JPH0614391B2 - Sales data processing equipment - Google Patents

Description

Description: [Industrial application] The present invention relates to a sales data processing device that collects sales results of sold products and creates various reports based on the collected data.

[Prior Art] Conventionally, as this type of sales data processing device, there is a POS system. In general, the POS system has a function of outputting a muscle product report on hot selling / dead.
However, the best-selling products in the conventional POS system /
The deadly product report simply lists up the rankings of the sales results of individual items (the number of units sold, the amount of sales, etc.) such as the best 50 and the worst 50 for each predetermined period, for example, every one month.

[Problems to be Solved by the Invention] Originally, a report for the analysis of dying muscles regardless of hot selling ones is a report for detecting a slowdown product and determining whether the product should be left in the sales floor or eliminated. There must be.

In this respect, the report created by the conventional POS system is not satisfactory. That is, it is not possible to judge whether the sales of the product is increasing or decreasing only by listing the best / worst ranking of the number of units sold and the amount of sales. Therefore,
If a product is mechanically excluded from the sales floor from such a report, there is a risk that even a product that is becoming popular in the future due to increased sales may be excluded.

The present invention solves such a problem, and an object of the present invention is to provide a sales data processing device capable of creating a report for deciding a muscle product in a deadly manner in consideration of the tendency of sales. .

[Means for Solving Problems] As shown in FIG. 6, the sales data processing device of the present invention totalizes sales results of sales commodities and creates various reports based on the totaled data. In the sales data processing device, for each product, the history data memory that stores the number of sales for each predetermined period for a plurality of periods, and the stored contents of the history data memory are updated for each predetermined period, and the sales data for the latest plurality of periods are constantly updated. A history data updating unit that stores the number of sales in the history data memory, and a deviation value for determining a sales tendency for each product as data for creating a report from the number of sales for each predetermined period stored in the history data memory. And a report output unit for outputting a report listing the products in the ascending or descending order of the deviation value. The arithmetic means is characterized by the following.

A variation deviation calculation unit that obtains a deviation of the variation in the number of sales for each predetermined period in the latest plurality of periods from the transition of the average number of sales for each predetermined period for each of the predetermined periods.

An average sales volume calculation unit that calculates the average sales volume for a specified period from the total sales volume during the latest multiple periods.

An addition unit that calculates the deviation value by adding the average sales number to the fluctuation deviation.

[Operation] The sales data processing device according to the present invention obtains a sales tendency of each product based on the transition of the sales result data of each product, and adds it to create a report suitable for deciding a dead product. . The data for creating the report is a deviation value for judging the sales tendency of each product.To obtain the data, first, for each product, store the number of sales for each predetermined period for a plurality of periods, and from the stored contents, The variation deviation of the number of sales for each predetermined period in the latest multiple periods is calculated, and the average number of sales in a predetermined period unit is calculated from the total number of sales in the latest multiple periods, and the variation deviation and the average number of sales are calculated. By adding, the deviation value in which the sales tendency is taken into consideration is obtained.

[Embodiment] An embodiment of the present invention will be described below with reference to the drawings as an embodiment of the present invention.

First, a part similar to the conventional one will be described.

This POS system mainly comprises a store controller (stock controller) and a plurality of POS registers, which communicate by polling the store controller.
The POS register is located at the checkout counter in the store and is equipped with a bar code scanner (fixed, wand, or pen). The main role of the POS register is to register the customer's purchased products and exchange money with the customer (there is also a payment by a card).

On the other hand, the store controller, which is a personal computer or a mini computer, is placed in the back room or office of the store. This store controller is configured as indicated by the reference numeral 1 in FIG. That is, it is composed of a CPU (central processing unit) 2, a ROM 3, a RAM 4, a floppy disk outside (external storage device) 5, and various interfaces 6, 7, 8, 9, 10. ROM
A system control program is stored in the ROM 3, and various files are stored in the ROM 4. These files include a fixed data file such as a product master file and an actual result file. Further, the actual result file includes a sales file by individual item, a sales file by department, a sales file by register, and the like.

The interface 6 is for communication with the POS register, and is configured to use an optical cable for removing the influence of noise, for example. As an interface for communication, a communication interface (modem) with a computer for managing a plurality of stores at the headquarters may be provided. The interface 7 is for connecting the floppy disk 5, the interface 8 is for connecting the CRT 11, the interface 9 is for connecting the keyboard 12, and the interface 10 is for connecting the printer 13.

The main role of such a store controller 1 is PO
Bar code of the product (JAN
Code) to search the product master file, return the price of the product with the barcode to the POS register, and collect the sales data of the products registered from the POS register into various performance files, Creating various reports.

The above configuration is similar to the store controller in the conventional POS system.

In the case of the present invention, the history data file is stored in the RAM 4 of the store controller 1. In this history data file, areas as shown in FIG. 2 are secured for each product (for each JAN code or PLU number). A reference numeral 14 in the figure is attached to the history data file.

The area for each product in the history data file 14 has a storage area for the number of sales of the product every two weeks and the number of working days during that period.
And areas M1, M2, M3, M4, M5 for the past five periods
Is secured. Storage areas M0, M1, M of each period
2, M3, M4, M5 stores the number of sales T, A,
B, C, D, and E, and the operating days stored in them are Td, Ad, Bd, Cd, and Ed. In addition, a storage area M6 for a dead line deviation value, which will be described later, is secured in the area for each product in the history data file 14.

By using the history data file 14 as described above, the store controller 1 processes the data with the history for the past five periods (10 weeks), and the deadly product list (described later) as shown in FIG. Create) as a report. The function of the store controller 1 will be described later together with the operation.

Next, the operation will be described.

The store controller 1 aggregates the sales performance data for each product input from the POS register, and uses it as the number of sold products for each predetermined two weeks, and the history data file 14
In addition, the history data file 14 stores the number of working days in every predetermined two weeks.

Then, the store controller 1 updates the contents of the history data file 14 every two weeks. That is, when the current period reaches 2 weeks and the number of sold items and the number of working days for the current 2 weeks are stored in the storage area M0, the contents of the area M5 5 years ago are discarded and the contents of the area M4 4 years ago are deleted. Similarly, the contents of area M3 are shifted to area M4, the contents of area M2 to area M3, the contents of area M1 to area M2, and the contents of area M0 to area M1. Therefore, the history data file 14 always stores the latest sales history for each product for five periods.

The store controller 1 arithmetically processes the stored data of the history data file 14 to obtain the sales tendency of each product.

Therefore, the calculation will be described step by step.

First, for each product, the average number of sales per day for the last five weeks every two weeks is calculated by the following formula.

= A / Ad, = B / Bd, = C / Cd, = D / Dd, = E / Ed Next, for each product, the above-mentioned average daily sales figures,
The deviation value of the transition of the ,,,, is obtained and summed up to calculate the sales fluctuation deviation SD. Sales fluctuation deviation S
The calculation formula of D is as follows.

SD = {(−) + (−) + (−) + (−)} This sales fluctuation deviation SD is positive when the number of sold items is increasing, and is negative when the number of sold items is decreasing, When the number of sold products is average, it becomes “0”.

Next, for each product, the average daily sales number SQ for the past five periods (for 10 weeks) is calculated by the following formula.

Next, for each product, sales fluctuation deviation SD, sales number S
The deviation value AD for determining the sales tendency is calculated by adding Q.

AD = SD + SQ The calculated deviation value AD is stored in the storage area M6 of the history data file 14 corresponding to the product. The meaning of the deviation value AD will be described later.

The store controller 1 performs the above arithmetic processing on each product. The above series of arithmetic processing is shown in the flowchart of FIG. The store controller 1 starts this arithmetic processing when it is instructed to create a dead line report,
Sales fluctuation deviation SD in steps S1, S2, S3 and 1
An average daily sales number SQ and a deviation value AD are obtained. And
In step S4, the deviation value AD is stored in the storage area M6. Therefore, step S1 corresponds to the above process, step S2 corresponds to the above process, and steps S3 and S4 correspond to the above process. Therefore,
The functional unit that obtains the fluctuation deviation SD by the process of step S1 is the "variation deviation calculation unit", and the functional unit that calculates the average sales amount by the process of step S2 is the "average sales number calculation unit".
The functional unit that obtains the deviation value AD by the process of step S3 is referred to as an "adding unit". In step S1, the following formula is used to calculate the sales fluctuation deviation SD. Of course, the results are the same.

SD = A / Ad-E / Ed After the above steps S1, S2, S3, and S4 are completed for one product, it is determined whether the product is the final product (step S5). If it is not the final product,
The stored data of the history data file 14 of the next product is read (step S6), and the steps S1, S2 are again performed.
The calculation process is performed in S3, and the deviation value AD of the product is stored in the storage area M6 corresponding to the product in step S4.

Hereinafter, similarly, the deviation value AD for each product is obtained and stored. Then, when the calculation process for the final product is completed, the process returns to this routine.

Next, the meaning of the deviation value AD will be described.

This deviation value AD represents the sales tendency of each product,
When it is positive, it can be judged that the product is a hot selling product, and when it is negative, it can be judged that the product is a dead selling product. FIG. 4 shows the relationship between the sales fluctuation deviation SD, the average daily sales number SQ, and the deviation value AD. The vertical axis represents the sales fluctuation variation SD, the horizontal axis represents the average daily sales number SQ, and the deviation value AD is represented by the numbers in the table. The more negative the deviation value AD is and the larger the deviation value AD, the more the product is dead.

The store controller 1 has a function of creating a report based on such a deviation value AD. One of the reports is created as a deadly product list as shown in FIG. The deadline product list is a list of products with the smallest deviation value AD, that is, in the order of the worst deviation value as the deadline, for example, the worst 50 products. In the case of this example,
The number of sold products SQ and the sales fluctuation difference SD are also printed together with the product code, product name, selling price, and deviation value AD. The sales number SQ and the sales fluctuation deviation SD are values stored when the deviation value AD is calculated, or values re-calculated after being rearranged in the order of the deviation value AD.

The person in charge of goods finds a deadly muscle product by such a report, confirms the inventory, and then determines the disposal method.

The store controller 1 can also create various reports based on the deviation value AD in addition to such a dead line list. For example, it is possible to create a report listing products whose deviation value AD is -10 or more.

By the way, the data collected in the history data file 14 is not limited to every two weeks, and the point is that the data may be collected for a certain period. However, sales on Saturday and Sunday are different from weekdays, so it is better to be on a weekly basis. In the case of a store that is open 24 hours, it is not necessary to store the working days in the history data file 14.

Further, the calculation of the sales fluctuation deviation SD and the deviation value AD is not limited to the arithmetic expressions of the above-described embodiments. For example, sales fluctuation variation SD
May be calculated by the following arithmetic expression.

SD = {(−) + (−) + (−) + (−)} In addition to the simple addition formula described above, the deviation value AD can be calculated by weighted addition or division of data,
It is also possible to calculate by multiplication.

Further, in the above embodiment, the history data file 14 is stored in the RA
Although the case of storing in M4 has been described, it may be stored in a hard disk or a floppy disk.

Further, in the above-described embodiment, the report is printed and output, but the printing is not limited to the printing and may be displayed on the display unit as a display screen, for example.

Further, in the above embodiment, the store controller and the plurality of POs are used.
The case where the present invention is applied to the POS system including the S register has been described, but the present invention is not limited to this. For example, a parent POS register having the function of a store controller and a child POS managed by the parent POS register.
It is also possible to obtain the same effect by applying the present invention to a POS system including a register and an electronic cash register (ECR) having a function of totalizing sales results of sold products. Further, the predetermined period when obtaining the sales fluctuation deviation SD for each predetermined period and the predetermined period unit when obtaining the average number of sales SQ in a predetermined period unit can be individually set to arbitrary periods, Nothing specified.

[Effects of the Invention] As described above, the sales data processing device of the present invention obtains the sales tendency of each product based on the transition of the sales result data of each product and creates a report by adding the sales tendency to each product. It is possible to create and provide a suitable report for judging a muscle product. In other words, instead of just simply predicting sales based on past sales results as in the past, the deviation value that also takes into account the sales trend of each product is calculated, so it is ideal as a deadline report for early detection of slow sales products. Such reports can be created to provide accurate information on whether the product should be left in the sales floor or excluded.

[Brief description of drawings]

Drawing is a figure for explaining one example of the present invention,
FIG. 1 is a block diagram, FIG. 2 is an explanatory diagram of a history data file, FIG. 3 is a flowchart of arithmetic processing, FIG. 4 is an explanatory diagram of the relationship between the arithmetic result and the sales tendency of goods, and FIG. FIG. 6 is an explanatory view of the dead item list, and FIG. 6 is a diagram corresponding to the configuration of the present invention. 1 ... Store controller, 2 ... CPU, 3 ... RO
M, 4 ... RAM, 14 ... History data file.

Claims (1)

[Claims] 1. A sales data processing device that totals sales results of sales products and creates various reports based on the totaled data, and stores the number of sales for each predetermined period for each product for a plurality of periods. A history data memory, a history data updating unit that updates the stored contents of the history data memory every predetermined period, and always stores the latest number of sales for a plurality of periods in the history data memory, and stores the history data memory in the history data memory. From the number of sales for each predetermined period, calculating means for calculating a deviation value for sales trend determination for each product as data for creating a report, and a report listing the products in ascending or descending order of the deviation value. A sales data processing device comprising: a report output unit for outputting; and the arithmetic unit including: A variation deviation calculation unit that obtains a deviation of the variation in the number of sales for each predetermined period in the latest plurality of periods from the transition of the average number of sales for each predetermined period for each of the predetermined periods. An average sales volume calculation unit that calculates the average sales volume for a specified period from the total sales volume during the latest multiple periods. An addition unit that calculates the deviation value by adding the average sales number to the fluctuation deviation.