JP6953232B2 - Business feasibility evaluation system and business feasibility evaluation method - Google Patents

Description

The embodiment relates to a business feasibility evaluation system and a business feasibility evaluation method.

When a financial institution or the like makes a loan to a company or the like, the loan amount is generally determined based on the financial condition of the company, collateral / guarantee, and the like. In recent years, business analysis and evaluation (hereinafter referred to as business feasibility evaluation) based on the business content of the company and business growth potential have been conducted, and the loan amount is determined after taking into account the results of this business feasibility evaluation. The number of cases is increasing.

Japanese Unexamined Patent Publication No. 2015-32023

In the business feasibility evaluation, in order to clarify the value of the loan to the company, the business is evaluated based on a plurality of evaluation items defined from all viewpoints such as finance, management, and technology. For example, in the local benchmark method published by the Ministry of Economy, Trade and Industry, the business condition of a company is analyzed by inputting data on financial information and non-financial information into special software. In addition, for example, Japan Finance Corporation sets evaluation items for management ability and management strategy and evaluates for financing.

However, depending on the commercial field, it may be difficult to perform an appropriate evaluation because the information necessary for performing the above-mentioned evaluation is insufficient. For example, in the field of agriculture, forestry and fisheries, producers (agriculture, forestry and fisheries businesses) often realize stable supply based on their own experience or intuition. In this case, since the issues and points for improvement of the technology actually used are unclear, financial institutions and the like cannot judge the growth potential of the business by providing the loan.

The present invention has been made in view of the above circumstances, and provides a business feasibility evaluation system that easily analyzes the business of a producer and evaluates the business feasibility appropriately.

According to the embodiment, the business feasibility evaluation system includes a plurality of process classifications, a plurality of business elements, and a plurality of importance related to the business to be evaluated, and the importance is given to the combination of the process classification and the business elements. A storage unit that stores importance data associated with a degree, a reception unit that receives input evaluation values for the process classification and the business element, and the importance for the input evaluation value for each process classification and the business element. For each process classification obtained by summing the first calculation unit for calculating the process classification and the first score for each business element and the first score for each process classification, reflecting the degree. A second calculation unit that determines a first evaluation value for each process classification based on the second score, and each business element obtained by summing the first score for each business element. A third calculation unit that determines a second evaluation value for each business element based on the third score, and a third evaluation value based on the first evaluation value and the second evaluation value. It includes a fourth calculation unit for determining. In determining the third evaluation value, the fourth calculation unit selects the first comprehensive evaluation value having the highest first importance to the process classification from among the plurality of the first evaluation values. Then, the second comprehensive evaluation value having the highest second importance for the business element is selected from the plurality of the second evaluation values, and the first importance and the second importance are selected. When the first importance is greater than the second importance, the first comprehensive evaluation value is determined as the third evaluation value, and the second importance is the second importance. When it is larger than the first importance, the second comprehensive evaluation value is determined as the third evaluation value.

According to this embodiment, it is possible to provide a business feasibility evaluation system and a business feasibility evaluation method for easily performing business analysis of a producer and performing an appropriate business feasibility evaluation.

FIG. 1 is a block diagram showing an example of a business feasibility evaluation system according to an embodiment. FIG. 2 is a diagram showing an example of item data according to the embodiment. FIG. 3 is a diagram showing the relationship between the setting data, the input data, and the result data according to the embodiment. FIG. 4 is a diagram showing an example of the process classification coefficient according to the embodiment. FIG. 5 is a diagram showing an example of process element coefficients according to the embodiment. FIG. 6 is a diagram showing an example of the business element coefficient according to the embodiment. FIG. 7 is a diagram showing an example of element coefficients according to the embodiment. FIG. 8 is a flowchart showing an example of processing of the item selection unit according to the embodiment. FIG. 9 is a flowchart showing an example of processing of the evaluation determination unit according to the embodiment. FIG. 10 is a diagram showing an example of a process of calculating a score and an evaluation value according to an embodiment.

Hereinafter, embodiments of the invention will be described with reference to the drawings. In this description, common reference numerals are given to common parts throughout the drawings.

Hereinafter, a case where the business feasibility evaluation system 1 according to the present embodiment evaluates the business feasibility of a business that produces items in the agriculture, forestry and fisheries fields will be described. However, the business feasibility evaluation system 1 can also be applied to business feasibility evaluation of industries other than agriculture, forestry and fisheries (for example, manufacturing industry, service industry, etc.).

The user of the business feasibility evaluation system 1 according to the present embodiment inputs evaluation values for items defined for each process and business element for each item to be evaluated for business feasibility. The business feasibility evaluation system 1 calculates an evaluation value for each process and an evaluation value for each business element using a preset evaluation calculation function, a weighting coefficient, and the like based on the input evaluation value. Further, the business feasibility evaluation system 1 determines the evaluation value of the entire business based on the evaluation value for each process and the evaluation value for each business element.

FIG. 1 is a block diagram showing a business feasibility evaluation system 1 according to the present embodiment.

The business feasibility evaluation system 1 includes a first memory 2, a second memory 3, a processor 4, an output unit 5, a database DB, and the like. The first memory 2, the second memory 3, the processor 4, the output unit 5, and the database DB are connected to each other so as to be able to communicate with each other via the bus B.

The database DB stores, for example, setting data S, input data I, and result data R.

The setting data S is data preset in the business feasibility evaluation system 1. The setting data S includes, for example, item data H, item data D, a weighting coefficient table T, and an evaluation calculation function F.

Item data H indicates, for example, an item produced in a business. Details of the item data H will be described later with reference to FIG.

The item data D includes, for example, a process classification item D1, a process element item D2, and a business element item D3.

The process classification item D1 indicates a major classification of the production process of the product produced by the business. For example, the process classification item D1 of the process of producing agricultural products includes seedling procurement, soil preparation, cultivation, harvesting, storage by producers, shipping, distribution, storage by distributors, sales, and the like.

The process element item D2 indicates a sub-classification process that is a component of the process classification item D1. In other words, the process element item D2 is an item obtained by subdividing the process classification item D1. For example, the process element item D2 for seedling procurement included in the process classification item D1 includes variety selection, seedling procurement, and the like. In addition, the process element item D2 for soil preparation included in the process classification item D1 includes soil confirmation, cultivator, original fertilizer, sowing and planting. Details of the process element item D2 for each process classification item D1 are shown in FIG.

The business element item D3 indicates, for example, a component that constitutes a business. The business element item D3 of the business of producing agricultural products includes, for example, production base, production control, production technology, products, market analysis, distribution and sales management, and the like.

The evaluation calculation function F is a function used when the business feasibility evaluation system 1 calculates an evaluation value based on the input evaluation value I1 described later. The evaluation calculation function F is used in the process of processing executed by the evaluation determination unit 43, which will be described later.

The weighting coefficient table T numerically represents the importance (weight) between items included in the item data D. It is preferable that the weighting coefficient table T is, for example, table-type data in which the importance is arranged at the intersection position of the first item group and the second item group that are related to each other. However, the weighting coefficient table T may be in a format other than the table format. The weighting coefficient table T is, for example, a process classification coefficient T1 representing the importance between the process classification items D1, a process element coefficient T2 representing the importance between the process element items D2, and a business element representing the importance between the business element items D3. Includes coefficient T3.

The weighting coefficient table T is used in the process of processing executed by the evaluation determination unit 43, which will be described later. The details of the process classification coefficient T1 will be described later in FIG. 4, the details of the process element coefficient T2 will be described in FIG. 5, and the details of the business element coefficient T3 will be described later in FIG.

The input data I is data input to the business feasibility evaluation system 1. The input data I includes the input evaluation value I1. The input evaluation value I1 indicates, for example, an evaluation for each item (hereinafter referred to as an input evaluation item) in which the process classification item D1 or the process element item D2 and the business element item D3 are combined. The evaluation may be, for example, a numerical score or a symbolic qualitative evaluation. The qualitative evaluation by the symbol is, for example, "A: excellent", "B: good", "C: acceptable", "D: impossible" and the like. A specific example of the input evaluation value I1 will be described later with reference to FIG.

The user of the business feasibility evaluation system 1 evaluates the input evaluation items required for each production item, and inputs the evaluation result into the business feasibility evaluation system 1. The business feasibility evaluation system 1 stores the input evaluation result as the input evaluation value I1 in the database DB.

The input evaluation value I1 may be generated by another system or device other than the business feasibility evaluation system 1. In addition, the required input evaluation items may differ for each production item.

The result data R is data obtained as a result of processing by the business feasibility evaluation system 1. The result data R includes, for example, a process classification evaluation value R1, a process element evaluation value R2, a business element evaluation value R3, a business feasibility evaluation value R4, and a score data R5.

The process classification evaluation value R1 indicates an evaluation value for each process classification item D1 determined based on the process element evaluation value R2. The evaluation value may be, for example, a score (numerical value) or a symbol. Numerical scores may be converted to symbols based on predetermined thresholds. The qualitative evaluation by the symbol is, for example, "A: excellent", "B: good", "C: acceptable", "D: impossible" and the like.

The process element evaluation value R2 indicates an evaluation value for each process element item D2, which is determined by the business feasibility evaluation system 1 performing an evaluation process based on the input evaluation value I1. The mode of the evaluation value is the same as that of the process classification evaluation value R1.

The business element evaluation value R3 indicates an evaluation value for each business element item D3, which is similarly determined by the business feasibility evaluation system 1 performing evaluation processing based on the input evaluation value I1. The evaluation value may be, for example, a score or a symbol. Numerical scores may be converted to symbols based on predetermined thresholds. The qualitative evaluation by the symbol is, for example, "A: Business growth is expected", "B: Business stable continuation is expected", "C: There is no problem in the business", "D: There is a problem in the business", and the like.

The business feasibility evaluation value R4 indicates an evaluation value of the entire business determined based on the process classification evaluation value R1 and the business element evaluation value R3. The evaluation value may be, for example, a score or a symbol. Numerical scores may be converted to symbols based on predetermined thresholds. The qualitative evaluation using symbols is the same as in the case of the business element evaluation value R3.

The score data R5 stores a score or the like obtained during the evaluation process by the business feasibility evaluation system 1 based on the input evaluation value I1. For example, the evaluation determination unit 43, which will be described later, is required for calculation results and calculations in the middle of the process of determining the process classification evaluation value R1, the process element evaluation value R2, the business element evaluation value R3, and the business feasibility evaluation value R4. Intermediate values and the like are stored as score data R5. As a result, for example, even if the setting data S or the input data I is changed and recalculation is required, the evaluation determination unit 43 can read the score data R5 and easily perform the recalculation.

The first memory 2 is composed of, for example, a hard disk, an SSD (Solid State Drive), a flash memory, or the like, and constitutes a storage area together with the second memory 3.

The first memory 2 stores various software or data. Various software includes an operating system (OS), a data management program, various application programs, and the like. The first memory 2 stores a program P that executes various processes for business feasibility evaluation.

Further, the first memory 2 may store, for example, a part or all of the setting data S, the input data I, and the result data R to be processed by the processor 4.

The setting data S, the input data I, and the result data R may be stored in the second memory 3.

The second memory 3 as the main memory is composed of, for example, a RAM (Random Access Memory) and is used as a work area or the like. The work area is used when the processor 4 executes various software.

The processor 4 executes various software (programs) and controls the entire business feasibility evaluation system 1. The processor 4 is, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a DSP (Digital Signal Processor), or the like.

The processor 4, for example, by executing the program P stored in the first memory 2 or read from the first memory 2 to the second memory 3, for example, the input receiving unit 41, the item selection. It functions as a unit 42, an evaluation determination unit 43, or an output control unit 44.

The input receiving unit 41 receives the input of the input data I from the user of the business feasibility evaluation system 1. For example, the input receiving unit 41 stores the input input evaluation value I1 in the database DB.

The item selection unit 42 reads the input data I stored in the database DB, and searches or selects the setting data S corresponding to the item of the input data I. Further, the item selection unit 42 reads the searched or selected setting data S into the first memory 2 or the second memory 3.

The evaluation determination unit 43 calculates the process classification evaluation value R1, the process element evaluation value R2, the business element evaluation value R3, and the business feasibility evaluation value R4 by processing the input data I using the setting data S.

More specifically, for example, the evaluation determination unit 43 converts the input evaluation value I1 into a score when the input evaluation value I1 is a qualitative evaluation by a symbol. The evaluation determination unit 43 calculates the score for each combination of the process element item D2 and the business element item D3 by multiplying the input evaluation value I1 converted into the score by the process element coefficient T2 and the business element coefficient T3. .. The evaluation determination unit 43 determines the process element evaluation value R2 based on the calculated score, and determines the process classification evaluation value R1 based on the process element evaluation value R2. The evaluation determination unit 43 determines the business element evaluation value R3 based on the calculated score. Further, the evaluation determination unit 43 determines the business feasibility evaluation value R4 based on the process classification evaluation value R1 and the business element evaluation value R3.

The output control unit 44 transmits the result data R stored in the first memory 2 or the second memory 3 to the output unit 5. The output control unit 44 may be included in the evaluation determination unit 43.

The output unit 5 outputs the result data R. The output unit 5 may be, for example, a display or a printer.

In the present embodiment, the function of the program P will be described separately for convenience by dividing it into an input reception unit 41, an item selection unit 42, an evaluation determination unit 43, and an output control unit 44. However, the program P may include other processing units, may be composed of one processing unit, or may be divided into a plurality of processing units in a mode other than that shown in FIG.

FIG. 2 is a diagram showing an example of items according to the present embodiment.

The items handled in this embodiment are registered in the database DB with the item name HN and the item index HI in advance.

The item data H includes, for example, a set of an item index HI, an item name HN, or an item index HI and an item name HN for one item. The setting data S is preferably set in advance for each item data H.

The types and order of the item name HN and the item index HI shown in FIG. 2 are merely examples, and other items may be registered.

FIG. 3 is a diagram showing the relationship between the setting data S, the input data I, and the result data R according to the present embodiment. FIG. 3 is represented, for example, in tabular form.

The columns of the table shown in FIG. 3 represent the process classification item D1, and the rows of the table shown in FIG. 3 represent the business element item D3. Further, an example of the process element item D2 corresponding to each process classification item D1 is shown. The process element item D2 may include items other than those shown in FIG.

The user of the business feasibility evaluation system 1 can use the process classification items based on, for example, the evaluation from an external expert obtained for the business currently being carried out, or the measured value by a device for measuring the state of the product. The input evaluation value I1 is input for each item separated by D1 and the business element item D3. More specifically, for example, it is assumed that the user has obtained an evaluation that the item "production control" (cell X1) of the business element item D3 in the item "seedling procurement" of the process classification item D1 is "good". In this case, the user inputs the symbol "B" corresponding to the evaluation into the business feasibility evaluation system 1 as the evaluation of the cell X1. Similarly, the user inputs an evaluation for the items shown in other cells into the business feasibility evaluation system 1.

Further, the process classification evaluation value R1 is determined for each item included in the process classification item D1 by the processing of the evaluation determination unit 43. Similarly, the business element evaluation value R3 is determined for each item included in the business element item D3 by the processing of the evaluation determination unit 43. Further, the business feasibility evaluation value R4 is determined based on the process classification evaluation value R1 and the business element evaluation value R3 by the processing of the evaluation determination unit 43.

FIG. 4 is a diagram showing an example of the process classification coefficient T1 according to the present embodiment.

The process classification coefficient T1 is a numerical value (coefficient) representing the importance between the process classification items D1 and is determined for each process classification item D1. The total value of the process classification coefficient T1 is, for example, 1. The process classification coefficient T1 may be determined separately for, for example, a process classification item D1 belonging to the production stage and a process classification item D1 belonging to the distribution stage. The process classification item D1 belonging to the production stage includes, for example, the items “seedling procurement”, “soil preparation”, “cultivation”, “harvest”, “storage (producer)”, and “shipment”. Further, the process classification item D1 belonging to the distribution stage includes, for example, the items "distribution", "storage (distribution)", and "sales".

In the example of FIG. 4, the total coefficient J1 of the process classification coefficient T1 in the production stage and the total coefficient J2 of the process classification coefficient T1 in the distribution stage are set to be equal to each other. That is, the total coefficient J1 and the total coefficient J2 are 0.5 each. Further, the process classification coefficient T1 at the production stage is determined as the numerical value J3, and the process classification coefficient T1 at the distribution stage is determined as the numerical value J4.

FIG. 5 is a diagram showing an example of the process element coefficient T2 according to the present embodiment.

The process element coefficient T2 is a numerical value (coefficient) representing the importance of each combination of the process element item D2 and the business element item D3. In the following, the process element coefficient T2 included in the item “seed and seedling procurement” of the process classification item D1 will be described. The same applies to the process element coefficient T2 included in the other process classification item D1.

The weighting coefficient K1 indicates whether or not the item “seedling procurement” of the process classification item D1 is related to each item of the business element item D3. For example, the item "seedling procurement" of the process classification item D1 is not related to the items "production base", "product", "market analysis", and "distribution and sales management" of the business element item D3, and therefore corresponds to these. The weighting coefficient K1 is, for example, 0. On the other hand, since the item "seedling procurement" of the process classification item D1 is related to the items "production control" and "production technology" of the business element item D3, the weighting coefficient K1 corresponding to these is, for example, 1.

The weighting coefficient K2 indicates the importance of each of the business element items D3 of the items “variety selection” and “seed and seedling procurement” of the process element item D2. In other words, the weighting coefficient K2 is a value obtained by distributing the weighting coefficient K1 for each business element item D3 according to the importance of each of the items "variety selection" and "seedling procurement" of the process element item D2.

More specifically, for example, in the item "production control" of the business element item D3, the weighting coefficient K2 of the item "variety selection" and the item "seedling procurement" of the process element item D2 is 0.5 each. This indicates that in the item "production control" of the business element item D3, the items "variety selection" and the item "seedling procurement" of the process element item D2 are of the same importance. Further, in the item "production technology" of the business element item D3, the weighting coefficient K2 of the item "variety selection" of the process element item D2 is 0.4, and the weighting coefficient K2 of the item "seedling procurement" is 0.6. This indicates that in the item "production technology" of the business element item D3, the item "seedling procurement" of the process element item D2 is more important than the item "variety selection".

FIG. 6 is a diagram showing an example of the business element coefficient according to the present embodiment.

The business element coefficient T3 is a numerical value (coefficient) representing the importance between the business element items D3 in each process classification item D1. In the following, the business element coefficient T3 included in the item “seedling procurement” of the process classification item D1 will be described. The same applies to the business element coefficient T3 included in the other process classification item D1.

The weighting coefficient K3 indicates the importance between each item of the business element item D3 in the item “seedling procurement” of the process classification item D1. The total value of the weighting coefficient K3 is, for example, 1.

In the example of FIG. 6, the weighting coefficients K2 of the item “production control” and the item “production technology” of the business element item D3 are 0.5 each, and the coefficients of the other items are 0. This is because in the item "seedling procurement" of the process classification item D1, the importance of the item "production control" and the item "production technology" of the business element item D3 is about the same, and it is not important for other items (related). There is no).

FIG. 7 is a diagram showing an example of the element coefficient T4 according to the present embodiment.

The element coefficient T4 is obtained by multiplying the process element coefficient T2 and the business element coefficient T3. In other words, the element coefficient T4 is a process element coefficient T2 that takes into account the importance between the business element items D3. For example, in the element coefficient T4, the weighting coefficient K4 included in the item “seedling procurement” of the process classification item D1 is the weighting coefficient K2 (and the weighting coefficient K1) of FIG. 5 and the weight of FIG. 6 for each business element item D3. It is obtained by multiplying the coefficient K3. The evaluation determination unit 43 calculates the element coefficient T4 by the above procedure and stores it in the second memory 3.

The total coefficient K5 is a value obtained by totaling the coefficients included in the element coefficient T4 for each item of the process element item D2. For example, the total coefficient K5 of the item "variety selection" of the process element item D2 is 0.45, and the total coefficient K5 of the item "seedling procurement" of the process element item D2 is 0.55. The total coefficient K5 for each process classification item D1 is 1.

The total coefficient K6 is a value obtained by totaling the coefficients included in the element coefficient T4 for each item of the business element item D3. For example, the total coefficient K6 of the item “production base” of the business element item D3 is 0.9, and the total coefficient K6 of the item “production control” of the business element item D3 is 2.3.

The business element importance K7 is a numerical value obtained by normalizing the total coefficient K6 so that the total value of the element coefficients T4 is 1.

The database DB may store the element coefficient T4 instead of the process element coefficient T2 and the business element coefficient T3.

Hereinafter, with reference to FIGS. 8 to 10, the details of the processing executed by the processor 4 after the input evaluation value I1 is input and before the business feasibility evaluation value R4 is determined will be described.

FIG. 8 is a flowchart showing an example of processing of the item selection unit 42 according to the present embodiment.

In step S101, the item selection unit 42 reads the input data I stored in the database DB into the first memory 2 or the second memory 3.

In step S102, the item selection unit 42 identifies the item having the input evaluation value I1. More specifically, for example, the item selection unit 42 reads a tag, a header, metadata, or other information attached to the input evaluation value I1 for identifying the item attached to the input evaluation value I1. , The item may be identified. The item selection unit 42 obtains the item index HI of the identified item by referring to the item data H.

In step S103, the item selection unit 42 searches for and selects the setting data S corresponding to the item index HI obtained in step S102.

In step S104, the item selection unit 42 reads the selected setting data S into the first memory 2 or the second memory 3.

FIG. 9 is a flowchart showing an example of processing of the evaluation determination unit 43 according to the present embodiment. A part or all of the processing shown in FIG. 9 is included in the evaluation calculation function F.

In step S201, the evaluation determination unit 43 converts the input evaluation value I1 into a score based on a predetermined rule. The predetermined rule is, for example, when the input evaluation value I1 is any of "A: excellent", "B: good", "C: acceptable", and "D: impossible", "A: 95 points" and "B: 80 points". "C: 60 points" "D: 30 points" "None (blank): 0 points" and the like. If the input evaluation value I1 is a numerical score, the process of step S201 may not be necessary.

In step S202, the evaluation determination unit 43 calculates the element coefficient T4 from the process element coefficient T2 and the business element coefficient T3. The calculation method of the element coefficient T4 is as described above in FIG. If the database DB includes the element coefficient T4, step S202 can be omitted.

In step S203, the evaluation determination unit 43 multiplies the score obtained in step S201 by the element coefficient T4, and calculates the score for each combination of the process element item D2 and the business element item D3. For example, the evaluation determination unit 43 multiplies the score of the input evaluation value I1 of the item “seedling procurement” of the process classification item D1 by the weighting coefficient K4 (see FIG. 7), thereby multiplying the score of the item “seedling” of the process classification item D1. Calculate the score for each business element item D3 of "procurement" and the item "variety selection" and item "seedling procurement" of the process element item D2.

In step S204, the evaluation determination unit 43 calculates the total process score obtained by summing the scores obtained in step S203 for each process element item D2, and the total business element score obtained by summing the scores for each business element item D3.

Further, the evaluation determination unit 43 calculates the process score ratio based on the total process score and the business element score ratio based on the total business element score. The process score ratio is obtained by dividing the total process score by the process reference point for each process element item D2. The process reference point is, for example, a value obtained by multiplying the total coefficient K5 (see FIG. 7) by 100. Similarly, the business element score ratio is obtained by dividing the total business element score by the business element reference point for each business element item D3. The business element reference point is, for example, a value obtained by multiplying the total coefficient K6 (see FIG. 7) by 100.

In step S205, the evaluation determination unit 43 determines the process element evaluation value R2 for each process element item D2 based on the process score ratio obtained in step S204. More specifically, the evaluation determination unit 43 converts the score ratio into the process element evaluation value R2 based on a predetermined rule (hereinafter, referred to as an evaluation value conversion rule). When the process element evaluation value R2 is represented by the symbols A to D, the evaluation value conversion rule is, for example, "score ratio of 0.9 or more: A" and "score ratio of 0.7 or more and less than 0.9". : B, "Score ratio is 0.4 or more and less than 0.7: C", "Score ratio is less than 0.4: D", and the like.

Similarly, the evaluation determination unit 43 determines the business element evaluation value R3 for each business element item D3 based on the business element score ratio obtained in step S204. The conversion from the business element score ratio to the business element evaluation value R3 is performed based on, for example, the above-mentioned evaluation value conversion rule.

In step S206, the evaluation determination unit 43 determines the process classification evaluation value R1. For example, the evaluation determination unit 43 determines the process classification evaluation value R1 of the process classification item D1 as the evaluation value having the largest number among the process element evaluation values R2 included in the process classification item D1. When the number of evaluation values having the largest number is the same, it is preferable that the lower evaluation value is selected.

Further, for example, when the process element evaluation value R2 includes an evaluation value equal to or less than a predetermined evaluation value (for example, “D”), the evaluation determination unit 43 sets the process classification evaluation value R1 as the predetermined evaluation value (or most). It may be decided to have a low evaluation value).

In step S207, the evaluation determination unit 43 determines the process comprehensive evaluation value in which the process classification evaluation value R1 is integrated into one evaluation value based on the process classification evaluation value R1. Here, the process classification coefficient T1 and the process classification evaluation value R1 correspond to each process classification item D1. The evaluation determination unit 43 totals the process classification coefficient T1 of each item of the process classification item D1 for each evaluation value (for example, “A” to “D”) included in the process classification evaluation value R1. Further, the evaluation determination unit 43 sets the evaluation value corresponding to the process comprehensive evaluation coefficient having the largest value among the coefficients for each total evaluation value (hereinafter, referred to as process comprehensive evaluation coefficient) as the process comprehensive evaluation value.

In addition, for example, when the process classification evaluation value R1 includes an evaluation value equal to or less than a predetermined evaluation value (for example, “D”), the evaluation determination unit 43 sets the process comprehensive evaluation value as a predetermined evaluation value (or the lowest evaluation). Value) may be determined.

In step S208, the evaluation determination unit 43 determines a business comprehensive evaluation value in which the business element evaluation value R3 is integrated into one evaluation value based on the business element evaluation value R3. Here, the business element importance K7 (see FIG. 7) and the business element evaluation value R3 correspond to each business element item D3. The evaluation determination unit 43 totals the business element importance K7 of each item of the business element item D3 for each evaluation value (for example, “A” to “D”) included in the business element evaluation value R3. Further, the evaluation determination unit 43 sets the evaluation value corresponding to the largest business comprehensive evaluation coefficient among the coefficients for each total evaluation value (hereinafter referred to as the business comprehensive evaluation coefficient) as the business comprehensive evaluation value.

In addition, for example, when the business element evaluation value R3 includes an evaluation value equal to or less than a predetermined evaluation value (for example, “D”), the evaluation determination unit 43 sets the business comprehensive evaluation value as a predetermined evaluation value (or the lowest evaluation). Value) may be determined.

In step S209, the evaluation determination unit 43 determines the business feasibility evaluation value R4 based on the process comprehensive evaluation value and the business comprehensive evaluation value. The evaluation decision unit 43 compares the process comprehensive evaluation coefficient corresponding to the process comprehensive evaluation value with the business comprehensive evaluation coefficient corresponding to the business comprehensive evaluation value, and evaluates the business feasibility of the evaluation value corresponding to the larger coefficient. Determined to be the value R4. When the compared process comprehensive evaluation coefficient and the business comprehensive evaluation coefficient are the same, it is preferable that a lower evaluation value is selected. Further, the evaluation determination unit 43 sets the business feasibility evaluation value R4 as a predetermined evaluation value when the process comprehensive evaluation value and the business comprehensive evaluation value include an evaluation value equal to or less than a predetermined evaluation value (for example, “D”). (Or the lowest evaluation value) may be determined.

In step S210, the output control unit 44 outputs at least one or more of the process classification evaluation value R1, the business element evaluation value R3, the business feasibility evaluation value R4, and the score data R5 included in the result data R. Send to. The output unit 5 outputs the received data. The output unit 5 preferably outputs the received data in, for example, a table format. More specifically, the output unit 5 may output a part or all of the table shown in FIG. 3 or a part or all of the table shown in FIG. However, the output unit 5 may output the received data in, for example, an itemized text format.

In addition, the evaluation determination unit 43 includes various scores for each process element item D2 obtained by step S209, total process scores, process reference points, process score ratios, various scores for each business element item D3, and total business element scores. The business element reference point, the business element score ratio, and the like may be stored in the database DB as score data R5, respectively.

FIG. 10 is a diagram showing an example of a calculation process of the business feasibility evaluation value R4 according to the present embodiment. More specifically, FIG. 10 shows the process classification evaluation value R1, the business element evaluation value R3, and the business feasibility evaluation value R4, respectively, when the input evaluation value I1 shown in FIG. 3 is input to the business feasibility evaluation system 1. Shows the process by which is determined. It is assumed that the element coefficient T4 has already been calculated.

First, the process of the process in which the process classification evaluation value R1 is determined will be described.

For example, in the input evaluation value I1 of the item "seedling procurement" of the process classification item D1, the item "production control" of the business element item D3 is "B" (see cell X1 in FIG. 3), and the item of the business element item D3. The "production technology" is "C" (see cell X2).

The input evaluation value I1 is converted into a score by the evaluation determination unit 43 (see step S201). More specifically, for example, the input evaluation value "B" is converted to 80 points, the input evaluation value "C" is converted to 60 points, and the item without the input evaluation value is converted to 0 points.

By multiplying this score by the element coefficient T4 (see FIG. 7), the score for each business element item D3 of the process classification item D1 and the process element item D2 is calculated (see step S203).

More specifically, the score L1 is calculated by multiplying the item "seedling procurement" of the process classification item D1 by the weighting coefficient K4. For example, the score of the item "production control" of the business element item D3 is multiplied by the coefficient of the item "production control" of the business element item D3 in the weighting coefficient K4. As a result, the score of the item that combines the item "seed and seedling procurement" of the process classification item D1 and the item "production control" of the business element item D3 becomes 40 points. In addition, the score obtained by combining the items "variety selection" and "seedling procurement" of the process element item D2 and the item "production control" of the business element item D3 is 20 points each.

The score L1 is totaled for each process element item D2, and the total process score L2 is calculated. The total process score L2 is divided by the process reference point L3 calculated based on the total coefficient K5 (see FIG. 7). As a result, the process score ratio L4 is calculated (see step S204).

The process element evaluation value L5 is determined based on the calculated process score ratio L4 and the above-mentioned evaluation value conversion rule (see step S205).

The process element evaluation value L5 includes one evaluation value “B” and one evaluation value “C”, and the number of the most numerous evaluation values is the same, so that the process classification evaluation value L6 is lower. The evaluation value is determined to be “C” (see step S206).

Similarly, by performing the same processing in all the other process classification items D1, all the process element evaluation values R2 are determined, and further the process classification evaluation value R1 is determined.

Next, the process of processing in which the business element evaluation value R3 is determined will be described.

The scores for all process element items D2 and business element item D3 obtained by multiplying the score of the input evaluation value I1 by the element coefficient T4 are totaled for each business element item D3, and the total business element score L10 is calculated. Calculated. The total business element score L10 is divided by the business element reference point L11 calculated based on the total coefficient K6 (see FIG. 7). As a result, the business element score ratio L12 is calculated (see step S204).

The business element evaluation value R3 is determined based on the calculated business element score ratio L12 and the evaluation value conversion rule (see step S205).

Further, the process of processing in which the business feasibility evaluation value R4 is determined will be described.

First, the process comprehensive evaluation value L13 is determined based on the process classification evaluation value R1 (see step S207). In the example of FIG. 10, the process classification item D1 of the evaluation value “B” is the item “soil preparation” and “storage (producer)”, and the total of the process classification coefficients T1 (see FIG. 4) corresponding to these is 0.025 + 0.025 = 0.05. Similarly, the process classification item D1 with the evaluation value "C" is the item "seedling procurement", "cultivation", "harvest", "shipment", "distribution", "storage (distribution)", and the corresponding processes. The sum of the classification coefficients T1 is 0.03 + 0.045 + 0.2 + 0.175 + 0.1 + 0.1 = 0.65. Similarly, the process classification item D1 of the evaluation value “D” is the item “sales”, and the total of the corresponding process classification coefficients T1 is 0.3. The process classification evaluation value R1 does not include the evaluation value "A". Therefore, the process comprehensive evaluation coefficient for each evaluation value is "A: 0", "B: 0.05", "C: 0.65", and "D: 0.3". Among these, the evaluation value “C” having the largest process comprehensive evaluation coefficient can be the process comprehensive evaluation value L13. However, since the process classification evaluation value R1 includes a predetermined evaluation value “D”, the evaluation value “D” is determined to be the process comprehensive evaluation value L13.

Next, the overall business evaluation value L14 is determined based on the business element evaluation value R3 for each business element item D3 (see step S208). In the example of FIG. 10, the business element item D3 of the evaluation value “B” is the item “production base” and “production control”, and the total of the corresponding business element importance K7 (see FIG. 7) is 0.1+. 0.255 = 0.355. Similarly, the business element item D3 with the evaluation value "C" is the item "production technology", "product", "market analysis", and "distribution and sales management", and the total of the corresponding business element importance K7 is , 0.156 + 0.056 + 0.244 + 0.189 = 0.645. The business element evaluation value R3 does not include the evaluation values "A" and "D". Therefore, the overall business evaluation coefficient for each evaluation value is "A: 0", "B: 0.355", "C: 0.645", and "D: 0". Of these, the evaluation value “C” having the largest overall business evaluation coefficient is determined to be the overall business evaluation value L14.

Then, the process comprehensive evaluation coefficient (0.3) corresponding to the process comprehensive evaluation value L13 “D” and the business comprehensive evaluation coefficient (0.645) corresponding to the business comprehensive evaluation value L14 “C” are compared. In this case, since the value of the business comprehensive evaluation coefficient is large, the business comprehensive evaluation value L14 “C” can be the business feasibility evaluation value R4. However, since the process comprehensive evaluation value L13 "D" is a predetermined evaluation value, the evaluation value "D" is determined to be the business feasibility evaluation value R4.

In the present embodiment described above, the business feasibility evaluation system 1 converts the input evaluation value I1 into a score, and further uses the weighting coefficient table T for each process classification item D1, process element item D2, and business element item D3. Calculate the score of. The business feasibility evaluation system 1 calculates the process element evaluation value R2 for each process element item D2, and calculates the process classification evaluation value R1 for each process classification item D1 based on the process element evaluation value R2. Further, the business feasibility evaluation system 1 calculates the business element evaluation value R3 for each business element item D3. Further, the business feasibility evaluation system 1 calculates the business feasibility evaluation value R4 based on the process classification evaluation value R1 and the business element evaluation value R3. As a result, the entire business can be evaluated after analyzing both the process side and the business side, so that an appropriate business feasibility evaluation result can be obtained.

In the present embodiment, the output control unit 44 and the output unit 5 use the process classification evaluation value R1, the business element evaluation value R3, and the business feasibility evaluation value R4 as the process classification item D1, the process element item D2, and the business element item D3. Output in a visible tabular format for each. As a result, the user of the business feasibility evaluation system 1 can easily grasp the business problem in units of process classification, process element, and business element.

In the present embodiment, the user of the business feasibility evaluation system 1 can mechanically obtain the business feasibility evaluation by inputting the input evaluation value I1 into the business feasibility evaluation system 1. Therefore, the business feasibility evaluation system 1 can assist a quick credit examination in, for example, a financial institution.

In the present embodiment, by using the process classification coefficient T1, the process element coefficient T2, and the business element coefficient T3, between each item included in the process classification item D1, the process element item D2, and the business element item D3. Weighting can be done flexibly. By setting each coefficient of the process classification coefficient T1, the process element coefficient T2, and the business element coefficient T3 in detail, the relevance of each item can be expressed in detail.

In the present embodiment, the business feasibility evaluation system 1 may store feedback data for determining whether or not the result data R output in the past is appropriate in the database DB. The business feasibility evaluation system 1 may recognize the characteristics of the production item, the characteristics of the process, and / or the characteristics of the business based on this feedback data, and reflect them in the weighting coefficient table T. As a result, the evaluation accuracy by the business feasibility evaluation system 1 can be improved by using the past business feasibility evaluation results.

The present invention is not limited to the embodiments described above, and each embodiment can be implemented by deleting, adding, or modifying components. Further, by appropriately combining or exchanging the components of each embodiment, it can be implemented in a further different form. As described above, even if the embodiment is directly different from the embodiment described above, the embodiment having the same purpose as the present invention will be described as the embodiment of the present invention, and the description thereof will be omitted. There is.

1 ... Business feasibility evaluation system, 2 ... 1st memory, 3 ... 2nd memory, 4 ... Processor, 5 ... Output unit, 42 ... Item selection unit, 43 ... Evaluation determination unit, 43 ..., 44 ... Output control unit , B ... Bus, DB ... Database, D ... Item data, D1 ... Process classification item, D2 ... Process element item, D3 ... Business element item, F ... Evaluation calculation function, H ... Item data, I ... Input data, I1 ... Input evaluation value, P ... program, R ... result data, R1 ... process classification evaluation value, R2 ... process element evaluation value, R3 ... business element evaluation value, R4 ... business feasibility evaluation value, R5 ... score data, S ... setting data , T ... Weight coefficient table, T1 ... Process classification coefficient, T2 ... Process element coefficient, T3 ... Business element coefficient.

Claims (5)

A storage unit that includes a plurality of process classifications, a plurality of business elements, and a plurality of importance related to the business to be evaluated, and stores importance data in which the importance is associated with the combination of the process classification and the business element. When,
A reception unit that accepts input evaluation values for the process classification and each business element,
A first calculation unit that reflects the importance of the input evaluation value for each of the process classification and the business element and calculates a first score for each of the process classification and the business element.
A second calculation unit that determines a first evaluation value for each process classification based on a second score for each process classification obtained by summing the first scores for each process classification.
A third calculation unit that determines a second evaluation value for each business element based on a third score for each business element obtained by summing the first score for each business element.
A fourth calculation unit that determines a third evaluation value based on the first evaluation value and the second evaluation value, and
Equipped with
The fourth calculation unit determines the third evaluation value.
From the plurality of first evaluation values, the first comprehensive evaluation value having the highest first importance to the process classification is selected.
From the plurality of second evaluation values, the second comprehensive evaluation value having the highest second importance for the business element is selected.
The first importance is compared with the second importance, and when the first importance is larger than the second importance, the first comprehensive evaluation value is evaluated as the third evaluation. A business feasibility evaluation system that determines a value and determines the second comprehensive evaluation value as the third evaluation value when the second importance is greater than the first importance. The above-mentioned business is a production business of agriculture, forestry and fishery products.
The plurality of process classifications include breeding, storage, shipping, and distribution.
The plurality of business elements include production control, production technology, products, and market analysis.
The business feasibility evaluation system of claim 1. The importance includes the importance among a plurality of process elements that further subdivide the process classification.
A fifth calculation unit for determining a fourth evaluation value for each process element is provided based on a fourth score for each process element obtained by summing the first score for each process element. death,
The business feasibility evaluation system according to claim 1 or 2, wherein the second calculation unit determines the first evaluation value based on the fourth evaluation value. In the importance data, the plurality of process elements are set as the first item group, the plurality of business elements are set as the second item group, and the importance level is located at the intersection of the process elements and the business elements that are related to each other. Is the table format data in which
The business feasibility evaluation system of claim 3. The processor stores importance data that includes a plurality of process classifications, a plurality of business elements, and a plurality of importance related to the business to be evaluated, and associates the importance with the combination of the process classification and the business element. Remember in the club,
The processor receives the input evaluation value for each process classification and the business element, and receives the input evaluation value.
The processor reflects the importance of the input evaluation value for each of the process classification and the business element, and calculates the first score for the process classification and the business element.
Based on the second score for each process classification obtained by summing the first score for each process classification by the processor, the first evaluation value for each process classification is determined.
Based on the third score for each business element obtained by summing the first score for each business element by the processor, the second evaluation value for each business element is determined.
The processor determines a third evaluation value based on the first evaluation value and the second evaluation value .
In determining the third evaluation value,
The processor selects the first comprehensive evaluation value having the highest first importance to the process classification from among the plurality of the first evaluation values.
The processor selects the second comprehensive evaluation value having the highest second importance for the business element from the plurality of the second evaluation values.
The processor compares the first importance with the second importance, and when the first importance is larger than the second importance, the first comprehensive evaluation value is determined. A business that determines a third evaluation value and determines the second comprehensive evaluation value as the third evaluation value when the second importance is greater than the first importance. Sex evaluation method.

Images