A mobile phone inventory management method and system based on sales curve matching

Abstract

The application relates to a mobile phone inventory management method and system based on sales curve matching, and relates to the technical field of inventory management. The application comprises the following steps: acquiring a store number and a store sales database; searching for a remaining inventory quantity and a total inventory quantity, and calculating a remaining inventory proportion according to the remaining inventory quantity and the total inventory quantity; acquiring a mobile phone model to be purchased; searching for a corresponding current sales curve from the store sales database, and acquiring a historical sales curve; matching the current sales curve with the historical sales curve one by one to obtain a similar sales curve; determining a current sales node, and determining a current sales quantity and a similar sales quantity; acquiring a sales cycle, and calculating a sales proportion according to the current sales quantity and the similar sales quantity; intercepting a similar future cycle sales quantity on the similar sales curve according to the current sales node and the sales cycle, and calculating a current future cycle sales quantity; generating a replenishment scheme, and replenishing according to the replenishment scheme. The application has the effect of improving inventory turnover accuracy.

Description

Technical Field

[0001] This invention relates to the field of inventory management technology, and in particular to a mobile phone inventory management method and system based on sales curve matching. Background Technology

[0002] With the development of the retail industry, inventory management of electronic products such as mobile phones has become a core aspect of enterprise operations management. Due to the characteristics of mobile phone products, such as frequent model updates, high unit value, and large sales fluctuations, retail stores must ensure a sufficient supply of popular models while preventing the accumulation of slow-moving inventory.

[0003] In related technologies, the management of store inventory mostly relies on manual experience-based judgment or fixed-period replenishment. Specifically, in the manual experience-based judgment model, store managers subjectively assess the stockout risk of each mobile phone model based on their own observations of mobile phone sales and their experience accumulated from past work, combined with information such as current inventory levels, recent customer traffic, and feedback from sales staff, and determine the models that need to be replenished and the corresponding replenishment quantities accordingly.

[0004] Regarding the aforementioned technologies, the replenishment results are highly subjective, which can easily lead to insufficient replenishment of popular models or excessive replenishment of slow-moving models, thereby affecting normal sales in stores and resulting in low inventory turnover accuracy. Summary of the Invention

[0005] To improve the accuracy of inventory turnover, this invention provides a mobile phone inventory management method and system based on sales curve matching.

[0006] In a first aspect, the present invention provides a mobile phone inventory management method based on sales curve matching, which adopts the following technical solution: A mobile phone inventory management method based on sales curve matching includes: Step 1: Obtain the store number and store sales database; Step 2: Find the remaining inventory and total inventory from the store sales database based on the store number, and calculate the remaining inventory percentage based on the remaining inventory and total inventory. Step 3: When the remaining inventory ratio is less than the preset inventory warning threshold, obtain the mobile phone models to be purchased; Step 4: Based on the store number and the model of the mobile phone to be purchased, find the corresponding current sales curve from the store sales database, and obtain the historical sales curve from the store sales database; Step 5: Match the current sales curve with the historical sales curves one by one to obtain similar sales curves; Step 6: Determine the current sales node based on the current sales curve and similar sales curves, and segment the current sales curve and similar sales curves based on the current sales node to determine the current sales volume and similar sales volume; Step 7: Obtain the sales cycle and calculate the sales ratio based on the current sales volume and similar sales volumes; Step 8: Based on the current sales node and sales cycle, extract the sales volume of similar future cycles from the similar sales curve, and calculate the sales volume of the current future cycle based on the sales volume of similar future cycles and the sales ratio; Step 9: Generate a replenishment plan based on the mobile phone models to be purchased and the current and future sales volume, and replenish the stock according to the replenishment plan.

[0007] By adopting the above technical solution, the remaining inventory ratio is obtained from the sales database using the store number as an index. When the inventory is insufficient, the replenishment process is triggered. The current sales curve is matched with a large number of historical sales curves. The sales volume in the future period is predicted by using the historical curve that is most similar to the current trend. This can more accurately determine the replenishment volume and thus improve the accuracy of replenishment.

[0008] Optionally, methods for obtaining the model of the mobile phone to be purchased include: Step 30: Obtain the phone model and corresponding phone inventory; Step 31: When the mobile phone inventory is lower than the preset inventory threshold, retrieve the mobile phone sales curve from the store sales database based on the mobile phone model and store number; Step 32: Obtain the most recent sales time period; Step 33: Extract the most recent sales volume by cutting the mobile phone sales curve according to the most recent sales time period; Step 34: When the recent sales volume exceeds the preset minimum sales volume, define the mobile phone model as the mobile phone model to be purchased.

[0009] By adopting the above technical solution, after the replenishment process is triggered, each mobile phone model is further screened. This requires both that the mobile phone inventory be below a threshold to identify models with insufficient stock, and that the sales volume in the most recent sales period be higher than the minimum sales volume to identify models with genuine sales activity. This eliminates interference from slow-moving models, ensuring that purchases are only initiated for models that truly need replenishment, reducing inventory backlog caused by ineffective replenishment. Optionally, it also includes a control method for when the current sales curve does not exist, the method including: Step 40: If the current sales curve does not exist, search for similar mobile phone models in the store sales database based on the mobile phone model and store number; Step 41: Search for similar sales curves in the store sales database based on similar mobile phone models and store numbers; Step 42: Treat the same type of sales curve as the current sales curve and execute steps 5 to 9.

[0010] By adopting the above technical solution, when a certain mobile phone model does not have a current sales curve due to reasons such as being newly launched, the system automatically searches for similar mobile phone models based on attributes such as brand and configuration, and uses their sales curves as alternative data sources. This makes the replenishment forecast for new products also reliable, fills the gap in new product sales forecasting, and ensures the complete applicability of inventory management methods.

[0011] Optionally, methods for matching the current sales curve with historical sales curves one by one to obtain similar sales curves include: Step 50: Match the current sales curve with the historical sales curves one by one to obtain the curve overlap. Step 51: Sort the curve overlap of each historical sales curve in descending order to obtain the maximum curve overlap. Step 52: If the maximum curve overlap is greater than the preset overlap threshold, define the historical sales curve corresponding to the maximum curve overlap as a similar sales curve. Step 53: If the maximum curve overlap is less than the overlap threshold, perform curvature analysis on the current sales curve based on the most recent sales period to obtain the real-time sales change rate and the final sales change rate, and extract the sales volume of the current period from the current sales curve according to the sales cycle. Step 54: When the real-time sales change rate is always greater than zero or the real-time sales change rate is always less than zero, calculate the future sales volume based on the current period sales volume and the final sales change rate. Step 55: When the real-time sales change rate has both positive and negative values, use the current period's sales volume as the future period's sales volume.

[0012] By adopting the above technical solution, the first step is to use the curve overlap threshold to screen highly similar historical curves as the prediction benchmark. When there are no sufficiently similar curves, the curvature analysis technique is used to judge the trend characteristics of the current sales curve itself. If the sales show a one-sided trend of continuous rise or continuous fall, the future sales are dynamically estimated by combining the rate of change. If the sales show a fluctuating state, a conservative period shift estimation is used, which improves the predictive adaptability under different sales patterns.

[0013] Optional, also includes: Step 10: After replenishing stock according to the replenishment plan, obtain the models of phones that were shorted and the corresponding shortfall in quantity; Step 11: Based on the model of the phone to be replenished, find the store number and inventory quantity that can be adjusted from the store sales database; Step 12: Calculate the adjustable inventory level by performing steps 2 to 8 based on the adjustable store number; Step 13: When the adjustable inventory is greater than the shortfall amount, replenish the store number according to the adjustable store number based on the shortfall amount. Step 14: When the adjustable inventory is less than the shortfall amount, search for the adjustable store number again from the store sales database and execute steps 11 to 13.

[0014] By adopting the above technical solution, when there is still an inventory gap after the actual replenishment is completed, the system automatically finds other stores that hold the same model of inventory and whose inventory status is available for transfer. It calculates the adjustable inventory of each candidate store after meeting its own future needs, and prioritizes the store with a single adjustable inventory that is sufficient to fill the gap for transfer and replenishment, thus realizing inventory control between stores.

[0015] Optional, also includes: Step 15: When the adjustable inventory is still less than the shortfall amount after traversing the adjustable store numbers, sort the adjustable inventory corresponding to each adjustable store number in order of size to form an adjustable store number group. Step 16: Select the controllable store numbers in sequence according to the controllable store number group and define them as replenishment store numbers. Then, sum up the controllable inventory corresponding to the replenishment store numbers to obtain the total controllable inventory. Step 17: When the total controlled inventory equals the shortfall, control the replenishment store number to replenish the store number according to the corresponding controllable inventory.

[0016] By adopting the above technical solution, when there is no single store with sufficient adjustable inventory to fill the gap, the system sorts and accumulates the inventory of multiple adjustable stores until it equals the amount of the shortfall, thus achieving precise matching of joint allocation among multiple stores, thereby supplying the stores that need replenishment and improving the stability of inventory control among stores.

[0017] Optionally, it also includes a control method when multiple adjustable inventory levels exceed the shortfall amount, the method including: Step 130: When multiple adjustable inventory levels exceed the shortfall amount, locate the adjustable store in the store sales database based on the adjustable store number. Step 131: Locate the store location from the store sales database based on the store number; Step 132: Obtain the distance between stores based on their locations and the locations of adjustable stores; Step 133: Sort the nearest adjustable store number in ascending order according to the distance between each adjustable store number; Step 134: Control the most recently adjustable store number to replenish the store number according to the shortfall amount.

[0018] By adopting the above technical solution, when multiple stores have the ability to independently fill inventory gaps, the system further calculates the geographical distance between each candidate store and the target store, and prioritizes the nearest store as the source of the transfer. This minimizes transportation time and logistics costs while meeting replenishment needs, thereby improving the economy and timeliness of inventory transfer.

[0019] Optionally, another control method is also included when multiple adjustable inventory levels exceed the shortfall amount, the method comprising: Step 1300: When multiple adjustable inventory levels exceed the shortfall amount, search the store sales database for the available sales curve based on the adjustable store number and the shortfall mobile phone model. Step 1301: Extract the most recent replenishable sales volume from the replenishable sales curve according to the most recent sales time period; Step 1302: When the most recent replenishable sales volume is less than the minimum sales volume, define the controllable store number as the priority controllable store number; Step 1303: Control priority to adjust store number and replenish store number according to the difference in replenishment amount.

[0020] By adopting the above technical solution, when multiple stores have the ability to independently fill inventory gaps, the system obtains the available sales curves for the missing mobile phone models in each candidate store, extracts the sales volume in the most recent sales period as the judgment basis, and prioritizes stores with recent sales volumes lower than the minimum sales volume as the transfer recipients. This allows slow-moving inventory to be prioritized for transfer to stores with shortages, which not only solves the shortage problem but also accelerates the reduction of slow-moving inventory, achieving two-way optimization of the inventory structure.

[0021] Optional, also includes: Step 1304: When there are multiple priority control store numbers, sort them in descending order of the controllable inventory corresponding to each priority control store number to obtain a priority control store number group. Step 1305: Define the first priority control store number in the priority control store number group as the store number with the most remaining quantity. Step 1306: Control the maximum remaining quantity of store numbers and replenish the store numbers according to the shortfall replenishment quantity.

[0022] By adopting the above technical solution, when multiple slow-moving stores meet the priority control conditions at the same time, the system further sorts them according to the controllable inventory of each store from largest to smallest, and prioritizes the store with the largest surplus inventory as the transferee, thereby improving the overall inventory turnover efficiency.

[0023] Secondly, the present invention provides a mobile phone inventory management system based on sales curve matching, which adopts the following technical solution: A mobile phone inventory management system based on sales curve matching, comprising: The acquisition module is used to obtain the store number, store sales database, and sales cycle. The memory is used to store a program for a mobile phone inventory management method based on sales curve matching as described above; The processor loads and executes programs from memory.

[0024] By adopting the above technical solution, the inventory turnover management method is stored in the memory in the form of a program and loaded and executed by the processor, realizing the automated operation of the method. The acquisition module is responsible for collecting necessary input data such as store number, sales database and sales cycle. It works in conjunction with the memory and processor to form a complete software and hardware execution environment with good scalability and practicality.

[0025] In summary, the present invention has at least one of the following beneficial technical effects: By matching the current sales curve with the historical sales curve, and using the historical curve with the most similar trend to predict future sales volume, the replenishment quantity can be determined more objectively and accurately, reducing replenishment deviations caused by subjective judgment. For new product models without historical data, substitution prediction is made by using curves of similar models, which fills the data gap in the existing technology for new product replenishment decisions and improves the prediction accuracy in different sales scenarios. When there is still a shortage of external replenishment, the system automatically identifies the surplus inventory of other stores and calculates the surplus quantity that can be transferred by taking into account the future demand of each store. It supports various strategies such as single-store transfer, multi-store joint transfer, transfer based on distance, and transfer based on slow-moving inventory, thereby improving the overall inventory turnover efficiency. Attached Figure Description

[0026] Figure 1 This is a flowchart of a mobile phone inventory management method based on sales curve matching in an embodiment of this application; Figure 2 This is a schematic diagram of the current sales curve and similar sales curves in the embodiments of this application. Detailed Implementation

[0027] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0028] This invention discloses a mobile phone inventory management method based on sales curve matching. (Refer to...) Figure 1 A mobile phone inventory management method based on sales curve matching includes: Step 1: Obtain the store number and store sales database.

[0029] A store number is a unique identifier for each store. Store numbers are assigned in advance by staff based on factors such as the store's region, location, and opening order. Store numbers are used to distinguish between different stores.

[0030] The store sales database refers to a database that records mobile phone sales data for each store. The store sales database is obtained by updating sales data in real time from each store. The stored data includes store number, mobile phone model, sales data for each mobile phone model, sales volume at different time points, remaining inventory, and total inventory.

[0031] Step 2: Find the remaining inventory and total inventory from the store sales database based on the store number, and calculate the remaining inventory percentage based on the remaining inventory and total inventory.

[0032] Remaining inventory refers to the total number of mobile phones in stock at the store corresponding to the current store number. Total inventory refers to the total number of mobile phones that can be stored within the store's total storage capacity. Both remaining inventory and total inventory can be retrieved from the store's sales database by searching for the store number.

[0033] The remaining inventory percentage refers to the proportion of remaining inventory to total inventory. The formula for calculating the remaining inventory percentage is: Remaining inventory percentage = Remaining inventory / Total inventory × 100%.

[0034] Step 3: When the remaining inventory ratio is less than the preset inventory warning threshold, obtain the mobile phone model to be purchased.

[0035] The mobile phone models to be purchased refer to the mobile phone models that currently need to be replenished. When the remaining inventory ratio of a store is lower than the inventory warning threshold, it indicates that the store's existing inventory is insufficient and a replenishment process needs to be triggered. At this time, based on the inventory status of each model of mobile phone in the store's sales data, the mobile phone models with insufficient inventory can be selected as the mobile phone models to be purchased. The specific method for obtaining the mobile phone models to be purchased is described in detail in steps 30 to 34.

[0036] Step 4: Find the corresponding current sales curve from the store sales database based on the store number and the model of the mobile phone to be purchased, and obtain the historical sales curve from the store sales database.

[0037] The current sales curve refers to a curve based on sales volume, recorded in chronological order for the mobile phone models to be purchased. The current sales curve is obtained by searching the store's sales database using the mobile phone models to be purchased as the search term.

[0038] Historical sales curves refer to the sales curves for all mobile phones stored in the store's sales database, excluding the current sales curve for the model to be purchased. These historical sales curves are directly retrieved from the store's sales database, and all historical sales curves stored in the database are automatically plotted based on real-time updates of sales data from each store.

[0039] Generally, both current and historical sales curves are constructed with the number of days on the horizontal axis and daily sales volume on the vertical axis.

[0040] Step 5: Match the current sales curve with the historical sales curves one by one to obtain similar sales curves.

[0041] A similar sales curve refers to a historical sales curve that most closely resembles the current sales curve. By comparing the current sales curve with each historical sales curve in terms of similarity, similar sales curves that meet the preset similarity requirements can be selected. The specific method for obtaining similar sales curves is described in detail in steps 50 to 55.

[0042] Step 6: Determine the current sales node based on the current sales curve and similar sales curves, and segment the current sales curve and similar sales curves based on the current sales node to determine the current sales volume and similar sales volume.

[0043] like Figure 2 As shown, the current sales node refers to the curve node obtained by projecting the last known sales data point on the current sales curve onto a similar sales curve. The current sales node is obtained by traversing all recorded coordinate points on the current sales curve, taking the point with the largest time coordinate, and projecting it onto a similar sales curve.

[0044] Current sales volume refers to the cumulative sales volume from the starting point of the current sales curve to the current sales node. The specific calculation method for current sales volume is as follows: obtain the sales volume value corresponding to each time point on the current sales curve, and sum these values ​​to obtain the current sales volume.

[0045] Step 7: Obtain the sales cycle and calculate the sales ratio based on the current sales volume and similar sales volume.

[0046] The sales cycle refers to the period between each replenishment and the next replenishment. The sales cycle is set by staff based on past sales experience, for example, by averaging the time interval between previous replenishments.

[0047] The sales ratio is the ratio between current sales volume and similar sales volume. Sales ratio = Current sales volume / Similar sales volume.

[0048] Step 8: Based on the current sales node and sales cycle, extract the sales volume of similar future cycles from the similar sales curve, and calculate the sales volume of the current future cycle based on the sales volume of similar future cycles and the sales ratio.

[0049] Similar future period sales volume refers to the total sales volume on a similar sales curve, calculated by taking a sales cycle forward from the position corresponding to the current sales node. The specific method for obtaining similar future period sales volume is as follows: Take a sales cycle forward from the current sales node on the similar sales curve, obtain the sales volume corresponding to each time node within this period, and sum them up; the total sum is the similar future period sales volume.

[0050] The current future cycle sales volume is calculated based on the similar future cycle sales volume and sales ratio. The calculation formula is: Current future cycle sales volume = Similar future cycle sales volume × Sales ratio.

[0051] Step 9: Generate a replenishment plan based on the mobile phone models to be purchased and the current and future sales volume, and replenish the stock according to the replenishment plan.

[0052] A replenishment plan is a scheme that includes each mobile phone model to be purchased and the corresponding replenishment quantity for each model. The replenishment quantity is the current future sales volume calculated for each mobile phone model. Once the replenishment plan is generated, staff can carry out replenishment according to the plan.

[0053] The methods for obtaining the mobile phone models to be purchased include: Step 30: Obtain the phone model and corresponding phone inventory.

[0054] A mobile phone model is a unique identifier assigned by a mobile phone manufacturer to differentiate mobile phone products with different specifications, configurations, and appearances. Mobile phone inventory refers to the actual remaining available quantity of a specific mobile phone model in the store corresponding to the current store number. Both the mobile phone model and inventory quantity are obtained by directly retrieving the corresponding inventory field for each mobile phone model from the store's sales database using the store number as the search term.

[0055] Step 31: When the mobile phone inventory is lower than the preset inventory threshold, retrieve the mobile phone sales curve from the store sales database based on the mobile phone model and store number.

[0056] Inventory threshold is a critical value used to determine whether a mobile phone needs to be replenished. The inventory threshold is set by staff based on the historical sales speed of that mobile phone model, the supplier's replenishment cycle, and the store's safety stock requirements.

[0057] A mobile phone sales curve is a graph that shows the sales trend of a specific mobile phone model in a corresponding store, with time as the horizontal axis and daily sales volume as the vertical axis. The mobile phone sales curve is retrieved from the store's sales database using a combination of store number and mobile phone model as search keywords.

[0058] Step 32: Obtain the most recent sales time period.

[0059] The most recent sales period refers to a time interval that stretches backward from the current point in time. This period is set by staff based on the sales cycle characteristics of the mobile phone product, such as the last 7 days or the last 14 days. The most recent sales period can be used to analyze the recent sales activity of a mobile phone model.

[0060] Step 33: Extract the most recent sales volume by cutting the mobile phone sales curve according to the most recent sales time period.

[0061] Recent sales volume refers to the total number of a specific mobile phone model actually sold within the most recent sales period. It is obtained by extracting the sales values ​​corresponding to all coordinate points on the mobile phone sales curve that fall within the start and end dates of the most recent sales period, and then summing these values.

[0062] Step 34: When the recent sales volume exceeds the preset minimum sales volume, define the mobile phone model as the mobile phone model to be purchased.

[0063] Minimum sales volume refers to a standard value used to judge sales activity. It is set by staff based on store operational requirements and can be used to filter out mobile phone models that have genuine sales demand in the near future, rather than being slow-moving.

[0064] When the recent sales volume exceeds the preset minimum sales volume, it indicates that the mobile phone model has been selling actively recently and the inventory level has fallen below the safety stock standard, meeting the replenishment requirements. Therefore, it is defined as a mobile phone model to be purchased.

[0065] When the recent sales volume is lower than the minimum sales volume, it indicates that the sales of this mobile phone model have not been active recently. Even if the inventory is low, there is no need to replenish the stock urgently. Therefore, this mobile phone model is not included in the range of mobile phone models to be purchased.

[0066] Furthermore, there is another way to obtain the mobile phone models to be purchased, which is by identifying newly launched models. Since there is no historical sales data for newly launched models, staff directly define the newly launched models as the mobile phone models to be purchased.

[0067] This also includes a control method for when the current sales curve does not exist, which includes: Step 40: If the current sales curve does not exist, search for similar mobile phone models in the store sales database based on the mobile phone model and store number.

[0068] Similar phone models refer to other phone models with similar positioning and configuration parameters to those currently without sales curves. These similar phone models are pre-classified by staff based on product attributes and stored in the store's sales database. They can be retrieved directly by searching the database using the phone model and store number.

[0069] Step 41: Search for similar sales curves in the store sales database based on similar mobile phone models and store numbers.

[0070] A similar sales curve refers to the sales volume change curve of similar mobile phone models in stores with the same store number, recorded in chronological order. Similar sales curves are obtained directly from the store's sales database by using the store number and similar mobile phone models as search keywords.

[0071] Step 42: Treat the same type of sales curve as the current sales curve and execute steps 5 to 9.

[0072] By treating similar sales curves as the current sales curve and executing steps 5 to 9, even when the current sales curve does not exist, a more reasonable replenishment quantity can still be calculated using existing sales data of similar products, thus improving the accuracy of replenishment.

[0073] One method for obtaining similar sales curves by matching the current sales curve with historical sales curves one by one includes: Step 50: Match the current sales curve with the historical sales curves one by one to obtain the curve overlap.

[0074] Curve coincidence refers to the quantified value of the similarity between the current sales curve and each historical sales curve in terms of shape, trend, and fluctuation pattern. The higher the curve coincidence value, the closer the two curves are. Curve coincidence is calculated by comparing each coordinate point on the current sales curve with the corresponding coordinate points on the historical sales curve at each time point, calculating the difference in the ordinate of the two curves at each time node, and normalizing all differences to obtain the similarity score. For example, a cosine similarity algorithm can be used to calculate it, which measures the consistency in direction by calculating the dot product of the two sequence vectors and dividing by the product of their respective magnitudes.

[0075] Step 51: Sort the curve overlap of each historical sales curve in descending order to obtain the maximum curve overlap.

[0076] The maximum curve overlap refers to the highest curve overlap value among all historical sales curves involved in the matching. The maximum curve overlap is obtained by placing the curve overlap values ​​calculated in step 50 into a list, using a sorting algorithm to sort the list in descending order of values, and then extracting the value of the first element in the sorted list.

[0077] Step 52: If the maximum curve overlap is greater than the preset overlap threshold, define the historical sales curve corresponding to the maximum curve overlap as a similar sales curve.

[0078] The overlap threshold is a similarity threshold set by staff based on matching accuracy requirements. For example, it may be set to 85%. Only when the overlap of curves exceeds this threshold can the two curves be considered to have a sufficiently high similarity for subsequent prediction.

[0079] Step 53: If the maximum curve overlap is less than the overlap threshold, perform curvature analysis on the current sales curve based on the most recent sales period to obtain the real-time sales change rate and the final sales change rate, and extract the sales volume of the current period from the current sales curve according to the sales cycle.

[0080] Real-time sales change rate refers to the instantaneous direction and magnitude of sales volume changes between adjacent time points within the most recent sales period. Final sales change rate refers to the overall sales trend of the current sales curve within the complete time period from the beginning to the end of the most recent sales period. Both real-time and final sales change rates are obtained by performing curvature analysis on the current sales curve, i.e., calculating the slope of the tangent line at each point on the curve or the sign and magnitude of the difference between adjacent points, and statistically analyzing the slope changes within the most recent sales period and the ratio of the difference between the first and last endpoints of the entire curve segment.

[0081] Current period sales volume refers to the cumulative sales volume within the current sales period on the current sales curve. It is calculated by obtaining the sales volume value corresponding to each time point on the current sales curve from the current time to the start time of the current sales period, and summing these values.

[0082] Step 54: When the real-time sales change rate is always greater than zero or the real-time sales change rate is always less than zero, calculate the future sales volume based on the current period sales volume and the final sales change rate.

[0083] Future sales volume refers to the total quantity that is expected to be sold in the next sales cycle. The formula is: Future sales volume = Current sales volume × (1 + Final sales change rate).

[0084] When the real-time sales change rate is always greater than zero or always less than zero, it indicates that the current sales curve shows a stable trend of continuous rise or continuous fall. At this time, the sales volume of the current period can be adjusted by amplifying or shrinking according to the final sales change rate to directly obtain the sales volume of the future period. After obtaining the sales volume of the future period, you can directly jump to step 9 to generate a replenishment plan.

[0085] Step 55: When the real-time sales change rate has both positive and negative values, use the current period's sales volume as the future period's sales volume.

[0086] When the real-time sales change rate has both positive and negative values, it indicates that the current sales curve does not have a clear trend of continuous increase or decrease. Therefore, the current period sales volume can be directly used as the future period sales volume. Similarly, after obtaining the future period sales volume, proceed to step 9 to generate a replenishment plan.

[0087] This also includes: Step 10: After replenishing the stock according to the replenishment plan, obtain the models of phones that were shorted and the corresponding shortfall in quantity.

[0088] "Short-replenishment phone models" refers to phone models for which the required replenishment quantity is still insufficient after replenishment. "Short-replenishment difference" refers to the difference between the actual replenishment quantity of this phone model and the current / future sales volume in the replenishment plan. Both "short-replenishment phone models" and "short-replenishment difference" are determined by conducting an inventory check of each phone model after replenishment, comparing the inventory results with the planned quantity in the replenishment plan, identifying phone models where the actual quantity is less than the planned quantity, and calculating the difference.

[0089] Step 11: Based on the model of the phone to be replenished, find the store number and inventory quantity that can be adjusted from the store's sales database.

[0090] An adjustable store number is a unique identifier for other stores that hold inventory of a particular mobile phone model that is in short supply and that inventory is available for allocation. The adjustable store number is obtained by filtering the store sales database using the short-supply mobile phone model as the search term, identifying all store records that hold inventory of that model and whose inventory status is marked as "available for allocation".

[0091] The inventory holding quantity refers to the actual quantity of the missing mobile phone model currently held in the store corresponding to the controllable store number. The inventory holding quantity is obtained by reading the relevant inventory quantity field for the missing mobile phone model from these controllable store numbers.

[0092] Step 12: Calculate the adjustable inventory based on steps 2 to 8 according to the adjustable store number.

[0093] Adjustable inventory refers to the surplus inventory at an adjustable store that is not expected to be consumed in the next sales cycle and can be allocated to other stores. The specific calculation method for adjustable inventory is as follows: Input the adjustable store number obtained in step 11 as the store number in step 2. Perform steps 2 through 8 sequentially for that adjustable store to calculate its expected sales volume in the current future cycle. Then, subtract the calculated sales volume for the current future cycle from the current inventory held by the adjustable store; the difference is the adjustable inventory.

[0094] Step 13: When the adjustable inventory is greater than the shortfall amount, replenish the store number according to the adjustable store number based on the shortfall amount.

[0095] When the adjustable inventory is greater than the shortage replenishment quantity, it means that the store corresponding to the adjustable store number can allocate the shortage replenishment quantity of the same mobile phone model to the store corresponding to the store number. This can meet the shortage demand of the store number without affecting the subsequent sales of the adjustable store itself. Therefore, the adjustable store number is controlled to replenish the store number according to the shortage replenishment quantity.

[0096] Step 14: When the adjustable inventory is less than the shortfall amount, search for the adjustable store number again from the store sales database and execute steps 11 to 13.

[0097] When the adjustable inventory is less than the shortage replenishment amount, it means that the inventory corresponding to the currently selected adjustable store number cannot meet the shortage replenishment needs of the out-of-stock store. Therefore, it is necessary to return to the search stage and reselect the next adjustable store that has the available inventory for the missing mobile phone model until an adjustable store that can meet the shortage replenishment needs is found to complete the replenishment.

[0098] This also includes: Step 15: After traversing the adjustable store numbers, if the adjustable inventory is still less than the shortfall amount, sort the adjustable inventory corresponding to each adjustable store number in order of size to form an adjustable store number group.

[0099] A controllable store number group refers to a group of numbers formed by various controllable store numbers, arranged in descending order of controllable inventory. If, after traversing all controllable store numbers, the controllable inventory is still less than the required supplementary amount, it indicates that the store corresponding to a single controllable store number cannot meet the required supplementary amount.

[0100] This is achieved by extracting all the adjustable store numbers that have been traversed and their corresponding adjustable inventory values, calling a sorting algorithm to arrange these stores in descending or ascending order of adjustable inventory, and then storing the sorted store numbers into a list or queue structure.

[0101] Step 16: Select the controllable store numbers in sequence according to the controllable store number group and define them as replenishment store numbers. Then, sum up the controllable inventory corresponding to the replenishment store numbers to obtain the total controllable inventory.

[0102] The replenishment store number refers to the controllable store number selected for replenishment. The replenishment store number is obtained by selecting stores from the controllable store number group in descending order of controllable inventory.

[0103] Total controllable inventory refers to the cumulative sum of the controllable inventory corresponding to each of the selected replenishment store numbers. The calculation method for total controllable inventory is as follows: following the order in the controllable store number group, starting from the first store, select each store as a replenishment store number one by one, and gradually accumulate the controllable inventory of that store from zero until the accumulation meets the minimum replenishment requirement, at which point the accumulation stops.

[0104] Step 17: When the total controlled inventory equals the shortfall, control the replenishment store number to replenish the store number according to the corresponding controllable inventory.

[0105] When the total controlled inventory equals the shortfall in replenishment, it means that the sum of the controlled inventory provided by several stores selected sequentially from the controlled store number group is just enough to completely fill the current store's inventory gap. At this time, the system issues a transfer instruction to the store corresponding to each replenishment store number. Each replenishment store transfers a specified number of shortfall mobile phone models to the store corresponding to its own controlled inventory value.

[0106] This also includes a control method when multiple adjustable inventory levels exceed the shortfall amount, and this method includes: Step 130: When multiple adjustable inventory levels exceed the shortfall amount, locate the adjustable store in the store sales database based on the adjustable store number.

[0107] Adjustable store location refers to the actual physical location information of the store corresponding to the adjustable store number. The adjustable store location is obtained by directly reading the address field corresponding to the adjustable store number from the store sales database.

[0108] Step 131: Find the store location from the store sales database based on the store number.

[0109] Store location refers to the actual physical location information corresponding to the store number. The store location is also obtained by directly reading the address field corresponding to the store number from the store sales database.

[0110] Step 132: Obtain the distance between stores based on their location and the location of adjustable stores.

[0111] The distance between two physical locations refers to the actual travel distance between the store location and the adjustable store location. This distance can be obtained through map interfaces, such as by inputting the store location and the adjustable store location into a map engine like Gaode Maps.

[0112] Step 133: Sort the nearest adjustable store number in ascending order according to the distance between each adjustable store number.

[0113] The nearest adjustable store number refers to the number of the adjustable store that is geographically closest to the store corresponding to that store number. The nearest adjustable store number is obtained by extracting the distance values ​​corresponding to each adjustable store that meets the conditions, sorting these stores in ascending order according to the distance, and taking the number of the first store in the sorted list.

[0114] Step 134: Control the most recently adjustable store number to replenish the store number according to the shortfall amount.

[0115] By controlling the nearest adjustable store number to replenish stock according to the shortfall, the demand for stockouts can be met while minimizing the distance of transfer and transportation, and reducing logistics costs and time losses during the transfer process.

[0116] This also includes another control method when multiple adjustable inventory levels exceed the shortfall amount, which includes: Step 1300: When multiple adjustable inventory levels exceed the shortfall amount, search the store sales database for the available sales curve based on the adjustable store number and the shortfall mobile phone model.

[0117] A replenishable sales curve refers to the sales volume change curve of a particular mobile phone model that is in short supply in a controllable store, recorded in chronological order. The replenishable sales curve is obtained by retrieving data from the store's sales database using the controllable store number and the mobile phone model in short supply as combined search keywords.

[0118] Step 1301: Extract the most recent available sales volume from the available sales curve according to the most recent sales time period.

[0119] Recent replenishable sales volume refers to the total number of mobile phone models that can be replenished in the controllable stores within the most recent sales period. Recent replenishable sales volume is obtained by extracting and summing the sales values ​​corresponding to all coordinate points on the replenishable sales curve that fall within the start and end dates of the most recent sales period.

[0120] Step 1302: When the most recent replenishable sales volume is less than the minimum sales volume, define the controllable store number as the priority controllable store number.

[0121] The priority control store number refers to the number of the store that has a shortage of a particular mobile phone model among multiple controllable stores with replenishment capabilities, and which is considered slow-moving stock within that store. When the nearest replenishable sales volume calculated in step 1301 is less than the minimum sales volume, the system marks the controllable store and defines it as the priority control store number, meaning that the inventory of that model in that store is slow-moving inventory and is more suitable as the transferor.

[0122] Step 1303: Control priority to adjust store number and replenish store number according to the difference in replenishment amount.

[0123] By controlling and prioritizing the replenishment of store numbers according to the amount of stock difference, the system prioritizes the allocation of goods to stores with slow-moving inventory, thereby enabling the turnover of goods from slow-moving stores to stores with shortages.

[0124] This also includes: Step 1304: When there are multiple priority control store numbers, sort them in descending order of the controllable inventory corresponding to each priority control store number to obtain a priority control store number group.

[0125] The priority control store number group refers to the ordered sequence of store numbers formed by sorting all the stores marked as priority control stores in descending order of their respective controllable inventory values. The priority control store number group is obtained by extracting the controllable inventory of each priority control store, applying a sorting algorithm to arrange these stores in descending order of their controllable inventory values, and then storing the sorted store numbers sequentially into a list structure.

[0126] Step 1305: Define the first priority control store number in the priority control store number group as the store number with the most remaining quantity.

[0127] The store number with the largest remaining inventory refers to the number corresponding to the store with the largest adjustable inventory among all priority control stores. The store number with the largest remaining inventory is obtained by taking the first element of the sorted list from the priority control store number group obtained in step 1304.

[0128] Step 1306: Control the maximum remaining quantity of store numbers and replenish the store numbers according to the shortfall replenishment quantity.

[0129] By controlling the store number with the largest surplus and replenishing it according to the difference in quantity, the system prioritizes stores with the largest surplus as the transferees, thereby reducing the pressure of unsold inventory in these stores.

[0130] Based on the same inventive concept, embodiments of the present invention provide a mobile phone inventory management system based on sales curve matching.

[0131] A mobile phone inventory management system based on sales curve matching, comprising: The acquisition module is used to obtain the store number, store sales database, and sales cycle. The memory is used to store a program for a mobile phone inventory management method based on sales curve matching; The processor loads and executes programs from memory.

[0132] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0133] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A mobile phone inventory management method based on sales curve matching, characterized by, include: Step 1: Obtain the store number and store sales database; Step 2: Find the remaining inventory and total inventory from the store sales database based on the store number, and calculate the remaining inventory percentage based on the remaining inventory and total inventory. Step 3: When the remaining inventory ratio is less than the preset inventory warning threshold, obtain the mobile phone models to be purchased; Step 4: Based on the store number and the model of the mobile phone to be purchased, find the corresponding current sales curve from the store sales database, and obtain the historical sales curve from the store sales database; Step 5: Match the current sales curve with the historical sales curves one by one to obtain similar sales curves; Step 6: Determine the current sales node based on the current sales curve and similar sales curves, and segment the current sales curve and similar sales curves based on the current sales node to determine the current sales volume and similar sales volume; Step 7: Obtain the sales cycle and calculate the sales ratio based on the current sales volume and similar sales volumes; Step 8: Based on the current sales node and sales cycle, extract the sales volume of similar future cycles from the similar sales curve, and calculate the sales volume of the current future cycle based on the sales volume of similar future cycles and the sales ratio; Step 9: Generate a replenishment plan based on the mobile phone models to be purchased and the current and future sales volume, and replenish the stock according to the replenishment plan.

2. The mobile phone inventory management method based on sales curve matching according to claim 1, wherein, Methods for obtaining the mobile phone models to be purchased include: Step 30: Obtain the phone model and corresponding phone inventory; Step 31: When the mobile phone inventory is lower than the preset inventory threshold, retrieve the mobile phone sales curve from the store sales database based on the mobile phone model and store number; Step 32: Obtain the most recent sales time period; Step 33: Extract the most recent sales volume by cutting the mobile phone sales curve according to the most recent sales time period; Step 34: When the recent sales volume exceeds the preset minimum sales volume, define the mobile phone model as the mobile phone model to be purchased.

3. The mobile phone inventory management method based on sales curve matching according to claim 1, characterized in that, It also includes a control method for when the current sales curve does not exist, which includes: Step 40: If the current sales curve does not exist, search for similar mobile phone models in the store sales database based on the mobile phone model and store number; Step 41: Search for similar sales curves in the store sales database based on similar mobile phone models and store numbers; Step 42: Treat the same type of sales curve as the current sales curve and execute steps 5 to 9.

4. The mobile phone inventory management method based on sales curve matching according to claim 2, characterized in that, Methods for matching the current sales curve with historical sales curves one by one to obtain similar sales curves include: Step 50: Match the current sales curve with the historical sales curves one by one to obtain the curve overlap. Step 51: Sort the curve overlap of each historical sales curve in descending order to obtain the maximum curve overlap. Step 52: If the maximum curve overlap is greater than the preset overlap threshold, define the historical sales curve corresponding to the maximum curve overlap as a similar sales curve. Step 53: If the maximum curve overlap is less than the overlap threshold, perform curvature analysis on the current sales curve based on the most recent sales period to obtain the real-time sales change rate and the final sales change rate, and extract the sales volume of the current period from the current sales curve according to the sales cycle. Step 54: When the real-time sales change rate is always greater than zero or the real-time sales change rate is always less than zero, calculate the future sales volume based on the current period sales volume and the final sales change rate. Step 55: When the real-time sales change rate has both positive and negative values, use the current period's sales volume as the future period's sales volume.

5. A mobile phone inventory management method based on sales curve matching according to claim 2, characterized in that, Also includes: Step 10: After replenishing stock according to the replenishment plan, obtain the models of phones that were shorted and the corresponding shortfall in quantity; Step 11: Based on the model of the phone to be replenished, find the store number and inventory quantity that can be adjusted from the store sales database; Step 12: Calculate the adjustable inventory level by performing steps 2 to 8 based on the adjustable store number; Step 13: When the adjustable inventory is greater than the shortfall amount, replenish the store number according to the adjustable store number based on the shortfall amount. Step 14: When the adjustable inventory is less than the shortfall amount, search for the adjustable store number again from the store sales database and execute steps 11 to 13.

6. The mobile phone inventory management method based on sales curve matching according to claim 5, characterized in that, Also includes: Step 15: When the adjustable inventory is still less than the shortfall amount after traversing the adjustable store numbers, sort the adjustable inventory corresponding to each adjustable store number in order of size to form an adjustable store number group. Step 16: Select the controllable store numbers in sequence according to the controllable store number group and define them as replenishment store numbers. Then, sum up the controllable inventory corresponding to the replenishment store numbers to obtain the total controllable inventory. Step 17: When the total controlled inventory equals the shortfall, control the replenishment store number to replenish the store number according to the corresponding controllable inventory.

7. The mobile phone inventory management method based on sales curve matching according to claim 5, characterized in that, It also includes a control method when multiple adjustable inventory levels exceed the shortfall amount, the method including: Step 130: When multiple adjustable inventory levels exceed the shortfall amount, locate the adjustable store in the store sales database based on the adjustable store number. Step 131: Locate the store location from the store sales database based on the store number; Step 132: Obtain the distance between stores based on their locations and the locations of adjustable stores; Step 133: Sort the nearest adjustable store number in ascending order according to the distance between each adjustable store number; Step 134: Control the most recently adjustable store number to replenish the store number according to the shortfall amount.

8. The mobile phone inventory management method based on sales curve matching according to claim 5, characterized in that, It also includes another control method when multiple controllable inventory levels exceed the under-compensation amount, which includes: Step 1300: When multiple adjustable inventory levels exceed the shortfall amount, search the store sales database for the available sales curve based on the adjustable store number and the shortfall mobile phone model. Step 1301: Extract the most recent replenishable sales volume from the replenishable sales curve according to the most recent sales time period; Step 1302: When the most recent replenishable sales volume is less than the minimum sales volume, define the controllable store number as the priority controllable store number; Step 1303: Control priority to adjust store number and replenish store number according to the difference in replenishment amount.

9. A mobile phone inventory management method based on sales curve matching according to claim 8, characterized in that, Also includes: Step 1304: When there are multiple priority control store numbers, sort them in descending order of the controllable inventory corresponding to each priority control store number to obtain a priority control store number group. Step 1305: Define the first priority control store number in the priority control store number group as the store number with the most remaining quantity. Step 1306: Control the maximum remaining quantity of store numbers and replenish the store numbers according to the shortfall replenishment quantity.

10. A mobile phone inventory management system based on sales curve matching, characterized in that, include: The acquisition module is used to obtain the store number, store sales database, and sales cycle. A memory for storing a program of a mobile phone inventory management method based on sales curve matching as described in any one of claims 1 to 9; The processor loads and executes programs from memory.

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