JPH0223461A - Sales predicting system - Google Patents

Abstract

PURPOSE:To make accurate the prediction of the number of the sales of commodities sold by weight by calculating the number of the sales at every day of the week based on the sales number data for the past several weeks, and rewriting the number into the predicted number of the bargain sales obtained from the number of the bargain sales when the bargain sale is set. CONSTITUTION:The mean number of the sales based on the sales number data for the past several weeks of the plural commodities sold by weight, which are stored into a date classification record file (a), is stored into a basic memory (c), and stored into a predicted sales memory (d) as the predicted number of the sales for one week. Further, the number of the sales in the past bargain sale of the commodity sold by weight is stored into a bargain sale record memory (b), when the commodity sold by weight, for which the bargain sale is set, exists in a bargain sale setting memory (e) to set the presence and absence of the bargain sale for one week, the predicted number of the bargain sales of the commodities sold by weight is obtained from the number of the sales stored into the bargain sale record memory (b), the predicted number of the sales on the bargain sale day of the week of the predicted sales memory (d) is rewritten to the obtained predicted number of the bargain sales by a bargain sale rewriting means (f), and the sales prediction for one week is executed based on the predicted number of the sales in the predicted sales memory (d).

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial Application Field] The present invention relates to a sales forecasting system for forecasting sales of weighed products sold in packs on a weekly basis.

[Prior Art] Conventionally, for example, POS systems and the like are known to aggregate the sales of each sales product on a daily basis or monthly basis.

However, this was merely a tabulation, and there was no way to use the tabulated results to predict the sales of each product.

[Question 8 to be solved by the invention] By the way, among commercial products, products sold by weight such as meat and fish are usually sold in packs.

In order to sell products in packs, the raw materials must be processed, measured, and packaged in advance. Since most of the items sold in such packages are fresh foods, if they are overproduced and left unsold, they will be discarded because it would be problematic to sell them the next day.

Therefore, for products sold by weight such as fresh foods that are sold in packages, it is necessary to predict in advance the number of units to be sold the next day, process and pack them.

SUMMARY OF THE INVENTION Therefore, the present invention aims to provide a sales prediction system that can more accurately predict the number of sold products sold by weight in packs.

[Means for Solving the Problems] As shown in FIG. , a bargain sale record memory b that stores at least the number of sold items in past special sales of each weighed sale item, and a past number of a plurality of weighed sale items calculated based on the sales number data stored in the daily record file a. A basic memory C that stores at least the average number of sold items for each day of the week for the week, and a forecast that stores the average number of sold items for each day of the week of each weighed product stored in this basic memory C as the expected number of sold items for one week. There is a sales memory d, a special sale setting memory e for setting whether or not there is a special sale for each weighed product in one week, and when there is a weighed sales product for which special sale is set in the special sale setting memory e, the special sale of that weighed sales product is set. The expected number of units is calculated from the number of units sold for the applicable weighed product stored in the sale record memory b, and the estimated number of units sold on the sale day of the applicable weighed item in the estimated sales memory d is rewritten to the calculated expected number of units for sale. A special sale rewriting means f is provided, and the expected sales memo IJ is
The sales forecast for each weighed product for one week is made based on the expected sales volume of d.

In addition, a means is provided for weighting the sales quantity data for the past several weeks of multiple measured sales items stored in the daily performance file a, and the sales quantity data in the daily performance file is weighted by this means. The basic memory C stores at least the average sales number of a plurality of weighed and sold products for each day of the week calculated based on the following.

Furthermore, the holiday performance memory stores at least the sales quantity of each weighed and sold product on past holidays, and when there is a holiday next week, the predicted sales volume of each weighed and sold product on the day of the week corresponding to the holiday is stored in the holiday performance memory. This system is provided with a holiday rewriting means for rewriting based on the sales quantity data.

[Function] In the present invention having such a configuration, the daily results file a stores at least the daily sales numbers of a plurality of weighed and sold products for the past several weeks, and the special sales results memory b stores the past sale items. To store at least the number of sold products by weight. Then, based on the sales number data in the daily performance file a, the average sales number of each weighed product for the past several weeks for each day of the week is calculated and stored in the basic memory C. and it is 1
It is stored in the expected sales memory d as the expected weekly sales number.

Furthermore, if there is a weighed product to be sold on sale in the predicted week, the past sale record number of the weighed sale product is calculated from the sales number of the weighed sale product in the bargain sale record memory b, and the corresponding weighed sale product in the predicted sales memory d is calculated. Rewrite the expected sales quantity on the special sale day of the week. In this way, the final predicted sales number of each weighed product for each day of the week is obtained from the predicted sales memory d, and the sales forecast is made according to that number, and the weighed and sold products are processed.

Furthermore, by weighting the data in the date record file by taking into account the season, for example, the predicted sales quantity can be calculated more accurately.

Furthermore, the sales numbers of each weighed and sold product on past holidays are stored in the holiday performance memory, and when there is a holiday in the expected week, the predicted sales volume for the day of the week corresponding to the holiday in the forecast sales memory d is stored in the holiday performance memory. The data is rewritten based on the stored sales quantity data of the relevant measured product. This makes the predicted sales volume more accurate.

[Example] Embodiments of the present invention will be described below with reference to the drawings.

Fig. 2 is a block diagram showing the configuration, where 11 is a microprocessor that constitutes the main body of the control unit, 12 is a perishable product mask in which the product name and code of perishable products as sold by weight are set, and 13 is an analysis period and data. Perishable food management mask that stores various data for managing weights etc. applied to food, 14 is P
A PLU master that manages products by LU (Price Look Up) code, 15 a perishable daily record file that manages daily sales data for perishable products, and 16 a holiday track record that stores sales data for perishable products on holidays. memory,
Reference numeral 17 denotes a bargain sale record memory that stores sales data of fresh products on the day of the bargain sale, and 18 denotes a bargain sale setting memory in which the fresh products to be sold on sale and their period are set.

The microprocessor 11 and each master 12゜13.1
4. Daily results file 15 and each memory 16.17.1
8 are connected via a pass line 19.

Further, 20 is a host interface connected to a host computer, 21 is a CRT controller that controls a CRT display 22, 23 is a printer controller that controls a printer 24, and 25 controls data transmission and reception with an externally connected weighing label issuing device 26. This is a transmitting/receiving controller.

The microprocessor 11, the interface 20 and each controller 21, 23, 25 are connected via a path line 27.

As shown in FIG. 3, the perishable product master 12 contains the product code, product name for PO8 (for receipts), and product name for data station (CR) for each perishable product sold in packs.
It is also used for the T display and the weighing label issuing device 26. ),
Processing code to distinguish processing light, average unit price of 1 back, 1
A product setting memory 28 is provided in which the average weight of the bag, single item code, group code, event flag set when an event such as a special sale is held, unit price per unit weight, tare weight/quantity, valid days, processing date, etc. There is. Further, a predicted sales memory 29 for this week, a predicted sales memory 30 for next week, and a basic memory 31 are provided for each fresh product. Each memory 29, 30, and 31 has areas (1) to (7) for storing the maintenance flag, number of units sold, average weight per pack, and average unit price per pack for exactly one week. There is.

That is, the perishable product master 12 includes a product setting memory 28, this week's expected sales memory 29, and next week's expected sales memory for each perishable product to be sold in packs.

As shown in FIG. 4, the perishable daily performance file 15 includes, for each perishable product, the product code, date (year, month, day), single product code, event flag, planned processing pack quantity, and planned sales pack. The number of packs and average unit price, the number of packs, total price, and total weight of actual processing, the number of packs, total price, and total weight of actual sales, the number of packs, total price, and total weight of actual luminosity, the number of packs and total price of packs discarded, and A memory 32 for storing total weight and days of the week is provided, for example, for five weeks (35 days).

The microprocessor updates the perishable date record file 15 every time it receives daily sales data for each perishable product from the host computer via the interface 20. This update clears the oldest data from 36 days ago and stores the received data as the newest data. Note that the host computer is configured to aggregate sales data from a plurality of PO8 terminals.

For example, if one week is defined as Monday to Sunday,
At the set time on Sunday night at the end of the week, the microprocessor 11 automatically creates a sales plan. For each fresh product, data for the past five weeks is first read out from the perishable date record file 15 for each day of the week, and the average sales quantity, average weight per pack, and 1 pack' are calculated for each day of the week.
The average unit price per hit is determined, and the contents of the basic memory 31 are rewritten based on the contents. At this time, if it is set to apply weight to the data in the perishable date record file 15, the calculation will be based on the weighted data. (Means for applying weights) Then, the contents of next week's expected sales memory 30 are transferred to this week's expected sales memory 29, and the contents of next week's expected sales memory 30 are rewritten based on the contents of the basic memory 31.

Next, the microprocessor 11 checks whether a special sale for the perishable product is set in the special sale setting memory 18 from this week to next week.

If a sale is set, the data for the corresponding day of the week in this week's and next week's expected sales memory 29.30 is rewritten based on the past sale record data for the perishable product stored in the sale record memory 17. . (Special Sale Rewriting Means) In this way, when a certain perishable product is on sale, the expected sales quantity is calculated based on past sale results rather than data on past days of the week.

The microprocessor 11 also checks whether there is a holiday next week. If there is a holiday, the data on the day of the week corresponding to the holiday in the next week's expected sales memory 30 is rewritten based on the sales performance data for the relevant perishable product on past holidays stored in the holiday performance memory 16. (Holiday Rewriting Means) When there is a holiday in this way, the expected sales quantity is calculated based on the sales performance of the past holiday instead of the data on the past day of the week.

In this embodiment having such a configuration, the daily sales performance data of each perishable product is filed in the perishable daily performance file 15. The file 15 stores performance data for the past five weeks for each fresh product.

Then, at the set time on Sunday, based on the past 5 weeks' worth of performance data in the perishable day performance file 15, the estimated sales quantity for each day of the week, the average weight per pack, 1
Find the average unit price per pack. At this time, if there is a perishable product for which weight data is set in the perishable product management mask 13, weighting is applied based on the set weight data when calculating the expected sales quantity of the perishable product.

This allows the expected sales volume to be adjusted according to changes in sales over time.

The basic memory 31 is rewritten in accordance with the predicted sales quantity of each fresh product for each day of the week, average weight per pack, and average unit price per pack thus determined.

The predicted sales data that has been stored in the next week's predicted sales memory 30 is then transferred to this week's predicted sales memory 29, and the rewritten contents of the basic memory 31 are also set in the next week's predicted sales memory 30.

In this way, this week's expected sales memory 29 stores the expected sales quantity for each perishable product for one week from tomorrow's Monday, and next week's expected sales memory 30 stores the expected sales number for each perishable product for one week from next Monday. The expected sales quantity will be stored.

In addition, if the special sale period for a perishable product in this week and the next week is set in the special sale setting memory 18, the actual sales quantity of the perishable product during past special sales is read from the special sale record memory 17, and the corresponding sale quantity is applied according to the actual sale quantity. Rewrite the predicted sales quantity for the corresponding day of the week in the predicted sales memory 29.30 for this week and next week for perishable products. In this case, the data in this week's expected sales memory 29 is transferred from next week's expected sales memory 30, and therefore, if the day of the sale has already been determined one week ago, the data will be set in next week's expected sales memory 30. has already been rewritten to special sale data. Therefore, when the contents of this week's expected sales memory 29 are rewritten by specifying a special sale, a special sale is urgently set after data is set in next week's expected sales memory 30.

In this way, for perishable products that have a special sale, the expected sales quantity on the special sale day is set based on the past sale results.

Further, if there is a holiday in the next week, the predicted sales quantity for the corresponding holiday Sunday in the next week's predicted sales memory 30 for each fresh product is set based on the actual sales quantity on past holidays stored in the holiday record memory 16.

In this way, when there is a holiday, the expected sales quantity is set based on the actual sales quantity on past holidays.

In this way, this week's expected sales memory 29 and next week's expected sales memory 30 store the expected sales numbers of each perishable product determined by taking into account sales results for each day of the week over the past five weeks, weights by time, special sales, and holidays. Therefore,
The contents of each predicted sales memory 29.30 are sent to the printer 24.
This can be confirmed by controlling and printing out the information, or by controlling and displaying the CRT display 22.

In this way, we calculate the expected sales volume for each day of the week for each perishable product, and the expected sales volume is determined by taking into account the sales results for each day of the week over the past five weeks, the weighting due to the time of the week, special sales, and holidays. This will give you a more accurate expected sales volume.

Therefore, if the raw materials are processed and packaged products are prepared in advance based on the expected sales number of each outputted perishable product for each day of the week, there will be less chance of excess or shortage. Become.

In addition, since the predicted sales memory 30 for next week stores the predicted sales number of each fresh product for each day of the week, it is possible to make a sales plan based on this data in relation to the budget.

Furthermore, if each fresh product can be divided into categories using group codes, etc., it becomes possible to determine budgets and make sales plans for each department.

Furthermore, since a processing code that distinguishes the processing light is set corresponding to each perishable product, processing instructions can be easily given by calculating the expected sales number of perishable products for each day of the week for each processing code.

Furthermore, if the data in the estimated sales memory 29.30 is sent to the weighing label issuing device 1126 via the transmission/reception controller 25, the number of processed products to be packed will be automatically set in the weighing label issuing device 26, and the number of processed products to be packed will be automatically set. becomes easier.

[Effects of the Invention] As detailed above, according to the present invention, it is possible to provide a sales prediction system that can more accurately predict the number of sold products sold by weight in packs.

[Brief explanation of the drawing]

Fig. 1 is a functional block diagram showing the configuration of the present invention, Figs. 2 to 4 show embodiments of the present invention, Fig. 2 is a block diagram, and Fig. 3 is a main memory of the perishable product mask. FIG. 4 is a diagram showing the structure of the daily performance data of the perishable date performance file. DESCRIPTION OF SYMBOLS 11... Microprocessor, 12... Perishable product mask, 15... Perishables date track record file, 16... Holiday track record memory, 17... Sale track record memory, 18...
Special sale setting memory, 29...This week's expected sales memory, 30
...Estimated sales memory for next week, 31...Basic memory. Applicant's agent Patent attorney Takehiko Suzue

Claims (3)

[Claims] (1) A daily performance file that stores at least the number of units sold each day for the past several weeks of multiple weighted products sold in packs, and a sale performance memory that stores at least the number of units sold in past special sales of each of the weighted and sold items. and a basic memory that stores at least the average number of sold items for each day of the week for the past several weeks of the plurality of measured sales items calculated based on the sales number data stored in the daily performance file;
A predicted sales memory that stores the average number of units sold for each day of the week of each weighed product stored in this basic memory as the expected sales number for one week, and whether or not there will be a special sale for each weighed product in one week is set. When there is a sale setting memory and a weight sale item for which sale is set in the sale setting memory, the expected sale quantity of the weight sale item is calculated from the sales number of the corresponding weight sale item stored in the sale record memory. seek,
A bargain sale rewriting means is provided for rewriting the predicted sales quantity of the corresponding weighed sale item on the sale day of the week in the predicted sale memory to the obtained bargain sale predicted quantity, and the sale price of each weighed sale item is rewritten based on the predicted sale quantity of the predicted sale memory. A sales forecasting system characterized by forecasting sales for one week. (2) A daily performance file that stores at least the number of units sold each day for the past several weeks of a plurality of weighted items sold in packs, and a sale performance memory that stores at least the number of units sold in past sales of each of the weighted items. and a means for weighting the past several weeks' worth of sales quantity data of the plurality of measured sales items stored in the daily result file; a basic memory for storing at least an average sales quantity for each day of the week of the plurality of weighted sales items calculated based on sales quantity data; An expected sales memory that stores the average number of sold items as the expected number of sold items per week, a special sale setting memory that sets whether or not there will be a special sale for each weighed product in one week, and a weighing unit in which the special sale setting memory is set to have a special sale. When there is an item for sale, the predicted sale quantity of the weighed sale item is calculated from the sales quantity of the applicable weighted sale item stored in the sale record memory, and the predicted sale day of the weighted sale item in the said predicted sales memory is calculated. The sales forecast is characterized in that a special sale rewriting means is provided for rewriting the sales quantity to the obtained predicted sale quantity, and a one-week sales forecast for each of the weighed sales items is made based on the predicted sales quantity in the predicted sales memory. system. (3) A daily performance file that stores at least the number of units sold each day for the past several weeks of a plurality of weighted products sold in packs, and a sale performance memory that stores at least the number of units sold in past special sales of each of the weighted and sold items. a holiday performance memory that stores at least the number of sold items on past holidays for each of the items sold by weight; and a past record of the plurality of items sold by weight calculated based on the sales number data stored in the daily performance file. A basic memory that stores at least the average number of units sold for each day of the week for several weeks, and a forecast that stores the average number of units sold for each day of the week of each weighed product stored in this basic memory as the expected number of units sold for one week. A sales memory, a special sale setting memory for setting whether or not there will be a special sale for each weighed product in one week, and when there is a weighed sales product for which special sale is set in this special sale setting memory, the expected number of sale items for that weighed sales product. is calculated from the sales quantity of the corresponding weighed sales product stored in the sale record memory, and the predicted sales quantity of the corresponding weighed sales product on the special sale day in the predicted sales memory is rewritten to the calculated sale forecasted quantity. a rewriting means; and a holiday for rewriting the predicted sales quantity of each weighed and sold product on the day of the week corresponding to the holiday in the predicted sales memory based on the sales quantity data stored in the holiday performance memory when there is a holiday in the predicted week. 1. A sales forecasting system, comprising a rewriting means, and forecasting sales of each weighed product for one week based on the predicted sales number in the predicted sales memory.