JP2018195173A - Information processing apparatus, information processing method, and information processing program - Google Patents

Abstract

To make it possible to determine a user's characteristics.SOLUTION: An information processing apparatus according to the present application comprises: a calculation part; an analysis part; and an output control part. The calculation part calculates the score on merchandise delivery of a store to be analyzed on the basis of information on a result of merchandise delivery of the store to be analyzed. The analysis part performs analysis on merchandise delivery of the store to be analyzed on the basis of the score of the store to be analyzed calculated by the calculation part. The output control part performs output of information based on a result of analysis performed by the analysis part.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an information processing apparatus, an information processing method, and an information processing program.

  In order to increase the efficiency of merchandise delivery, a technique for analyzing merchandise delivery processing is desired. Conventionally, analysis of merchandise delivery processing has been performed based on the operation results of the distribution system.

JP 2001-297140 A

  However, the conventional technology only analyzes the operation of the distribution system, and cannot be said to be performing a highly accurate analysis regarding product delivery.

  The present application has been made in view of the above, and an object of the present application is to enable highly accurate analysis relating to product delivery.

  The information processing apparatus according to the present application includes: a calculation unit that calculates a score related to product delivery in the analysis target store based on performance information related to product delivery in the analysis target store; and a product in the analysis target store based on the score in the analysis target store An analysis unit that performs analysis relating to delivery, and an output control unit that outputs information based on the analysis result of the analysis unit.

  According to one aspect of the embodiment, it is possible to perform highly accurate analysis relating to product delivery.

FIG. 1 is a diagram illustrating an outline of the operation of the information processing apparatus according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of the information processing apparatus according to the embodiment. FIG. 3 is a diagram illustrating a configuration example of the record information storage unit. FIG. 4 is a diagram illustrating an example of performance information. FIG. 5 is a diagram for explaining the merchandise delivery process. FIG. 6 is a diagram illustrating a configuration example of the score information storage unit. FIG. 7 is a diagram illustrating an example of score information. FIG. 8 is a diagram illustrating a configuration example of the business information storage unit. FIG. 9 is a diagram illustrating an example of business information. FIG. 10 is a functional block diagram of the control unit. FIG. 11 is a flowchart of the analysis process. FIG. 12 is a hardware configuration diagram illustrating an example of a computer that implements the functions of the information processing apparatus.

  Hereinafter, an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as “embodiment”) will be described in detail with reference to the drawings. Note that the information processing apparatus, the information processing method, and the information processing program according to the present application are not limited to the following embodiments. In the following embodiments, the same portions are denoted by the same reference numerals, and redundant description is omitted.

[1. Outline of operation of information processing apparatus]
First, an outline of the operation of the information processing apparatus 10 according to the present embodiment will be described. The information processing apparatus 10 is an apparatus that performs analysis related to product delivery in a store (for example, comparison with another store for each product delivery process). The product delivery process is a process constituting the product delivery process. The information processing apparatus 10 performs analysis related to the product delivery in the store based on the past information related to the product delivery in the store (for example, online store). In the following description, the store to be analyzed by the information processing apparatus 10 is referred to as an analysis target store.

  FIG. 1 is a diagram illustrating an outline of the operation of the information processing apparatus 10 according to the embodiment. The information processing apparatus 10 is connected to the terminal device 1 and the server 2 via a network. There may be a plurality of terminal apparatuses 1 and servers 2 connected to the information processing apparatus 10. The terminal device 1 is a terminal used by the store. The terminal device 1 is, for example, a user terminal such as a smartphone, a mobile phone, a tablet terminal, or a personal computer. The server 2 is a server host computer that provides various services to a user or a store. The server 2 is a server that functions as an EC (Electronic Commerce) site, for example. The server 2 provides a service related to product delivery (for example, product delivery management service) to a store clerk who operates the terminal device 1.

  In addition, the server 2 has a management function (order management function) related to the delivery processing of products. The server 2 provides a management service (order management service) related to the merchandise delivery processing to a plurality of stores. The merchandise delivery process is composed of a plurality of merchandise delivery processes such as a shipment waiting process and a shipping process. The server 2 manages the status of the product delivery process for the product delivery process related to the designated product in the store using a flag or the like. The status change may be performed by a store clerk using a user interface provided in the server 2. Further, the server 2 may change the status based on input from a product purchaser, a bank, or the like. The server 2 determines the time taken by the store for each merchandise delivery process based on information on the timing at which the status changes (for example, the timing at which the status changes from waiting for shipment to during shipping processing). The server 2 accumulates the determined time information as store performance information. The product delivery process will be described in detail later. Hereinafter, the outline of the operation of the information processing apparatus 10 will be described with reference to FIG.

  First, the information processing apparatus 10 acquires performance information of an analysis target store (for example, store A) from the server 2 (step S1). The track record information is track record information related to the merchandise delivery process of the store. The merchandise delivery process is composed of a plurality of merchandise delivery processes such as a shipment waiting process and a shipping process. The information processing apparatus 10 acquires, for example, information on the length of time taken for each product delivery process as performance information. For example, the information processing apparatus 10 informs the server 2 that the time spent by the store A in the past “shipping process”, “shipping process” is 5.1 hours and 2.5 hours from the server 2. get. The time may be an average of a past certain period.

  And the information processing apparatus 10 calculates the score regarding the merchandise delivery of an analysis object store based on track record information (step S2). The score indicates the degree of superiority or inferiority of the store product delivery process (or the store product delivery process) by a numerical value or a symbol. For example, the score is obtained by normalizing the processing time required for the merchandise delivery process (or the processing time required for the merchandise delivery process) according to a preset criterion. Various normalization methods can be used. For example, the information processing apparatus 10 may include a time / score conversion table, and calculate the score by applying the processing time to the conversion table. The information processing apparatus 10 may calculate a score so that the shorter the processing time, the better the score (for example, a higher numerical value), and the longer the processing time, the worse the score (for example, the lower numerical value). You may calculate a score so that it may become a high score when close to a reference value. At this time, the “preset reference value” may be, for example, an average value, a mode value, or a median value of processing times of a plurality of stores (for example, a plurality of similar stores). The information processing apparatus 10 calculates a score for the entire product delivery process and a score for each product delivery process. In the example of FIG. 1, the score of the entire product delivery process is “67”, and the scores of the process waiting for shipment and the process in process of shipment are “16” and “88”, respectively.

  Next, the information processing apparatus 10 acquires score information of other stores. The other store is a store different from the analysis target store. There may be a plurality of other stores. The information processing apparatus 10 acquires score information of a plurality of stores. In the example of FIG. 1, the information processing apparatus 10 acquires score information of the store B, score information of the store C, and the like. The score information stores a score calculated according to the same calculation standard as the score of the analysis target store. In the example of FIG. 1, the scores of the entire product delivery process, the shipping waiting process, and the shipping process in store B are “66”, “56”, and “75”, respectively. Further, in the example of FIG. 1, the scores of the entire product delivery process of the store C, the process waiting for shipment, and the process in process of shipment are “64”, “69”, and “52”, respectively.

  Subsequently, the information processing apparatus 10 performs analysis related to product delivery in the analysis target store based on the score of the analysis target store (step S3). For example, the information processing apparatus 10 performs a comparison regarding product delivery between the analysis target store and the other store based on the score of the analysis target store and the score of the other store. Specifically, the information processing apparatus 10 compares the average score of other stores with the score of the analysis target store, and sets the comparison result as the analysis result. For example, if there are two other stores, store A and store B, the information processing apparatus 10 determines the score “66” of the entire product delivery process of store B and the score “64” of the entire product delivery process of store C. An average score of “65” is calculated. Then, the information processing apparatus 10 compares the average score “65” with the score “67” of the entire merchandise delivery process of the store A, and analyzes whether the score of the analysis target store (store A) is high or not. Get as. For example, the information processing apparatus 10 acquires information such as “store A has a higher score” as an analysis result.

  Similarly, the information processing apparatus 10 compares each product delivery process. For example, the information processing apparatus 10 calculates the average score “62.5” of the score “56” of the shipment waiting process of the store B and the score “69” of the shipment waiting process of the store C. Then, the information processing apparatus 10 compares the average score with the score “16” of the store A waiting process for shipping, and acquires information as to whether or not the score of the analysis target store is high as an analysis result. Further, the information processing apparatus 10 calculates an average score “63.5” of the score “75” of the store B shipping process and the score “52” of the store C shipping process. Then, the information processing apparatus 10 compares the average score with the score “88” of the process in the shipping process of the store A, and acquires information as to whether or not the score of the analysis target store is high as an analysis result.

  Note that the information processing apparatus 10 may extract a product delivery process having a score lower than the average score from a plurality of product delivery processes, and acquire the extraction result as an analysis result. For example, it is assumed that only the score of the process waiting for shipment among the plurality of product delivery processes of the store A is lower than the average score. At this time, the information processing apparatus 10 may acquire information such as “low score for waiting for shipment” as an analysis result.

  The other store to be compared may be a similar store similar to the comparison store. For example, the information processing apparatus 10 selects a similar store similar to the store A from other stores using a technique such as clustering. For example, if the store A is a home appliance sales store, the information processing apparatus 10 selects a store whose business type is home appliance sales from other stores as a similar store. Then, the information processing apparatus 10 compares the average score of the similar store and the score of the store A, and acquires a comparison result (for example, information on a product delivery process having a score lower than the average score) as an analysis result.

  And the information processing apparatus 10 outputs an analysis result toward the terminal device 1 (step S4). For example, the information processing apparatus 10 outputs information on a product delivery process having a score lower than the average score as an analysis result. In the example of FIG. 1, the information processing apparatus 10 transmits information indicating that “the shipment waiting score is low” to the terminal apparatus 1.

  As described above, the information processing apparatus 10 calculates the score related to the product delivery of the analysis target store based on the performance information related to the product delivery of the analysis target store. Then, the information processing apparatus 10 performs analysis related to product delivery in the analysis target store based on the score of the analysis target store. The information processing apparatus 10 can accurately analyze the product delivery of the store, not the analysis of the logistics system.

[2. Configuration example of information processing apparatus]
Next, the configuration of the information processing apparatus 10 according to the present embodiment will be described in detail. The information processing apparatus 10 is a computer that processes various types of information. For example, the information processing apparatus 10 is a server host computer (hereinafter simply referred to as “server”) that processes a request from a client terminal (for example, the terminal apparatus 1 or the server 2). The information processing apparatus 10 may be a PC server, a midrange server, or a mainframe server. Moreover, the information processing apparatus 10 may be comprised by one server, and may be comprised by the some server which cooperates and performs a process. When the information processing apparatus 10 includes a plurality of servers, the installation locations of these servers may be separated. Even if the installation locations are separated, these servers can be regarded as one information processing apparatus 10 as long as the processes are executed in cooperation.

  FIG. 2 is a diagram illustrating a configuration example of the information processing apparatus 10 according to the embodiment. The information processing apparatus 10 includes a communication unit 11, an output unit 12, a storage unit 13, and a control unit 14. Note that the configuration shown in FIG. 2 is a functional configuration, and the hardware configuration may be different.

(Communication unit 11)
The communication unit 11 is a communication interface that communicates with an external device. The communication unit 11 may be a network interface or a device connection interface. For example, the communication unit 11 may be a LAN interface such as a NIC (Network Interface Card) or a USB interface configured by a USB (Universal Serial Bus) host controller, a USB port, or the like. The communication unit 11 may be a wired interface or a wireless interface. The communication unit 11 functions as a communication unit of the information processing apparatus 10. The communication unit 11 communicates with an external device under the control of the control unit 14.

(Output unit 12)
The output unit 12 is an output device for notifying the user of information. The output unit 12 is, for example, a display device such as a liquid crystal display or an organic electroluminescence display. Of course, the output unit 12 is not limited to a display device. For example, the output unit 12 may be a sound generator such as a speaker or a buzzer, or may be a lighting device such as an LED (Light Emitting Diode) lamp. The output unit 12 functions as an output unit (notification unit) of the information processing apparatus 10. The output unit 12 outputs various information to the user based on the control of the control unit 14.

(Storage unit 13)
The storage unit 13 is a storage device capable of reading and writing data, such as DRAM (Dynamic Random Access Memory), SRAM (Static Random Access Memory), flash memory, and hard disk. The storage unit 13 functions as a storage unit of the information processing apparatus 10. The storage unit 13 includes a performance information storage unit 131, a score information storage unit 132, and a business information storage unit 133.

(Result information storage unit 131)
The record information storage unit 131 is a storage area for storing record information. The track record information is information that records track records related to merchandise delivery processing in the store. The achievement information is acquired and stored from the server 2 by the acquisition unit 141 described later, for example. The record information may be stored in the record information storage unit 131 by a store clerk, or may be stored in the record information storage unit 131 in advance by the designer or operator of the information processing apparatus 10. FIG. 3 is a diagram illustrating a configuration example of the record information storage unit 131. The record information storage unit 131 stores record information of each of a plurality of stores. For example, the record information storage unit 131 stores record information of store A, record information of store B, record information of store C, and the like. FIG. 4 is a diagram illustrating an example of performance information. In the example of FIG. 4, information on the length of time taken for each product delivery process (processing time information) is stored as performance information. The processing time may be an average time of a predetermined period in the past. In the example of FIG. 4, the average time taken for a new order process, a new reservation process, a reservation process, a payment waiting process, a shipment waiting process, a shipping processing process, an order completion waiting process, an order completion process, and a hold process is 4.3 hours, 4.1 hours, 278.6 hours, 73.5 hours, 5.1 hours, 2.5 hours, 18.3 hours, 1.4 hours, and 17.3 hours, respectively. Information is stored.

  Here, a product delivery process constituting the product delivery process will be described. FIG. 5 is a diagram for explaining the merchandise delivery process. The product delivery process includes a new order process P1, a new reservation process P2, a reservation process P3, a payment waiting process P4, a shipment waiting process P5, a shipping processing process P6, and an order completion waiting process. It has a process P7 and an order completion process P8. Note that each product delivery process shown in FIG. 5 shows an example of classification of product delivery processing. The classification of the merchandise delivery process is not limited to the classification shown in FIG. For example, in the example of FIG. 5, the hold process is not shown, but the product delivery process may include a hold process as the product delivery process. The server 2 has a function of managing which product delivery process the product delivery process is currently in. The store clerk uses the terminal device 1 to determine which status the delivery process of the corresponding product is currently in (that is, which product delivery process the store is currently executing regarding the delivery process of the corresponding product). Input to server 2. It should be noted that the server 2 may automatically input a part of statuses (for example, “new order”, “new reservation”) based on an input (order) related to product purchase by the product purchaser.

  The new order process P1 is a process executed when the store receives an order for a product in stock from a user. In this process, the store clerk performs, for example, confirmation processing of the customer's order contents. The store clerk may perform a process of securing a product in stock using an in-house system or the like so that the ordered product is not sold to other customers. When the user's order is made using the online shopping service of the server 2, the server 2 performs the change of the status to the new order (or the new launch of the status related to the delivery processing of the corresponding product). Also good. When the new order process P1 is completed, the store clerk shifts the merchandise delivery processing to the shipment waiting process P5 or the shipping processing process P6 and sets the status managed by the server 2 to “waiting shipment” or “shipping processing”. Change to If payment from the customer cannot be confirmed, the store clerk may shift the product delivery processing to the payment waiting process P4 and change the status managed by the server 2 to “waiting for payment”. The case where the payment from the customer cannot be confirmed is, for example, the case where the settlement method is bank transfer (not credit settlement or cash on delivery). The server 2 calculates and stores the time (processing time T1 shown in FIG. 5) from when the status is changed to “new order” until it is changed to another status. The processing time T1 calculated by the server 2 may be an average time of the new order process P1 in the past certain period.

  The new reservation process P2 is a process executed when the store receives an order for a product that is not in stock from the user. In this process, the store clerk performs, for example, confirmation processing of the customer's order contents. If the ordered product is a product that has already been released, the store clerk performs a process of placing an order with the manufacturer. When the user's order is made using the online shopping service of the server 2, the server 2 performs the change of the status to the new reservation (or the new launch of the status related to the delivery processing of the corresponding product). Also good. When the new reservation process P2 is completed, the store clerk shifts the product delivery process to the shipment waiting process P5 and changes the status managed by the server 2 to “waiting for shipment”. When the ordered product is not yet released, the store clerk shifts the product delivery process to the reservation process P3 and changes the status managed by the server 2 to “waiting for reservation”. May be. The server 2 calculates and stores a time (processing time T2 shown in FIG. 5) from when the status is changed to “new reservation” until it is changed to another status. The processing time T2 calculated by the server 2 may be an average time of the new reservation process P2 over a certain past period.

  The on-reservation process P3 is a process executed when a product for which an order (reservation order) has been received from a customer is a product that has not yet been released. In this process, the store clerk performs, for example, time limit management until the product release date. A store clerk may place an order for a product from a manufacturer. When the reservation process P3 ends (for example, when a product release date arrives), the store clerk shifts the product delivery process to the shipment waiting process P5 or the shipping process P6 and the status managed by the server 2 Is changed to “Waiting for shipment” or “During shipping”. If payment from the customer cannot be confirmed, the store clerk may shift the product delivery processing to the payment waiting process P4 and change the status managed by the server 2 to “waiting for payment”. The server 2 calculates and stores a time (processing time T3 shown in FIG. 5) from when the status is changed to “reserved” until it is changed to another status. The processing time T3 calculated by the server 2 may be an average time of the reserved process P3 in the past certain period.

  The payment waiting process P4 is a process executed when payment from the customer cannot be confirmed. In this process, the store clerk performs, for example, a confirmation process as to whether or not the customer has received money in the designated account. When the payment waiting process P4 is completed (for example, when payment is confirmed), the store clerk shifts the product delivery process to the shipment waiting process P5 or the shipping process P6 and changes the status managed by the server 2 to “ Change to “Waiting for shipment” or “Processing for shipment”. The server 2 calculates and stores the time (processing time T4 shown in FIG. 5) from when the status is changed to “waiting for payment” until the status is changed to another status. The processing time T4 calculated by the server 2 may be the average time of the payment waiting process P4 in the past certain period.

  The shipment waiting process P5 is a process for preparing shipment (shipping) of goods. In this process, the store clerk performs various processes for preparing for shipment (for example, slip processing). If the product ordered by the customer is out of stock, the store clerk performs a process of confirming whether or not the product has been received from the manufacturer. When the shipment waiting process P5 is completed, the store clerk shifts the product delivery process to the shipping process P6 and changes the status managed by the server 2 to “shipping process”. The server 2 calculates and stores the time (processing time T5 shown in FIG. 5) from when the status is changed to “waiting for shipment” until it is changed to another status. The processing time T5 calculated by the server 2 may be an average time of the shipment waiting process P5 in a certain past period.

  The shipping process P6 is a process for shipping (shipping) merchandise. In this process, a store clerk performs packing and shipping of a product (for example, a delivery instruction to a delivery company). When the shipping process P6 is completed (for example, when shipping of the product is completed), the store clerk shifts the product delivery processing to the order completion waiting process P7 and sets the status managed by the server 2 to “waiting for completion of order”. Change to "". The server 2 calculates and stores the time (processing time T6 shown in FIG. 5) from when the status is changed to “shipping processing” to when the status is changed to another status. The processing time T6 calculated by the server 2 may be an average time of the shipping process P6 in a certain past period.

  The order completion waiting process P7 is a process for confirming the completion of arrival of goods. In this process, the store clerk performs, for example, confirmation processing as to whether or not the product has reached the customer. When the order completion waiting process P7 is completed (for example, when arrival of the product can be confirmed), the store clerk shifts the product delivery processing to the order completion process P8 and sets the status managed by the server 2 to “order completed”. Change to Note that if the delivery company performs the delivery of the product, the status may be changed by the server 2 based on the delivery completion information of the delivery company. The server 2 calculates and stores the time (processing time T7 shown in FIG. 5) from when the status is changed to “waiting for completion of order” until the status is changed to another status. The processing time T7 calculated by the server 2 may be an average time of the order completion waiting process P7 in a certain past period.

  The order completion process P8 is a process for order completion processing. The order completion process is a process for closing the merchandise delivery process (for example, an input to an in-house system for notifying each department in the company that the merchandise delivery has been completed). When the order completion process P8 ends, the store clerk closes the status regarding the corresponding order. The server 2 calculates and stores the time (processing time T8 shown in FIG. 5) from when the status is changed to “order completed” until it is closed. The processing time T8 calculated by the server 2 may be an average time of the order completion process P8 for a certain period in the past.

  The pending process is a process when irregularity occurs. The holding process shifts from, for example, one of the product delivery processes (for example, the new order process P1). In this process, the store clerk checks, for example, whether or not the merchandise is in stock or inquires the customer about the contents of the order. When the problem is solved, the store clerk returns the product delivery process to the original product delivery process and returns the status managed by the server 2 to the original status. The server 2 may calculate and store the time from when the status is changed to “pending” until it returns to the original status. The time calculated by the server 2 may be an average time of a pending process in a past certain period.

(Score information storage unit 132)
The score information storage unit 132 is a storage area for storing score information. The score information is information on a score related to product delivery in the store. The score information stored in the score information storage unit 132 may be a score calculated by the calculation unit 142 described later. The score information may be calculated by another device as long as the calculation criteria are the same. FIG. 6 is a diagram illustrating a configuration example of the score information storage unit 132. The score information storage unit 132 stores score information for each of a plurality of stores. For example, the score information storage unit 132 stores store A score information, store B score information, store C score information, and the like.

  FIG. 7 is a diagram illustrating an example of score information. The score information includes the score of the new order process P1, the score of the new reservation process P2, the score of the reservation process P3, the score of the payment waiting process P4, the score of the waiting process P5, and the shipping process P6. , The order completion waiting process P7 score, the order completion process P8 score, the hold process score, the pre-shipment period score, the post-shipment period score, the overall product delivery process score, and the user Satisfaction and are included. User satisfaction is also a kind of score. The score shown in FIG. 7 is an example. The score information may include a score other than the score shown in FIG. 7, or may not include a part of the score shown in FIG.

  The score of the new order process P1 is a score calculated based on information on the processing time T1 of the new order process P1. In the example of FIG. 7, “82” is stored as the score of the new order process P1. The score of the new reservation process P2 is a score calculated based on information on the processing time T2 of the new reservation process P2. In the example of FIG. 7, “83” is stored as the score of the new reservation process P2. The score of the reserved process P3 is a score calculated based on the information of the processing time T3 of the reserved process P3. In the example of FIG. 7, “75” is stored as the score of the reservation process P3. The score of the payment waiting process P4 is a score calculated based on the information of the processing time T4 of the payment waiting process P4. In the example of FIG. 7, “64” is stored as the score of the deposit waiting process P4. The score of the shipment waiting process P5 is a score calculated based on the information of the processing time T5 of the shipment waiting process P5. In the example of FIG. 7, “16” is stored as the score of the shipment waiting process P5. The score of the shipping process P6 is a score calculated based on the processing time T6 information of the shipping process P6. In the example of FIG. 7, “88” is stored as the score of the shipping process P6. The score of the order completion waiting process P7 is a score calculated based on the processing time T7 information of the order completion waiting process P7. In the example of FIG. 7, “66” is stored as the score of the order completion waiting process P7. The score of the order completion process P8 is a score calculated based on information on the processing time T8 of the order completion process P8. In the example of FIG. 7, “76” is stored as the score of the order completion process P8. The score of the holding process is a score calculated based on information on the time taken for the holding process. In the example of FIG. 7, “53” is stored as the score of the pending process.

  The score of the pre-shipment period is a score calculated based on the information of the pre-shipment period of the store (TA shown in FIG. 5). The “pre-shipment period” is a period required from receiving an order for a specified product to shipping. In the example of FIG. 5, a period TA from the start of the new order process P1 or the new reservation process P2 to the end of the shipping process P6 (start of the order completion waiting process P7) is the pre-shipment period. At this time, the pre-shipment period TA may be the total of the processing times T1 to T6 of the new order process P1 to the shipping process P6. In the example of FIG. 7, “68” is stored as the score of the pre-shipment period.

  The score of the post-shipment period is a score calculated based on the information of the post-shipment period of the store (TB shown in FIG. 5). The “post-delivery period” is the time taken from the shipment of the designated product to the arrival of the designated product. In the example of FIG. 5, a period TB from the end of the shipping process P6 (start of the order completion waiting process P7) to the end of the order completion waiting process P7 (start of the order completion waiting process P8) is a post-shipment period. . At this time, the post-shipment period TB may be the order completion waiting process P7 itself. In the example of FIG. 7, “66” is stored as the score of the post-shipment period.

  The score of the entire product delivery process is a score calculated based on information on the time (TC shown in FIG. 5) required for the entire product delivery process. The processing time TC of the entire product delivery process may be an average of the time taken by the store for the entire delivery process for a certain period in the past. For example, the processing time TC of the entire product delivery process may be the sum of the processing times T1 to T8 of the new order process P1 to the order completion process P8. The processing time TC of the entire product delivery process may include the time taken for the hold process. In the example of FIG. 7, “67” is stored as the score of the entire product delivery process.

  The user satisfaction level is a score indicating the degree of user satisfaction regarding the delivery of merchandise in the store. The user satisfaction may be a score calculated based on the subjective evaluation of the user. For example, the user satisfaction may be a score calculated based on a questionnaire result (for example, a score given by the user subjectively) directed to the user after reaching the product. Alternatively, the user satisfaction may be a score calculated based on an objective index. For example, the user satisfaction is a score calculated based on an index (for example, store sales, number of products delivered from the store in a certain period, customer repeat rate, etc.) that seems to have a correlation with user satisfaction. There may be. Of course, it may be a score calculated using both the subjective evaluation of the user and the objective index. In the example of FIG. 7, “62” is stored as the user satisfaction.

(Business information storage unit 133)
The business information storage unit 133 is a storage area for storing business information. The business information is information related to the product delivery business of the store. The business information is acquired and stored from the server 2 by the acquisition unit 141 described later, for example. The business information may be stored in the business information storage unit 133 by the store clerk, or the designer or operator of the information processing apparatus 10 may store the business information in the business information storage unit 133 in advance. FIG. 8 is a diagram illustrating a configuration example of the business information storage unit 133. The business information storage unit 133 stores business information for each of a plurality of stores. For example, the business information storage unit 133 stores business information of the store A, business information of the store B, business information of the store C, and the like.

  FIG. 9 is a diagram illustrating an example of business information. The business information includes order receiving business information, shipping business information, used delivery company information, and the like. The order receiving work information is information related to the order receiving work of the store. For example, the order receiving work information is information indicating which system the store order receiving system (for example, order receiving software) is. In the example of FIG. 9, information “Use System of Company X” is stored as the ordering work information. The shipping business information is information related to the store shipping business. For example, the shipping operation information is information indicating whether the store shipping operation (shipment operation) is automated or manual (manual). In the example of FIG. 9, information “Use System of Company X” is stored as shipping business information. The used delivery company information is information about a delivery company used by the store for delivery of merchandise. In the example of FIG. 9, information “Use Company Z” is stored as delivery company information.

  The business information shown in FIG. 9 is an example. The business information may not include a part of the information shown in FIG. Further, the business information may include information other than the information shown in FIG. For example, delivery location information, delivery distance information, delivery procedure information, and shipping frequency information may be included. The delivery location information is information indicating to which location (for example, Kanto region in Japan, Kansai region in Japan) the store has been delivered in the past. The delivery distance information is information on the distance required for delivery of the product (for example, the total or average of the delivery distances of the products handled by the store in the past). The delivery procedure information is information indicating a delivery procedure (for example, information on delivery at a nearby convenience store or delivery at a customer's home). The shipping frequency information is information of shipping frequency information (for example, the number of shipments per day). There may be a plurality of shipping frequencies included in the shipping frequency information. For example, the shipping frequency information may include weekday shipping frequency information, holiday shipping frequency information, and shipping frequency information by time of day.

(Control unit 14)
The control unit 14 is a controller, for example, various programs (an example of an analysis program) stored in a storage device inside the information processing apparatus 10 by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. Is realized by using the RAM as a work area. The control unit 14 is a controller, and is realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  FIG. 10 is a functional block diagram of the control unit 14. The control unit 14 includes an acquisition unit 141, a calculation unit 142, an analysis unit 143, a generation unit 144, and an output control unit 145. The blocks (acquisition unit 141 to output control unit 145) that constitute the control unit 14 are functional blocks that indicate the functions of the control unit 14, respectively. These functional blocks may be software blocks or hardware blocks. For example, each functional block described above may be one software module realized by software (including a microprogram), or may be one circuit block on a semiconductor chip (die). Of course, each functional block may be one processor or one integrated circuit. The method of configuring the functional block is arbitrary. As long as “analysis processing” is realized, the control unit 14 may be configured by a functional unit different from these functional blocks.

(Acquisition part 141)
The acquisition unit 141 acquires a score of another store of the calculation unit 142. In addition, the acquisition unit 141 acquires business information related to product delivery from the analysis target store and business information related to product delivery from other stores. In addition, the acquisition unit 141 acquires user satisfaction information regarding product delivery from other stores. The operation of the acquisition unit 141 will be described in detail later in the description of analysis processing.

(Calculation unit 142)
The calculation unit 142 calculates a score related to product delivery in the analysis target store based on the performance information related to product delivery in the analysis target store. For example, the calculation unit 142 calculates at least one individual score of a plurality of product delivery processes constituting the product delivery based on the result information. The operation of the calculation unit 142 will be described in detail later in the description of analysis processing.

(Analysis unit 143)
The analysis unit 143 performs analysis related to product delivery in the analysis target store based on the score of the analysis target store. For example, the analysis unit 143 performs a comparison regarding product delivery between the analysis target store and the other store based on the score of the analysis target store and the score of the other store. The operation of the analysis unit 143 will be described in detail later in the description of analysis processing.

(Generator 144)
The generation unit 144 generates proposal information based on the analysis result of the analysis unit 143. The operation of the generation unit 144 will be described in detail later in the description of analysis processing.

(Output control unit 145)
The output control unit 145 outputs information based on the analysis result of the analysis unit. The output control unit 145 outputs a comparison result between the score of the analysis target store and the average score. Further, the output control unit 145 outputs the proposal information generated by the generation unit 144. The operation of the output control unit 145 will be described in detail later in the description of analysis processing.

[3. Details of operation of information processing apparatus]
Next, the operation of the information processing apparatus 10 will be described. FIG. 11 is a flowchart of the analysis process. The analysis process is a process for performing an analysis related to product delivery in the analysis target store. For example, the analysis process is a process of comparing scores of the analysis target store and other stores and outputting the comparison result as an analysis result. When receiving a processing start instruction from the terminal device 1 via the communication unit 11, the control unit 14 of the information processing device 10 starts analysis processing of the analysis target store (for example, a store that owns the terminal device 1). Hereinafter, the analysis process will be described with reference to FIG.

  First, the acquisition part 141 acquires the performance information regarding the product delivery of an analysis object store (step S11). The acquisition unit 141 may acquire the record information from the server 2 or may acquire the record information directly from the terminal device 1. Moreover, the acquisition part 141 may acquire the performance information previously preserve | saved in the performance information storage part 131 as performance information of an analysis object store. Further, the acquisition unit 141 may acquire the business information of the analysis target store in addition to the result information. At this time, the acquisition unit 141 may acquire business information from the server 2 or may directly acquire business information from the terminal device 1. The acquisition unit 141 may acquire the business information stored in the business information storage unit 133 as the business information of the analysis target store. The acquisition unit 141 may acquire user satisfaction information from the server 2.

  Next, the calculation unit 142 calculates a score related to product delivery in the analysis target store based on the record information acquired in step S11 (step S12). Various methods can be used for calculating the score. For example, the calculation unit 142 may include a time / score conversion table, and calculate the score by applying the processing time included in the record information to the conversion table. Alternatively, the calculation unit 142 acquires a plurality of pieces of processing time information related to product delivery from other stores, sets the plurality of processing times as a population, and scores the processing time positions (for example, deviation values) of the analysis target store in the population. May be calculated as The calculation unit 142 specifies the processing time TC of the entire product delivery process based on the processing time information included in the performance information, and calculates the score of the entire product delivery process based on the processing time TC.

  Further, the calculation unit 142 calculates a score (hereinafter, referred to as an individual score) of each product delivery processing process based on the processing time information of the product delivery processing process included in the record information. For example, the calculation unit 142 calculates the individual score of the new order process P1 based on the processing time T1 of the new order process P1 included in the record information. Similarly, the calculation unit 142 calculates individual scores of the new order process P1 to the order completion process P8 based on the processing times T2 to T8 of the new reservation process P2 to the order completion process P8 included in the record information. In addition, the calculation unit 142 specifies the pre-shipment period TA based on the processing time information included in the record information. Then, the calculation unit 142 calculates a score of the post-shipment period TA based on the post-shipment period TA. In addition, the calculation unit 142 specifies the post-shipment period TB based on the processing time information included in the record information. Then, the calculation unit 142 calculates the score of the post-shipment period TB based on the post-shipment period TB. The score of the post-shipment period TA and the score of the post-shipment period TB are also a kind of individual score.

  Note that the calculation unit 142 may calculate the user satisfaction based on the record information. For example, the calculation unit 142 may calculate the user satisfaction based on the processing time TC of the entire product delivery process. The calculation method may be the same calculation method as the score of the entire product delivery process. In addition, the calculation unit 142 may calculate the user satisfaction based on information separately acquired from the server 2. Then, the acquisition unit 141 may acquire the user satisfaction calculated by the calculation unit 142 as the user satisfaction of the analysis target store.

  Next, the acquisition unit 141 acquires information on other stores (step S13). For example, the acquisition unit 141 acquires a score of another store calculated based on the same calculation standard as the score calculated in step S12. The acquisition unit 141 may acquire a score stored in the score information storage unit 132 as a score of another store, or acquire a score calculated by another device (for example, the server 2) as a score of another store. May be. At this time, the acquisition unit 141 acquires the individual score of each product delivery process in addition to the score of the entire product delivery process. The acquisition unit 141 also acquires the individual score of the post-shipment period TA, the individual score of the post-shipment period TB, and the user satisfaction.

  In addition, the acquisition unit 141 acquires business information of other stores. At this time, the acquisition unit 141 may acquire business information from the server 2 or may directly acquire business information from the terminal device 1. In addition, the acquisition unit 141 may acquire the business information stored in the business information storage unit 133 as business information of another store. In addition, the acquisition unit 141 may acquire information on user satisfaction of other stores from the server 2.

  Next, the analysis unit 143 extracts a store to be compared (hereinafter referred to as a comparison target store) from other stores (step S14). For example, the analysis unit 143 selects a similar store similar to the analysis target store from other stores as the comparison target store. Various methods can be used for selecting similar stores. For example, the analysis unit 143 may select a similar store by cluster analysis based on store information. At this time, the store information is, for example, location information indicating the location of the store, handled product information indicating products handled by the store, and business type information indicating the type of store business (for example, sales of home appliances, food products, etc.). The analysis unit 143 may simply select a store of the same industry as a similar store. For example, if the analysis target store is a home appliance store, a store in which the type of business is home appliance sales may be selected as a similar store from other stores.

  The analysis unit 143 may select a store having a score that satisfies a preset criterion from other stores as a comparison target store. For example, the analysis unit 143 may select a store having the highest score of the entire product delivery process or the highest user satisfaction as a comparison target store from other stores. The other store may be a similar store. For example, the analysis unit 143 may select a store having a score that satisfies a preset criterion from the similar stores as a comparison target store. At this time, the analysis unit 143 may select, as a comparison target store, a store having the highest score of the entire product delivery process from among similar stores. Of course, the analysis unit 143 may select all other stores that have acquired information in step S13 as comparison target stores.

  Subsequently, the analysis unit 143 performs analysis related to product delivery in the analysis target store (that is, analysis of product delivery processing) (step S15). For example, the analysis unit 143 performs a comparison regarding product delivery between the analysis target store and the comparison target store based on the score of the analysis target store and the score of the comparison target store. If the comparison target store is a similar store of the analysis target store, the analysis unit 143 performs the comparison as follows, for example.

  First, the analysis unit 143 calculates an average score of similar stores. The average score is the average score of similar stores. For example, it is assumed that there are two similar stores, store B and store C, the score of the entire product delivery process of store B is “66”, and the score of the entire product delivery process of store C is “64”. At this time, the analysis unit 143 calculates the average score of the entire product delivery process of the similar store as “65”. The average score may be an average individual score. The average individual score is an average of individual scores of similar stores. For example, it is assumed that there are two similar stores, store B and store C, the individual score of the store B waiting process P5 is “56”, and the individual score of the store C waiting process P5 is “69”. At this time, the analysis unit 143 calculates the average individual score of the shipment waiting process P5 of the similar store as “62.5”. Similarly, the analysis unit 143 calculates individual average scores of other product delivery processes. The analysis unit 143 also calculates average individual scores for the pre-shipment period and the post-shipment period. The analysis unit 143 may calculate an average of user satisfaction levels of similar stores.

  And the analysis part 143 compares the score of an analysis object store with an average score, and acquires a comparison result as an analysis result. For example, it is assumed that the score of the entire product delivery process of the analysis target store is “67” and the average score of the entire product delivery process of the similar store is “65”. At this time, the analysis unit 143 compares the score “67” of the entire product delivery process of the analysis target store with the average score “65” of the entire product delivery process of the similar store, and compares the comparison result (for example, “ Information with a higher score ”is obtained as an analysis result. Further, it is assumed that the individual score of the process P5 waiting for shipment in the analysis target store is “16”, and the average individual score of the process P5 waiting for shipment in the similar store is “62.5”. At this time, the analysis unit 143 compares the individual score “16” of the waiting-for-shipment process P5 in the analysis target store with the average individual score “62.5” of the waiting-for-shipment process P5 in the similar store, and compares the comparison result (for example, “ Information that the individual score of the analysis target store is lower ”is acquired as an analysis result. Similarly, the analysis unit 143 also compares the individual score and the average individual score for the pre-shipment period and the post-shipment period. The analysis unit 143 may perform comparison between the user satisfaction level of the analysis target store and the average user satisfaction level of the similar store.

  The analysis unit 143 may compare the plurality of individual scores of the analysis target store with the corresponding average individual scores of the similar stores. And the analysis part 143 may extract the goods delivery process which satisfy | fills the preset reference | standard from the several goods delivery process of an analysis object store based on a comparison result. For example, the analysis unit 143 compares the individual score of the new order process P1 of the analysis target store with the average individual score of the new order process P1 of the similar store. Similarly, the analysis unit 143 compares the individual scores of the new reservation process P2 to the order completion process P8 of the analysis target store with the average individual scores of the new reservation process P2 to the order completion process P8 of the similar store. Then, the analysis unit 143 extracts a product delivery process having a score lower (or higher) than the average individual score from a plurality of product delivery processes in the analysis target store. For example, if only the individual score “16” of the shipment waiting process P5 of the analysis target store is lower than the average individual score, the analysis unit 143 extracts the shipment waiting process P5 as a product delivery process that satisfies the criteria. The analysis unit 143 acquires the extracted product delivery process as an analysis result.

  The analysis unit 143 may select a store having a score that satisfies a preset criterion from the similar stores as a comparison target store. For example, the analysis unit 143 may select the store having the highest score among the similar stores as the comparison target store. More specifically, the analysis unit 143 may select, as a comparison target store, a store having the highest score of the entire product delivery process among similar stores. Alternatively, the analysis unit 143 may select a store having the highest user satisfaction among similar stores as a comparison target store. Of course, the analysis unit 143 may select the store having the lowest score among the similar stores as the comparison target store.

  Then, the analysis unit 143 may compare the score of the selected store (store having a score that satisfies a preset criterion among similar stores) and the score of the analysis target store. For example, the analysis unit 143 compares the individual score of each product delivery process of the comparison target store with the individual score of each product delivery process of the comparison target store, and the individual score of the comparison target store is lower (or higher). Extract the product delivery process. The analysis unit 143 acquires the extracted product delivery process as an analysis result.

  In addition, the analysis unit 143 compares the business information of the selected store (store having a score satisfying a preset criterion among similar stores) with the business information of the analysis target store, and extracts a difference in business. May be. For example, the analysis unit 143 may compare the order receiving work information, the shipping work information, the used delivery company information, the delivery location information, the delivery distance information, the delivery procedure information, and the shipping frequency information, and extract a different part. For example, it is assumed that the order receiving work information of the analysis target store is “use X company system” and the order receiving work information of the selected store is “use Y company system”. In this case, the analysis unit 143 extracts a system used for order receiving work as a different part. Note that the analysis unit 143 extracts business differences by comparing the business information of a store having a score satisfying a preset criterion in “other stores” and not the similar store, with the business information of the analysis target store. May be. The analysis unit 143 acquires a different part as an analysis result.

  Next, the production | generation part 144 produces | generates proposal information based on the analysis result of the analysis part 143 (step S16). The proposal information is recommended information for proposing business improvement to the analysis target store. For example, it is assumed that the individual score of the shipment waiting process P5 of the analysis target store is lower than the average individual score of the shipment waiting process P5 of the similar store. In this case, for example, the generation unit 144 may provide the proposal information that “the score of the process waiting for shipment is low. The score of the entire product shipping process may be improved by improving the work of the process P5 waiting for shipment”. Is generated. Further, it is assumed that the difference between the business of the analysis target store and the business of the comparison target store (for example, the store with high user satisfaction) is a system used for the order receiving business. In this case, for example, the generation unit 144 may propose that the score of the new order process and the new reservation process P2 may be improved by changing the system used for the order receiving work to the Y company system. Is generated.

  Next, the output control unit 145 outputs information based on the analysis result of the analysis unit (step S17). For example, it is assumed that the individual score of the shipment waiting process P5 of the analysis target store is lower than the average individual score of the shipment waiting process P5 of the similar store. In this case, for example, the generation unit 144 outputs information indicating that “the score of the process waiting for shipment is low” to the terminal device 1. The output control unit 145 may output information on the different parts of the business, or may output the proposal information generated in step S16. Note that the output control unit 145 may output information to the output unit 12 instead of the terminal device 1.

  When the output of information is completed, the control unit 14 ends the analysis process.

[4. effect〕
According to the present embodiment, the information processing apparatus 10 is based on the calculation unit 142 that calculates the score related to the product delivery in the analysis target store based on the performance information related to the product delivery in the analysis target store, and the score in the analysis target store. , An analysis unit 143 that performs analysis related to product delivery in the analysis target store, and an output control unit 145 that outputs information based on the analysis result of the analysis unit 143. Since the information processing apparatus 10 performs analysis based on the score of the analysis target store, the information processing device 10 can accurately analyze the product delivery of the store without depending on the physical distribution system used by the store.

  The information processing apparatus 10 further includes an acquisition unit 141 that acquires a score of another store. And the analysis part 143 performs the comparison regarding merchandise delivery of an analysis object store and another store based on the score of an analysis object store, and the score of another store. Then, the output control unit 145 outputs information based on the comparison result of the analysis unit 143. Thereby, the information processing apparatus 10 can perform highly accurate analysis based on comparison with other stores. Since the score of the analysis target store is compared with the score of the other store, even if the distribution system used by the analysis target store is different from the distribution system used by the other store, the information processing apparatus 10 is related to the product delivery. A comparison can be made.

  The other stores include similar stores similar to the analysis target store. And the analysis part 143 performs the comparison regarding goods delivery of an analysis object store and a similar store based on the score of an analysis object store, and the score of a similar store. Then, the output control unit 145 outputs information based on the comparison result of the analysis unit 143. Since the information processing apparatus 10 does not simply compare with other stores but compares with similar stores, it can perform analysis with higher accuracy.

  The analysis unit 143 also compares the score of the analysis target store with the average score that is the average of the scores of the similar stores. Then, the output control unit 145 outputs information based on the comparison result of the analysis unit 143. This makes it easy for the user (analysis target store) to know his / her position in the entire similar store.

  The analysis unit 143 also compares the score of the analysis target store with the score of a store having a score that satisfies a predetermined criterion in the similar stores. Then, the output control unit 145 outputs information based on the comparison result of the analysis unit 143. Thereby, the user (analysis target store) can easily compare the store with a high (or low) score with itself.

  In addition, the acquisition unit 141 acquires information on user satisfaction regarding product delivery in the similar store, and the analysis unit 143 stores the score of the analysis target store and the user satisfaction satisfying predetermined criteria in the similar store. The score is compared. Then, the output control unit 145 outputs information based on the comparison result of the analysis unit 143. Thereby, the user (analysis target store) can easily compare the store with high (or low) user satisfaction with the store itself.

  The acquisition unit 141 acquires business information related to product delivery in the analysis target store and business information related to product delivery in another store, and the analysis unit 143 is based on the score of the analysis target store and the score of the other store. The store having a score satisfying a predetermined criterion is selected from the other stores, the business information of the store is compared with the business information of the analysis target store, and the business difference is extracted, and the output control unit 145 Outputs information indicating the difference. Thereby, the user can know the difference in business between the analysis target store and the comparison target store.

  Further, the business information includes at least one information selected from the order business information, shipping work information, used delivery company information, delivery location information, delivery distance information, delivery procedure information, and shipping frequency information. Thereby, the user can know the difference in various operations between the analysis target store and the comparison target store.

  In addition, the calculation unit 142 calculates a score based on the length of time taken for product delivery. Thereby, the information processing apparatus 10 can perform highly accurate analysis based on the length of time.

  The product delivery is composed of a plurality of product delivery processes. Further, the score relating to the product delivery includes an individual score that is a score of the product delivery process. Then, the calculation unit 142 calculates at least one individual score of the plurality of product delivery processes based on the result information. And the analysis part 143 performs the analysis regarding goods delivery of an analysis object store based on the individual score of an analysis object store. Since the information processing apparatus 10 performs analysis related to product delivery in the analysis target store using the individual score, analysis with higher accuracy can be performed.

  The information processing apparatus 10 further includes an acquisition unit 141 that acquires individual scores of other stores. And the analysis part 143 performs the comparison regarding merchandise delivery of an analysis object store and another store based on the individual score of an analysis object store, and the individual score of another store. Then, the output control unit 145 outputs information based on the comparison result of the analysis unit 143. Thereby, the information processing apparatus 10 can perform highly accurate analysis based on comparison with other stores. Since the individual score of the analysis target store is compared with the individual score of the other store, even if the distribution system used by the analysis target store is different from the distribution system used by the other store, the information processing apparatus 10 It is possible to compare delivery.

  The other stores include similar stores similar to the analysis target store. Then, the analysis unit 143 compares the product delivery between the analysis target store and the similar store based on the individual score of the analysis target store and the individual score of the similar store, and the output control unit 145 determines the comparison result of the analysis unit 143. Output information based on. Since the information processing apparatus 10 does not simply compare with other stores but compares with similar stores, it can perform analysis with higher accuracy.

  The analysis unit 143 compares the individual score of the analysis target store with the average individual score that is the average of the scores of the similar stores, and the output control unit 145 outputs information based on the comparison result of the analysis unit 143. I do. This makes it easy for the user (analysis target store) to know his / her position in the entire similar store.

  In addition, the calculation unit 142 calculates individual scores for a plurality of product delivery processes in the analysis target store, and the analysis unit 143 calculates a plurality of individual scores in the analysis target store respectively for the average individual corresponding to the similar store. A product delivery process that satisfies a predetermined standard is extracted from a plurality of product delivery processes in the analysis target store based on the comparison result, and the output control unit 145 extracts the product delivery process extracted by the analysis unit 143. The information indicating is output. Thereby, the user (analysis object store) can easily know the product delivery process inferior or superior to other stores.

  The plurality of product delivery processes include a new order process P1, a new reservation process P2, a reservation process P3, a payment waiting process P4, a shipping waiting process P5, a shipping processing process P6, and an order completion waiting process. A process P7 and an order completion process P8 are included. Thereby, the user can know the analysis result of various goods delivery processes.

  Moreover, the production | generation part 144 which produces | generates proposal information based on the analysis result of the analysis part 143 is further provided. The output control unit 145 outputs proposal information. Thereby, the user (analysis target store) can easily know the work to be improved.

[5. (Modification)
The above-described embodiment shows an example, and various changes and applications are possible.

  For example, in the above-described embodiment, an online store is exemplified as a “store” that handles products, but the store is not limited to an online store. For example, the store may be an actual store where a store is set up and a customer is bought and sold. It is also possible to regard an individual who conducts a business transaction as a store.

  In the above-described embodiment, the pre-shipment period TA is a period from the start of the new order process P1 or the new reservation process P2 to the end of the shipping process P6 (start of the order completion waiting process P7). However, the pre-shipment period TA may be different for each designated product. For example, the pre-shipment period TA may be different for products that are in stock in the store and products that are not in stock. For example, in the case of a commodity in stock in the store, the pre-shipment period TA is the sum of the processing time T1 of the new order process P1, the processing time T5 of the waiting process P5, and the processing time T6 of the shipping process P6. It may be. For products that are not in stock in the store, the pre-shipment period TA is the sum of the processing time T2 of the new reservation process P2, the processing time T5 of the waiting process P5, and the processing time T6 of the shipping process P6. May be. The processing time T3 of the reservation process P3 and the processing time T4 of the payment waiting process P4 may or may not be included in the pre-shipment period TA.

  In the above-described embodiment (step S12), the calculation unit 142 calculates the score based on the length of time taken for the product delivery. However, the calculation unit 142 may calculate the score based on unevenness of time (for example, variance, standard deviation) required for product delivery. For example, the calculation unit 142 acquires a plurality of processing times for the entire product delivery in the store, and calculates a variance of the plurality of processing times. Alternatively, the calculation unit 142 acquires a plurality of processing times required for a product delivery process with a store, and calculates a variance of the plurality of processing times. And the calculation part 142 may calculate a score based on dispersion | distribution.

  In this case, the calculation unit 142 may change the score calculation method for each designated product. For example, in the case of a product that is not in stock in the store (or a reserved product for which the release date has not yet arrived), the calculation unit 142 calculates a score based on unevenness in the time taken to deliver the product, and otherwise (for example, In the case of a product in stock in the store, the score may be calculated based on the length of time taken for the product delivery. Then, the analysis unit 143 performs an analysis using a score based on the unevenness of the time taken for the delivery of the product when the product is not in stock in the store (or a reserved product for which the release date has not yet arrived). In the case of other than (for example, a product in stock in the store), the analysis may be performed using a score based on the length of time taken to deliver the product.

  In the above-described embodiment (step S12), the calculation unit 142 calculates the individual scores for all of the plurality of product delivery processes. However, the individual score calculated by the calculation unit 142 may be a part of a plurality of product delivery processes. For example, the calculation unit 142 may calculate individual scores of the shipment waiting process P5, the shipping process P6, and the order completion waiting process P7 among the plurality of product delivery processes. Then, the analysis unit 143 receives the individual scores of the process P5, the shipping process P6, and the order completion process P7 of the analysis target store, the shipping process P5, the shipping process P6, and the order completion of the other stores. Based on the individual score of the waiting process P7, an analysis related to product delivery in the analysis target store may be performed. The shipment waiting process P5, the shipping process P6, and the order completion waiting process P7 are merchandise delivery processes that do not depend much on customer behavior. The information processing apparatus 10 performs analysis using the individual scores of the shipment waiting process P5, the shipping process P6, and the order completion waiting process P7, thereby enabling more realistic analysis.

  In the above-described embodiment (step S15), an example of processing performed by the analysis unit 143 assuming that the comparison target store is a similar store is shown, but the comparison target store is not necessarily a similar store. The comparison target store may simply be “another store”. In this case, the term “similar store” shown in step S15 can be replaced with “other store”.

  In the above-described embodiment (step S15), the comparison between the analysis target store and the comparison target store is “analysis regarding product delivery”, but “analysis regarding product delivery” is a comparison between the analysis target store and the comparison target store. It is not limited to. For example, the “analysis regarding product delivery” may be a comparison between a score (or individual score) of the analysis target store and a score (or individual score) set in the information processing apparatus 10 in advance.

  Further, in the above-described embodiment (step S17), the output control unit 145 outputs information on a product delivery process with a low individual score and information on a part of a business difference. However, the information output by the output control unit 145 is not limited to such information. For example, the output control unit 145 may be configured to output to the user information on the processing time of each product delivery process (for example, information on the average processing time of each product delivery process) included in the record information. At this time, the output control unit 145 may be configured to output processing time information to the user together with a process diagram as shown in FIG. 5, for example. The output control unit 145 may be configured to output a delivery shortening period when the analysis target store performs business improvement according to the proposal information.

  Further, the information output by the output control unit 145 may be an alert (warning) to the user (analysis target store). For example, the output control unit 145 outputs an alert when the score (or individual score) of the analysis target store continuously satisfies a preset criterion (for example, when the score is lower than a threshold) for a preset period. It may be configured to. The alert may be information displayed on the screen, or may be a sound notification (for example, a buzzer or a sound warning).

  The control device that controls the information processing apparatus 10 according to the present embodiment may be realized by a dedicated computer system or an ordinary computer system. For example, a program for executing the above-described operation is stored and distributed in a computer-readable recording medium such as an optical disk, a semiconductor memory, a magnetic tape, or a flexible disk, the program is installed in the computer, and the above-described processing is performed. You may comprise a control apparatus by performing. The control device may be an external device (for example, a personal computer) of the information processing apparatus 10 or an internal device (for example, the control unit 14). Further, the program may be stored in a disk device provided in a server device on a network such as the Internet so that it can be downloaded to a computer. Further, the above-described functions may be realized by cooperation between an OS (Operating System) and application software. In this case, a part other than the OS may be stored and distributed in a medium, or a part other than the OS may be stored in a server device and downloaded to a computer.

[6. Hardware configuration)
The information processing apparatus 10 according to the embodiment and the modification can be realized by a computer 1000 having a configuration as illustrated in FIG. 12, for example. FIG. 12 is a hardware configuration diagram illustrating an example of a computer that implements the functions of the information processing apparatus 10. The computer 1000 includes a CPU (Central Processing Unit) 1100, a RAM 1200, a ROM 1300, an HDD (Hard Disk Drive) 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F). ) 1700.

  The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 and controls each unit. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, a program depending on the hardware of the computer 1000, and the like.

  The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. The communication interface 1500 receives data from other devices via the network N and sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the network N.

  The CPU 1100 controls an output device such as a display and a printer and an input device such as a keyboard and a mouse via an input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. In addition, the CPU 1100 outputs the generated data to the output device via the input / output interface 1600.

  The media interface 1700 reads a program or data stored in the recording medium 1800 and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads such a program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. Etc.

  For example, when the computer 1000 functions as the information processing apparatus 10 according to the embodiment, the CPU 1100 of the computer 1000 implements the function of the control unit 14 by executing a program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them. However, as another example, these programs may be acquired from other devices via the network N.

  As described above, some of the embodiments of the present application have been described in detail with reference to the drawings. However, these are merely examples, and various modifications based on the knowledge of those skilled in the art, including the aspects described in the disclosure line of the invention. It is possible to implement the present invention in other forms with improvements.

[7. Others]
In addition, among the processes described in the above embodiments, all or a part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed All or a part of the above can be automatically performed by a known method. In addition, the processing procedures, specific names, and information including various data and parameters shown in the document and drawings can be arbitrarily changed unless otherwise specified. For example, the various types of information illustrated in each drawing is not limited to the illustrated information.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured.

  Moreover, each embodiment mentioned above can be combined suitably in the range which does not contradict a process content.

  In addition, the “section (module, unit)” described above can be read as “means” or “circuit”. For example, the calculation unit can be read as calculation means or a calculation circuit.

DESCRIPTION OF SYMBOLS 1 ... Terminal device 2 ... Server 10 ... Information processing apparatus 11 ... Communication part 12 ... Output part 13 ... Memory | storage part 131 ... Performance information memory | storage part 132 ... Score information memory | storage part 133 ... Business information memory | storage part 14 ... Control part 141 ... Acquisition part 142 ... Calculation unit 143 ... Analysis unit 144 ... Generation unit 145 ... Output control unit

Claims (20)

A calculation unit that calculates a score related to product delivery in the analysis target store based on the performance information related to product delivery in the analysis target store;
Based on the score of the analysis target store, an analysis unit that performs analysis on product delivery of the analysis target store;
An output control unit for outputting information based on the analysis result of the analysis unit;
An information processing apparatus comprising: An acquisition unit for acquiring scores of other stores;
The analysis unit, based on the score of the analysis target store and the score of the other store, performs a comparison regarding product delivery between the analysis target store and the other store,
The output control unit outputs information based on the comparison result of the analysis unit;
The information processing apparatus according to claim 1. The other store includes a similar store similar to the analysis target store,
The analysis unit performs a comparison regarding product delivery between the analysis target store and the similar store based on the score of the analysis target store and the score of the similar store,
The output control unit outputs information based on the comparison result of the analysis unit;
The information processing apparatus according to claim 2. The analysis unit compares the score of the analysis target store with an average score that is an average of the scores of the similar stores,
The output control unit outputs information based on the comparison result of the analysis unit;
The information processing apparatus according to claim 3. The analysis unit compares the score of the analysis target store with the score of a store having a score satisfying a predetermined criterion in the similar store,
The output control unit outputs information based on the comparison result of the analysis unit;
The information processing apparatus according to claim 3, wherein the information processing apparatus is an information processing apparatus. The acquisition unit acquires user satisfaction information related to product delivery of the similar store,
The analysis unit compares the score of the analysis target store with the score of a store having user satisfaction satisfying a predetermined criterion in the similar store,
The output control unit outputs information based on the comparison result of the analysis unit;
The information processing apparatus according to claim 3, wherein the information processing apparatus is an information processing apparatus. The acquisition unit acquires business information related to product delivery of the analysis target store and business information related to product delivery of the other store,
The analysis unit selects a store having a score satisfying a predetermined criterion from the other stores based on the score of the analysis target store and the score of the other store, and the business information of the store and the analysis target store Compare with the business information of
The output control unit outputs information indicating the difference;
The information processing apparatus according to any one of claims 2 to 6. The business information includes at least one information selected from order business information, shipping work information, used delivery company information, delivery location information, delivery distance information, delivery procedure information, and shipping frequency information.
The information processing apparatus according to claim 7. The calculation unit calculates a score based on the length of time taken for the product delivery.
The information processing apparatus according to claim 1, wherein the information processing apparatus is an information processing apparatus. The calculation unit calculates a score based on unevenness of time required for product delivery.
The information processing apparatus according to any one of claims 1 to 9. The product delivery comprises a plurality of product delivery processes,
The score related to the product delivery includes an individual score that is a score of the product delivery process,
The calculation unit calculates at least one individual score of the plurality of product delivery processes based on the performance information,
The analysis unit performs an analysis on product delivery of the analysis target store based on the individual score of the analysis target store.
The information processing apparatus according to claim 1. An acquisition unit for acquiring individual scores of other stores;
The analysis unit performs a comparison on product delivery between the analysis target store and the other store based on the individual score of the analysis target store and the individual score of the other store,
The output control unit outputs information based on the comparison result of the analysis unit;
The information processing apparatus according to claim 11. The other store includes a similar store similar to the analysis target store,
The analysis unit performs a comparison of product delivery between the analysis target store and the similar store based on the individual score of the analysis target store and the individual score of the similar store,
The output control unit outputs information based on the comparison result of the analysis unit;
The information processing apparatus according to claim 12. The analysis unit compares an individual score of the analysis target store with an average individual score that is an average of scores of the similar stores,
The output control unit outputs information based on the comparison result of the analysis unit;
The information processing apparatus according to claim 13. The calculation unit calculates individual scores for a plurality of product delivery processes in the analysis target store,
The analysis unit compares each of the plurality of individual scores of the analysis target store with a corresponding average individual score of the similar store, and determines from a plurality of product delivery processes of the analysis target store based on a comparison result Product delivery processes that meet the criteria of
The output control unit outputs information indicating a product delivery process extracted by the analysis unit;
The information processing apparatus according to claim 13 or 14, characterized in that: The plurality of product delivery processes include a new order process, a new reservation process, a reservation process, a payment waiting process, a shipment waiting process, a shipping processing process, an order completion waiting process, and an order completion process. , Including,
The information processing apparatus according to any one of claims 12 to 15. The calculation unit calculates an individual score of a process waiting for shipment, a process in process of shipping, and a process waiting for completion of order among the plurality of product delivery processes,
The analysis unit includes individual scores of a process waiting for shipment of the analysis target store, a process waiting for shipping, and a process waiting for completion of orders, and individual scores of a process waiting for shipment of the other store, a process waiting for shipping, and a process waiting for completion of orders. And analyzing the product delivery of the analysis target store based on
The information processing apparatus according to claim 16. A generation unit that generates proposal information based on the analysis result of the analysis unit;
The output control unit outputs the proposal information;
The information processing apparatus according to claim 1, wherein the information processing apparatus is an information processing apparatus. An information processing method executed by an information processing apparatus,
A calculation step of calculating a score relating to the product delivery of the analysis target store based on the result information relating to the product delivery of the analysis target store;
Based on the score of the analysis target store, an analysis step for performing analysis related to product delivery of the analysis target store;
An output control step for outputting information based on the analysis result of the analysis step;
An information processing method comprising: A calculation procedure for calculating a score relating to product delivery in the analysis target store based on the performance information relating to product delivery in the analysis target store;
Based on the score of the analysis target store, an analysis procedure for performing analysis related to product delivery of the analysis target store;
An output control procedure for outputting information based on the analysis result of the analysis procedure;
An information processing program for causing a computer to execute.

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