JP2013077047A - Information processing program, information processing method and information processing device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To appropriately assist operator work.SOLUTION: An information processing device 100 receives content of work from an operator terminal and detects a series of transactions included in the work. The information processing device 100 determines whether content of data items of the series of transactions included in the work handled by an operator overlaps or not. The information processing device 100 distinguishes error occurrence rates between when the content of data items overlaps and when the content of data items does not overlap, and stores them in an error occurrence rate table 140c.

Description

  The present invention relates to an information processing program and the like.

  In recent years, there is an increasing number of cases where part-timers, not regular employees, serve as operators at financial institutions. Part timers are more prone to mistakes when performing operator operations than regular employees, and there is a need for technology that supports operator operations.

  For example, in the prior art, there is a technique for supporting an operator's work by displaying a series of transactions for performing a work in a time series on a part of the screen when an input for performing a certain work is made. The business here corresponds to, for example, business such as opening a new account for an ordinary deposit and cash transfer. If the business is to open a new account for ordinary deposits, a series of transactions included in this business includes name identification, cash set, account opening, seal registration, and the like.

  Further, in the prior art, there is a technique for determining the strength and weakness of each operator based on the operation history of the operator.

Japanese Patent Laid-Open No. 9-94287 JP 2001-331655 A

  However, the above-described conventional technology has a problem in that it cannot properly support operator work.

  For example, in the case of a series of transactions included in the business, if the information entered in the front transaction can be reused in the rear transaction, the operator's error rate decreases, but the conventional technology assumes such a case. Thus, it does not provide support for operator operations.

  The disclosed technique has been made in view of the above, and an object thereof is to provide an information processing program, an information processing method, and an information processing apparatus that can appropriately support an operator's work.

  The disclosed information processing program causes a computer to execute the following processing. Let the computer identify the task that the user wants to operate. A computer stores a business management table in which a business, a series of transactions constituting the business, and data items used in the business are associated with each other. A transaction and a data item used for the transaction are detected. Whether or not the content of the data item of the backward transaction among the two consecutively performed transactions overlaps the content of the data item of the forward transaction in the detected series of data items of the plurality of transactions. Let it be judged. Based on the determination result, the computer discriminates the error occurrence rate when the data item content overlaps from the error occurrence rate when the data item content does not overlap, and associates the error occurrence rate for each transaction. It is stored in the error occurrence rate table of the storage device.

  According to the disclosed information processing program, it is possible to appropriately support the operator's work.

FIG. 1 is a diagram illustrating the configuration of the system according to the first embodiment. FIG. 2 is a functional block diagram of the configuration of the information processing apparatus according to the first embodiment. FIG. 3 is a diagram illustrating an example of the data structure of the business management table according to the first embodiment. FIG. 4 is a diagram illustrating an example of the data structure of the transaction management table according to the first embodiment. FIG. 5 is a diagram illustrating an example of the data structure of the miss occurrence rate table. FIG. 6 is a diagram illustrating a correspondence relationship between the transaction and the takeover data. FIG. 7 is a diagram showing an example of the error occurrence rate derived from the relationship between each transaction and the takeover data. FIG. 8 is a diagram (1) illustrating an example of a screen displayed on the screen of the operator terminal by the display control unit. FIG. 9 is a diagram (2) illustrating an example of a screen displayed on the screen of the operator terminal by the display control unit. FIG. 10 is a flowchart of the process procedure of the information processing apparatus according to the first embodiment. FIG. 11 is a flowchart illustrating a processing procedure of a miss occurrence probability calculation process. FIG. 12 is a diagram illustrating a configuration of a system according to the second embodiment. FIG. 13 is a functional block diagram of the configuration of the information processing apparatus according to the second embodiment. FIG. 14 is a diagram illustrating an example of the data structure of the business management table according to the second embodiment. FIG. 15 is a diagram illustrating an example of the data structure of the attribute table according to the second embodiment. FIG. 16 is a diagram illustrating an example of the data structure of the transaction attribute table according to the second embodiment. FIG. 17 is a diagram illustrating an example of the data structure of the skill determination table according to the second embodiment. FIG. 18 is a diagram for explaining the process of the skill determination unit according to the second embodiment. FIG. 19 is a flowchart of a process procedure of the information processing apparatus according to the second embodiment. FIG. 20 is a flowchart illustrating the processing procedure of the primary skill determination processing according to the present embodiment. FIG. 21 is a flowchart of a process procedure of the skill determination process according to the second embodiment. FIG. 22 is a diagram illustrating an example of another data structure of the attribute table. FIG. 23 is a diagram illustrating an example of a computer that executes an information processing program.

  Embodiments of an information processing program, an information processing method, and an information processing apparatus disclosed in the present application will be described below in detail with reference to the drawings. Note that the present invention is not limited to the embodiments.

  FIG. 1 is a diagram illustrating the configuration of the system according to the first embodiment. As shown in FIG. 1, this system includes an information processing apparatus 100 and operator terminals 10a to 10d. The information processing apparatus 100 and operator terminals 10 a to 10 d are connected via a network 50. In the following description, the operator terminals 10a to 10d are collectively referred to as an operator terminal 10 as appropriate.

  The operator terminal 10 is a terminal that displays various types of information related to work. For example, the business corresponds to business such as opening a new account for ordinary deposits and cash transfer. If the business is to open a new account for ordinary deposits, a series of transactions included in this business includes name identification, cash set, account opening, seal registration, and the like.

  When the operator terminal 10 receives the contents of the business from the operator, the operator terminal 10 inquires of the information processing apparatus 100 about the transactions included in the business and sequentially displays the transactions. The operator refers to the contents of the displayed transaction and inputs data items corresponding to the transaction. The operator terminal 10 transmits a data item corresponding to the transaction to the information processing apparatus 100.

  Also, the operator terminal 10 receives, from the information processing apparatus 100, information on a transaction that is likely to cause an operator to make a data item input mistake among transactions included in the business. The operator terminal 10 displays a warning message when displaying a transaction that is likely to cause an input error.

  The information processing apparatus 100 is a device that holds various types of information related to a business and calculates an occurrence probability of an operator input error for each transaction included in the business. The information processing apparatus 100 notifies the operator terminal 10 of transaction information that is likely to cause an operator to make a data item input error.

  A configuration of the information processing apparatus 100 according to the first embodiment will be described. FIG. 2 is a functional block diagram of the configuration of the information processing apparatus according to the first embodiment. As illustrated in FIG. 2, the information processing apparatus 100 includes a communication unit 110, an input unit 120, a display unit 130, a storage unit 140, and a control unit 150.

  The communication unit 110 is a processing unit that performs data communication with the operator terminal 10 via the network 50. For example, the communication unit 110 receives, from the operator terminal 10, business data selected by the operator, data input in a transaction data item, and the like, and outputs the received information to the control unit 150. In addition, when the communication unit 110 receives data addressed to the operator terminal 10 from the control unit 150, the communication unit 110 transmits the data to the operator terminal 10. The control unit 150 described later exchanges data with the operator terminal 10 via the communication unit 110. The communication unit 110 corresponds to a communication device such as a communication module.

  The input unit 120 is an input device that inputs various types of information. For example, the input unit 120 corresponds to a keyboard, a mouse, and a touch panel. The display unit 130 is a display device that displays various types of information. For example, the display unit 130 corresponds to a display or a touch panel.

  The storage unit 140 is a storage device that stores a business management table 140a, a transaction management table 140b, and a miss occurrence rate table 140c. The storage unit 140 corresponds to, for example, a semiconductor memory device such as a random access memory (RAM), a read only memory (ROM), or a flash memory, or a storage device such as a hard disk or an optical disk.

  The business management table 140a is a table that associates business and transactions included in the business. FIG. 3 is a diagram illustrating an example of the data structure of the business management table according to the first embodiment. In the example shown in FIG. 3, the business “new savings deposit” includes (1) name identification, (2) cash set, (3) account opening, (4) seal registration, and (5) office approval. included. The business “cash transfer” includes transactions of (1) name identification, (2) form reading, (3) cash set, (4) seal verification, and (5) data input. Each transaction is processed in the order of (1) to (5).

  The transaction management table 140b is a table that associates transactions with data items input in the corresponding transactions. FIG. 4 is a diagram illustrating an example of the data structure of the transaction management table according to the first embodiment. For example, in the transaction “name collation”, there are (1) account number, (2) address, (3) name, (4) telephone number, and (5) account balance as data items.

  The error occurrence rate table 140c is a table for associating transactions, the number of times data has been input to the data item corresponding to the transaction, and the number of error occurrences when data has been input to the data item. In addition, the miss occurrence rate table 140c stores the number of executions and the number of misses depending on whether there is no takeover data, when takeover data is mixed, or when there is takeover data. FIG. 5 is a diagram illustrating an example of the data structure of the miss occurrence rate table.

  Here, the takeover data will be described. In the data item of a series of business transactions, when the content of the data item of the backward transaction overlaps the content of the data item of the forward transaction, this duplicated data is taken as the inherited data. For example, the business “create new savings” includes (1) name identification, (2) cash set, (3) account opening, (4) seal registration, and (5) office approval. Here, since the data item “account number” of the name identification overlaps with the data item “account number” of the cash set behind, the data input to the data item “account number” of the name identification is the data item “cash set data“ The account number can be used as it is. Such overlapping data is taken as inherited data.

  In FIG. 5, the number of executions and the number of mistakes in the case where the transfer data cannot be diverted are registered in all the data items corresponding to the transaction as the number of executions and the number of mistakes of “no takeover data”. For example, in the first row of FIG. 5, the transaction “name identification” indicates that the number of misses is “5” out of the number of executions “15” in the case of “no transfer data”.

  In FIG. 5, the number of executions and the number of mistakes when “takeover data can be diverted” are registered in part of the data items corresponding to the transaction as the number of executions and the number of mistakes of “mixed takeover data”. For example, in the first row of FIG. 5, the transaction “name collation” indicates that the number of misses is “4” out of the number of executions “18” in the case of “mixed takeover data”.

  In FIG. 5, the number of executions and the number of mistakes in the case where transfer data can be diverted are registered in all the data items corresponding to the transaction as the number of executions and the number of mistakes of “with transfer data”. For example, in the first row of FIG. 5, the transaction “name identification” indicates that the number of misses is “0” out of the number of executions “8” in the case of “with transfer data”.

  The control unit 150 includes a detection unit 150a, a determination unit 150b, a display control unit 150c, and an update unit 150d. The control unit 150 corresponds to an integrated device such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). Moreover, the control part 150 respond | corresponds to electronic circuits, such as CPU and MPU (Micro Processing Unit), for example.

  The detection unit 150a receives from the operator terminal 10 the content of the business operated by the operator. The detection unit 150a detects the transaction included in the business by comparing the content of the business with the business management table 140a. The detection unit 150a outputs transaction information included in the business to the determination unit 150b. For example, when the content of the business is “create new savings”, the detection unit 150a (1) name identification, (2) cash set, (3) account opening, (4) seal registration, (5) office approval Is detected.

  The determination unit 150b uses the transaction management table 140b to compare the data items of each transaction of the business, and determines whether the content of the data item of the back transaction overlaps the content of the data item of the front transaction. judge. Then, the determination unit 150b associates each transaction with one of “no takeover data”, “mixed takeover data”, and “with takeover data”. FIG. 6 is a diagram illustrating a correspondence relationship between the transaction and the takeover data.

  The case where business transactions are (1) name identification, (2) cash set, (3) account opening, (4) seal registration, and (5) office approval will be described. The transaction “name identification” is the first transaction. Since there is no transfer data that can be diverted, as shown in FIG. 6, the determination unit 150b associates “name identification” with “no transfer data”.

  The data item “account number” of the transaction “cash set” overlaps with the data item “account number” of the transaction “name identification”, and other data items do not overlap. In this case, as illustrated in FIG. 6, the determination unit 150 b associates “cash set” with “transfer data mixture”.

  The data items “account number”, “name”, and “address” of the transaction “open account” overlap with the data items “account number”, “name”, and “address” of the transaction “name identification”. The data item “amount” of the transaction “open account” overlaps with the data item “amount” of the cash set. Other data items do not overlap. In this case, as illustrated in FIG. 6, the determination unit 150 b associates “account opening” with “transfer data mixture”.

  The data item “account number” of the transaction “seal registration” overlaps with the data item “account number” of the transaction “name identification”. The data item “subject” of the transaction “register seal” overlaps with the data item “subject” of the transaction “open account”. Other data items do not overlap. In this case, as illustrated in FIG. 6, the determination unit 150 b associates “seal registration” with “transfer data mixture”.

  The data items “account number” and “name” of the transaction “approval approval” overlap with the data items “account number” and “name” of the transaction “name identification”. The data item “Amount” of the transaction “Bonus Approval” overlaps with the data item “Amount” of the cash set. Other data items do not overlap. In this case, as illustrated in FIG. 6, the determination unit 150 b associates “account opening” with “transfer data mixture”.

  The determination unit 150b outputs information on the correspondence relationship between the transaction and the takeover data to the display control unit 150c and the update unit 150d.

  The display control unit 150 c is a processing unit that sequentially displays business transactions on the operator terminal 10. For example, when the business operated by the operator is “create new ordinary deposit”, the display control unit 150c displays (1) name identification, (2) cash set, (3) account opening, (4) on the operator terminal 10. Display seal registration and (5) executive approval in order.

  In addition, when displaying a transaction, the display control unit 150c displays a transaction with a miss occurrence rate equal to or higher than a predetermined value in an identifiable manner. For example, the predetermined value is 20%. The display control unit 150c specifies a miss occurrence rate for each transaction based on the correspondence relationship in FIG. 6 and the miss occurrence rate table 140c.

  The display control unit 150c acquires, from the miss occurrence rate table 140c, the miss occurrence rate corresponding to the set of the transaction and the relationship of the takeover data corresponding to the transaction based on the correspondence relationship. FIG. 7 is a diagram showing an example of the error occurrence rate derived from the relationship between each transaction and the takeover data. Each miss occurrence rate in FIG. 7 is obtained by multiplying the value obtained by dividing the number of misses by the number of implementations by 100.

  For example, since the relationship of the transfer data corresponding to the transaction “name identification” is “no transfer data”, the error occurrence rate of the transaction “name identification” is “33.3%”. Since the relationship of the transfer data corresponding to the transaction “cash set” is “mixed transfer data”, the error occurrence rate of the transaction “cash set” is “10.0%”. Since the relationship of the transfer data corresponding to the transaction “open account” is “mixed transfer data”, the error occurrence rate of the transaction “open account” is “20.0%”. Since the relationship of the transfer data corresponding to the transaction “registration seal registration” is “mixed data transfer”, the error occurrence rate of the transaction “registration seal registration” is “8.3%”. Since the relationship of the transfer data corresponding to the transaction “approval approval” is “mixed transfer data”, the error occurrence rate of the transaction “approval approval” is “12.5%”.

  In the above example, transactions with a miss occurrence rate equal to or higher than a predetermined value are “name identification” and “account opening”. For this reason, the display control unit 150c displays the transactions “name collation” and “account opening” in an identifiable manner.

  8 and 9 are diagrams illustrating examples of screens that the display control unit displays on the screen of the operator terminal. As illustrated in FIG. 8, the display control unit 150 c displays a progress bar 20 </ b> A that indicates a transaction of a business “create a new ordinary deposit”. Then, “name identification” and “account opening” that cause the error occurrence rate to be a predetermined value or more are highlighted. For example, the transactions “name collation” and “account opening” on the screen are displayed in red or the like.

  Further, as shown in FIG. 9, the display control unit 150c displays a warning message 20B on a screen for inputting a data item of a transaction with a miss occurrence rate equal to or higher than a predetermined value. In the example illustrated in FIG. 9, the display control unit 150 c displays the alert message 20 </ b> B on the input screen for the data item of the transaction “name identification”.

  The display control unit 150c may change the display color according to the magnitude of the error occurrence rate. For example, the display control unit 150c displays a transaction in blue when the error occurrence rate is less than 10%. The display control unit 150c displays a transaction in yellow when the error occurrence rate is 10% or more and less than 20%. The display control unit 150c displays the transaction in red when the error occurrence rate is 20% or more.

  The update unit 150d is a processing unit that receives an input result of a transaction data item from the operator terminal 10 and updates the error occurrence rate table 140c. The update unit 150d increments the number of executions by 1 when data is input to the transaction data item. Further, if there is a mistake in the data input in the transaction data item, 1 is incremented to the number of misses. The update unit 150d updates the number of executions and the number of mistakes in association with the relationship between the transaction and the takeover data corresponding to the transaction.

  For example, the relationship between the transaction and the takeover data corresponding to the transaction is shown in FIG. In this case, the update unit 150d updates the number of executions and the number of mistakes corresponding to “no takeover data” in the transaction “name identification” in the error occurrence rate table 140c of FIG. The update unit 150d updates the number of executions and the number of mistakes corresponding to “mixed data takeover” in the transactions “cash set”, “account opening”, “stamp registration”, and “approval approval”.

  The update unit 150d may determine whether or not there is a mistake in the data input to the transaction data item. For example, the update unit 150d accesses the master data that manages the address, name, telephone number, account number, and the like using the account number as a key, and determines whether the data input at the operator terminal 10 is correct. Good. For example, in the master data, the name corresponding to the account number key “1234567” is “Taro Nagura”, and the name corresponding to the account number key “1234567” of the data input at the operator terminal 10 is “Jiro Nagura”. . In this case, the update unit 150d determines that there is an input error because the name corresponding to the account number key is different. The master data may be held by the information processing apparatus 100 or may be held by an external data server.

  If there is a mistake in the data input to the transaction data item, the update unit 150d displays the information indicating that the data is input to the transaction data item on the operator terminal 10 again.

  Next, a processing procedure of the information processing apparatus 100 according to the first embodiment will be described. FIG. 10 is a flowchart of the process procedure of the information processing apparatus according to the first embodiment. The process shown in FIG. 10 is executed, for example, when the contents of the business operated by the operator are received.

  As shown in FIG. 10, the information processing apparatus 100 accepts the contents of the business (step S101), and reads the business management table 140a, the transaction management table 140b, and the miss occurrence rate table 140c (step S102).

  The information processing apparatus 100 executes a miss occurrence probability calculation process (step S103), and displays a progress bar on the operator terminal 10 (step S104). In step S <b> 104, the information processing apparatus 100 highlights a transaction on the progress bar whose miss occurrence rate is equal to or higher than a predetermined value. The information processing apparatus 100 displays the transaction on the operator terminal 10 (step S105).

  The information processing apparatus 100 determines whether or not the miss occurrence rate is greater than or equal to a predetermined value (step S106). When the error occurrence rate is less than the predetermined value (No at Step S106), the information processing apparatus 100 proceeds to Step S108.

  When the miss occurrence rate is equal to or higher than the predetermined value (step S106, Yes), the information processing apparatus 100 displays a warning message on the screen displaying the transaction data items (step S107). A transaction is executed at the operator terminal 10 (step S108), and the information processing apparatus 100 determines whether an error has occurred (step S109).

  If an error has occurred (YES in step S109), the information processing apparatus 100 proceeds to step S108. If no error occurs (No at Step S109), the information processing apparatus 100 updates the error occurrence rate table 140c (Step S110).

  When the information processing apparatus 100 is not the final transaction (No at Step S111), the information processing apparatus 100 proceeds to Step S106. On the other hand, in the case of the final transaction (step S111, Yes), the information processing apparatus 100 ends the process.

  Next, the process procedure of the error occurrence probability calculation process shown in step S103 of FIG. 10 will be described. FIG. 11 is a flowchart illustrating a processing procedure of a miss occurrence probability calculation process.

  As illustrated in FIG. 11, the information processing apparatus 100 acquires a transaction (step S201), acquires a data item (step S202), compares the data items of front and rear transactions, and determines whether there is data duplication. Is determined (step S203).

  If there is no data duplication (No at Step S203), the information processing apparatus 100 calculates a miss occurrence rate as no takeover data (Step S204), and proceeds to Step S208.

  On the other hand, if there is data duplication (step S203, Yes), the information processing apparatus 100 determines whether all data items are duplicated (step S205). If some of the data items match (No at Step S205), the information processing apparatus 100 calculates a miss occurrence rate as a mixture of inherited data (Step S206), and proceeds to Step S208.

  If all the data items match (step S205, Yes), the information processing apparatus 100 calculates a miss occurrence rate assuming that there is succeeding data (step S207), and proceeds to step S208.

  The information processing apparatus 100 determines whether the transaction is over (step S208). If the transaction is not over (No at Step S208), the information processing apparatus 100 proceeds to Step S201. When the transaction ends (step S208, Yes), the information processing apparatus 100 displays the transaction display color based on the error occurrence rate (step S209).

  Next, effects of the information processing apparatus 100 according to the first embodiment will be described. The information processing apparatus 100 determines whether or not the contents of a series of transaction data items included in the business processed by the operator overlap. Then, the information processing apparatus 100 distinguishes between the error occurrence rate when the contents of the data items overlap and the error occurrence rate when the data items do not overlap, and stores them in the error occurrence rate table 140c. For this reason, according to the information processing apparatus 100, by using the error occurrence rate table 140c, it is possible to accurately specify the operator error occurrence rate based on the presence or absence of the takeover data, and to appropriately perform the operator support.

  In addition, the information processing apparatus 100 identifies the error occurrence rate for each transaction based on the correspondence between whether the transaction and the transfer data can be used, and displays the transaction in which the error occurrence rate is equal to or higher than a predetermined value in an identifiable manner. , Operator input errors can be prevented.

  In addition, the information processing apparatus 100 displays a series of transactions included in the business with a progress bar, and displays on the progress bar a transaction with an error occurrence rate exceeding a predetermined value, so that an input error occurs. Easy transactions can be warned in advance to the operator.

  Note that the information processing apparatus 100 may register the number of executions and the number of mistakes for the entire operator in the error occurrence rate table 140c illustrated in FIG. 5 or may be registered separately for each operator.

  FIG. 12 is a diagram illustrating a configuration of a system according to the second embodiment. As shown in FIG. 12, this system includes an information processing apparatus 200 and operator terminals 10a to 10d. The information processing apparatus 200 and the operator terminals 10 a to 10 d are connected via the network 50. In the following description, the operator terminals 10a to 10d are collectively referred to as an operator terminal 10 as appropriate.

  The operator terminal 10 is a terminal that displays various types of information related to work. When the operator terminal 10 receives the contents of the business from the operator, the operator terminal 10 inquires the information processing apparatus 200 about the transactions included in the business, and sequentially displays the transactions. The operator refers to the contents of the displayed transaction and inputs data items corresponding to the transaction. The operator terminal 10 transmits a data item corresponding to the transaction to the information processing apparatus 200.

  Also, the operator terminal 10 receives, from the information processing apparatus 200, information on a transaction that is likely to cause an operator to make a data item input mistake among transactions included in the business. The operator terminal 10 displays a warning message when displaying a transaction that is likely to cause an input error.

  The information processing apparatus 200 is an apparatus that holds various types of information related to a business and calculates an occurrence probability of an operator input error for each transaction included in the business. The information processing device 200 notifies the operator terminal 10 of transaction information that is likely to cause an operator to make an input error in a data item.

  A configuration of the information processing apparatus 200 according to the second embodiment will be described. FIG. 13 is a functional block diagram of the configuration of the information processing apparatus according to the second embodiment. As illustrated in FIG. 13, the information processing apparatus 200 includes a communication unit 210, an input unit 220, a display unit 230, a storage unit 240, and a control unit 250.

  The communication unit 210 is a processing unit that performs data communication with the operator terminal 10 via the network 50. For example, the communication unit 210 receives business data selected by the operator, data input in a transaction data item, and the like from the operator terminal 10, and outputs the received information to the control unit 250. Further, when the communication unit 210 receives data addressed to the operator terminal 10 from the control unit 250, the communication unit 210 transmits the data to the operator terminal 10. A control unit 250 described later exchanges data with the operator terminal 10 via the communication unit 210. The communication unit 210 corresponds to a communication device such as a communication module.

  The input unit 220 is an input device that inputs various types of information. For example, the input unit 220 corresponds to a keyboard, a mouse, and a touch panel. The display unit 230 is a display device that displays various types of information. For example, the display unit 230 corresponds to a display or a touch panel.

  The storage unit 240 is a storage device that stores a business management table 240a, an attribute table 240b, a transaction attribute table 240c, and a skill determination table 240d. The storage unit 240 corresponds to, for example, a semiconductor memory device such as a RAM, a ROM, or a flash memory, or a storage device such as a hard disk or an optical disk.

  The business management table 240a is a table that associates a business with a transaction included in the business. FIG. 14 is a diagram illustrating an example of the data structure of the business management table according to the second embodiment. In the example shown in FIG. 14, the business “new savings account” includes (1) name identification, (2) cash set, (3) account opening, (4) seal registration, and (5) office approval. included. The business “cash transfer” includes transactions of (1) name identification, (2) form reading, (3) cash set, (4) seal verification, and (5) data input. Each transaction is processed in the order of (1) to (5).

  The attribute table 240b is a table that associates attributes with factors. FIG. 15 is a diagram illustrating an example of the data structure of the attribute table according to the second embodiment. As shown in FIG. 15, for example, attributes include data input, customer, and cash transaction.

  Factors corresponding to the attribute “data input” include “number of characters” and “character type”. The “number of characters” is classified into 50 characters or less, 51 to 100 characters, and 101 characters or more. Then, the time zone “morning”, “daytime”, and “evening” are associated with each other to determine whether or not the operator is good. The morning corresponds to 9:00 to 12:00, the noon corresponds to 12:00 to 13:00, and the evening corresponds to 13:30 to 15:00. For example, a circle mark indicates that he is good, a triangle mark is normal, and a cross mark is not good.

  For example, in the attribute “data input” in FIG. 15, when the number of characters input by the operator is “50 characters or less”, the operator is required regardless of the time zone “morning”, “daytime”, and “evening”. Processing is shown to be good. Further, for example, in the attribute “data input”, when the character type input by the operator is “kanji” and the time zone is “morning” or “noon”, it is indicated that such processing is normal. Yes. In addition, when the time zone is “evening”, it is indicated that the processing is not good.

  The factor corresponding to the attribute “customer” includes “age”. For example, “age” is classified into 20 years old or less, 21 years old or more and 50 years old or less, and 51 years old or more. Then, the time zone “morning”, “daytime”, and “evening” are associated with each other to determine whether or not the operator is good.

  For example, in the attribute “customer” in FIG. 15, when the customer's age is “20 years or younger” and the time zone is “morning”, the operator indicates that he / she is not good at dealing with the customer. Has been. In addition, in the attribute “customer”, when the customer's age is “20 years or younger” and the time zone is “daytime” or “evening”, the operator indicates that he / she is good at the business with the customer. Has been.

  The factor corresponding to the attribute “cash transaction” includes “amount”. For example, “amount” is classified into 1 million yen or less, 1010,000 yen or more and 5 million yen or less, and 51,000 yen or more. Then, the time zone “morning”, “daytime”, and “evening” are associated with each other to determine whether or not the operator is good.

  For example, in the attribute “cash transaction” in FIG. 15, when the amount of the customer is “1 million yen or less” and the time zone is “morning”, it is indicated that the operator is good at the business of the cash transaction. ing. In addition, in the attribute “cash transaction”, when the amount of the customer is “1 million yen or less” and the time zone is “daytime” or “evening”, the operator indicates that the business of the cash transaction is normal. Has been.

  The transaction attribute table 240c is a table indicating which attribute each transaction belongs to. FIG. 16 is a diagram illustrating an example of the data structure of the transaction attribute table according to the second embodiment. As shown in FIG. 16, the transaction “name identification” belongs to data input and customer. The transaction “cash set” belongs to a cash transaction. The transaction “Open Account” belongs to data entry, customer. The transaction “register seal” belongs to data entry. The transaction “appointment approval” does not belong to any attribute. The transaction “read form” belongs to data entry.

  The skill determination table 240d is a table used when totaling the number of good, normal, and weak points for each transaction. FIG. 17 is a diagram illustrating an example of the data structure of the skill determination table according to the second embodiment. As shown in FIG. 17, the skill determination table 240 d associates transactions, attributes, time zones, factors, numbers of strengths, normal numbers, and numbers of weaknesses.

  For example, the number of characters of the factor corresponding to the name identification attribute “data input” is “50 characters or less”, and the character type is “Kana”. When the time zone is “daytime” and the number of characters is “50 characters or less”, referring to FIG. 15, the operator is good at such work. If the time zone is “daytime” and the character type is “kana”, referring to FIG. 15, the operator is good at such work. Therefore, the number of good points corresponding to the data input is “2”, and the other numbers are “0”.

  The age of the factor corresponding to the name identification attribute “customer” is “21 to 50 years old”. When the time zone is “daytime” and the age is “21 to 50 years old”, referring to FIG. 15, the operator is good at such work. Therefore, the number of customers corresponding to the customer is “1”, and the other numbers are “0”.

  The control unit 250 includes a detection unit 250a, a skill determination unit 250b, a display control unit 250c, and an update unit 250d. The control unit 250 corresponds to, for example, an integrated device such as an ASIC or FPGA. Moreover, the control part 250 respond | corresponds to electronic circuits, such as CPU and MPU, for example.

  The detection unit 250a receives from the operator terminal 10 the content of the business operated by the operator. The detection unit 250a compares the business content with the business management table 240a to detect a transaction included in the business. The detection unit 250a outputs transaction information included in the business to the skill determination unit 250b. For example, when the content of the business is “Create new savings”, the detection unit 250a (1) name identification, (2) cash set, (3) account opening, (4) seal registration, (5) office approval Is detected.

  The skill determination unit 250b uses each transaction, the attribute table 240b, the transaction attribute table 240c, and the skill determination table 240d to add up the number of good points, the normal number, and the poor points for each transaction. The determination unit 250b determines whether or not to alert the corresponding transaction according to the number of good points, the normal number, and the number of weak points for each transaction.

  The process of the skill determination unit 250b will be specifically described. The skill determination unit 250b determines the attribute to which the transaction belongs based on the transaction attribute table 240c, registers the transaction and the attribute in association with each other in the skill determination table 240d. Initial values and time zones of factors corresponding to pairs of transactions and attributes are set in advance.

  The skill determination unit 250b compares the factor of the skill determination table 240d with the transaction attribute table 240c, and counts the number of good points, the normal number, and the weak point for each attribute for each transaction. Then, for example, when there is a transaction with the number of unsatisfactory one or more, the skill determination unit 250b determines that such a transaction is a transaction that the operator is unsatisfactory, and therefore alerts.

  The contents of the factors in the skill determination table 240d are sequentially updated by the update unit 250d in accordance with the data input in the transaction data item after the transaction of the business is started. Each time the factor of the skill determination table 240d is updated, the skill determination unit 250b updates the number of good points, the normal number, and the number of weak points in the skill determination table 240d, and determines a transaction that the operator is not good at. Re-determine whether or not to call attention.

  FIG. 18 is a diagram for explaining the process of the skill determination unit according to the second embodiment. As shown in FIG. 18, the number of characters of the factor corresponding to the data input is updated to “101 characters or more”, and the character type is updated to “mixed”. Referring to FIG. 15, when the time zone is “daytime” and the number of characters is “101 characters or more”, the operator is “not good at” such work. Further, when the time zone is “daytime” and the character type is “mixed”, the operator is not good at such work. Therefore, the skill determination unit 250b updates the number of weak points to “2” and the other numbers to “0”. Since the number of weak points is 1 or more, the skill determination unit 250b determines that the transaction “name identification” is to be alerted.

  The skill determination unit 250b outputs information on the business, a series of transactions included in the business, and transactions that the operator is not good at to the display control unit 250c.

  The display control unit 250 c is a processing unit that sequentially displays business transactions on the operator terminal 10. For example, when the operation operated by the operator is “create new ordinary deposit”, the display control unit 250 c displays (1) name identification, (2) cash set, (3) account opening, (4) on the operator terminal 10. Display seal registration and (5) executive approval in order.

  Moreover, when displaying a transaction, the display control unit 250c displays a transaction for which an alert is made to be identifiable. In addition, when the operator inputs data to the data item, the display control unit 250c displays a warning when receiving information from the skill determination unit 250b that calls attention. Further, similarly to the first embodiment, the display control unit 250c may display a progress bar and highlight a transaction for calling attention. In addition, the display control unit 250c may display transactions in different colors according to the number of good points, the normal number, and the number of poor points.

  The update unit 250d is a processing unit that acquires the data item input to the operator terminal and updates the factor and time zone of the skill determination table 240d based on the content of the acquired data item. In addition, the update unit 250d determines whether or not there is a mistake in the data input to the transaction data item in the same manner as the update unit 150d of the first embodiment. Then, the update unit 250d may update the attribute table 240b based on the determination result. For example, the update unit 250d is not good at updating items in which mistakes have been continuously made, and is good at updating items in which no mistakes are continuously made.

  For example, the factors “number of characters”, “50 or less”, and the time zone “morning” in FIG. 15 are good. Here, in the case of “number of characters”, “50 or less”, and the time zone “morning”, the updating unit 250d changes his / her strength to be unsatisfactory when mistakes occur continuously for a predetermined number of times.

  Next, a processing procedure of the information processing apparatus 200 according to the second embodiment will be described. FIG. 19 is a flowchart of a process procedure of the information processing apparatus according to the second embodiment. The process illustrated in FIG. 19 is executed, for example, when the contents of the business operated by the operator are received.

  The information processing apparatus 200 receives the business content (step S301). The information processing apparatus 200 reads the business management table 240a, the attribute table 240b, and the transaction attribute table 240c (step S302). The information processing apparatus 200 executes a primary skill determination process (step S303).

  The information processing apparatus 200 displays the transaction (step S304) and accepts data (step S305). The information processing apparatus 200 executes skill determination processing (step S306). The information processing apparatus 200 executes the transaction (step S307) and determines whether an error has occurred (step S308).

  If an error has occurred (YES in step S308), the information processing apparatus 200 proceeds to step S307. If no error has occurred (No in step S308), the information processing apparatus 200 updates the attribute table 240b (step S309).

  When the information processing apparatus 200 is not the final transaction (No at Step S310), the information processing apparatus 200 proceeds to Step S304. In the case of the final transaction (step S310, Yes), the information processing apparatus 200 ends the process.

  Next, the processing procedure of the primary skill determination process shown in step S303 of FIG. 19 will be described. FIG. 20 is a flowchart illustrating the processing procedure of the primary skill determination processing according to the present embodiment. As shown in FIG. 20, the information processing apparatus 200 extracts attributes of each transaction (step S320), and sets initial values of attribute factors in the skill determination table 240d (step S321).

  If the attribute is not the end (step S322, No), the information processing apparatus 200 proceeds to step S321. When the attribute is the end (step S322, Yes), the information processing apparatus 200 counts the number of good points, the normal number, and the poor point of each transaction (step S323). The information processing apparatus 200 displays the display color of the transaction based on the number of good points, the normal number, and the number of weak points of each transaction (step S324).

  Next, the process procedure of the skill determination process shown in step S306 of FIG. 19 will be described. FIG. 21 is a flowchart of a process procedure of the skill determination process according to the second embodiment. As shown in FIG. 21, the information processing apparatus 200 extracts factors of each attribute from the data (step S330), and determines the goodness, normality, and weakness corresponding to the factors (step S331).

  If the factor is not the end (step S332, No), the information processing apparatus 200 proceeds to step S331. When the factor is the end (step S332, Yes), the information processing apparatus 200 counts the number of good deals, the normal number, and the number of weak points (step S333). The information processing apparatus 200 displays the display color of the transaction based on the number of good points, the normal number, and the number of weak points of each transaction (step S334).

  Next, effects of the information processing apparatus 200 according to the second embodiment will be described. The information processing apparatus 200 uses each transaction and the attribute table 240b, the transaction attribute table 240c, and the skill determination table 240d to add up the number of good points, the normal number, and the poor point for each transaction. The information processing apparatus 200 determines whether or not to alert the corresponding transaction according to the number of good points, the normal number, and the number of weak points for each transaction. For this reason, in the case of a transaction in which the operator is not good, the operator can be alerted, and an operator's input mistake can be prevented.

  Incidentally, the data structure of the attribute table 240b according to the second embodiment is not limited to that shown in FIG. For example, the concept of time zone may be removed from the attribute table 240b. FIG. 22 is a diagram illustrating an example of another data structure of the attribute table. In FIG. 15, the goodness, normality, and weakness of each factor changed depending on the time zone, but in FIG. 22, it is fixed regardless of the time zone. For example, in the attribute “data input” in FIG. 22, when the number of characters input by the operator is “50 characters or less”, it is indicated that the operator is good at such processing. The skill determination unit 250b may count the number of good, normal, and weak points for each transaction using the attribute table 240b shown in FIG.

  Next, an example of a computer that executes an information processing program that realizes the same function as the information processing apparatus 100 shown in the embodiment will be described. FIG. 23 is a diagram illustrating an example of a computer that executes an information processing program.

  As illustrated in FIG. 23, the computer 300 includes a CPU 301 that executes various arithmetic processes, an input device 302 that receives input of data from a user, and a display 303. The computer 300 also includes a reading device 304 that reads a program or the like from a storage medium, and an interface device 305 that exchanges data with other computers via a network. The computer 300 also includes a RAM 306 that temporarily stores various types of information and a hard disk device 307. The devices 301 to 307 are connected to the bus 308.

  The hard disk device 307 includes, for example, a detection program 307a, a determination program 307b, a display control program 307c, and an update program 307d. The CPU 301 reads each program 307 a to 307 d and develops it in the RAM 306.

  The detection program 307a functions as a detection process 306a. The determination program 307b functions as a determination process 306b. The display control program 307c functions as a display control process 306c. The update program 307d functions as an update process 306d.

  For example, the detection process 306a corresponds to the detection unit 150a. The determination process 306b corresponds to the determination unit 150b. The display control process 306c corresponds to the display control unit 150c. The update process 306d corresponds to the update unit 150d.

  Note that the programs 307a to 307d are not necessarily stored in the hard disk device 307 from the beginning. For example, each program is stored in a “portable physical medium” such as a flexible disk (FD), a CD-ROM, a DVD disk, a magneto-optical disk, and an IC card inserted into the computer 300. Then, the computer 300 may read the programs 307a to 307d from these and execute them.

  The following supplementary notes are further disclosed with respect to the embodiments including the above examples.

(Supplementary note 1)
Identify the business that the user wants to operate,
A plurality of transactions associated with the identified business from a storage device that stores a business management table in which the business, a series of transactions constituting the business, and data items used for the business are associated with each other; Detecting data items used in each of the plurality of transactions,
In the detected series of multiple transaction data items, it is determined whether or not the content of the backward transaction data item overlaps the content of the forward transaction data item among the two transactions performed in succession,
Based on the determination result, the error occurrence rate of the operation by the user when the content of the data item overlaps with the error occurrence rate of the operation by the user when the content of the data item does not overlap, An information processing program for executing each process of associating an error occurrence rate of an operation by a user for each transaction and storing it in the error occurrence rate table of the storage device.

(Supplementary note 2) The operation by the user when the content of the data item overlaps with the content of the data item of another transaction and the content of the data item of each transaction stored in the error occurrence rate table overlaps Corresponding to the miss occurrence rate, the use in the case where the content of the data item does not overlap with the content of the data item of other transactions and the content of the data item of each transaction stored in the miss occurrence rate table The error rate of the
The information processing program according to supplementary note 1, further causing a computer to execute a process of outputting a transaction having an error occurrence rate equal to or higher than a predetermined value in an identifiable manner.

(Appendix 3) Displaying a series of transactions that constitute the business that the user is to operate, and identifying a transaction with a miss occurrence rate equal to or greater than a predetermined value from the displayed series of transactions The information processing program according to appendix 1 or 2, further causing the computer to execute processing to be displayed on the screen.

(Appendix 4) An information processing method executed by a computer,
Identify the business that the user wants to operate,
A plurality of transactions associated with the identified business from a storage device that stores a business management table in which the business, a series of transactions constituting the business, and data items used for the business are associated with each other; Detecting data items used in each of the plurality of transactions,
In the detected series of multiple transaction data items, it is determined whether or not the content of the backward transaction data item overlaps the content of the forward transaction data item among the two transactions performed in succession,
Based on the determination result, the error occurrence rate of the operation by the user when the content of the data item overlaps with the error occurrence rate of the operation by the user when the content of the data item does not overlap, An information processing method, wherein an error occurrence rate of an operation by a user is associated with each transaction and stored in an error occurrence rate table of the storage device.

(Additional remark 5) The operation | movement by the said user when the content of the data item of another transaction and the content of the data item of another transaction and the content of the data item of each transaction memorize | stored in the said error occurrence rate table overlap Corresponding to the miss occurrence rate, the use in the case where the content of the data item does not overlap with the content of the data item of other transactions and the content of the data item of each transaction stored in the miss occurrence rate table The error rate of the
The information processing method according to appendix 4, wherein the computer further executes a process of outputting a transaction having an error occurrence rate equal to or higher than a predetermined value in an identifiable manner.

(Appendix 6) Displaying a series of transactions that make up the business that the user is to operate, and among the displayed series of transactions, transactions that have a miss occurrence rate equal to or greater than a predetermined value can be identified 6. The information processing method according to appendix 4 or 5, further comprising causing the computer to execute a process to be displayed on the screen.

(Supplementary note 7) A memory for storing a business management table that identifies a business to be operated by a user and associates the business, a series of transactions constituting the business, and data items used for the business. From the device, a detection unit that detects a plurality of transactions associated with the identified business, and data items used in each of the plurality of transactions,
Whether or not the content of the data item of the rear transaction of two consecutive transactions performed in the series of data items of the plurality of transactions detected by the detection unit overlaps the content of the data item of the front transaction A determination unit for determining
Based on the determination result of the determination unit, the error occurrence rate of the operation by the user when the content of the data item overlaps, and the error occurrence rate of the operation by the user when the content of the data item does not overlap Distinguishing, an update unit that stores the error occurrence rate of the operation by the user in the error occurrence rate table of the storage device in association with each transaction,
An information processing apparatus comprising:

(Additional remark 8) The operation | movement by the said user when the content of the data item of another transaction and the content of the data item of each transaction stored in the said error occurrence rate table overlap. Corresponding to the miss occurrence rate, the use in the case where the content of the data item does not overlap with the content of the data item of other transactions and the content of the data item of each transaction stored in the miss occurrence rate table The information processing apparatus according to appendix 7, further comprising: a display control unit that associates a mistake occurrence rate of a person and outputs a transaction in which the mistake occurrence rate is equal to or greater than a predetermined value in an identifiable manner.

(Additional remark 9) The said display control part displays the series of several transactions which comprise the operation | work which the said user makes operation object, and mistake occurrence rate is more than predetermined value among these displayed series of several transactions The information processing apparatus according to appendix 7 or 8, further causing the computer to execute a process for displaying the transaction to be identifiable.

DESCRIPTION OF SYMBOLS 100 Information processing apparatus 110 Communication part 120 Input part 130 Display part 140 Storage part 150 Control part

Claims (5)

On the computer,
Identify the business that the user wants to operate,
A plurality of transactions associated with the identified business from a storage device that stores a business management table in which the business, a series of transactions constituting the business, and data items used for the business are associated with each other; Detecting data items used in each of the plurality of transactions,
In the detected series of multiple transaction data items, it is determined whether or not the content of the backward transaction data item overlaps the content of the forward transaction data item among the two transactions performed in succession,
Based on the determination result, the error occurrence rate of the operation by the user when the content of the data item overlaps with the error occurrence rate of the operation by the user when the content of the data item does not overlap, An information processing program for executing each process of associating an error occurrence rate of an operation by a user for each transaction and storing it in the error occurrence rate table of the storage device. A transaction in which the content of the data item overlaps with the content of the data item of another transaction, and an error occurrence rate of the operation by the user when the content of the data item of each transaction stored in the error occurrence rate table overlaps Occurrence of a user's mistake when the content of the data item does not overlap with the content of the data item of another transaction and the content of the data item of each transaction stored in the error occurrence rate table does not overlap Map rates to
The information processing program according to claim 1, further causing the computer to execute a process of outputting a transaction having an error occurrence rate equal to or greater than a predetermined value in an identifiable manner.   A process for displaying a series of transactions that constitute a business to be operated by the user, and displaying among the displayed series of transactions a transaction having an error occurrence rate equal to or higher than a predetermined value in an identifiable manner The information processing program according to claim 1, further causing the computer to execute. An information processing method executed by a computer,
Identify the business that the user wants to operate,
A plurality of transactions associated with the identified business from a storage device that stores a business management table in which the business, a series of transactions constituting the business, and data items used for the business are associated with each other; Detecting data items used in each of the plurality of transactions,
In the detected series of multiple transaction data items, it is determined whether or not the content of the backward transaction data item overlaps the content of the forward transaction data item among the two transactions performed in succession,
Based on the determination result, the error occurrence rate of the operation by the user when the content of the data item overlaps with the error occurrence rate of the operation by the user when the content of the data item does not overlap, An information processing method, wherein an error occurrence rate of an operation by a user is associated with each transaction and stored in an error occurrence rate table of the storage device. From a storage device that stores a business management table that identifies a business to be operated by a user, and associates a business, a series of transactions constituting the business, and data items used for the transaction. A detection unit for detecting a plurality of transactions associated with the identified business and data items used in each of the plurality of transactions;
Whether or not the content of the data item of the rear transaction of two consecutive transactions performed in the series of data items of the plurality of transactions detected by the detection unit overlaps the content of the data item of the front transaction A determination unit for determining
Based on the determination result of the determination unit, the error occurrence rate of the operation by the user when the content of the data item overlaps, and the error occurrence rate of the operation by the user when the content of the data item does not overlap Distinguishing, an update unit that stores the error occurrence rate of the operation by the user in the error occurrence rate table of the storage device in association with each transaction,
An information processing apparatus comprising:

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