Consumable demand quantity determination method and device, equipment and storage medium

Abstract

The invention provides a consumable demand quantity determination method and device, equipment and a storage medium, and relates to the field of big data. The method comprises the steps that the demand quantity of computer accessory consumables in each month in a preset historical time period is obtained, and the historical time period is a time period determined in advance according to the service life of computer accessories; obtaining the number of computer accounts in each month in the historical time period; and according to the number of the computer accounts in each month and the demand quantity of the computer accessory consumables in each month in the historical time period, determining the target demand quantity of the computer accessory consumables in the next month. When the target demand quantity of the consumables is calculated, not only is the historical condition of accessory use considered, but also the actual account number change is combined, so that the actual fluctuation of the demand can be better reflected, the accuracy of predicting the demand quantity of the consumables is improved, and capital occupation and storage cost increase caused by excessive inventory are avoided; and the problem of accessory shortage caused by insufficient inventory can be avoided, and continuity and smoothness of business operation are ensured.

Description

Technical Field

[0001] The present application relates to the field of big data, and in particular to a method, device, equipment and storage medium for determining the demand for consumables. Background Art

[0002] With the popularity of remote and flexible office work, laptops have become one of the essential devices for modern enterprises. As accessories of laptops, batteries and mice have a direct impact on the efficiency of equipment use and the work experience of employees. To ensure the normal operation of equipment and avoid work interruptions, enterprises need to manage inventory accurately to ensure timely replacement of damaged accessories.

[0003] Due to the long procurement cycle, companies often rush to purchase when inventory is insufficient, resulting in excessive purchases. When demand decreases, the accessories may expire or cannot be used in time, resulting in inventory backlogs. On the contrary, if forecasting errors lead to insufficient inventory, there may be a situation where batteries are urgently needed but cannot be obtained in time, affecting employee work efficiency.

[0004] Therefore, how to accurately predict the future demand for computer accessories and consumables is an urgent problem to be solved. Summary of the invention

[0005] The present application provides a method, device, equipment and storage medium for determining the demand for consumables, so as to improve the accuracy of predicting the future demand for computer accessories consumables.

[0006] In a first aspect, the present application provides a method for determining a required amount of consumables, the method comprising:

[0007] Obtaining the monthly demand for computer accessories consumables within a preset historical time period, wherein the historical time period is a time period pre-determined based on the service life of the computer accessories;

[0008] Get the number of computer accounts for each month in the historical time period;

[0009] The target demand for computer accessories and consumables for the next month is determined based on the number of computer accounts and the demand for computer accessories and consumables for each month during the historical time period.

[0010] Optionally, determining the target demand for computer consumables for the next month according to the number of computer accounts and the demand for computer consumables for each month in the historical time period includes:

[0011] Determine the target baseline demand for computer accessories and consumables for the next month based on the demand for computer accessories and consumables each month;

[0012] Based on the number of computer accounts each month, determine the average number of accounts over the historical time period;

[0013] Divide the current number of accounts by the average number of accounts to obtain the account coefficient;

[0014] The target base demand is multiplied by the account coefficient to obtain the target demand.

[0015] Optionally, determining the target baseline demand for computer accessories and consumables for the next month based on the demand for computer accessories and consumables each month includes:

[0016] Get the number of online days for each computer account in each month;

[0017] Determine the consumption coefficient for each month according to the online days and the preset working days for each month;

[0018] Determine the monthly baseline demand based on the monthly demand and consumption coefficient of computer parts and consumables;

[0019] The target baseline demand is determined based on the monthly baseline demand.

[0020] Optionally, determining the consumption coefficient for each month according to the online days and the preset working days for each month includes:

[0021] Determine the total actual working time of all computer accounts based on the number of online days and the daily online time;

[0022] Determine the total standard working hours for all computer accounts based on the number of working days and the preset standard working hours;

[0023] The actual working time is divided by the standard working time to obtain the consumption coefficient.

[0024] Optionally, the determination of the monthly benchmark demand based on the monthly demand and consumption coefficient of computer accessories and consumables includes:

[0025] The monthly benchmark demand is obtained by multiplying the monthly demand for computer accessories and consumables by the consumption coefficient.

[0026] Optionally, determining the target baseline demand according to the monthly baseline demand includes:

[0027] Determine the slope and intercept of the linear regression equation according to the monthly benchmark demand;

[0028] The target baseline demand for the next month is determined based on the slope and the intercept.

[0029] In a second aspect, the present application further provides a device for determining a required amount of consumables, the device comprising:

[0030] A first acquisition module is used to acquire the demand for computer accessories consumables each month within a preset historical time period, wherein the historical time period is a time period pre-determined according to the battery life of the computer accessories;

[0031] A second acquisition module is used to acquire the number of computer accounts in each month within the historical time period;

[0032] The determination module is used to determine the target demand for computer accessories and consumables for the next month based on the number of computer accounts in each month and the demand for computer accessories and consumables in each month during the historical time period.

[0033] Optionally, the determining module includes:

[0034] The first determination unit is used to determine the target baseline demand for computer accessories and consumables for the next month based on the demand for computer accessories and consumables each month;

[0035] A second determining unit is used to determine the average number of accounts in the historical time period according to the number of computer accounts in each month;

[0036] A third determining unit is used to divide the current number of accounts by the average number of accounts to obtain an account coefficient;

[0037] The fourth determining unit is used to multiply the target base demand by the account coefficient to obtain the target demand.

[0038] Optionally, the first determining unit is specifically configured to:

[0039] Get the number of online days for each computer account in each month;

[0040] Determine the consumption coefficient for each month according to the online days and the preset working days for each month;

[0041] Determine the monthly baseline demand based on the monthly demand and consumption coefficient of computer parts and consumables;

[0042] The target baseline demand is determined based on the monthly baseline demand.

[0043] Optionally, the third determining unit is specifically configured to:

[0044] Determine the total actual working time of all computer accounts based on the number of online days and the daily online time;

[0045] Determine the total standard working hours for all computer accounts based on the number of working days and the preset standard working hours;

[0046] The actual working time is divided by the standard working time to obtain the consumption coefficient.

[0047] Optionally, the first determining unit is further configured to:

[0048] The monthly benchmark demand is obtained by multiplying the monthly demand for computer accessories and consumables by the consumption coefficient.

[0049] Optionally, the fourth determining unit is specifically configured to:

[0050] Determine the slope and intercept of the linear regression equation according to the monthly benchmark demand;

[0051] The target baseline demand for the next month is determined based on the slope and the intercept.

[0052] In a third aspect, the present application further provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0053] The memory stores computer-executable instructions;

[0054] The processor executes the computer-executable instructions stored in the memory to implement the method as described in any one of the first aspects.

[0055] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method as described in any one of the first aspects.

[0056] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the method as described in any one of the first aspects.

[0057] The present application provides a method, device, equipment and storage medium for determining the demand for consumables, the method comprising: obtaining the demand for computer accessories consumables in each month within a preset historical time period, wherein the historical time period is a time period determined in advance according to the service life of computer accessories; obtaining the number of computer accounts in each month within the historical time period; determining the target demand for computer accessories consumables for the next month according to the number of computer accounts in each month within the historical time period and the demand for computer accessories consumables in each month. By obtaining historical data (including the number of computer accounts and the demand for accessories in each month), the demand trend can be analyzed according to the actual usage and the change in the number of accounts, and an accurate prediction result can be obtained. When calculating the target demand for consumables, not only the historical situation of the use of accessories is considered, but also the actual change in the number of accounts is combined, which can better reflect the actual fluctuation of demand and improve the accuracy of the prediction of consumable demand. Avoiding the increase in capital occupation and storage costs caused by excessive inventory, and avoiding the problem of accessories shortage caused by insufficient inventory, can ensure the continuity and smoothness of business operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0059] Figure 1 A flow chart of a method for determining the amount of consumables required provided for this application;

[0060] Figure 2 Schematic diagram of the process of determining the consumables demand provided in this application Figure 2 ;

[0061] Figure 3 Schematic diagram of the process of determining the consumables demand provided in this application Figure 3 ;

[0062] Figure 4 A schematic diagram of the structure of a device for determining the demand for consumables provided in this application;

[0063] Figure 5 A schematic diagram of the structure of the electronic device provided in this application.

[0064] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0065] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0066] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0067] In addition, this application involves conducting big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.), and using artificial intelligence technology to make automated decisions, and making technical solutions that have a significant impact on personal rights and interests based on the results of automated decisions. The application provides users with corresponding operation entrances for them to choose to agree or reject the results of automated decisions; if the user chooses to reject, the expert decision-making process will be entered.

[0068] It should be noted that the method, device, equipment and storage medium for determining the demand for consumables provided in the present application can be used in the field of big data, and can also be used in any field other than big data. The application field of the method, device, equipment and storage medium for determining the demand for consumables in the present application is not limited.

[0069] As the scale of enterprises continues to expand, the types and quantities of office equipment are also increasing, involving a wide variety of consumables, such as laptop batteries and mice. The existing procurement method is that when accessories need to be replaced, users submit applications for subsequent consumable procurement. However, this method takes a very long time and cannot achieve efficient inventory allocation. If a large number of computer accessories are purchased at one time, if the inventory is not accurately controlled, it may result in inventory backlogs, waste of resources and other consequences.

[0070] Based on this, the present application provides a method for determining the demand for consumables, which is used to predict the demand for consumables in the future. The demand for consumables can be preliminarily predicted based on the monthly demand for consumables. In addition, the future demand for consumables is positively correlated with the number of computers used. Therefore, by introducing the number of computers used to determine the final demand, the accuracy of the consumables demand prediction can be improved, avoiding excessive inventory that leads to capital occupation and increased storage costs.

[0071] The present application can be applied to the demand forecast of laptop computer battery consumables, and can also be applied to the demand forecast of computer mouse, as well as the demand forecast of computer accessory consumables such as computer memory, keyboard, etc.

[0072] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0073] Figure 1 A flow chart of a method for determining the amount of consumables required provided for this application, such as Figure 1 As shown, the following steps are included:

[0074] S101. Obtain the demand for computer accessories consumables each month within a preset historical time period, wherein the historical time period is a time period determined in advance based on the service life of the computer accessories.

[0075] The demand for computer accessories and consumables consumed from inventory each month is recorded in advance, where computer accessories and consumables can be the demand for laptop batteries, keyboards, or mice.

[0076] For each accessory, determine the historical time period for future demand forecasting based on the service life of the computer accessory. For example, if the service life of a laptop battery is 3 years, then select the demand for each month in the past 3 years as historical data. If the service life of a mouse is 1 year, then select the demand for the past 12 months as historical data.

[0077] The actual computer parts replacement data for each month can be obtained through the company's monthly purchasing records or the monthly inventory reduction.

[0078] S102: Obtain the number of computer accounts in each month within a historical period.

[0079] In this step, the computer accessories needed each month are positively correlated with the number of computers currently in use, so the number of computers in use each month needs to be considered. The number of computers used by the company is related to the computer account. Each computer account corresponds to a computer. Therefore, the number of computer accounts can be used to represent the number of computers currently in use (that is, the number of users who have computer usage rights and are assigned computers). The number of computers issued is not used directly here, because some issued computers are not used, or the computer account is cancelled due to resignation, and the computer is not used.

[0080] S103. Determine the target demand for next month based on the number of computer accounts and the demand for computer accessories and consumables each month in a historical period.

[0081] In this step, combined with the changes in the demand for consumables each month, a preliminary forecast of the target baseline demand for next month can be made. Combined with the changing trend of the number of computer accounts, the target demand for next month can be further revised.

[0082] The target baseline demand can be determined in the following ways:

[0083] In one implementation, the slope and intercept of the linear regression equation are determined based on the monthly consumables demand; and the target baseline demand for the next month is determined based on the slope and intercept.

[0084] In one implementation, the average consumables demand is determined based on the consumables demand each month, and the average consumables demand is used as the target benchmark demand.

[0085] After calculating the target baseline demand, the target demand needs to be determined based on changes in the number of accounts.

[0086] In one implementation, the average number of accounts in a historical time period is determined based on the change in the number of computer accounts each month; the current number of accounts is obtained. The current number of accounts is divided by the average number of accounts to obtain the account coefficient; the target baseline demand is multiplied by the account coefficient to obtain the final target demand. In this way, the consumables required for next month is predicted, the current number of accounts is used as the number of accounts for next month, and then the change in the number of accounts is determined. For example, assuming that the company's accounts have been kept within a very small fluctuation range before, the company is facing an expansion, and the number of computer accounts has increased by 0.3 times this month. The computers distributed to this part of the staff are also in stock, and the computers used by this part of the users will also encounter the problem of replacing accessories. Through this method, it can be determined that the account coefficient is 1.3 times, multiplied by the target baseline demand, and the next number of accounts can be obtained. Similarly, when the company encounters a phenomenon of reducing staff and the number of accounts decreases, according to this method, the required consumables demand can also be dynamically adjusted based on the change in the number of accounts.

[0087] In one implementation, the number of computer accounts for the next month can be predicted based on the change in the number of computer accounts each month. The number of computers for the next month is divided by the average number of accounts in the historical period to obtain the account coefficient. The target baseline demand is multiplied by the account coefficient to obtain the final target demand. In this way, the number of consumables for the next month can be adjusted based on the predicted number of account changes.

[0088] Not only can the demand for consumables in the next month be predicted, but also the demand for consumables in the next two months, or the demand for consumables in a longer procurement cycle in the future.

[0089] This embodiment provides a method for determining the demand for consumables, which includes: obtaining the demand for computer accessories consumables in each month within a preset historical time period, wherein the historical time period is a time period determined in advance based on the service life of computer accessories; obtaining the number of computer accounts in each month within the historical time period; and determining the target demand for computer accessories consumables for the next month based on the number of computer accounts in each month within the historical time period and the demand for computer accessories consumables in each month. By obtaining historical data (including the number of computer accounts and the demand for accessories in each month), the demand trend can be analyzed based on actual usage and changes in the number of accounts to obtain accurate prediction results. When calculating the target demand for consumables, not only the historical situation of accessory use is considered, but also the actual changes in the number of accounts are combined, which can better reflect the actual fluctuations in demand and improve the accuracy of the prediction of consumable demand. Avoiding excessive inventory leading to increased capital occupation and storage costs, and avoiding the problem of accessory shortages caused by insufficient inventory can also ensure the continuity and smoothness of business operations.

[0090] During the use of a computer, the demand for accessories is not only related to the number of accounts, but also to the actual use time and frequency of the computer. The consumption rate of consumables is different when the computer is used for a long time or occasionally. The following is an example to introduce a method for predicting the demand for consumables under variable conditions combined with computer usage.

[0091] Figure 2 Schematic diagram of the process of determining the consumables demand provided in this application Figure 2 ,like Figure 2 As shown, the following steps are included:

[0092] S201. Obtain the number of online days of the computer account in each month.

[0093] First, we need to collect the number of days each computer account is online in each month. Usually, the number of days online refers to the number of days the computer account is actually used in that month. It is usually determined by the computer's connection to the intranet, or the status of the internal communication tool, or by the user's clock-in record corresponding to the computer account.

[0094] Users may take leave, vacation, or work overtime, so the number of online days per month for each computer account is different, and the number of online days per month for different computer accounts may also be different. The number of online days per month can be used to measure computer usage.

[0095] S202. Determine the consumption coefficient for each month according to the number of online days and the number of working days for each month.

[0096] In one implementation, the consumption coefficient of each computer account in each month is first calculated. For each computer account, the consumption coefficient for each month is obtained by dividing the number of online days by the number of working days. Then, based on the consumption coefficients of all computer accounts in that month, the average consumption coefficient is determined. The number of working days can be the standard number of working days (for example, 22 working days in a month), and the number of online days is the number of days each account is actually online. The consumption coefficient is used to indicate the degree of actual use. The larger the consumption coefficient, the greater the usage of the computer in that month.

[0097] For example, if there are 20 working days in a month and employee A's computer account is online for 15 days, the consumption coefficient of this account is 0.75. Employee B's computer account is online for 30 days, so the consumption coefficient of this account is 1.5. Employee B's computer account is online for 2 days, so the consumption coefficient of this account is 0.1. Then calculate the average consumption coefficient of all employee computer accounts as the consumption coefficient for each month.

[0098] In another implementation, the consumption coefficient for each month is determined based on the number of online days and working days in each month, combined with the actual working hours of each day.

[0099] S203. Determine the monthly baseline demand based on the monthly demand and consumption coefficient of computer accessories and consumables.

[0100] In one implementation, the consumption coefficient is multiplied by the monthly demand for computer accessories and consumables to obtain the monthly benchmark demand for each month. The calculated monthly benchmark demand represents the overall computer usage level for that month and is used to predict the subsequent consumables demand, but does not guide the consumables demand for that month.

[0101] S204. Determine the target baseline demand based on the monthly baseline demand.

[0102] After obtaining the benchmark demand for a single month in the historical period, the target benchmark demand for the next month can be calculated through a linear regression model, or the average value can be taken as the target benchmark demand.

[0103] S205. Determine the average number of accounts in a historical period based on the number of computer accounts in each month.

[0104] S206. Divide the current number of accounts by the average number of accounts to obtain the account coefficient.

[0105] In this step, the current number of accounts may be directly used as the number of accounts for next month to calculate the account coefficient, or the number of accounts for next month may be predicted according to the method in the above embodiment to further calculate the account coefficient.

[0106] S207. Multiply the target baseline demand by the account coefficient to obtain the target demand.

[0107] Through the above steps, the consumption coefficient is calculated based on the number of online days of the computer account, and the baseline demand is optimized. The greater the consumption, the more consumables will be needed in the future, thereby improving the accuracy of future forecasts.

[0108] The above embodiment takes into account the influence of the number of days the computer is used, but in actual use, the user's usage time is also very critical. There are cases where the user is online on the same day but does not use it. Therefore, when calculating the consumption coefficient of each account, the online time of the computer account can be combined.

[0109] Figure 3 Schematic diagram of the process of determining the consumables demand provided in this application Figure 3 ,like Figure 3 As shown, based on the above-mentioned embodiment 2, step S202 determines the consumption coefficient, including the following steps:

[0110] S2021. Determine the actual working hours based on the number of online days each month and the online hours each day.

[0111] Online days refer to the number of days that the user is actually connected to the computer and in working state. Daily online time refers to the time each account is online every day (for example, how many hours are actually worked). The "online time" here may be different from the working time. For example, there may be invalid time due to some reasons (such as rest, computer idleness, user inaction, etc.). Online time can be determined by the daily online time of the network or the online time of the communication software.

[0112] The online time of each computer account is calculated each month to get the actual working time of each account. Then the actual working time of all computer accounts is accumulated to get the total actual working time.

[0113] For example, if an account has 5 online days in a certain month, and the user's online time on these days is 8 hours, 9 hours, 1 hour, 8 hours, 0 hours, etc., then the user's actual working time is the sum of the online time on these days, which is 26 hours.

[0114] S2022. Determine the standard working hours based on the number of working days in each month and the standard working hours per day.

[0115] Standard working hours refer to the theoretical total working hours calculated based on the number of working days and the standard working hours per day. Assuming the standard working hours per day is 8 hours and there are 20 working days in this month, the standard working hours for a single user is 160 hours. The standard working hours of all computer accounts are accumulated to get the total standard working hours.

[0116] S2023. Divide the actual working hours by the standard working hours to obtain the consumption coefficient for each month.

[0117] When calculating the consumption coefficient, not only the number of online days is taken into account, but also the actual working hours of each account. The consumption coefficient reflects the ratio between the actual workload of the account and the standard workload. The higher the actual working hours of the user, the greater the consumption coefficient.

[0118] Through the above method, the working hours and actual consumption of each account can be accurately measured. Based on the online time and actual working time of each account, the calculated consumption coefficient can more accurately reflect the actual work intensity of the account, providing a more valuable basis for subsequent consumable demand forecasting.

[0119] Based on the working hours considered in the above embodiment, different types of users have different degrees of computer usage. For example, the computers of R&D personnel require a large amount of computing and the tasks to be performed are complex, while the tasks of warehouse management and other jobs are simple. Therefore, when calculating the consumption coefficient, it is necessary to introduce a type of work coefficient to distinguish the degree of computer usage. Specifically, after calculating the actual working hours of each computer account, multiply it by the type of work coefficient to obtain the optimized actual working hours. Then, the total actual working hours of all computer accounts are accumulated and calculated. Exemplarily, the type of work coefficient of R&D personnel can be set to 1.1, the type of work coefficient of warehouse management personnel can be set to 0.9, and the type of work coefficient of testers can be set to 1.

[0120] After obtaining the forecast results of the consumables demand for the next month or the next period of time, the relevant departments need to review and approve them. First, the data analysis team will summarize the forecast results and submit them to the procurement, finance, warehouse and production departments for review. The procurement department confirms whether the supply is sufficient, and the warehouse checks whether the inventory can meet the consumables demand. If it does not meet the consumables demand, purchase them in time.

[0121] Figure 4 A schematic diagram of a device for determining the amount of consumables required provided in this application is shown in FIG. Figure 4 As shown, the device 40 for determining the consumables demand comprises:

[0122] The first acquisition module 401 is used to acquire the demand for computer accessories consumables in each month within a preset historical time period, wherein the historical time period is a time period pre-determined according to the battery life of the computer accessories;

[0123] The second acquisition module 402 is used to acquire the number of computer accounts in each month within the historical time period;

[0124] The determination module 403 is used to determine the target demand for computer accessories and consumables for the next month according to the number of computer accounts and the demand for computer accessories and consumables in each month during the historical time period.

[0125] Optionally, the determining module 403 includes:

[0126] The first determining unit 4031 is used to determine the target baseline demand for computer parts and consumables for the next month according to the demand for computer parts and consumables each month;

[0127] The second determining unit 4032 is used to determine the average number of accounts in the historical time period according to the number of computer accounts in each month;

[0128] The third determining unit 4033 is used to divide the current number of accounts by the average number of accounts to obtain an account coefficient;

[0129] The fourth determining unit 4034 is configured to multiply the target baseline demand by the account coefficient to obtain the target demand.

[0130] Optionally, the first determining unit 4031 is specifically configured to:

[0131] Get the number of online days for each computer account in each month;

[0132] Determine the consumption coefficient for each month according to the online days and the preset working days for each month;

[0133] Determine the monthly baseline demand based on the monthly demand and consumption coefficient of computer parts and consumables;

[0134] The target baseline demand is determined based on the monthly baseline demand.

[0135] Optionally, the third determining unit 4033 is specifically configured to:

[0136] Determine the total actual working time of all computer accounts based on the number of online days and the daily online time;

[0137] Determine the total standard working hours for all computer accounts based on the number of working days and the preset standard working hours;

[0138] The actual working time is divided by the standard working time to obtain the consumption coefficient.

[0139] Optionally, the first determining unit 4031 is further configured to:

[0140] The monthly benchmark demand is obtained by multiplying the monthly demand for computer accessories and consumables by the consumption coefficient.

[0141] Optionally, the fourth determining unit 4034 is specifically configured to:

[0142] Determine the slope and intercept of the linear regression equation according to the monthly benchmark demand;

[0143] The target baseline demand for the next month is determined based on the slope and the intercept.

[0144] The device for determining the demand for consumables provided in this embodiment can execute the method provided in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be described in detail here.

[0145] Figure 5 This is a schematic diagram of the structure of the electronic device provided in this application. Figure 5 As shown, the electronic device 50 provided in this embodiment includes: at least one processor 501 and a memory 502. Optionally, the device 50 also includes a communication component 503. The processor 501, the memory 502 and the communication component 503 are connected via a bus 504.

[0146] In a specific implementation process, at least one processor 501 executes the computer-executable instructions stored in the memory 502, so that at least one processor 501 executes the above method.

[0147] The specific implementation process of the processor 501 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0148] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0149] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0150] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0151] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0152] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0153] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0154] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0155] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0156] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0157] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0158] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0159] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0160] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for determining the demand for consumables, characterized in that: The method comprises: Obtaining the monthly demand for computer accessories consumables within a preset historical time period, wherein the historical time period is a time period pre-determined based on the service life of the computer accessories; Get the number of computer accounts for each month in the historical time period; The target demand for computer accessories and consumables for the next month is determined based on the number of computer accounts and the demand for computer accessories and consumables for each month during the historical time period.

2. The method according to claim 1, characterized in that Determining the target demand for computer consumables for the next month based on the number of computer accounts and the demand for computer consumables for each month in the historical time period includes: Determine the target baseline demand for computer accessories and consumables for the next month based on the demand for computer accessories and consumables each month; Based on the number of computer accounts each month, determine the average number of accounts over the historical time period; Divide the current number of accounts by the average number of accounts to obtain the account coefficient; The target base demand is multiplied by the account coefficient to obtain the target demand.

3. The method according to claim 2, characterized in that The target baseline demand for computer accessories and consumables for the next month is determined based on the demand for computer accessories and consumables each month, including: Get the number of online days for each computer account in each month; Determine the consumption coefficient for each month according to the online days and the preset working days for each month; Determine the monthly baseline demand based on the monthly demand and consumption coefficient of computer parts and consumables; The target baseline demand is determined based on the monthly baseline demand.

4. The method according to claim 3, characterized in that Determining the consumption coefficient for each month according to the online days and the preset working days for each month includes: Determine the total actual working time of all computer accounts based on the number of online days and the daily online time; Determine the total standard working hours for all computer accounts based on the number of working days and the preset standard working hours; The actual working time is divided by the standard working time to obtain the consumption coefficient.

5. The method according to claim 3, characterized in that: The monthly benchmark demand is determined based on the monthly demand and consumption coefficient of computer parts and consumables, including: The monthly benchmark demand is obtained by multiplying the monthly demand for computer accessories and consumables by the consumption coefficient.

6. The method according to any one of claims 3 to 5, characterized in that: The step of determining the target baseline demand according to the monthly baseline demand includes: Determine the slope and intercept of the linear regression equation according to the monthly benchmark demand; The target baseline demand for the next month is determined based on the slope and the intercept.

7. A device for determining the amount of consumables required, characterized in that: The device comprises: A first acquisition module is used to acquire the demand for computer accessories consumables each month within a preset historical time period, wherein the historical time period is a time period pre-determined according to the battery life of the computer accessories; A second acquisition module is used to acquire the number of computer accounts in each month within the historical time period; The determination module is used to determine the target demand for computer accessories and consumables for the next month based on the number of computer accounts in each month and the demand for computer accessories and consumables in each month during the historical time period.

8. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when being executed by a processor.

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