JPH09198448A - System and device for automatically ordering commodity - Google Patents

Abstract

PROBLEM TO BE SOLVED: To calculate the optimum number of composites to be ordered, and to automatically order commodities while keeping proper stock by predicting the amount of commodities to be ordered from a predictive index found from the index of the next week and a corrected value and a result value for each latest day of a week. SOLUTION: First of all, the result in the previous year corresponding to a predictive week is compared with the result of the next week in the last year and the index of the next week in the last year is found. Namely, it is made into index how the index of the next week in the last year changes at the same period the last year. In order to consider the fluctuation transition of this year, the corrected value is provided by comparing the weighted mean of closest three weeks in this year with the weighted mean of the same period in the last year (of closest three weeks in the last year). The prediction index is found from the next week index in the last year and the correction value. When there is a sales result as shown in the figure and the number of displays at starting time is '400', for example, in the case of order on Monday and delivery on Wednesday, the number of commodities to be ordered becomes the total of sales of the last week from Monday to Sunday, namely, 20+10+30+35+40+60+80=275. Thus, stock efficiency is improved as well and the optimum amount of commodities to be ordered can be decided without sold out commodities.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a sales forecast type automatic merchandise ordering system and an automatic merchandise ordering device, and in particular, an automatic ordering system for each individual product in consideration of sales fluctuations such as seasonal fluctuations, store holidays and sales promotion. It is about.

[0002]

2. Description of the Related Art There are an extremely large number of products handled in home centers and supermarkets, and replenishment orders are frequently made. With respect to these supplementary orders, efforts have been made to introduce sales information quickly and accurately by introducing a POS system.

However, in reality, an ordering method such as a fixed point replenishment ordering method or a sales record ordering method, which has many defects, has been adopted.

The fixed point replenishment ordering system is a system in which the maximum display quantity, the ordering point quantity, and the ordering point quantity are determined for each product, and when the inventory falls below the ordering point, the shortage with the maximum display quantity is ordered. . For example, if the maximum display quantity for product A is 30, and the current product is 8, then (30-8)
= 22 (pieces).

The sales record ordering system is a system in which the latest sales quantity is simply ordered.

[0006]

The fixed point replenishment ordering system described above does not directly consider the sales record, and therefore cannot deal with seasonal fluctuations that often change greatly during the year. There is a problem that it is not possible to reflect the detailed daily sales trends such as calendar adjustment in the replenishment order. In addition, there is a fatal problem that it is impossible to deal with a peculiar change in sales due to sales promotion.

In particular, holidays may reach three times as much as sales on weekdays, and in addition, advertising and sales promotion effects such as bargain sales and leaflets have become more effective in recent years, and these sales promotion effects are excluded. Unless it is a replenishment ordering system that can be managed, there is a fatal problem of inadequate inventory, and it is rarely used.

Further, the sales record ordering system does not use inventory data, so that the system cost can be kept relatively low, but it does not have a function of managing proper inventory, and is expected to prevent out-of-stock and excess inventory. This is not possible, and there is a problem in that it can be applied only to a sufficiently large number of products on display.

[0009] Further, the inventory check method of grasping the actual situation at the site using the handy terminal imposes a work burden on the sales floor staff, which is one-third of the daily work, resulting in extremely low economic efficiency and accuracy. There was a problem.

Therefore, most products can be handled,
It is strongly desired to develop an automatic merchandise ordering system and an automatic merchandise ordering system that can calculate the optimal number of replenishment orders in consideration of sales fluctuations and automatically place orders while maintaining proper inventory. It was rare.

[0011]

[Means for Solving the Problems] The present invention has been devised in view of the above problems, and includes the same-year sales result of the same week of the previous year, which is the sales performance of a week corresponding to the forecast week of the sales forecast. The first process that calculates the previous week's next week's index (the previous year's next week's results / the previous year's same week's results), which compares the sales results for the next week of the corresponding previous year's week, and the weighted average for the latest certain period of the predicted year , The second step of calculating a correction value (weighted average index of the last 3 weeks of the current year / weighted average index of 3 weeks of the previous year) comparing the weighted averages of the corresponding weeks of the previous year, and the index of the next week and the correction value It is characterized in that the ordering quantity is predicted from the third step of multiplying and calculating the prediction index, the prediction index, and the actual value of each latest day of the week.

In addition, the fixed period when the weighted average of the fixed period of the present invention is performed is March, and the order quantity can also be predicted by multiplying the forecast index by the actual value of each latest day of the week.

Further, according to the present invention, the first step of recording the sales on each day of the previous week corresponding to the day after the delivery date of the forecasted ordering date to the delivery date of the next order and the sales on each of these days are totaled. , And a second step in which the total number of sales is the number of orders.

According to the present invention, when the corresponding day of the previous week is a store holiday and the predicted corresponding day is a business day, the sales are recorded if the week before the business day is the business day before, and the sales of the week before the last day are recorded. If the corresponding day is a store holiday, it is possible to count the sales on the day following the store holiday of the previous week.

Further, according to the present invention, when the corresponding day of the previous week is a business day and the predicted corresponding day is a store holiday, the sales can be zero.

Further, according to the present invention, when the corresponding day of the previous week is a weekday and the predicted corresponding day is a holiday, the sales can be the sales of the latest Sunday.

Further, according to the present invention, when the corresponding day of the previous week is a holiday and the predicted corresponding day is a weekday, it is possible to record the sales on the next day (weekday) of the holiday of the previous week.

In the case of the sales promotion period, the present invention also provides
The buyer forecasts the number of sales that will increase during the promotion period, orders the increase separately, and either adds the remaining inventory during the promotion period to the number of stocks at the time of normal sales, or deducts the shortfall, and sells. For the promotion period, sales can be recorded on the same day of the previous week.

Further, according to the present invention, the first step of calculating the number of sales W in the period up to the delivery date by subtracting the number of period sales from the set order to the delivery from the current inventory (delivery date inventory number W = current inventory) V-the number of sales per period) and the number of sales per period divided by the number of days per period to determine the average number of sales per period X, and the number of delivery days inventory W divided by the average number of sales per period X to determine the number of units per day of delivery. Third day of calculating the delivery day inventory days, the set standard inventory days U, and the delivery day inventory days are subtracted to calculate the inventory days gap Y. Fourth step (inventory days gap Y
= U−W) and the period sales quantity is corrected by the inventory day gap Y to calculate the order quantity (period sales quantity + (stock days gap Y * period average sales quantity X)).

The present invention can also look back on the results of the previous week or the same day of the previous week when the stock due to the out of stock is zero.

According to the present invention, the number of items sold during the period is
It is also possible to use the order quantity calculated in ~ 8.

According to the present invention, the sales result of the same week of the previous year corresponding to the forecast week which is the target of the sales forecast, and the sales result of the corresponding week of the previous week corresponding to the same week of the previous year corresponding to the sales result of the corresponding week of the previous year. Next week's index comparing
Compensated value (weighted average index for the last 3 weeks of the current year) that compares the weighted average of the latest certain period of the year to be predicted with the 1st process for calculating the same week of the previous year) The second step to calculate the weighted average index for the last 3 weeks of the previous year, and
The third step of calculating the forecast index by multiplying the next week index and the correction value, the fourth step of obtaining the forecast index for each day of the week, multiplying it by the number of sales on the most recent day of the week, and summing it, and the past constant Number of safety stock days is calculated by multiplying the average sales value for the period by the set safety stock days U for each class
From the process (safety stock quantity Y = (sales quantity in the past fixed period W / stock days) * safety stock day quantity U by class) and these calculated values, (safety stock quantity Y + next week sales forecast quantity X)-(current stock quantity) V-the number of fluctuations in inventory after ordering), and the sixth step of ordering this value.

In the present invention, the safety stock quantity Y in the fifth step can also be calculated by Y = (average sale quantity / operating days) * (standard inventory days + safety inventory days).

Further, the automatic merchandise ordering apparatus of the present invention has an input means for inputting the standard inventory days U and the like, a storage means for storing the sales of each day of the previous year, and a forecast week as a target of the sales forecast. Corresponding to the previous week's same week's sales results for the previous year and the corresponding previous week's next week's sales results for the previous week, the previous year's index (the previous week's actual
Correction value (weighted average of the last 3 weeks of the current year) from the first arithmetic processing means for calculating the same week of the previous year), the weighted average of the most recent fixed period of the year to be predicted, and the weighted average of the corresponding corresponding week of the previous year Index / three most recent year weighted average index) second arithmetic processing means, third arithmetic processing means for multiplying the next week index and the correction value to calculate a predicted index, and a current storage Fourth arithmetic processing means for calculating the number of sales W (delivery date inventory number W = (current inventory V-period sales number)) by subtracting the number of period sales from ordering to delivery set from the number And a fifth arithmetic processing means for dividing the number of period sales by the number of period days to determine the average number of period sales X, and the number of delivery day inventory W divided by the average number of period sales X, and the delivery date inventory of the number of delivery date inventory Sixth arithmetic processing means for calculating the number of days and the set standard stock date And U, pulling the delivery date inventory days, inventory days gap Y (inventory days gap Y = U-
W) and a seventh arithmetic processing means for calculating an order quantity (period sales number + (stock days gap Y * average period sales number X)) by correcting the period sales number by the inventory days gap Y.
It is characterized in that the period sales quantity is a value obtained by multiplying the forecast index by the sales quantity on the most recent day of the week.

Further, the automatic merchandise ordering apparatus of the present invention has an input means for inputting the number of days of safety stock U and the like, a storage means for storing the sales of each day of the previous year, and a forecast week which is a target of the sales forecast. Corresponding to the previous week's same week's sales results for the previous year and the corresponding previous week's next week's sales results for the previous week, the previous year's index (the previous week's actual
Correction value (weighted average of the last 3 weeks of the current year) from the first arithmetic processing means for calculating the same week of the previous year), the weighted average of the most recent fixed period of the year to be predicted, and the weighted average of the corresponding corresponding week of the previous year Index / previous 3 weeks weighted average index) second arithmetic processing means, third arithmetic processing means for multiplying the next week index and the correction value, and calculating a prediction index, and the prediction An index is calculated for each day of the week, multiplied by the number of sales on the most recent day of the week, and summed, and the set safety stock days U by class is set for the average sales value for the past certain period. Multiply, safety stock number Y (safety stock number Y
= (The number of sales in the past fixed period W / the number of days in stock) * the number of days of safety stock in class U) and the tenth arithmetic processing means, and from these calculated values, (the number of safety stock Y + the number of sales forecast next week X)
-(Current number of stocks V-Number of stock changes after order) is calculated to obtain the order quantity.

The automatic merchandise ordering device of the present invention is the first
The calculation of the safety stock number Y by the calculation processing unit of 0 is Y =
It is also possible to calculate by (average number of sold days / operating days) * (standard inventory days + safety inventory days).

[0027]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention constructed as described above
In the 1st process, the previous year's same week results, which are the sales results for the previous week corresponding to the forecast week that is the target of the sales forecast, and the corresponding sales results for the following week of the corresponding previous week, were compared. Compensation value that calculates the previous week's next week index (previous year's next week actual / previous year's same week actual) and compares the weighted average for the latest certain period of the year to be predicted with the corresponding weighted average for the same period of the previous year in the second process (The most recent 3 week weighted average index of the current year / the most recent 3 week weighted average index of the previous year) is calculated, and in the third step, the next week index is multiplied by the correction value to calculate the predicted index, and the predicted index and the latest index are calculated. The order quantity can be predicted from the actual value on each day of the week.

Further, the fixed period when the weighted average of the fixed period of the present invention is performed is March, and the order quantity can be predicted by multiplying the forecast index and the actual value of each latest day of the week.

Further, in the present invention, in the first step, the sales on each day of the previous week corresponding to the next day from the delivery date of the forecast corresponding order date to the delivery date of the next order are recorded, and in the second step, each of these sales is recorded. It is also possible to total the sales on the day of the week and use the total number of sales as the number of orders.

According to the present invention, if the corresponding day of the previous week is a store holiday and the predicted corresponding day is a business day, the sales are recorded if the week before the business day is the business day before, and the sales of the week before the last day are recorded. If the corresponding day is a store holiday, it is possible to count the sales on the day following the store holiday of the previous week.

Further, according to the present invention, when the corresponding day of the previous week is a business day and the predicted corresponding day is a store holiday, the sales can be zero.

Further, in the present invention, when the corresponding day of the previous week is a weekday and the predicted corresponding day is a holiday, the sales can be the sales of the most recent Sunday.

Further, according to the present invention, when the corresponding day of the previous week is a holiday and the predicted corresponding day is a weekday, the sales on the day after the holiday of the previous week (weekday) can be recorded.

In the case of the sales promotion period, the present invention is
The buyer predicts the number of sales that will increase during the sales promotion period, orders the increased amount separately, and either adds the remaining inventory during the sales promotion period to the number of stocks at the time of normal sales, or deducts the shortfall, and promotes the sales. For the period, it is possible to record sales on the same day of the previous week.

Further, according to the present invention, in the first step, the number of items sold during the period from the set order to the delivery is subtracted from the current inventory,
Calculate the number of sales W until the delivery date, and in the second step,
The period sales number is divided by the period days to determine the average period sales number X, and in the third process, the delivery day inventory number W is set to the period average sales number X.
Divide by to calculate the number of days to deliver and the number of days to deliver
In the process, the set standard inventory days U and the delivery day inventory days are subtracted to calculate the inventory days gap Y, and in the fifth process, the period sales quantity is corrected by the inventory days gap Y to calculate the order quantity. You can also

Further, in the present invention, when the stock is 0, it is possible to use the results of the previous week or the same day of the previous week.

Further, the number of products sold in a period according to the present invention is defined in claims 1 to 8.
It is also possible to use the order quantity calculated in.

In the present invention, the predictive index is calculated for each day of the week in the fourth step, multiplied by the number of sales on the most recent day of the week, and summed up. In the fifth step, the average sales value in the past fixed period is calculated. , Multiply the set safety stock days U by class,
The safety stock quantity is calculated, and in the sixth step, (safety stock quantity Y + next week sales forecast quantity X) − (current stock quantity V−stock fluctuation quantity after order) is calculated, and this value is ordered. It can also be a quantity.

According to the present invention, the safety stock quantity Y in the fifth step can also be calculated by Y = (average number of sold days / operating days) * (standard inventory days + safety inventory days).

Further, in the automatic merchandise ordering apparatus of the present invention, the input means inputs the standard inventory days U and the like, the storage means stores the sales of each day of the previous year, and the first arithmetic processing means makes the sales forecast. From the same week last year that is the sales result for the previous week corresponding to the forecast week that is subject to the above, and the previous week next week that is the sales result for the corresponding week of the previous year. The second arithmetic processing unit calculates the correction value (weighted for the last three weeks of the current year) from the weighted average of the predicted latest fixed period of the year and the weighted average of the corresponding corresponding week of the previous year. Average index / weighted average index of the last 3 weeks of the previous year), the third calculation processing means multiplies the next week index and the correction value to calculate a prediction index, and the fourth calculation processing means calculates the current stock. From the number of items set to the period from ordering to delivery And the fifth arithmetic processing unit divides the number of period sales by the number of period days to determine the average number of period sales X, and the sixth arithmetic processing unit determines the number of delivery date stock W Is divided by the period average sales number X to calculate the delivery date inventory days of the delivery date inventory number, and the seventh arithmetic processing means subtracts the set standard inventory days U from the delivery date inventory days,
The eighth calculation processing means calculates the inventory days gap Y, and
The order sales quantity can be calculated by correcting the period sales quantity by the inventory day gap Y, and the ninth arithmetic processing means can set the period sales quantity to a value obtained by multiplying the forecast index by the sales quantity of the nearest day of the week.

Further, in the automatic merchandise ordering apparatus of the present invention, the input means inputs the safety stock days U, etc., and the ninth arithmetic processing means obtains the forecast index for each day of the week, and obtains the sales number of the most recent day of the week. The tenth arithmetic processing means calculates the safety stock quantity Y by multiplying the sales average value in the past fixed period by the set safety stock days U, and the eleventh arithmetic processing means. However, from these calculated values, (safety stock quantity Y + next week sales forecast quantity X)-(current stock quantity V-post-order inventory fluctuation quantity) is calculated as the order quantity.

The automatic merchandise ordering device of the present invention is the first
The calculation of the safety stock number Y by the calculation processing unit of 0 is Y =
It is also possible to calculate by (average number of sales / days of operation) * (standard number of days of inventory + number of days of safety inventory).

[0043]

[Calculation of sales forecast]

Here, the calculation of the sales forecast number will be described.

[Prediction index setting date]

First, the timing for automatically setting the prediction index will be described. As shown in the figure, daily closing processing is performed on the last day of each week, Sunday is usually set, and then this forecast data is used for one week.

The prediction index can always be changed.

First, the result of the previous year corresponding to the predicted week and the result of the next week of the previous year are compared to calculate the previous week's index.

Previous year's next week index = (previous year's next week result / previous year's same week result) ... Formula 1

That is, the previous year's next week index is an index of how the index fluctuates during the same period of the previous year.

Then, in order to take into consideration the change in the current year, the weighted average of the latest 3 weeks of the current year and the weighted average of the same period of the previous year (the latest 3 weeks of the previous year) are compared to obtain a correction value.

Correction value = weighted average index for the last 3 weeks of the current year / weighted average index of 3 weeks for the previous year ... Formula 2

Furthermore, the predicted index can be calculated from the previous week's index of the first formula and the correction value of the second formula.

Prediction index = previous week's week index * correction value ... Formula 3

The actual number of orders can be determined from the prediction index of the third formula and the actual value of each day of the week immediately before the order date.

(A) "Sales discount type automatic ordering"

Sales-subscription type automatic ordering is for stores that are often used in small and medium-sized retail chains and cannot manage individual items, by omitting the logic of "sales forecast type automatic ordering" and the appropriate stock check function by checking "standard inventory days". It is simple and can be operated at low cost, and the conventional method is a method with significantly improved accuracy. The order quantity this time is determined based on the order and delivery pattern of each product with respect to securing the inventory. In addition, the order quantity to be secured is set by adjusting the various variable factors by the sales results of the most recent days from the day following the delivery date for this order until the delivery date for the next order, When the total value of the set sales numbers is the number of order lots, the rounded value is set as the order number.

In this case, whether the order is rounded every time,
On the contrary, in order to prevent over-ordering by rounding up, the balance is maintained by carrying over the rounding up / down of the second order calculation.

For example, there is a sales record as shown in FIG.
If the number of displays at the start is 400, if Monday ordering, Wednesday delivery,

Orders = Total sales of the previous week from Monday to Sunday = 20 + 10 + 30 + 35 + 40 + 60 + 80 = 275

Is obtained.

Furthermore, Monday order, Wednesday delivery, Thursday order,
When ordering twice a week for Saturday delivery, as shown in Figure 2,

Monday Orders = "Sales" on Thursday, Friday and Saturday = 3
5 + 40 + 60 = 135 pieces Thursday's order quantity = day to “sales quantity” = 80 + 20 + 10 +
30 = 140.

[Calendar adjustment]

Here, the calendar adjustment will be described.

That is, when a store holiday or a holiday is entered in the next week, the past performance is automatically corrected if it is different from the past week on the same day.

(1) When the previous week is a store holiday and this week is a business day

As shown in FIG. 3, if the week before last is a business day, the result is substituted, and if it is a store holiday, the result of the day after the store holiday of the previous week is substituted.

That is, if the last two business days is a business day, the number is 20, and if it is a store holiday, the number 25, which is the result of the previous Wednesday, is adopted.

(2) When the previous week is a business day and this week is a store holiday

As shown in FIG. 4, zero is substituted.

(3) When the previous week is a weekday and this week is a holiday

As shown in FIG. 5, when the previous week is a weekday and this week is a holiday, the actual results of the latest Sunday are substituted.

(4) When the previous week is a holiday and this week is a weekday

As shown in FIG. 6, if the week before last is a weekday, the result is adopted, and if it is a holiday or a store holiday, the result on the day after the holiday of the previous week (weekday) is adopted.

That is, if the week before the second week is a weekday, 20 pieces are adopted, and if it is a holiday or a store holiday, 25 pieces on Thursday, which is the next day (weekday) of the holiday, is adopted.

“Lot rounding”

Fractions with respect to the included number are rounded off. That is, if the number of pieces is 12,

When the number of orders = 27, 27-12 * 2
= 3 (carry over next time), round down, order 24 pieces,

When the number of orders = 29, 29-12 * 2
Round up to 5 (carry over next time) and order 36 pieces.

[Correction at the time of sales promotion]

In the case of the sales promotion period, the buyer predicts the increased number of sales in the sales promotion period, orders the increased amount separately, and adds the remaining inventory of the sales promotion period to the number of stocks at the time of normal sales. Alternatively, the shortfall can be deducted, and the sales promotion period can be recorded as sales on the same day of the previous week.

That is, as shown in FIG. 7, the proper inventory is 1
In the case of 00 pieces and the special sale order is 30, the sales exceeding 30 pieces are subtracted from the proper inventory from the second day when the special sale inventory is exhausted.

When the special sale comes in the previous week, the actual result of the previous week is replaced.

"Proper inventory"

This "sales-based automatic ordering" system always returns to the first stock based on the stock quantity at the time of system start. Through analysis, an appropriate inventory display quantity report is output every month, which complements the forecast type and inventory rotation type functions.

(B) "Inventory rotation type automatic ordering"

The inventory rotation type automatic ordering is a system in which a step of correcting a gap between the sales discount type automatic ordering and the standard stock days set in advance for each product is added, and the step of predicting from the "prediction type" is omitted. It was done.

First, the number of items sold from the current inventory to the time of delivery from the set order is subtracted, and the number of items sold until the date of delivery is calculated. That is, as shown in FIG.

Inventory on delivery date W = current inventory V−number of items sold per period ··· Formula 4

In the example of FIG. 8, the number of inventory changes after ordering =
A + B + C

Period sales = D + E + F

Next, the period sales number is divided by the period days to determine the period average sales number.

Average number of sales in period X = (D + E + F) / 3 ... Formula 5

Further, the delivery day inventory quantity W of the fourth formula is divided by the period average sales quantity X to calculate the delivery day inventory quantity of the delivery date inventory quantity.

Then, the standard inventory days U set for each line and the delivery date inventory days of the fourth formula are subtracted to calculate the inventory days gap.

Inventory Days Gap Y = U−W ··· Formula 6

Regarding the number of orders, the period sales number is corrected by the inventory days gap, the inventory rotation type order number is calculated, and the rounded value is set as the order number.

Number of orders = number of sales per period + (gap in inventory days * average number of sales per period)

That is, in this embodiment,

Order quantity = (D + E + F) + (Y * X)

It becomes

Note that the number of items sold per period = D + E + F can be calculated by the above-mentioned “sales discount type automatic ordering”.

Further, when the stock is 0, it is possible to use the results of the previous week or the same day of the previous week.

(C) "Sales forecast type automatic ordering"

The forecasted sales quantity is calculated using the forecasted values in which the previous year's results and trends and this year's trends are taken into consideration, and the ordering is performed in consideration of the safety stock days. This will be described with reference to FIG.

First, the previous week's next week index is calculated, and the predicted index shown in the third formula is calculated using the correction value of the second formula. Then, the latest weekly sales quantity is calculated by multiplying the latest daily sales quantity by the day-of-week forecast index and summing.

That is,

Next Week Sales Forecast Number = Sigma (Sales Number by Last Day of Week * Sales Forecast Index) ... Formula 7

Here, the prediction index of Monday is a, the prediction index of Tuesday is b ... The prediction index of Sunday is g,
Last Monday's sales is E, last Tuesday's sales is F, last Wednesday's sales is G, last Thursday's sales is A, last Friday's sales is B, last Saturday's sales If the number is C and the number of sales on the last Sunday is D,

Next week sales forecast X = (E * a) + (F *
b) + (G * c) + (A * d) + (B * e) + (C *
f) + (D * g)

The forecast index for this day of the week is adjusted on a weekly basis.

Next, the average number of sales in the past two weeks is multiplied by the safety stock days U set for each class to calculate the safety stock days.

Safety Stock Number = (Sales Number in Past Two Weeks / Inventory Days) * Safety Stock Days by Class ・ ・ ・ ・ ・ Equation 8

In the case of this embodiment, if the number of working days is 13,

Safety stock quantity Y = (Sales quantity W / 1 for the past two weeks)
3) * Safety inventory days U

Then, the number of orders is calculated from the current number V of stocks, the number Y of safety stocks, and the like.

Order quantity = (Safety stock quantity Y + Next week's sales forecast quantity X)-(Current stock quantity V-Number of stock fluctuations after order)

...... Formula 9

The safety stock number Y can be calculated by Y = (average number of sales / number of working days) * (reference number of days of inventory + safety number of days).

FIG. 10 shows an automatic commodity ordering apparatus 100000.
The input means 100 of the present embodiment is for inputting the standard inventory days U and the like, and the storage means 200.
But I remember the sales of each day of the previous year.

The first arithmetic processing means 1000 uses the same week last year's sales record, which is the sales record for the previous week corresponding to the forecast week subject to the sales forecast, and the sales record for the corresponding week's next week. The previous year's next week index (the previous year's next week result / the same year's same week result) is calculated from a certain previous year's next week result.

The second arithmetic processing means 2000 corrects the weighted average of the latest certain period of the year to be predicted and the weighted average of the corresponding corresponding week of the previous year (the most recent three-week weighted average index / the most recent previous year). 3 week weighted average index) is calculated.

The third arithmetic processing means 3000 is for multiplying the next-week index and the correction value to calculate the predicted index.

The fourth arithmetic processing means 4000 calculates the number of sales W in the period up to the delivery date by subtracting the number of inventory fluctuations after the ordering and the delivery date from the set period sales number and the current number of stocks. belongs to.

The fifth arithmetic processing means 5000 is for dividing the number of period sales by the number of period days to determine the average number X of period sales.

The sixth arithmetic processing means 6000 is for dividing the number of delivery days inventories W by the period average sales number X to calculate the number of delivery days inventory days of the number of delivery days inventory.

The seventh arithmetic processing means 7000 is for calculating the inventory day gap Y by subtracting the set standard inventory day U and delivery date inventory days.

The eighth calculation processing means 8000 is for calculating the order quantity by correcting the period sales quantity by the inventory day gap Y.

The order quantity can be calculated by performing the calculation by the method of "stock-turning type automatic ordering" described above. In addition,
First arithmetic processing means 1000 to ninth arithmetic processing means 90
Up to 00, it can also be executed by one electronic computer.

FIG. 11 shows an automatic merchandise ordering device 200,000.
The input means 100 of the present embodiment is for inputting the safety stock days U and the like, and the storage means 200.
But I remember the sales of each day of the previous year.

The ninth arithmetic processing means 9000 is for obtaining a prediction index for each day of the week and multiplying it by the number of sales of the most recent day of the week and summing them.

The tenth arithmetic processing means 10000 calculates the safety stock number Y by multiplying the average sales value in the past fixed period by the set safety stock days U.

The eleventh arithmetic processing means 11000 calculates (the number of safety stock Y + the number of sales forecast next week X) from these calculated values.
This is for calculating − (current stock number V−number of inventory fluctuations after order) to calculate the order quantity.

The order quantity can be calculated by performing the calculation by the method of "sales forecast type automatic order" described above. In addition,
First arithmetic processing means 1000 to eleventh arithmetic processing means 1
Up to 1000 can be executed by one electronic computer.

Incidentally, the first arithmetic processing means 1000 to the third
The automatic merchandise ordering apparatus 10 up to the calculation processing means 3000
The description is omitted because it is the same as 0000.

The automatic merchandise ordering apparatus 100000 and the automatic merchandise ordering apparatus 200000 can also automatically transmit the calculated order quantity to the supplier through the communication line.

[0138]

[Effect] According to the present invention configured as described above, the sales result of the same week of the previous year corresponding to the forecast week which is the target of the sales forecast and the sales amount of the corresponding week of the previous year corresponding to the same week. The 1st process that calculates the previous year's next week index (the previous year's next week result / the previous year's same week result) that compares the actual results of the previous year's next week, the weighted average of the latest certain period of the year to be predicted, and the corresponding same week of the previous year The second step of calculating a correction value (weighted average index of the last 3 weeks of the current year / weighted average index of the last 3 weeks of the previous year) by comparing the weighted averages of the second step and the second step of calculating the prediction index by multiplying the next week index and the correction value It has a structure that predicts the order quantity from three processes, this forecast index, and the actual value of each latest day of the week, so that the order quantity can be adjusted to seasonal changes and sales trends without relying on field workers. Good inventory efficiency, and not out of stock There is an effect that it is possible to determine the optimum order quantity.

Then, according to the present invention, the first step (the delivery date inventory number W = the delivery date inventory number W = is calculated by subtracting the period sales number from the set order to the delivery to the delivery date) from the current inventory.
(Current inventory V-number of period sales) and the number of period sales divided by the number of period days to determine the average period sales number X, and the delivery date inventory number W divided by the average period sales number X to obtain the delivery date inventory Number of days of delivery, the third step of calculating the number of days of inventory, the set standard number of days of inventory U, and the number of days of inventory of the date of delivery are subtracted, and the fourth step of calculating the number of days of inventory gap Y (the number of days of inventory gap Y = U− W) and the period sales quantity are corrected by the inventory days gap Y to calculate the order quantity (period sales quantity + (inventory days gap Y * period average sales quantity X).
The product lineup is automatically modified for each store, and a store with optimal products can be realized.

The present invention also obtains a prediction index for each day of the week predicted for each week and multiplies it by the number of sales of the most recent day of the week,
Fifth step of calculating the safety stock quantity by multiplying the fourth step to sum up and the average sales value in the past constant time period by the set safety stock days U by class (safety stock quantity Y = (past constant time period Sales quantity W / stock days) * Safety stock days by class U), and from these calculated values, (safety stock quantity Y + next week forecast sales quantity X)-(current stock quantity V-stock fluctuation quantity after order) is calculated. Since this value consists of the sixth step of ordering in conjunction with the EOS system and the like, there is an outstanding effect that the work of the on-site staff can be completely labor-saving and a significant cost reduction can be achieved.

[0141]

[Brief description of drawings]

FIG. 1 is a diagram for explaining sales-based automatic ordering.

FIG. 2 is a diagram for explaining sales-based automatic ordering.

FIG. 3 is a diagram illustrating calendar adjustment.

FIG. 4 is a diagram illustrating calendar adjustment.

FIG. 5 is a diagram illustrating calendar adjustment.

FIG. 6 is a diagram illustrating calendar adjustment.

FIG. 7 is a diagram illustrating adjustment during sales promotion.

FIG. 8 is a diagram illustrating an inventory revolving type automatic order.

FIG. 9 is a diagram illustrating sales forecast type automatic ordering.

FIG. 10 is a diagram showing a configuration of an automatic product ordering device 100000.

FIG. 11 is a diagram showing a configuration of an automatic product ordering device 200000.

[Explanation of symbols]

 100000 Automatic commodity ordering apparatus 200000 Automatic commodity ordering apparatus 100 Input means 200 Storage means 1000 First arithmetic processing means 2000 Second arithmetic processing means 3000 Third arithmetic processing means 4000 Fourth arithmetic processing means 5000 Fifth arithmetic processing Means 6000 6th arithmetic processing means 7000 7th arithmetic processing means 8000 8th arithmetic processing means 9000 9th arithmetic processing means 10000 10th arithmetic processing means 11000 11th arithmetic processing means

Claims (16)

[Claims] [Claim 1] The same week previous year sales results corresponding to the forecast week that is the target of the sales forecast and the corresponding previous week next year sales results corresponding to the corresponding previous week are compared. Last week's index (previous week's results / previous week's results)
Compensated value comparing the weighted average of the first certain period of the year for which the calculation is performed and the weighted average of the latest certain period of the year predicted, and the weighted average of the corresponding week of the same period of the previous year Predict the order quantity from the second step of calculating the average index), the third step of calculating the forecast index by multiplying the next week index and the correction value, the forecast index, and the actual value of each latest day of the week Automatic product ordering system. 2. The automatic order according to claim 1, wherein the fixed period when performing the weighted average of the fixed period is March, and the order quantity is predicted by multiplying the forecast index by the actual value of each latest day of the week. Product ordering system. [Claim 3] The first step of recording the sales on each day of the previous week corresponding to the day after the delivery date of the forecast corresponding order date to the delivery date of the next order, and the sum of the sales on each of these days, and the total is obtained. An automatic merchandise ordering system consisting of a second process in which the number of sales is the number of orders. 4. In the first step, if the corresponding day of the previous week is a store holiday and the predicted corresponding day is a business day, the sales are recorded if the week before the second day is a business day, and the sales are recorded before and after. 4. The automatic product ordering system according to claim 3, wherein if the corresponding day of the week is a store holiday, the sales of the day following the store holiday of the previous week are recorded. 5. The automatic merchandise ordering system according to claim 3, wherein, in the first step, when the corresponding day of the previous week is a business day and the predicted corresponding day is a store holiday, the sales are zero. 6. The automatic merchandise ordering system according to claim 3, wherein, in the first step, if the corresponding day of the previous week is a weekday and the predicted corresponding day is a holiday, the sales are the sales of the most recent Sunday. 7. The automatic product according to claim 3, wherein in the first step, if the corresponding day of the previous week is a holiday and the predicted corresponding day is a weekday, the sales on the day following the holiday of the previous week (weekday) are recorded. Ordering system. 8. In the case of a sales promotion period separately, the buyer predicts the increased number of sales during the sales promotion period, orders the increased amount separately, and compares the sales amount of the above-mentioned sales promotion period with the stock number at the time of normal sales. 8. The automatic product ordering system according to claim 3, wherein the remaining inventory is added or the shortage is deducted, and sales are recorded on the same day of the previous week during the sales promotion period. 9. The number of sales W from the current inventory to the delivery date by subtracting the number of sales from the set order to delivery.
And the second step of determining the period average sales number X by dividing the period sales number by the period days, and the delivery date inventory number. W is divided by the period average sales number X to calculate the delivery day inventory days of the delivery day inventory number, the set standard inventory days U and the delivery date inventory days are subtracted, and the inventory day gap Y is calculated.
4th step of calculating (gap of inventory days Y = U−W)
And an automatic product ordering system that calculates the order quantity (period sales number + (stock days gap Y * average period sales number X)) by correcting the period sales number by the inventory days gap Y. 10. The automatic merchandise ordering system according to claim 9, wherein when the stock due to the out of stock is 0, it is transferred to the sales record of the previous week or the same day of the previous week. 11. The automatic merchandise ordering system according to claim 9, wherein the order sales quantity calculated in any one of claims 1 to 8 is used as the period sales quantity. 12. The sales result of the same week of the previous year corresponding to the forecast week which is the target of the sales forecast is compared with the sales result of the corresponding week of the previous week corresponding to the same week of the previous year. Correction value that compares the 1st process to calculate the previous week's next week index (the previous year's next week result / the previous year's same week result), the weighted average for the latest certain period of the year to be predicted, and the weighted average for the corresponding corresponding week of the previous year ( The second step of calculating the weighted average index of the last 3 weeks of the current year / the weighted average index of 3 weeks of the previous year) and the third step of calculating the prediction index by multiplying the index of the next week and the correction value, and for each day of the week Calculate the forecast index, multiply it by the number of sales on the most recent day of the week, and add up the fourth step, and the average sales value for the past certain period by the set safety stock days U by class to obtain the safety stock number. Fifth step to calculate (safety stock quantity Y = (constant in the past Period sales number W / stock days) * Safety stock days by class U), and from these calculated values, calculate (Safety stock number Y + Sales forecast for next week X)-(Current stock number V-Stock fluctuation after ordering) Then, an automatic product ordering system consisting of a sixth step of ordering this value. 13. The calculation of the safety stock quantity Y in the fifth step is Y
13. The automatic merchandise ordering system according to claim 12, which is calculated by: (average number of sales / number of working days) * (standard number of days of inventory + number of days of safety inventory). 14. An input means for inputting a standard inventory days U, a storage means for storing sales of each day of the previous year, and a week of the previous year corresponding to a forecast week which is a target of sales forecast. The previous year's next week index (the previous year's previous week result / the previous year's same week result) is calculated from the previous year's same week's sales result and the corresponding previous year's next week's next week's sales result.
Corrected value from the weighted average of the latest certain period of the year to be predicted and the weighted average of the corresponding corresponding weeks of the previous year (the most recent 3 week weighted average index of the current year / the most recent 3 week weighted average index of the previous year) A second calculation processing means for calculating, a third calculation processing means for calculating the forecast index by multiplying the next-week index and the correction value, and a period sale from the current stock to the set order to delivery. Decrease the number and sell W for the period up to the delivery date (delivery date inventory number W = current inventory V-period sale number)
And a fifth arithmetic processing means for determining the period average number of sales X by dividing the period sales number by the period average number of days, and the delivery date inventory number W divided by the period average number of sales X. The sixth arithmetic processing means for calculating the delivery day inventory number of the delivery date inventory number, the set standard inventory days U and the delivery date inventory days are subtracted to obtain the inventory day gap Y (inventory day gap Y = U -W) and a seventh arithmetic processing means for calculating the order quantity (period sales number + (stock days gap Y * period average sales number X)) by correcting the period sales number with the inventory days gap Y An automatic commodity ordering device, comprising: the calculation processing means of (1), and the period sales quantity is a value obtained by multiplying the forecast index by the sales quantity of the nearest day of the week. 15. An input means for inputting the safety stock days U and the like, a storage means for storing the sales of each day of the previous year, and a week of the previous year corresponding to a forecast week which is a target of sales forecast. The previous year's next week index (the previous year's previous week result / the previous year's same week result) is calculated from the previous year's same week's sales result and the corresponding previous year's next week's next week's sales result.
Correction value (weighted average index for the last 3 weeks of the current year / weighted average index of the last 3 weeks of the previous year) from the weighted average of the most recent fixed period of the predicted year and the weighted average of the corresponding corresponding weeks of the previous year And a third arithmetic processing means for calculating the prediction index by multiplying the next-week index and the correction value, and the prediction index for each day of the week. The ninth arithmetic processing means for multiplying by the number of sales on the day of the week and summing up, and the average sales value for the past certain period,
The tenth arithmetic processing for calculating the safety stock quantity Y (safety stock quantity Y = (number of sales in past fixed period W / stock day quantity) * safety stock day quantity U by class U) by multiplying the set safety stock day quantity U by class From the means and these calculated values,
An automatic merchandise ordering device including an eleventh arithmetic processing means that calculates + the next week's sales forecast number X)-(current stock number V-number of inventory changes after ordering) to obtain an order quantity. 16. The automatic calculation according to claim 15, wherein the calculation of the safety stock quantity Y by the tenth calculation processing means is carried out by Y = (average number of sales / operating days) * (reference stock days + safe stock days) Product ordering device.