JPH0336722B2 - - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a product order recommendation device in a retail store or the like.

[Conventional technology]

BACKGROUND ART Several methods have conventionally been used to order product replenishment at retail stores and the like. The first method is to check the products on the product shelf, record the names of products whose stock is running low, and place orders based on the names. This method is easy to see directly, but it has the disadvantage that once the shelf inventory reaches zero, you will not be able to tell what the product is, and after the inventory reaches zero, the empty space on the shelf will be on both sides. If there are no blank spaces left due to the movement of products, you will not be able to visually tell that the item is out of stock, and in the worst case scenario, you will never be able to place an order again. It also had The second method is to attach a shelf label to a shelf near the product placement position and place an order using the shelf label. The shelf tags include the product name, price, order unit, product code, and barcode. As with the first method, the ordering process involves visually finding a product that is out of stock, recording the product name or product code written on the shelf label corresponding to the product, and placing an order based on that. Additionally, if a barcode is printed on the shelf label, a handy terminal equipped with a barcode reader is used to mechanize the ordering process by reading the barcode on the shelf label with the barcode reader and specifying the product to be ordered. Sometimes. The ordering method using this shelf label is described in 1 above.
Although the product name of an out-of-stock item will not be lost as in the ordering method, if the blank space for an out-of-stock item is filled with products on both sides, even if a shelf label is attached. You may also miss out on the fact that the item is out of stock. Furthermore, in the method using shelf labels, accurate management of the shelf labels is an important condition. Specifically, adding products,
Shelf labels must be changed accurately in response to replacements, removals, changes in product placement, changes in prices, etc. This shelf label management was quite a difficult job and placed a heavy burden on store staff. In addition, in reality, it is often not always accurately managed, and as a result, there is a drawback that appropriate orders are not placed.

The third method is to place replenishment orders based on an order ledger. First, a product order ledger corresponding to the products on the shelf is created. When ordering, instead of looking at the products on the shelf, customers visually read the product names in the order they are written on the ledger, find the product with that name on the shelf, and decide whether to order based on the amount in stock. The main feature of this method is that
Since the items in the ledger are checked sequentially, out-of-stock items will not be overlooked. In addition, there is no need for shelf labels, so product placement can be changed to a certain extent. There is also a mechanized method of placing orders in which the contents of the product order ledger are stored in the memory of the handy terminal, and information corresponding to the contents of the product order ledger is sequentially displayed on the display by key operations on the handy terminal. EOB (Electronic
Also called Order Booking. The disadvantage of this method is that all products on the order ledger must be visually confirmed. Even though the products that need to be ordered are only a part of the total products, it is extremely inefficient to have to check whether or not there is a need to order many products that do not need to be ordered.

The fourth method is called the automatic ordering method.
This is a method of collecting sales information for each item using a POS scanner or collecting product tags at the time of sale and automatically placing orders based on the number of sales, and is usually processed by a computer. This method has the advantage of not requiring much labor, but depending on the product, it may be necessary to make some changes to past sales numbers and place orders depending on the season, fashion, social environment, climate, recent sales trends, etc. There were many cases in which conditions were not met, and the disadvantage was that inputting the conditions into a computer each time required manpower.

As explained above, the conventional ordering method or
The mechanized ordering system had several drawbacks.

[Purpose of the invention]

In view of these problems, the present invention is a POS
(Point of Sale) The present invention provides a device that combines single item sales information and previous order information to output an order recommendation without missing any orders and with high work efficiency.

[Means for solving problems]

In order to achieve the above object, the present invention includes a single item sales information input means, a sales data storage section for storing the single item sales information obtained by the single item sales information input means, and an ordering data for inputting ordering information. It includes an input section and an ordering data storage section that stores the ordering information, and the information is calculated from the previous order quantity stored in the ordering data storage section, from the previous ordering time to the current ordering time stored in the sales data storage section. It is equipped with a control unit that determines the necessity of ordering based on the difference in sales volume for each item, and an ordering recommendation means that makes an ordering recommendation based on the determination result obtained by the control unit. It is.

[Effect]

According to the present invention, the necessity of placing an order is determined based on the difference obtained by subtracting the sales volume from the previous order stored in the sales data storage unit to the current order for each item from the previous order quantity stored in the order data storage unit. A judgment is made and an order recommendation is made based on the judgment result.

〔Example〕

The present invention will be explained below using an embodiment suitable for ordering replenishment of merchandise at a certain store.

FIG. 1 is a block diagram of a product order recommendation device in this embodiment.

In FIG. 1, numeral 1 is a POS scanner that serves as a means for inputting information on single item sales, and reads barcodes printed or affixed to products. The read barcode information is input to the microcomputer 2 as a control unit, and is stored in the barcode product master storage unit 3.
If there is a product that matches the barcode information stored in the barcode, the product name, price, etc. can be read out. Products sold by the POS scanner 1 are stored in the sales data storage unit 4 as single item data.
is memorized. Here, a single item means the smallest possible classification item for a product.

The product order master storage unit 5 stores information necessary for ordering products, such as product name, product number, selling price, cost, supplier, department, etc.

The product order recommendation device according to this embodiment outputs the order recommendation as described below for product order work.

Referring to the flowchart in FIG. 3, when placing an order, first specify the product category to be ordered from the operation panel 9 and press the start button, then the microcomputer 2 will sequentially transfer the products of the specified product category to the product order master. The sales amount S of the read product since the previous order is read out from the storage section 5, and the previous order amount H of the product is read out from the order data storage section 8. Next, the difference D=H−S between the sales amount S and the previous order amount H is calculated.
The microcomputer 2, depending on the value of the difference D,
It is determined whether or not to recommend ordering the product, and the result is printed. The judgment in Fig. 3 is to print when D≦0, but
For example, the products are ranked according to the level of necessity of ordering, and an ordering recommendation output is printed for each product on a printing device 7 serving as an ordering recommendation means. For example, rank 1 is ``If you don't place an order as soon as possible, we will run out of stock,'' rank 2 is ``It's better to order,'' rank 3 is ``It's better to order if possible,'' and rank 4 is ``There's no need to order yet.'''', and the products are divided into ranks according to the ranks, and a list of recommended products to order is printed out on the printing device 7. The recommended ordering product list lists products in ranks according to the degree of need for ordering, so the ordering worker visually checks the inventory of the products on the shelf in that order and actually places the order. determine whether The ordering data thus determined by the ordering worker based on the recommendation of the recommended ordering product list is input into the microcomputer 2 from the ordering data input section (for example, a keyboard). The input order data is checked against the information in the product order master storage unit 5, and an order slip is printed by the printing device 7 for each supplier, for example, or an order is placed online through a telephone line. (Means for this purpose are not shown in FIG. 1). Further, the ordering data is stored in the ordering data storage section 8 as the ordering amount for each item as the previous ordering amount.

Next, a method for determining order recommendations will be explained. As mentioned above, the order recommendation is made based on the difference D=H-S between the sales amount S and the previous order amount H. The meaning of the difference D is as follows. In the first place, the purpose of ordering products is to prevent products from running out of stock on store shelves, that is, to prevent products from running out of stock, and to reduce excess inventory. Therefore, it is necessary to calculate the original stock amount of the product on the shelf and output an order recommendation based on the product stock amount. By the way, it is not possible to determine the amount of product in stock by simply taking an inventory at a certain point in time and then calculating it from the sales volume and purchase volume. For example, if the product is stolen, the number will remain as an error forever. In addition, there is an extra task of having to input the quantity when purchasing or arranging the products on the shelf. If the error between the product inventory amount and its calculated value becomes large, or if there is a concern that they do not match, the work of taking inventory and actually measuring the actual product inventory amount increases. As described above, the conventional product inventory calculation method has a major drawback in that extra work is required to improve the accuracy of inventory calculation.

Difference D=H− used in the embodiment according to the invention
Since the previous order quantity H at S is data input during the conventional ordering work that is indispensable for store management, no extra work is required. Further, the sales volume S can be automatically obtained in stores that have introduced a POS system using a POS scanner to analyze sales, and this also requires no extra work.

Product inventory amount on the shelf (hereinafter referred to as Z) and D, H, S
The relationship will be explained with reference to FIG. In the graph of FIG. 2, the vertical axis indicates the product inventory amount Z, and the horizontal axis indicates time T. Assuming that the product inventory amount is Z0 at time T0, the product inventory amount Z decreases as the product sells. At time T10, the product inventory amount Z is larger than the order limit amount ZL, so no order is placed. At the next ordering work time T1, the product inventory amount Z is smaller than the ordering limit ZL, so H2 items are ordered. Time delay d after ordering (delivery date)
After that, H2 items are delivered at time T2, and as a result, the product inventory increases by H2. Similarly, by placing an order at time T3 and delivering the product at time T4, the product inventory amount Z increases as shown in FIG.

The order quantity H2 at time T1 is the previous order quantity H=
If H2, the difference D at the next order time T3 is
From the previous sales volume S=S3, the difference D=D3=H2−S3
(S3=S3A+S3B). By the way, Z1+H2=
Since S3+Z3 holds true, from this H2−S3=Z3
−Z1, and when combined with the formula of D3, D3=Z3−Z1 is obtained. Here, D3 can be calculated because H2 and S3 are each obtained from the data stored in the product order recommendation device. Therefore, it turns out that Z3−Z1 can also be calculated.

Here, Z1 is the product inventory amount at the previous order time T1, and Z3 is the product inventory amount at the current order time T3.

Incidentally, the ordering decision at time T1 was made by the ordering worker who visually inspected the stock amount Z1 and made the decision based on the size relationship with the ordering limit ZL determined from various conditions. Considering that the judgment criteria are applied, it is desirable that the order recommendation output from the product order recommendation device be based on the same order judgment criteria as the order judgment criteria adopted by the ordering worker at time T1. This means that the amount in stock at the time of the last order was
Since it was at Z1, it is desirable that this order be placed when the inventory amount is close to or smaller than Z1. In other words, it is desirable to place an order when Z3≦Z1. By the way, Z3−Z1
=D3, this ordering criterion can be expressed as D3≦0. Depending on the value of D3, the device of this embodiment can output a recommendation based on the same ordering criteria as the ordering criteria of the ordering worker at T1 at the time of the previous ordering, as follows. it makes sense. The significance of this is that the order recommendation by the product order recommendation device can be made without using the information on the actual product inventory on the shelf, for example, without using the storage means for storing the current inventory amount shown in Japanese Patent Application Laid-Open No. 50-91536. Furthermore, the significance of this is that even if the product ordering recommendation device does not know the ordering criteria of the ordering worker, it can output the same ordering recommendation as if it had adopted ordering criteria close to the ordering criteria adopted by the previous ordering worker. This means that it is possible to do so. Since inventory information itself is not required, there is no need to take inventory from time to time to measure the actual inventory, and even if the inventory decreases due to product theft, the ordering worker can judge the amount by the amount. Therefore, the product order recommendation device of this embodiment does not need to know this fact, because it is compensated for by placing an order earlier or by increasing the order amount.

The ordering criteria for ordering workers is quite complex.
For example, the type of product, season, temperature, social environment, recent sales trends, fashions, etc. are taken into account.
Because of this complexity, conventional automated ordering by computer based on fixed ordering criteria has had major problems, and the reality is that it has hardly been put into practical use. In the product order recommendation device of this embodiment, the criteria for making an order recommendation are close to the ordering criteria of the ordering worker at the time of the previous order, so for example, the ordering worker can As the ordering criteria change, the product ordering recommendation device also has the adaptability of changing the criteria for making ordering recommendations accordingly.

As explained above, according to the product order recommendation device of this embodiment, a list of recommended order products created based on appropriate ordering criteria is printed, and the inventory of products is checked in order of order rank in the list.
For example, if you check the inventory of products listed in rank 1, most of them will need to be ordered, and as you check ranks 2 and 3, you will be able to decide whether or not to place an order based on the judgment of the ordering worker. Alternatively, you can decide on the order quantity.

As described above, the product order recommendation device of this embodiment makes use of the advantages of the ordering system based on the ordering ledger described in the third method of the prior art, but also has the disadvantage of having to check even products that do not need to be ordered. It is possible to place orders with good work efficiency and without missing any orders.

As explained above, it has been found that if an ordering recommendation is output based on the value of the difference D=HS-S, the ordering standard of the ordering recommendation will be close to the ordering standard held by the ordering worker. By the way, there are variations in the progress of sales in actual stores, and the time of ordering (day, day of the week, etc.) can vary, so it is important to output an order recommendation only when D≦0, as explained above. is not realistic. Therefore, as described above, it is actually better to output order recommendations (printed output, etc.) after ranking them according to the level of necessity of order placement based on the value of D. Various criteria may be used for this ranking D, but for example, the ranking may be based on the ratio of the previous order quantity H to D. Specifically, calculate R=D/H, and depending on the value of R, rank 1 if R≦0.1, rank 2 if 0.1<R≦0.2, rank 3 if 0.2<R≦0.4, etc. . Regarding this point, the choice can be made depending on the store owner's thinking or the type of product.

In the above description, the ordering recommendation output is printed out by the printing device 7 as the ordering recommendation means, but a display device may be used as another specific example, and this can be selected depending on the usage situation.

In the above explanation, the order data input unit 6 as the order data input means is a keyboard, but
Another specific example may be a touch panel switch attached to the display device.

In the above description, a POS scanner is used as the single item sales information input means, but other single item sales information input means may be a tag reader that collects and reads barcode tags attached to products. but
Using a POS scanner has the advantage that there is no time delay in obtaining sales information, and it also has a significant labor-saving effect.

〔Effect of the invention〕

According to the present invention, since there is no need for a means for storing the current inventory amount, it is possible to roughly manage the inventory without much effort, and therefore, ordering operations can be carried out efficiently.

[Brief explanation of the drawing]

FIG. 1 is a block diagram of an embodiment of the present invention, and FIG. 2 is a graph showing changes in product inventory over time when the embodiment of the present invention is applied. FIG. 3 is a flow chart of an embodiment of the present invention. 1... POS scanner, 2... Microcomputer, 4... Sales data storage section, 6... Order data input section, 7... Printing device, 8... Order data storage section, T1... Last order time, T3 ...Current order time, H2...previously ordered quantity, H4...currently ordered quantity.

Claims (1)

[Scope of Claims] 1. Single item sales information input means, a sales data storage section for storing single item sales information obtained by the single item sales information input means, and an order data input section for inputting order information. , and an ordering data storage unit that stores the ordering information, and calculates the sales volume from the previous ordering time to the current ordering time stored in the sales data storage unit, based on the previous ordering amount stored in the ordering data storage unit. The present invention is characterized by comprising a control unit that determines the necessity of ordering based on the difference reduced for each item, and an ordering recommendation means that makes an ordering recommendation based on the determination result obtained by the control unit. Product order recommendation device. 2. A product order recommendation device characterized in that a POS scanner is used as the unit sales information input means as set forth in claim 1.