JPH04168565A - Causal data analyzing and display device - Google Patents

Abstract

PURPOSE:To quicken the correspondence and to shorten the training period by coloring and instructing the meaning of a data value and the measure to be coped with. CONSTITUTION:A file read processing part 12 retrieves an analysis request information file 16 by using a commodity code inputted to an input device 11 as a key, and retrieves and read in a prescribed value information file 17 by a prescribed value item code of obtained analytic information. Based on a total sales amount of one day of the analytic information file from the processing part 12, an arithmetic processing part 13 calculates an elongation percentage of the sales amount by the causal, compares it with a prescribed value from the processing part 12, and a designator being smaller than or equal to the elongation percentage is determined by a numerical value decision processing part 14. By the designator obtained by the processing part 14, a color to be colored is determined by a processing part 15 and coloring is executed to a coloring position of prescribed value information obtained by the processing part 12 and it is outputted to an output device 18. In such a way, the correspondence is quickened and the training period can be shortened.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a POS data analysis system, and more particularly to a causal data analysis and display device for analyzing the correlation between cogels (sales characteristic factors) and sales.

[Conventional technology]

Conventionally, causal data analysis has involved simply displaying numerical values collected by a computer on a CRT or printer.

[Problem to be solved by the invention]

The conventional causal data analysis and display devices mentioned above simply display the collected data, so it is important to clarify the correlation between Kogels and sales, and to use cogels that can be consciously manipulated (for example, value In many cases, it is not clear how to utilize causal data, and it is often not clear how to use causal data. The disadvantage is that it is left up to individual judgment, making it difficult to take specific actions to improve sales.

[Means to solve the problem]

The causal data analysis device of the present invention includes a specified value information storage means that stores knowledge necessary for analysis as a specified value, and performs arithmetic processing based on data in a causal data analysis request information file and compares it with the specified value to make a determination. a numerical determination means for
and numerical coloring display means for coloring and displaying data based on the determination result.

〔Example〕

Next, the present invention will be explained with reference to the drawings.

FIG. 1 is a block diagram of an embodiment of the present invention. In the figure, the input device 11 is a keyboard or optical reader for inputting product codes, etc., the analysis request information file 16 is a file device for storing analysis request information, and the specified value information file 17 is a file device for storing specified value information. be.

The file read processing unit 12 searches the analysis request information file 16 using the product code inputted with the input device 11 as a key, reads the analysis request information of the product, and further specifies the specified value item code of the acquired analysis request information. The value information file 17 is searched and its standard value information is read.

The arithmetic processing section 13 calculates the growth rate of the sales amount due to Kogel based on the total sales amount for one day of the analysis request information file acquired by the file read processing section 12.

The numerical determination processing unit 14 compares the growth rate of sales amount due to causal presence calculated by the calculation processing unit 13 with the specified value (N) of the specified value information acquired by the file read processing unit 12, and determines the growth rate of sales amount due to cogel. An indicator N=1 to 5 that satisfies ≧specified value (N>) is determined.

The coloring processing unit 15 determines the color (N) to be colored based on the indicator N acquired by the numerical determination processing unit 14, and colors the position to be colored in the specified value information acquired by the file read processing unit 12, Output to the output device 18.

The output device 18 is a display and a printer for outputting the causal data analysis results.

The default value information change setting unit 19 registers and changes the default value information, and stores the registered value information in the default value information file 17.

Figure 2 is an explanatory diagram showing the format of the analysis request information file 16.S In the same figure, analysis request fixed information includes product code (code for searching analysis request information), day of the week, default value item code, causal item code, product Analysis request fluctuation information includes the daily sales total, sales amount by time zone, and sales points.This analysis request fluctuation information is aggregated based on past performance. This is the value.

FIG. 3 is an explanatory diagram showing the format of the specified value information file 17. In the figure, the default value information includes a default value item code (a code for searching for default value information), a default value item name, and default values (1) to (5).

These pieces of information, including each item of coloring colors (1) to (5) and nine coloring positions, are input from the default value information change setting section 19.

FIG. 4 is a flowchart showing the operation of the above causal data analysis and display device.

In the figure, when a product code, etc. is input from the input device 11 (step 21), the corresponding analysis request information is searched from the analysis request information file 16 based on this (step 22), and the regulations of the acquired analysis request information are The corresponding standard value information is searched from the standard value information file 17 using the value item code (step 23).

Next, calculate the growth rate of the sales amount due to the presence or absence of causality from the total sales amount of the day in the analysis request information obtained earlier (step 24), and calculate the growth rate of the sales amount and the specified value (N) obtained earlier. Compare and pick out indicators N = 1 to 5 for which the growth rate of sales amount by Kogel ≧ the specified value (N) (if N>5, there is no color to be colored), and determine the color (N) to be colored (Step 25 .26>. Then, coloring is performed on the colored position in the specified value information file 17 (step 27).Furthermore, based on the contents of the analysis request information file 16, the name of the analysis fixed information and the sales amount 1 of the analysis fluctuation information The score is displayed or printed as an analysis result on the display or printer of the output device 18 (step 28), and the process returns to step 21 for the next causal analysis.

FIG. 5 is an explanatory diagram showing an example of printing the analysis results of the above causal data analysis device. In the same figure, the number of sales points is 1. Cumulative sales 1 is a value output based on past performance data that does not have any sales factors, and sales points 2. Cumulative sales 2 is a value that is pressured based on past performance data that has a sales factor due to discount sales (which were held throughout the day). As the diagram shows, the company has succeeded in achieving its budget and increasing sales due to the sales factor of discount sales, but it cannot be said that specific actions to improve sales have been taken. Therefore, from the analysis results, we can immediately know whether or not this Kogel is effective or not, based on the color of the Kosal name.
This product has a time sale (for example, 11:00
It can be easily seen that sales will further improve if discount sales are carried out between the hours of 13:00 and 16:00 to 19:00.

〔Effect of the invention〕

As explained above, the present invention analyzes a huge amount of causal data collected through computerization, and by coloring and instructing what the data values mean and how to deal with them, Clarification of the correlation between sales and sales, as well as an effective and efficient way to increase sales by manipulating Kogels that can be operated consciously from the standpoint of individual retailers among various Kogels. It has the effect of being able to know and take concrete actions. In addition, even those with little experience can gain the valuable skills (know-how) of experienced people, which has the effect of speeding up responses and shortening the training period.

[Brief explanation of drawings]

Figure 1 is a configuration diagram showing an embodiment of the present invention, Figure 2 is an explanatory diagram showing the contents of the analysis request information file, Figure 3 is an explanatory diagram showing the contents of the standard value information file, and Figure 4 is the operation. FIG. 5 is an explanatory diagram showing an example of the result of the operation. 12... File read processing section, 13... Calculation processing section, 14... Numerical judgment processing section, 15... Coloring processing section, 16... Analysis request information file, 17... Standard value information File, 18... Output device.

Claims (1)

[Claims] A standard value information storage means for storing knowledge necessary for analysis as a standard value, a numerical judgment means for performing arithmetic processing based on the data in the causal data analysis request information file and comparing it with the specified value, 1. A causal data analysis and display device, comprising numerical coloring display means for coloring and displaying data based on the numerical value.