CN113947361A - Inventory trend analysis method, equipment and medium - Google Patents
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Abstract
The invention relates to the field of inventory management, and particularly discloses an inventory trend analysis method, equipment and a medium, wherein the method comprises the steps of obtaining the remaining inventory number of commodities in a current warehouse and the daily sales volume of the commodities in the last standard sales cycle; calculating the weighted daily sales volume of the inventory goods; the time of arrival of the commodities and the quantity of arrival of the commodities are obtained, the stock change trend of the commodities in a future period of time is calculated, the quantity of the commodities to be prepared is automatically calculated, and a replenishment suggestion is given. The invention provides the reference of the replenishment plan for the sales company by automatically calculating the quantity of the commodities to be prepared; the auxiliary merchant accelerates the fund turnover, reduces the stock backlog and improves the stock turnover rate; meanwhile, the workload of daily stock calculation of the sales department is reduced, so that the modern large and efficient E-commerce inventory management trend is adapted.
Description
Technical Field
The invention relates to the field of inventory management, in particular to an inventory trend analysis method, equipment and a medium.
Background
The inventory cost has a considerable proportion of the total cost of the enterprise, how to effectively control the inventory and reduce the inventory cost, and meanwhile, the continuous sales chain is also ensured, which is an important factor for reducing the total cost and improving the profit of the enterprise.
In recent years, with the rapid development of the mobile internet, the original network shopping with a higher threshold becomes simpler and more popular, and with the large increase of the transaction amount of the e-commerce platform, as the periodic outbreak shipment of 618-like and twenty-one preferential activities of the platform gradually becomes a normal state, the sudden increase of the commodity storage and the express quantity provides a serious challenge for the storage management capability. The storage management is of great importance to the e-commerce enterprises, and if the storage management is not good, a large amount of invalid storage is generated, so that the operation cost of the e-commerce enterprises is increased, or goods are insufficient, the goods cannot be kept to be delivered in time, and the problems of large-batch order loss and after-sale are caused. Therefore, dynamic management of e-commerce commodity warehousing is more important, the requirement of e-commerce enterprises on sufficient commodity inventory is met, and meanwhile, the cost input of e-commerce enterprises on important warehousing assets needs to be reduced, so that the operation cost of e-commerce is effectively reduced.
With the deep development of information technologies such as the internet, big data and the like, various industries pay more and more attention to the value of the data, and good economic benefits are generated by carrying out secondary analysis and utilization on the existing data through data mining related technologies. The accuracy and timeliness of inventory management information are of great importance to the operation of a modern E-commerce platform, the market trend of related commodities is effectively predicted by continuously monitoring historical order information, market information and policy information related to the inventory commodities, the inventory of the related commodities is adjusted according to the predicted market trend, and the dynamic and timely adjustment of the inventory of the commodities can be achieved.
The traditional management mode cannot really provide efficient and visual inventory analysis and prediction for managers, and is difficult to adapt to the current situations of large fluctuation, fast rhythm, fast expansion, and fast pace of product line development and cancellation of the current E-commerce storage management.
Disclosure of Invention
The invention provides an inventory trend analysis method, equipment and a medium, which aims to solve the problems that a company accelerates capital turnover, reduces inventory backlog, improves inventory turnover rate and reduces the workload of daily stock preparation calculation.
The technical scheme adopted by the invention is as follows: an inventory trend analysis method, comprising the following steps:
s1, data collection: appointing a plurality of days as a standard sale period, and acquiring the remaining inventory number of the commodities in the current warehouse, the daily sales volume of the commodities in a plurality of days in the past and the on-road period of commodity replenishment;
s2, calculating the weighted daily sales: counting commodity sales in a plurality of past time periods with different lengths in real time, distributing sales weight corresponding to each time period, and weighting daily sales (sales in a certain time period/days in the time period multiplied by the sales weight in the time period);
s3, calculating the number of bins: acquiring the scheduling sending time and the corresponding delivery quantity of all replenishment orders of commodities in a plurality of standard sales periods, wherein the scheduling to warehouse time is the scheduling sending time plus the in-transit period, and the delivery to warehouse quantity is equal to the sum of the delivery quantity from the current day to warehouse;
s4, calculating the stock trend: the remaining inventory number of the current day is the remaining inventory number of the previous day plus the quantity from the current day to the warehouse-the weighted daily sales volume, and the remaining inventory number of the commodities per day in a plurality of standard sales periods starting from the current date is calculated in sequence according to the formula;
s5, calculating a stock plan: and calculating whether replenishment is needed daily on the basis of the step S4, if the remaining stock quantity of the current day is less than or equal to the in-transit period multiplied by the weighted daily sales volume, taking the current day as the delivery time deadline of the replenishment order, forming a stock plan, sending the stock plan to a supplier for auditing, newly adding the replenishment order after the approval is passed, and repeating the steps S3, S4 and S5 until the remaining stock quantity of each day is more than the in-transit period multiplied by the weighted daily sales volume.
Preferably, the stock plan in step S5 further includes the following sub-steps before being sent to the consignee for review:
a1, whether to output stock plan: and calculating the gross interest rate of the commodity, if the gross interest rate of the commodity is less than a first threshold value, not outputting the stock plan of the commodity, and if the gross interest rate of the commodity is more than or equal to the first threshold value, automatically outputting the stock plan.
Preferably, the stock plan is provided with a plurality of priorities, and when the gross interest rate of the commodity is larger than or equal to the first threshold value, the priority of the corresponding stock plan is increased by one level when the gross interest rate of the commodity increases by a plurality of points.
Preferably, in the standard sales cycle in step S1, when the location of the warehouse is a local warehouse, the standard sales cycle is 7 days; when the warehouse is an overseas warehouse and an air transportation and express delivery mode is adopted, the standard sale period is 7 days, and when a marine transportation mode is adopted, the standard sale period is 14 days.
Preferably, the stock plan in step S5 further includes: the number of days available in the bin is calculated as the number of remaining inventory/weighted daily sales.
Preferably, the stock plan in step S5 further includes: and calculating the stock shortage date, wherein the stock shortage date is the current date + the number of the remaining stock/the weighted daily sales.
Preferably, in step S2, the weighted daily sales further include sales promotion amount, and the weighted daily sales on the day is ∑ (sales amount for a certain time slot/number of days in the time slot × sales weight for the time slot) + sales promotion amount on the date of the sales promotion.
An inventory trend analysis device comprising a storage means for storing one or more programs and a processor; when the one or more programs are executed by the processor, the processor implements the inventory trend analysis method described above.
A computer-readable storage medium storing at least one program, characterized in that: when executed by a processor, the program implements the inventory trend analysis method described above.
The invention has the beneficial effects that:
(1) the quantity of the commodities to be prepared is automatically calculated, and a reference of a replenishment plan is provided for a sales company;
(2) the capital turnover is accelerated, the stock backlog is reduced, and the stock turnover rate is improved; and meanwhile, the workload of daily calculation and stock of sales personnel and financial personnel is reduced.
Drawings
FIG. 1 is a flow chart of an inventory trend calculation of the present invention;
FIG. 2 is a inventory trend line graph of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and the detailed description, and it should be noted that any combination of the embodiments or technical features described below can be used to form a new embodiment without conflict.
Referring to fig. 1 to 2, the present invention is an inventory trend analysis method, apparatus, and medium.
The inventory trend analysis method comprises the following implementation steps:
s1, data collection: appointing a plurality of days as a standard sale period, and acquiring the remaining inventory number of the commodities in the current warehouse, the daily sales volume of the commodities in a plurality of days in the past and the on-road period of commodity replenishment;
s2, calculating the weighted daily sales: counting commodity sales in a plurality of past time periods with different lengths in real time, distributing sales weight corresponding to each time period, and weighting daily sales (sales in a certain time period/days in the time period multiplied by the sales weight in the time period);
s3, calculating the number of bins: acquiring the scheduling sending time and the corresponding delivery quantity of all replenishment orders of commodities in a plurality of standard sales periods, wherein the scheduling to warehouse time is the scheduling sending time plus the in-transit period, and the delivery to warehouse quantity is equal to the sum of the delivery quantity from the current day to warehouse;
s4, calculating the stock trend: the remaining inventory number of the current day is the remaining inventory number of the previous day plus the quantity from the current day to the warehouse-the weighted daily sales volume, and the remaining inventory number of the commodities per day in a plurality of standard sales periods starting from the current date is calculated in sequence according to the formula;
s5, calculating a stock plan: and calculating whether replenishment is needed daily on the basis of the step S4, if the remaining stock quantity of the current day is less than or equal to the in-transit period multiplied by the weighted daily sales volume, taking the current day as the delivery time deadline of the replenishment order, forming a stock plan, sending the stock plan to a supplier for auditing, newly adding the replenishment order after the approval is passed, and repeating the steps S3, S4 and S5 until the remaining stock quantity of each day is more than the in-transit period multiplied by the weighted daily sales volume.
Preferably, the stock plan in step S5, before being sent to the consignee for review, further includes the following sub-steps:
a1, whether to output stock plan: and calculating the gross interest rate of the commodity, if the gross interest rate of the commodity is less than a first threshold value, not outputting the stock plan of the commodity, and if the gross interest rate of the commodity is more than or equal to the first threshold value, automatically outputting the stock plan.
Preferably, the stock plan is provided with a plurality of priorities, and when the gross interest rate of the commodity is larger than or equal to the first threshold value, the priority of the corresponding stock plan is increased by one level when the gross interest rate of the commodity is increased by a plurality of points.
Preferably, in the standard sale period in step S1, when the location of the warehouse is a local warehouse, the standard sale period is 7 days; when the warehouse is an overseas warehouse and an air transportation and express delivery mode is adopted, the standard sale period is 7 days, and when a marine transportation mode is adopted, the standard sale period is 14 days.
Preferably, the stock plan in step S5 further includes: calculating the number of days available for sale in the warehouse, wherein the number of days available for sale in the warehouse is the number of the rest stock/the weighted daily sales; the method is convenient for salesmen and auditors for goods delivery to conveniently check the expected normal sales of the current warehouse for which days can be met under the condition that goods are not replenished, and is convenient to be used as a reference when adjusting the goods plan.
Preferably, the stock plan in step S5 further includes: calculating the stock shortage date, wherein the stock shortage date is the current date plus the remaining stock quantity/the weighted daily sales; the auditor for the salesperson and the incoming goods can conveniently check the current estimated selling time of the stock, and can conveniently be used as a reference when the goods plan is adjusted.
Preferably, in step S2, the weighted daily sales further include sales promotion amount, and the weighted daily sales on the day is ∑ (sales amount for a certain time slot/number of days in the time slot × sales weight for the time slot) + sales promotion amount on the date of the sales promotion.
An inventory trend analysis device includes a storage device for storing one or more programs and a processor; when the one or more programs are executed by the processor, the processor implements the inventory trend analysis method described above.
Wherein the device may also preferably comprise a communication interface for communication and data interactive transmission with an external device or the internet.
It should be noted that the memory may include a high-speed RAM memory, and may also include a nonvolatile memory (nonvolatile memory), such as at least one disk memory.
In a specific implementation, if the memory, the processor and the communication interface are integrated on a chip, the memory, the processor and the communication interface can complete mutual communication through the internal interface. If the memory, the processor and the communication interface are implemented independently, the memory, the processor and the communication interface may be connected to each other through a bus and perform communication with each other.
The present invention also discloses a computer-readable storage medium storing at least one program which, when executed by a processor, implements the above inventory trend analysis method.
It should be understood that the computer-readable storage medium is any data storage device that can store data or programs which can thereafter be read by a computer system. Examples of computer-readable storage media include: read-only memory, random access memory, CD-ROM, HDD, DVD, magnetic tape, optical data storage devices, and the like.
The computer readable storage medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.
Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, Radio Frequency (RF), etc., or any suitable combination of the foregoing.
In some embodiments, the computer-readable storage medium may also be non-transitory.
As one embodiment of the present invention, the above-mentioned scheme is implemented by a computer program based on Java language, a Spring group framework is adopted to build a software system, an Oracle database, a redis database and a mongodb database are used for data storage, and the operation flow of the program is as follows:
s1, data collection: appointing 7 days as a standard sale period, if the warehouse is overseas and the warehouse is prepared by a marine mode, the standard sale period is 14 days; acquiring the remaining inventory quantity of the commodities in the current warehouse in real time, and acquiring the on-road period of commodity replenishment according to the daily sales volume of the commodities in a plurality of days in the past;
s2, calculating the weighted daily sales: counting the sales of the commodities in the past 5 days, 10 days, 15 days and 30 days, wherein the sales weights are respectively 0.5, 0.25, 0.15 and 0.1, and the weighted daily sales are (5 days sales/5 multiplied by 0.5) + (10 days sales/10 multiplied by 0.25) + (15 days sales/15 multiplied by 0.15) + (30 days sales/30 multiplied by 0.1);
s3, calculating the number of bins: acquiring the scheduling sending time and the corresponding delivery quantity of all replenishment orders of commodities in a plurality of standard sales periods, wherein the scheduling to warehouse time is the scheduling sending time plus the in-transit period, and the delivery to warehouse quantity is equal to the sum of the delivery quantity of each scheduling to warehouse time on the same day;
s4, calculating the stock trend: the remaining inventory number of the current day is the remaining inventory number of the previous day plus the quantity from the current day to the warehouse-the weighted daily sales volume, and the remaining inventory number of the commodities per day in a plurality of standard sales periods starting from the current date is sequentially calculated according to the formula to form a statistical report and a curve graph output;
s5, calculating a stock plan:
calculating the number of days available for sale in the warehouse, wherein the number of days available for sale in the warehouse is the number of the rest stock/the weighted daily sales;
calculating the stock shortage date, wherein the stock shortage date is the current date plus the remaining stock quantity/the weighted daily sales;
calculating whether replenishment is needed daily on the basis of the step S4, and if the remaining inventory number on the current day is less than or equal to the in-transit period multiplied by the weighted daily sales, taking the current day as the delivery time deadline of the replenishment order;
calculating whether to output a stock plan: calculating the gross profit rate of the commodity, if the gross profit rate of the commodity is less than 10%, not outputting a stock plan of the commodity, and if the gross profit rate of the commodity is more than or equal to 10%, automatically outputting the stock plan for executing a replenishment purchasing process of the commodity;
and sending the stock plan to a stock taker for examination, adding the replenishment order after the examination is passed, and repeating the steps S3, S4 and S5 until the remaining stock quantity of each day is larger than the in-transit period multiplied by the weighted daily sales quantity.
The stock plan is also provided with a plurality of priorities, when the gross profit rate of the commodity is larger than or equal to 10%, the corresponding priority of the stock plan is improved by one level when the gross profit rate of the commodity is increased by 5%, the priority of the present embodiment is divided into 4 levels which respectively correspond to the gross profit rates of 10% -15%, 15% -20%, 20% -25% and more than 25%, and different priorities of automatic stock correspond to different prompting modes, evaluation flows, purchase priorities and the like, so that the commodity with higher profit can be subjected to priority replenishment purchase.
The sales department intuitively understands the inventory condition of the goods in a future period of time according to the inventory trend graph and the stock plan; meanwhile, the financial department can better and quickly evaluate the feasibility of stock according to the gross profit of stock and the stock sale period. Compared with the traditional inventory analysis and stock preparation flow:
1. the salesperson checks the stock condition and the sales condition, and calculates the quantity of the replenishment needed according to the stock condition and the sales condition;
2. according to the calculated quantity of the goods to be replenished, the salesperson creates a stock plan;
3. and the financial department evaluates the feasibility of stock according to the gross profit of stock and the stock sale period and carries out audit.
The scheme can automatically calculate the quantity of the commodities to be prepared, provide the reference of the replenishment plan for the sales company, make the preparation and inventory management of the commodities more clear and visual, and make the management more efficient and quick; the stock can be more reasonably prepared, so that the capital turnover is accelerated, the stock backlog is reduced, and the stock turnover rate is improved; and meanwhile, the workload of daily calculation and stock of sales personnel and financial personnel is reduced.
The above embodiments are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby, and any insubstantial changes and substitutions made by those skilled in the art based on the present invention are within the protection scope of the present invention.
Claims (9)
1. An inventory trend analysis method is characterized by comprising the following steps: the method comprises the following implementation steps:
s1, data collection: appointing a plurality of days as a standard sale period, and acquiring the remaining inventory number of the commodities in the current warehouse, the daily sales volume of the commodities in a plurality of days in the past and the on-road period of commodity replenishment;
s2, calculating the weighted daily sales: counting commodity sales in a plurality of past time periods with different lengths in real time, distributing sales weight corresponding to each time period, and weighting daily sales (sales in a certain time period/days in the time period multiplied by the sales weight in the time period);
s3, calculating the number of bins: acquiring the scheduling sending time and the corresponding delivery quantity of all replenishment orders of commodities in a plurality of standard sales periods, wherein the scheduling to warehouse time is the scheduling sending time plus the in-transit period, and the delivery to warehouse quantity is equal to the sum of the delivery quantity from the current day to warehouse;
s4, calculating the stock trend: the remaining inventory number of the current day is the remaining inventory number of the previous day plus the quantity from the current day to the warehouse-the weighted daily sales volume, and the remaining inventory number of the commodities per day in a plurality of standard sales periods starting from the current date is calculated in sequence according to the formula;
s5, calculating a stock plan: and calculating whether replenishment is needed daily on the basis of the step S4, if the remaining stock quantity of the current day is less than or equal to the in-transit period multiplied by the weighted daily sales volume, taking the current day as the delivery time deadline of the replenishment order, forming a stock plan, sending the stock plan to a supplier for auditing, newly adding the replenishment order after the approval is passed, and repeating the steps S3, S4 and S5 until the remaining stock quantity of each day is more than the in-transit period multiplied by the weighted daily sales volume.
2. The inventory trend analysis method of claim 1, wherein: the stock plan in step S5, before being sent to the consignee for review, further includes the following sub-steps:
a1, whether to output stock plan: and calculating the gross interest rate of the commodity, if the gross interest rate of the commodity is less than a first threshold value, not outputting the stock plan of the commodity, and if the gross interest rate of the commodity is more than or equal to the first threshold value, automatically outputting the stock plan.
3. The inventory trend analysis method of claim 2, wherein: the stock plan is provided with a plurality of priorities, and when the gross interest rate of the commodity is larger than or equal to a first threshold value, the priority of the corresponding stock plan is increased by one level when the gross interest rate of the commodity increases by a plurality of points.
4. The inventory trend analysis method of claim 1, wherein: in the standard sales cycle in step S1, when the location of the warehouse is a local warehouse, the standard sales cycle is 7 days; when the warehouse is an overseas warehouse and an air transportation and express delivery mode is adopted, the standard sale period is 7 days, and when a marine transportation mode is adopted, the standard sale period is 14 days.
5. The inventory trend analysis method of claim 1, wherein: the stock plan in step S5 further includes: the number of days available in the bin is calculated as the number of remaining inventory/weighted daily sales.
6. The inventory trend analysis method of claim 1, wherein: the stock plan in step S5 further includes: and calculating the stock shortage date, wherein the stock shortage date is the current date + the number of the remaining stock/the weighted daily sales.
7. The inventory trend analysis method of claim 1, wherein: in step S2, the weighted daily sales amount further includes a sales promotion amount, and the weighted daily sales amount on the day is ∑ (sales amount for a certain time slot/number of days in the time slot × sales amount weight for the time slot) + sales promotion amount on the date of the sales promotion.
8. An inventory trend analysis device, characterized by: the inventory trend analysis device includes a storage device for storing one or more programs and a processor; the one or more programs, when executed by the processor, implement the inventory trend analysis method of any one of claims 1-7.
9. A computer-readable storage medium storing at least one program, characterized in that: the program, when executed by a processor, implements the inventory trend analysis method according to any one of claims 1-7.
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| CN116051000A (en) * | 2023-02-16 | 2023-05-02 | 深圳一资源网络平台有限公司 | Data sales analysis method, system and readable storage medium |
| CN116342029A (en) * | 2023-03-06 | 2023-06-27 | 四川集鲜数智供应链科技有限公司 | Food inventory circulation method and food inventory circulation device |
| CN116823323A (en) * | 2023-08-28 | 2023-09-29 | 青岛场外市场清算中心有限公司 | Intelligent management method and system for market clearing data |
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