific method for obtaining the stock-in duration, and the implementation method comprises the following steps:
acquiring a purchase delivery period;
obtaining quality inspection time;
acquiring the number of saleable days after expected replenishment;
and calculating the stock duration based on the purchase delivery period, the quality inspection time and the number of saleable days after the expected replenishment.
The order of the quality inspection acquisition time and the number of saleable days after the replenishment is expected is not limited.
In the embodiment of the present application, it is mentioned in the foregoing scheme that when goods are put in storage after purchase, quality inspection may be performed to determine whether the goods meet requirements, and the quality inspection also requires time, and goods that have not been subjected to quality inspection cannot be sold, otherwise stores are easily sealed, and the like, so in the embodiment of the present application, the time length for stock preparation specifically includes a purchase delivery time, a quality inspection time, and a number of saleable days (safe days) after expected replenishment, and the time length for stock preparation = the purchase delivery time + the quality inspection time + the safe days, where the purchase delivery time means the time from generation of a purchase order to completion of purchase, the quality inspection time means the time from the time when the goods are put in storage to the time when the quality inspection is completed, the safe days when the goods are put in storage and after the quality inspection is completed, the number of sales of the goods can be sold can be obtained through the above data, and the sales volume of the goods in the future 60 days per day is calculated in the past, in the process, the local warehouse can purchase the stock in transit to be delivered, the non-quality-checked stock can be subjected to quality check, and the stock in transit sent to the FBA warehouse can reach the FBA warehouse. Here, we will calculate the inventory replenishment amount on the day according to the defined time for converting from the intermediate state to the saleable inventory, for example, if the local warehouse purchase estimated time to the shipment is 2021-03-13, the warehouse quality inspection needs 3 days after the shipment (assuming that the warehouse receives the goods and immediately performs the quality inspection), and the local warehouse sends to the FBA warehouse for 20 days (assuming that the warehouse quality inspection is finished and immediately delivers the goods to the FBA warehouse, and the quality inspection qualification rate is 100%), then this inventory will be calculated as the inventory replenishment amount on the day of 2021-04-09, and the inventory remaining on the day = the inventory remaining on the previous day + the inventory on the day-the expected sales amount on the day, so that the remaining inventory on the day of the future 60 days can be calculated in a simulated manner.
According to the method, the replenishment suggestion can be generated intelligently by acquiring daily sales data in preset time, stock data in preset time and stock duration, and how to acquire the data is mentioned in the scheme.
Calculating whether goods are broken or not in preset time and the time of the goods breaking based on daily sales data, inventory data and the time of the goods stock;
and calculating the purchasing amount and the purchasing time based on the outage time to generate a replenishment suggestion.
In the embodiment of the application, the remaining stock of each day in the future 60 days is calculated according to the previous simulation, which day is out of stock or is out of stock (namely, the remaining stock of the day is less than or equal to 0) can be found, and the out-of-stock time is called the earliest out-of-stock time. If the number of days from the current time to the earliest stock out time (recorded as the number of available days) is less than the length of stock preparation, the stock is considered to be needed.
The scheme of the application is also provided for avoiding the outage and reducing the outage risk, so that the replenishment suggestion is based on the reduction of the outage risk as an evaluation standard, the data is obtained, the day on which the outage exists can be calculated, the stock needs to be replenished before the day, and the stocking duration is combined, so that the stocking time meeting the requirement can be obtained, the replenishment suggestion is generated and is selected by a user.
The foregoing solution mentions that the replenishment suggestion is generated intelligently according to the related data, but the solution of the replenishment suggestion may include multiple solutions, and therefore, in the embodiment of the present application, the replenishment suggestion generation method further includes:
acquiring logistics timeliness and cost;
and screening to obtain a matched logistics mode based on the purchasing time, the purchasing quantity, the logistics timeliness and the cost.
In the embodiment of the application, the replenishment suggestions may include a plurality of types, because it is already calculated that the goods may be out of stock on any day, the stock needs to be replenished before the goods are out of stock, the latest replenishment time is calculated from the duration of the stock preparation, and the goods can be replenished before the latest replenishment time, so that the logistics aging (the time required for logistics transportation) corresponding to the replenishment needs to be less than or equal to the number of saleable days to replenish the stock in the FBA warehouse before the goods are out of stock on that day, otherwise, if the logistics aging is more than the number of saleable days, the goods are replenished, the goods are out of stock at will, and the purpose of avoiding the goods out of stock cannot be achieved. Therefore, in the embodiment of the application, the logistics with the lowest freight cost is selected from the logistics meeting the time efficiency and is embodied in the replenishment proposal, so that the replenishment scheme is further optimized.
To address the above issues, the present application also discloses a replenishment suggestion generation system, which refers to fig. 4 and is a structural block diagram of the system, wherein the system includes:
a daily sales data acquisition module 100 configured to acquire daily sales data within a predetermined time;
an inventory data acquisition module 200 for acquiring inventory data within a predetermined time;
a stock duration obtaining module 300, configured to obtain a stock duration;
and the replenishment suggestion module 400 is used for generating replenishment suggestions based on the daily sales data, the inventory data and the stock preparation duration.
In the embodiment of the present application, the daily sales data in a predetermined time are obtained by the daily sales data obtaining module 100, the inventory data are obtained by the inventory data obtaining module 200, and the stock duration is obtained by the stock duration obtaining module 300, and the replenishment suggestion is intelligently generated by the replenishment suggestion module 400, in the present application, the predetermined time can be selected by the user, in the embodiment of the present application, the predetermined time is set to 60 days, that is, the replenishment suggestion is generated based on the sixty days in the future, the daily sales data of the sixty days are obtained, the sales of the sixty days in the future can be known, the inventory data of each day can be known, for example, the daily sales of the first day is 20 pieces, then the inventory of the first day is subtracted by 20, and so on, according to the inventory data, it can be correspondingly obtained which day the existing inventory is insufficient to support the daily sales, it means that there is a risk of stock failure in the same day, that is, the stock needs to be replenished before the same day to avoid stock failure, and the stock stocking duration is obtained to obtain the time required for replenishing the stock, for example, the stock stocking duration is fifteen days, and then, fifteen days ahead of the day of the stock failure is the deadline for avoiding stock failure, and the stock stocking can avoid the stock failure before the same day, and there is a risk of stock failure after the same day.
The application also discloses a computer readable storage medium, wherein the computer readable storage medium is loaded by a processor and executes the replenishment suggestion generation method.
Through the above description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a general hardware platform, and may also be implemented by hardware. With this in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer electronic device (which may be a personal computer, a server, or a network electronic device, etc.) to execute the methods of the various embodiments or some parts of the embodiments.
Conditional language such as "can," "might," or "may" is generally intended to convey that a particular embodiment can include (yet other embodiments do not include) particular features, elements, and/or operations, among others, unless specifically stated otherwise or otherwise understood within the context as used. Thus, such conditional language is also generally intended to imply that features, elements, and/or operations are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without input or prompting, whether such features, elements, and/or operations are included or are to be performed in any particular embodiment
The embodiments of the present invention are preferred embodiments of the present application, and the scope of protection of the present application is not limited by the embodiments, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.
Claims (10)
1. A replenishment suggestion generation method, comprising:
acquiring daily sales data in a preset time;
acquiring inventory data in preset time;
acquiring the duration of stock preparation;
and generating a replenishment suggestion based on the daily sales data, the inventory data and the stock preparation duration.
2. The replenishment suggestion generation method according to claim 1, wherein the method of acquiring daily sales data within a predetermined time includes:
acquiring historical sales data;
acquiring a preset sales rule;
and calculating daily sales data in a preset time based on the historical sales data and the sales rule.
3. The replenishment suggestion generation method according to claim 1, wherein the method of acquiring stock data within a predetermined time comprises:
acquiring local existing inventory;
acquiring purchasing in-transit data;
local inventory data is calculated for a predetermined time based on the local inventory-on-hand and the procurement en-route data.
4. The replenishment suggestion generation method according to claim 3, wherein the method of acquiring inventory data for a predetermined time further comprises:
and acquiring the FBA inventory and the European shared inventory, removing duplication of the European shared inventory, and combining local inventory data to obtain final inventory data.
5. The replenishment suggestion generation method according to claim 2 or 4, wherein the method of acquiring daily sales data within a predetermined time further comprises:
the daily sales data is updated based on the FBA inventory and the european shared inventory.
6. The replenishment suggestion generation method according to claim 1, wherein the method of obtaining the stock duration comprises:
acquiring a purchase delivery period;
obtaining quality inspection time;
acquiring the number of saleable days after expected replenishment;
and calculating the stock duration based on the purchase delivery period, the quality inspection time and the number of saleable days after the expected replenishment.
7. The replenishment suggestion generation method according to claim 1, wherein the method for generating the replenishment suggestion based on the daily sales data, the stock data and the stock duration comprises:
calculating whether goods are broken or not in preset time and the time of the goods breaking based on daily sales data, inventory data and the time of the goods stock;
and calculating the purchasing amount and the purchasing time based on the outage time to generate a replenishment suggestion.
8. The replenishment suggestion generation method according to claim 1, characterized in that the method further comprises:
acquiring logistics timeliness and cost;
and screening to obtain a matched logistics mode based on the purchasing time, the purchasing quantity, the logistics timeliness and the cost.
9. A replenishment suggestion generation system, comprising:
the daily sales data acquisition module is used for acquiring daily sales data in preset time;
the inventory data acquisition module is used for acquiring inventory data in preset time;
the stock duration acquisition module is used for acquiring stock duration;
and the replenishment suggestion module is used for generating replenishment suggestions based on the daily sales data, the inventory data and the stock preparation duration.
10. A computer-readable storage medium storing a replenishment suggestion generation method capable of being loaded and executed by a processor according to claims 1-8.
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