Consignment quantity setting device and consignment quantity setting method for products used in call sales

There are provided a consignment quantity setting device and a consignment quantity setting method for products used in call sales that enable an appropriate consignment quantity to be set without relying on the intuition and experience of the salesperson. A periodic factor index that shows a trend of an increasing or decreasing quantity of consumption of a product in each period is stored in advance in a storage means 12 and the quantity of the product consumed by each customer is input using an input means 11 and stored in the storage means 12 . Average consumed quantity calculation means 13 acquires the quantity of the product consumed from the storage means 12 , calculates the average quantity of the product consumed by all customers and stores it in the storage means 12 . Consumption history index calculation means 14 acquires the quantity of the product consumed from the storage means 12 , calculates a consumption history index showing the quantity of the product consumed in the past in each period and stores this in the storage means 12 . A consignment quantity calculation means 15 acquires the average consumed quantity, the periodic factor index, and the consumption history index and calculates the quantity to be consigned for the current period relative to the quantity consigned for the previous period. The calculated quantity to be consigned for the current period is output using an output means 16 .

DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 1 is a schematic view of a business management system used in the field of call sales in an embodiment of the present invention; FIG. 2 is block diagram showing the consignment amount setting function of a host computer shown in FIG. 1 ; and FIG. 3 is a flow chart showing the processing of the business management system of FIG. 1 . As is shown in FIG. 1, a host computer (referred to below as “HC”) 2 for data tabulation analysis and a personal computer (referred to below as “PC”) 3 connected to the host computer 2 for data communication are installed in a head office 1 . The PC 3 is also installed in each sales office 4 and each sales person 5 carries a portable input/output terminal (referred to below as “HT”) 6 . The salesperson 5 inputs and records on the HT 6 all data relating to a customer 7 serving as the client such as data on the customer and data on the products consigned to that customer. Tabulation analysis is performed when the customer data and consigned product data recorded in the HT 6 are sent to the PC 3 . At this time, a telephone line, infrared communication, a PC card, or the like may be used for the means of communication between the HT 6 , and the PC 3 and a data file transfer is performed using these means. The customer data includes an area code, the customer's name, the customer's address, the call cycle, the date of the previous call, the days when the customer stays, the times when the customer stays, a residential map page, the previous credit balance, a record of the sales, the total sales amount, the amount recovered, the current credit balance, the date of the next payment collection, the clinical history, and the like. The consigned product data includes product names, regular prices of the product, product efficacy, names of the manufacturers, selling prices, discount prices, customer stock, limits on the time the product is left with the customer, instructions of consigned product items and quantity, salesperson stock items, salesperson stock numerical quantities, limits on expiry dates, total prices, and the like. The salesperson 5 calls on the customer in accordance with the call cycle of each customer. When the task of calling on the customer 7 is ended, the salesperson 5 sends the customer data and consigned product data input into the HT 6 to the PC 3 (step S 101 ). When the salesperson 5 is out, the day's transaction data may be transmitted from the HT 6 to the PC 3 by sending the data directly to the PC 3 by PC communication using a telephone line from the HT 6 carried by the salesperson 5 . The customer data and consigned product data sent to the PC 3 are tabulated by the PC 3 (step S 102 ), and the tabulated data is sent to the HC 2 (step S 103 ). In FIG. 2 , the HC 2 is provided with an input means 11 for inputting tabulated data sent from the PC 3 , a storage means 12 for storing inputted tabulated data and calculation results and the like, an average consumed quantity calculation means 13 for calculating the average quantity of a particular product consumed by all customers based on the tabulated data stored in the storage means 12 , a consumption history index calculation means 14 for calculating a consumption history index for a particular product based on the tabulated data stored in the storage means 12 , a consignment quantity calculation means 15 for calculating the amount of a product to be consigned based on the results of the calculation and tabulated data stored in the storage means 12 and the like, and an output means 16 for outputting the results of the calculations and tabulated data stored in the storage means 12 and the like to the PC 3 and printer 8 and the like. The tabulated data sent from the PC 3 is input using the input means 11 and stored in the storage means 12 (step S 104 ). The tabulated data stored in the storage means 12 include the call cycle of a customer and the quantity of each product consumed until a customer is called. The average consumed quantity calculation means 13 acquires the consumed quantities of each product that are stored in the storage means 12 , calculates the average consumed quantity of each product by all customers, and stores the respective calculated average consumed quantities in the storage means 12 (step S 105 ). Examples of the quantity of each product consumed by each customer until the customer is called on and of the average consumed quantity calculated by the average consumed quantity calculation means 13 are shown in Table 1. Here, the average consumed quantity calculation means 13 rounds up decimals of the calculated average consumed quantity to the next whole number. 1 TABLE 1 PRODUCT PRODUCT PRODUCT CALL A B C CYCLE CUSTOMER X 1 1 2 3 MONTHS CUSTOMER Y 1 2 2 3 MONTHS CUSTOMER Z 1 3 3 6 MONTHS AVERAGE 1 2 3 — QUANTITY CONSUMED A periodic factor index showing the trend of the increase or decrease in the quantity of consumption of each product per period is stored in advance in the storage means 12 . In the present embodiment, the period is the call cycle at which the salesperson 5 calls on the customer and the periodic factor index at this time is shown as a rate of increase or decrease determined from the quantity of each product consumed in the same period of previous years. For example, if the call cycle for a customer is 3 months and the current visit is in Jun., the periodic factor index is found by dividing the quantity consumed at the time of the Sep. call of the previous year by the quantity consumed at the time of the Jun. call of the previous year. Examples of the periodic factor index and the quantity consumed of a particular product for respective past periods are shown in Table 2. 2 TABLE 2 PERIOD OCT-DEC JAN-MAR APR-JUN JUL-SEP QUANTITY 4 2 1 4 CONSUMED PERIODIC 0.5 0.5 4.0 1.0 FACTOR INDEX The consumption history index calculation means 14 acquires the quantity of each product consumed by each customer from the storage means 12 and calculates a consumption history index showing the quantities of those products consumed in each period in the past. The calculated consumption history index is then stored in the storage means 12 (step S 106 ). The consumption history index is determined from the ratio of the sum quantity of the product consumed in the past to the total number of periods, namely, from the average of the quantity of the product consumed in the past. For example, if the sum quantity of a particular product consumed by a particular customer is a, if the number of the periods needed for consuming the product a is b, and if the quantity consumed in the previous period is c, then the average of the quantity of the product consumed in the past is a/b. The consumption history index at this time is found by c/(a/b). When c&equals;0, then c is taken as &equals;1. The consignment quantity calculation means 15 acquires the quantity of a particular product consigned for the previous period (in the present embodiment this is the time of the previous call) from the storage means 12 as well as the average quantity consumed, the periodic factor index, and the consumption history index and calculates the consignment quantity for the current period from the consignment quantity for the previous period using the following formula. The calculated consignment quantity is then stored in the storage means 12 (step S 107 ). current consignment quantity&equals;previous consignment quantity×average quantity consumed×periodic factor index ×consumption history index FIG. 4 shows an example where a current consignment quantity calculated by the consignment quantity calculation means 15 is output to the HT 6 by the output means 16 (step S 108 ) As is shown in FIG. 4, a product name 21 , a quantity consigned for the previous period 22 , a quantity consumed in the previous period 23 , and a consignment quantity for the current period 24 for each product are displayed on the HT 6 . On the right side thereof is displayed the consumed quantity history 25 of each product up to two periods before. As described above, based on the call cycle, by inputting the quantities of each product consumed at the time a salesperson calls on a customer into the HT 6 on each occasion and sending them to the PC 3 and HC 2 and inputting and accumulating them, and by calculating both the average quantity consumed by all customers of the products and the consumption history index for the products from these accumulated quantities of product consumed and matching them with a periodic factor index set in advance and by then calculating the consignment quantity for the current period from the consignment quantity for previous periods, it is possible to set a suitable consignment quantity that is estimated not only from the consumption quantities of a product by each customer, but also from the consumption trends of that product by all customers and that does not rely on the intuition and experience of the salesperson. Moreover, in the present embodiment, by adding a periodic factor index determined from the rate of increase or decrease in the quantity consumed in the same period in the past to the consignment quantity parameters, it is possible to obtain an even more appropriate consignment quantity for products such as those whose consumption quantities tend to change with the seasons such as between summer and winter. Furthermore, by adding a consumption history index determined from the average of past quantities of a product consumed to the consignment quantity parameters, it is possible to obtain an even more appropriate consignment quantity that has estimated based on also long term trends in consumption of the product. While the preferred form of the present invention has been described, it is to be understood that modifications will be apparent to those skilled in the art without departing from the spirit of the invention. The scope of the invention, therefore, is to be determined solely by the following claims.