WO2021181357A1

WO2021181357A1 - System and method for post-dispatched return to origin prediction of a package in logistics

Info

Publication number: WO2021181357A1
Application number: PCT/IB2021/052081
Authority: WO
Inventors: Vipul M YADAV; Bharat A. KAROTRA; Paresh Bhupat PARMAR; Nikul Jaysukhbhai DODIYA; Zaiba Umer SARANG
Original assignee: Ithink Logistic Quick Services Llp
Priority date: 2020-03-13
Filing date: 2021-03-12
Publication date: 2021-09-16

Abstract

A system for post-dispatched return to origin prediction of a package in logistics is disclosed. The system includes a return to origin factor collection subsystem configured to collect a plurality of post-dispatched return to origin (RTO) factors associated with a package delivery in the logistics; a post-dispatch return to origin score prediction subsystem configured to assign a post-dispatch return to origin (RTO) score corresponding to each of a plurality of collected post-dispatched return to origin factors, to compute a variation of an assigned post-dispatch return to origin (RTO) score based on one or more predefined conditions and to predict a post-dispatch return to origin score based on a computed variation of the assigned post-dispatch return to origin (RTO) score using a return to origin prediction technique.

Description

SYSTEM AND METHOD FOR POST-DISPATCHED RETURN TO ORIGIN PREDICTION OF A PACKAGE IN LOGISTICS

This International Application claims priority from a Patent application filed in India having Patent Application No. 202021010933, filed on March 13, 2020, and titled “SYSTEM AND METHOD FOR POST-DISPATCHED RETURN TO ORIGIN PREDICTION OF A PACKAGE IN LOGISTICS”.

BACKGROUND

Embodiments of the present disclosure relate to a logistics risk prediction and more particularly to, a system and a method for post-dispatched return to origin prediction of a package in logistics.

Logistics services field is important to people and businesses across the world. Providing managed and organised delivery services by the logistics partners is a challenging task with many facets. While the logistics services field has grown and matured over the years, delivery and shipping inefficiencies still cause substantial problems for shipping senders, shipping recipients, and shipping carriers alike. In particular, it becomes difficult for the shipping senders and/or recipients to accurately estimate transit time for a given shipment or package. Also, the risk prediction associated with the logistics becomes difficult. Generally, the risk associated with the logistics is related to return to origin (RTO) of the package. The RTO refers as a package has failed to deliver to an end consumer after more than one attempts by the logistics partners. There are various reasons for which the package doesn't reach to the end consumer and returns back to e-seller. Various systems are available which helps in estimating the RTO percentage of the package.

Conventionally, the system available for estimating the RTO percentage of the package includes identifying the one or more reasons which leads to failure of the package in reaching the customer end and instead returning to the e-seller. However, such conventional system are unable to help the e-seller to know about the future RTO and help to minimize the RTO ratio by identifying contribution of one or more significant factors for the RTO of the package. Also, such conventional system is unable to predict the package getting return to the seller or to the origin within a predefined interval of time upon dispatching. Moreover, such conventional system in unable to generate an automated action/communication channel to inform the seller as a result, there is a significant loss to the e-seller business.

Hence, there is a need for an improved system and a method for post-dispatched return to origin prediction of a package in logistics.

BRIEF DESCRIPTION

In accordance with an embodiment of the present disclosure, a system for post- dispatched return to origin prediction of a package in logistics is disclosed. The system includes a return to origin factor collection subsystem configured to collect a plurality of post-dispatched return to origin (RTO) factors associated with a package delivery in the logistics. The system also includes a post-dispatch return to origin score prediction subsystem operatively coupled to the return to origin factor collection subsystem. The post-dispatch return to origin score prediction subsystem is configured to assign a post-dispatch return to origin (RTO) score corresponding to each of a plurality of collected post-dispatched return to origin factors. The post-dispatch return to origin score prediction subsystem is also configured to compute a variation of an assigned post-dispatch return to origin (RTO) score based on one or more predefined conditions. The post-dispatch return to origin score prediction subsystem is also configured to predict a post-dispatch return to origin score based on a computed variation of the assigned post-dispatch return to origin (RTO) score using a return to origin prediction technique.

In accordance with another embodiment of the present disclosure, a method for post- dispatched return to origin prediction of a package in logistics is disclosed. The method includes collecting, by a return to origin factor collection subsystem, a plurality of post-dispatched return to origin (RTO) factors associated with a package delivery in the logistics. The method also includes assigning, by a post-dispatch return to origin score prediction subsystem, a post-dispatch return to origin (RTO) score corresponding to each of a plurality of collected post-dispatched return to origin factors. The method also includes computing, by the post-dispatch return to origin score prediction subsystem, a variation of an assigned post-dispatch return to origin (RTO) score based on one or more predefined conditions. The method also includes predicting, by the post-dispatch return to origin score prediction subsystem, a post dispatch return to origin score based on a computed variation of the assigned post dispatch return to origin (RTO) score using a return to origin prediction technique.

To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures. BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:

FIG. 1 is a block diagram of a system for post-dispatched return to origin prediction of a package in logistics in accordance with an embodiment of the present disclosure. FIG. 2 illustrates a schematic representation of an exemplary embodiment of a system for post-dispatched return to origin prediction of a package in logistics in accordance with an embodiment of the present disclosure.

FIG. 3 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure. FIG. 4 is a flow chart representing the steps involved in a method for post-dispatched return to origin prediction of a package in logistics of FIG. 1 in accordance with the embodiment of the present disclosure.

Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.

DETAILED DESCRIPTION

For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.

The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.

In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.

Embodiments of the present disclosure relate to a system for post-dispatched return to origin prediction of a package in logistics. The system includes a return to origin factor collection subsystem configured to collect a plurality of post-dispatched return to origin (RTO) factors associated with a package delivery in the logistics. The system also includes a post-dispatch return to origin score prediction subsystem operatively coupled to the return to origin factor collection subsystem. The post-dispatch return to origin score prediction subsystem is configured to assign a post-dispatch return to origin (RTO) score corresponding to each of a plurality of collected post-dispatched return to origin factors. The post-dispatch return to origin score prediction subsystem is also configured to compute a variation of an assigned post-dispatch return to origin (RTO) score based on one or more predefined conditions. The post-dispatch return to origin score prediction subsystem is also configured to predict a post-dispatch return to origin score based on a computed variation of the assigned post-dispatch return to origin (RTO) score using a return to origin prediction technique.

FIG. 1 is a block diagram of a system (100) for post-dispatched return to origin prediction of a package in logistics in accordance with an embodiment of the present disclosure. The system (100) includes a return to origin factor collection subsystem (110) configured to collect a plurality of post-dispatched return to origin (RTO) factors associated with a package delivery in the logistics. As used herein, the term ‘return to origin (RTO)’ is defined as a non-deliverability of a package to an end-consumer by a logistics partner and return of the package to a seller’s address. Similarly, the term ‘post-dispatched return to origin’ is defined as indicating a chance of the return to origin of the package after the package gets picked up from the seller’s address. In one embodiment, the plurality of post-dispatched return to origin (RTO) factors may include at least one of an identification of slow-moving status of a package, out for delivery (OFD) failed status for a package, a lost status of a package, a misrouted package, a pre-dispatched RTO point count, identification of logistics partner dispatch / delivery center (DC) performance (any name which refer to shipment out for delivery location), identification of total delay in dispatch, determination of delay in time from the DC to out for delivery, undelivered reasons or non-delivery remark or a combination thereof.

The system (100) also includes a post-dispatch return to origin score prediction subsystem (120) operatively coupled to the return to origin factor collection subsystem (110). The post-dispatch return to origin score prediction subsystem (120) is configured to assign a post-dispatch return to origin (RTO) score corresponding to each of a plurality of collected post-dispatched return to origin factors. In one embodiment, the post-dispatch RTO score corresponding to the each of the plurality of collected post-dispatched RTO factors may be assigned based on an initial performance measurement for a predefined situation.

The post-dispatch return to origin score prediction subsystem (120) is also configured to compute a variation of an assigned post-dispatch return to origin (RTO) score based on one or more predefined conditions. The variation of the assigned post-dispatch return to origin (RTO) score depends upon preference of each of the plurality of post- dispatched RTO factors for a predefined situation. The post-dispatch RTO score dynamically changes based on weightage of the each of the plurality of post- dispatched RTO factors. The post-dispatch return to origin score prediction subsystem (120) is also configured to predict a post-dispatch return to origin score based on a computed variation of the assigned post-dispatch return to origin (RTO) score using a return to origin prediction technique.

In one embodiment, the one or more predefined conditions associated with computation of the variation of the assigned post-dispatch return to origin score (RTO) may include an identification of a slow-moving status of a package by determining delay in turnaround time (TAT) of the package encountered in moving from a source location to a destination location. The post-dispatch return to origin score prediction subsystem (120) analyses one or more logistics partner’s status and determine on slow- moving status of the package whose last status is not updated based on defined TAT. The post-dispatch RTO score prediction subsystem (120) identifies the TAT for each small stage of the package while moving from source to destination. Again, the post dispatch RTO score prediction subsystem based on each stage TAT notifies the customer about the delay in the package and seller. Also, post-dispatch RTO score prediction subsystem (120) based on the TAT for each small stage updates the RTO scores which eventually helps in RTO score prediction.

In another embodiment, the one or more predefined conditions associated with computation of the variation of the assigned post-dispatch return to origin score (RTO) may include identification of an out for delivery (OFD) failed status for a package based on an authenticity of response information obtained upon identification of a customer’s intent and a logistics partner’s intent through a systematized action. The post-dispatch RTO score prediction subsystem (120) identifies the customer’s intent through a systematized artificial intelligence technique when the package does not reach at the customer's end and the logistics partner gives remark as OFD failed with OFD attempt count. The post-dispatch RTO score prediction subsystem (120) also upon identification of the customer’s intent authenticates the response information based on verification of true and false replies of the customer and the logistics partner. Again, based on the replies of the customer and the logistics partner, the assigned post dispatch RTO score varies and is dynamically updated and helps to predict RTO. Also, the authenticity of the response information helps the seller in obtaining real-time status of the logistics partner and the customer and take a necessary action based on RTO prediction value.

In yet another embodiment, the one or more predefined conditions associated with computation of the variation of the assigned post-dispatch return to origin (RTO) score may include detection of a lost status of a package dynamically upon determination of misplacement of a package from a connected network within a predefined interval of time. As used herein, a term ‘package lost’ is defined as a package or a shipment looping in a network for the predefined interval of time in any stage of shipment life cycle (SLC). The status of the package is detected as lost status when the package overpasses the predefined time interval within the connected network. In one embodiment, the predefined time interval may include 20-30 days. Upon detection of the lost status of the package, the assigned post-dispatch RTO score dynamically varies and predicts risk of the RTO of the package.

In one embodiment, the one or more predefined conditions associated with computation of the variation of the assigned post-dispatch return to origin (RTO) score may include identification of a misrouted package by determining deviation of the package from a predetermined assigned route to reach a destination location within a predefined time interval. The misrouted package includes a package which is deviated from the predetermined assigned route because of any manual mistake involved or an incorrect address information associated with the customer. In one embodiment, the predefined time interval may include a flagged time limit of 3-10 days with each stage of the shipment life cycle. The assigned post-dispatch RTO score gets dynamically updated upon identification of the misrouted package based on delayed time using flag and the customer’s intent and as a result predicts the risk of package getting return to the seller.

In a preferred embodiment, the one or more predefined conditions associated with the computation of the variation of the assigned post-dispatch RTO score may include identification of one or more logistics partners dispatch or delivery center (DC) performance. In such embodiment, the one or more logistics partners DC performance is identified based on historical performance data of the logistics using a performance measurement technique. In one embodiment, a pre-dispatched RTO score count may also help in computation of the post-dispatch RTO score for better accuracy. In such embodiment, the pre-dispatched RTO score count may be calculated based on a plurality of pre-dispatch RTO factors.

In a particular embodiment, the one or more predefined conditions associated with the computation of the variation of the assigned post-dispatch RTO score may include identification of total delay in dispatch in terms of number of days. In such embodiment, the total delay in the dispatch may be identified based on dispatch to first connection TAT status and in transit scan delay status. In an embodiment, the dispatch to the first connection status represents a beginning of in transit stage for the package. In another embodiment, the in-transit scan delay status may include total number of scan delays occurred between a source and a destination until the package reaches the destination.

In one embodiment, determination of the delay in time from the DC to out for delivery may include determination of the delay in the time based on TAT of the logistics partner for different delivery addresses having different location and pin code. In another embodiment, identification of the undelivered reasons or non-delivery remark may include identification of the undelivered reasons of the package based on at least one of an incomplete address, address and pin-code mismatch, duplicate order, cash on delivery (COD) amount not ready with customer, customer requested for digital payment, customer shifted to different address, customer opened packet of the package and refused to accept, customer requested for future delivery, customer unavailable at the time of delivery, customer snatched shipment, open delivery request by customer, customer out of station, customer cancelled the order, customer’s residence closed at the time of delivery, network delay, shipment misrouted, out of delivery area, unable to deliver packet to customer, self-collect, shipment hold at the DC, shipment undelivered with unidentified reason, shipment under investigation, shipment delayed due to logistics partner’s mistake, shipment damaged, shipment lost, shipment content mismatched, shipment quantity mismatched or a combination thereof.

In a specific embodiment, the system (100) further includes a post-dispatch return to origin notification subsystem (not shown in FIG. 1) operatively coupled to the post dispatch return to origin score prediction subsystem (120). The post-dispatch return to origin notification subsystem is configured to identify a customer’s intent and a logistics partner’s intent received through a plurality of communication channels. In one embodiment, the plurality of communication channels may include at least one of a short message service (SMS), an email, a web notification or a combination thereof. The identification of the customer’s intent and logistics partner’s intent helps the seller in deciding where to reattempt the delivery of the package or return the package. In some embodiment, the customer’s intent may include a chance of cancellation in receiving the package by the customer due to delay in delivery because of the misrouted package. The post-dispatch RTO notification subsystem is also configured to notify a seller a chance of the package to return to origin (RTO) based on an identified intent of the customer and an identified intent of the logistics partner. In some embodiment, the one or more sellers may be notified through at least one of voice calls, a text message, a push notification, the email and the like. The notification sent to the one or more sellers helps in alerting the one or more sellers and reducing the chance of the RTO of the package associated with the one or more customers.

FIG. 2 illustrates a schematic representation of an exemplary embodiment of a system for post-dispatched return to origin prediction of a package in logistics in accordance with an embodiment of the present disclosure. The system (100) for post-dispatched return to origin (RTO) of the package helps an electronic-commerce business platform especially an e-seller (105) of the electronic commerce platform. The system (100) helps the e-seller (105) in obtaining information about a chance of the return to origin (RTO) of the package due to one or more factors if the package is not delivered to the customer in scheduled time period. For example, let us assume that the e-seller (105) ‘A’ wants to deliver a package to a customer (108) ‘B’ via a logistics partner (115). In such a scenario, the system (100) helps in calculating and predicting the RTO percentage of the package to inform the e-seller (105) after the package is picked up from the seller’s end. For prediction of the RTO, a plurality of post-dispatched return to origin (RTO) factors associated with the package delivery in the logistics is collected by a return to origin factor collection subsystem (110). For example, the plurality of post-dispatched RTO factors may include at least one of an identification of slow-moving status of a package, out for delivery (OFD) failed status for a package, a lost status of a package, a misrouted package or a combination thereof.

Now, once the plurality of post-dispatched factors are collected, each of the plurality of factors are considered in detail for prediction of the post-dispatched RTO prediction. In a shipment life cycle, a post-dispatch return to origin (RTO) score corresponding to the each of the plurality of collected post-dispatched return to origin factors is assigned via a post-dispatch return to origin (RTO) score prediction subsystem (120). The post-dispatch RTO score is assigned based on an initial performance measurement of the each of the plurality of post-dispatched RTO factors for a predefined situation. Here, the assigned post-dispatch score for each of the plurality of post-dispatched RTO factors is stored in a database (125). Once, the assigned post-dispatch score varies dynamically, such score is updated in the database (125) in real-time.

Again, based on one or more predefined conditions, a variation of an assigned post dispatch RTO score is also computed by the post-dispatch RTO score prediction subsystem (120). Here, the post-dispatch RTO score dynamically changes based on weightage of the each of the plurality of post-dispatched RTO factors. The post dispatch return to origin score prediction subsystem (120) also predicts a post-dispatch return to origin score based on a computed variation of the assigned post-dispatch return to origin (RTO) score using a return to origin prediction technique.

For example, the assigned post-dispatch RTO score varies for the one or more predefined conditions which may include an identification of a slow-moving status of a package by determining delay in turnaround time (TAT) of the package encountered in moving from a source location to a destination location. Suppose, the customer (108) wants an urgent delivery of the package, which needs to be shipped from a place ‘X’ to place Ύ. Now, in duration of the delivery of the package if the package overpasses a predetermined limit of the TAT for each one or more stages within the shipment lifecycle, then the package is identified as a delayed package or a slow- moving package. Also, the assigned post-dispatch RTO prediction score varies based on the predetermined limit of the TAT for the each one or more stages.

Similarly, the one or more predefined conditions which are responsible for variation of the assigned post-dispatch RTO score may also include identification of an out for delivery (OFD) failed status for the package based on an authenticity of response information obtained upon identification of a customer’s (108) intent and a logistics partner’s (115) intent through a systematized action. Here, if the logistics partner (115) involved in the delivery of the package fails to deliver the package to the customer within stipulated time and gives a fake remark as OFD failed, then in such a scenario, the customers (108) intent is received by utilization of an automated artificial intelligence technique. The automated artificial intelligence techniques establishes an automated call with the customer for verification. Also, the intention of the customer (108) such as chance of cancellation or the chance of retention with the customer is identified based on automated verification call established through the artificial intelligence technique. Later, the RTO score is dynamically updated based on the customer (108) and logistics replies which help to predict RTO, and the seller (105) is notified about the status of package and customer purpose, which helps the seller to know about their shipment status and take a right action based on RTO Prediction.

Again, the one or more predefined conditions associated with computation of the variation of the assigned post-dispatch return to origin (RTO) score may also include detection of a lost status of a package dynamically upon determination of misplacement of a package from a connected network within a predefined interval of time. The status of the package is detected as lost status when the package overpasses the predefined time interval within the connected network. In some embodiment, the predefined time interval may include 20-30 days. Upon detection of the lost status of the package, the assigned post-dispatch RTO score dynamically varies and predicts risk of the RTO of the package.

Moreover, the one or more predefined conditions associated with computation of the variation of the assigned post-dispatch return to origin (RTO) score may include identification of a misrouted package by determining deviation of the package from a predetermined assigned route to reach a destination location within a predefined time interval. Here, the misrouted package includes a package which is deviated from the predetermined assigned route because of any manual mistake involved or an incorrect address information associated with the customer (108). In some embodiment, the predefined time interval may include a flagged time limit of 3-10 days with each stage of the shipment life cycle. The assigned post-dispatch RTO score gets dynamically updated upon identification of the misrouted package based on delayed time using flag and the customer’s intent and as a result predicts the risk of package getting return to the seller. For example, if urgent delivery of the package of the customer (108) gets misrouted, then the delivery time is exceeded by one week. As, the customer (108) has an urgent requirement of the package, there is a chance that he/she may cancel the order. In such a case, a situation of cancellation by the customer is predicted in advance. Also, the RTO score is dynamically updated based on customer (108) need and delayed time of package delivery and inform the seller (105) that chances of package return is high because it marked as urgent delivery from the customer end.

Further, upon completion of the post-dispatch RTO prediction, the post-dispatch RTO notification subsystem (130) notifies the seller (105) a chance of the package to get into the return to origin (RTO) in real-time based on an identified intent of the customer and an identified intent of the logistics partner. The notification sent to the seller (105) helps in alerting the seller (105) and reducing the chance of the RTO of the package associated with the customer (108).

FIG. 3 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure. The server (200) includes processor(s) (230), and memory (210) operatively coupled to the bus (220).

The processor(s) (230), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.

The memory (210) includes a plurality of subsystems stored in the form of executable program which instructs the processor (230) to perform the method steps illustrated in FIG. 1. The memory (210) is substantially similar to a system (100) of FIG.l. The memory (210) has following subsystems: a return to origin factor collection subsystem (110), and a post-dispatch return to origin score prediction subsystem (120).

The return to origin factor collection subsystem (110) configured to collect a plurality of post-dispatched return to origin (RTO) factors associated with a package delivery in the logistics. The post-dispatch return to origin score prediction subsystem (120) is configured to assign a post-dispatch return to origin (RTO) score corresponding to each of a plurality of collected post-dispatched return to origin factors. The post dispatch return to origin score prediction subsystem (120) is also configured to compute a variation of an assigned post-dispatch return to origin (RTO) score based on one or more predefined conditions. The post-dispatch return to origin score prediction subsystem (120) is also configured to predict a post-dispatch return to origin score based on a computed variation of the assigned post-dispatch return to origin (RTO) score using a return to origin prediction technique.

The bus (220) as used herein refers to be internal memory channels or computer network that is used to connect computer components and transfer data between them. The bus (220) includes a serial bus or a parallel bus, wherein the serial bus transmit data in bit-serial format and the parallel bus transmit data across multiple wires. The bus (220) as used herein, may include but not limited to, a system bus, an internal bus, an external bus, an expansion bus, a frontside bus, a backside bus and the like.

FIG. 4 is a flow chart representing the steps involved in a method (300) for post- dispatched return to origin prediction of a package in logistics of FIG. 1 in accordance with the embodiment of the present disclosure. The method (300) includes collecting, by a return to origin factor collection subsystem, a plurality of post-dispatched return to origin (RTO) factors associated with a package delivery in the logistics in step 310. In one embodiment, collecting the plurality of post-dispatched return to origin (RTO) factors associated with the package delivery may include collecting the plurality of post-dispatched RTO factors which may include but not limited to, an identification of slow-moving status of a package, out for delivery (OFD) failed status for a package, a lost status of a package, a misrouted package or a combination thereof. The method (300) also includes assigning, by a post-dispatch return to origin score prediction subsystem, a post-dispatch return to origin (RTO) score corresponding to each of a plurality of collected post-dispatched return to origin factors in step 320. In one embodiment assigning the post-dispatch return to origin (RTO) score may include assigning the post-dispatch RTO factors corresponding to each of the plurality of collected post-dispatched return to origin factors based on an initial performance measurement of the each of the plurality of collected post-dispatched RTO factors for a predefined situation. The method (300) also includes predicting, by the post-dispatch return to origin score prediction subsystem, a post-dispatch return to origin score based on a computed variation of the assigned post-dispatch return to origin (RTO) score using a return to origin prediction technique in step 340.

The method (300) also includes computing, by the post-dispatch return to origin score prediction subsystem, a variation of an assigned post-dispatch return to origin (RTO) score based on one or more predefined conditions in step 330. In one embodiment, computing the variation of the assigned post-dispatch return to origin (RTO) score based on the one or more predefined conditions may include computing the variation of the assigned post-dispatch RTO score based on identification of a slow-moving status of a package by determining delay in turnaround time (TAT) of the package encountered in moving from a source location to a destination location.

In some embodiment, computing the variation of the assigned post-dispatch return to origin (RTO) score based on the one or more predefined conditions may include computing the variation of the assigned post-dispatch RTO based on identification of an out for delivery (OFD) failed status for a package based on an authenticity of response information obtained upon identification of a customer’s intent and a logistics partner’s intent through a systematized action.

In another embodiment, computing the variation of the assigned post-dispatch return to origin (RTO) score based on the one or more predefined conditions may include computing the variation of the assigned post-dispatch RTO based on detection of a lost status of a package dynamically upon determination of misplacement of a package from a connected network within a predefined interval of time. In some embodiment, the predefined time interval may include 20-30 days. In yet another embodiment, computing the variation of the assigned post-dispatch return to origin (RTO) score based on the one or more predefined conditions may include computing the variation of the assigned post-dispatch RTO based on identification of a misrouted package by determining deviation of the package from a predetermined assigned route to reach a destination location within a predefined time interval. In such embodiment, the predefined time interval for the misrouted package may include 3-10 days.

In a specific embodiment, the method further includes identifying, by a post-dispatch return to origin notification subsystem, a customer’s intent and a logistics partner’s intent received through a plurality of communication channels. In one embodiment, the plurality of communication channels may include at least one of a short message service (SMS), an email, a web notification or a combination thereof. In one embodiment, the method further includes notifying a seller a chance of the package to return to origin (RTO) based on an identified intent of the customer and an identified intent of the logistics partner. In some embodiment, the one or more sellers may be notified through at least one of voice calls, a text message, a push notification, the email and the like.

Various embodiments of the present disclosure helps in preventing and reducing the RTO of the package by identifying the one or more customers intent in advance.

Moreover, the present disclosed system predicts the RTO of the package by using artificial intelligence driven systematisation approaches and as a result helps in reducing revenue loss and customer satisfaction.

Furthermore, the present disclosed system by identifying the one or more customers intent saves a lot of time of each sellers in RTO prediction after the package gets picked up from the seller’s end.

It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.

While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.

The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.

Claims

WE CLAIM:

1. A system (100) for post-dispatched return to origin prediction of a package in logistics comprising: a return to origin factor collection subsystem (110) configured to collect a plurality of post-dispatched return to origin (RTO) factors associated with a package delivery in the logistics; a post-dispatch return to origin score prediction subsystem (120) operatively coupled to the return to origin factor collection subsystem (110), wherein the post dispatch return to origin score prediction subsystem (120) is configured to: assign a post-dispatch return to origin (RTO) score corresponding to each of a plurality of collected post-dispatched return to origin factors; compute a variation of an assigned post-dispatch return to origin (RTO) score based on one or more predefined conditions; and predict a post-dispatch return to origin score based on a computed variation of the assigned post-dispatch return to origin (RTO) score using a return to origin prediction technique.

2. The system (100) as claimed in claim 1, wherein the plurality of post- dispatched return to origin (RTO) factors comprises at least one of an identification of slow-moving status of a package, out for delivery (OFD) failed status for a package, a lost status of a package, a misrouted package a pre-dispatched RTO point count, identification of logistics partner dispatch center (DC) performance, identification of total delay in dispatch, determination of delay in time from the DC to out for delivery, undelivered reasons or non-delivery remark or a combination thereof.

3. The system (100) as claimed in claim 1, wherein the one or more predefined conditions associated with computation of the variation of the assigned post dispatch return to origin score (RTO) comprises an identification of a slow-moving status of a package by determining delay in turnaround time (TAT) of the package encountered in moving from a source location to a destination location.

4. The system (100) as claimed in claim 1, wherein the one or more predefined conditions associated with computation of the variation of the assigned post dispatch return to origin score (RTO) comprises identification of an out for delivery (OFD) failed status for a package based on an authenticity of response information obtained upon identification of a customer’s intent and a logistics partner’s intent through a systematized action.

5. The system (100) as claimed in claim 1, wherein the one or more predefined conditions associated with computation of the variation of the assigned post dispatch return to origin (RTO) score comprises detection of a lost status of a package dynamically upon determination of misplacement of a package from a connected network within a predefined interval of time.

6. The system (100) as claimed in claim 1, wherein the one or more predefined conditions associated with computation of the variation of the assigned post dispatch return to origin (RTO) score comprises identification of a misrouted package by determining deviation of the package from a predetermined assigned route to reach a destination location within a predefined time interval.

7. The system (100) as claimed in claim 1, further comprising a post-dispatch return to origin notification subsystem (130) operatively coupled to the post dispatch return to origin score prediction subsystem (120), wherein the post- dispatch return to origin notification subsystem (130) is configured to: identify a customer’s intent and a logistics partner’s intent received through a plurality of communication channels; notify a seller a chance of the package to return to origin (RTO) based on an identified intent of the customer and an identified intent of the logistics partner.

8. A method (300) comprising: collecting, by a return to origin factor collection subsystem, a plurality of post-dispatched return to origin (RTO) factors associated with a package delivery in the logistics (310); assigning, by a post-dispatch return to origin score prediction subsystem, a post-dispatch return to origin (RTO) score corresponding to each of a plurality of collected post-dispatched return to origin factors (320); computing, by the post-dispatch return to origin score prediction subsystem, a variation of an assigned post-dispatch return to origin (RTO) score based on one or more predefined conditions (330); and predicting, by the post-dispatch return to origin score prediction subsystem, a post-dispatch return to origin score based on a computed variation of the assigned post-dispatch return to origin (RTO) score using a return to origin prediction technique (340).

9. The method (300) as claimed in claim 8, further comprising identifying, by a post-dispatch return to origin notification subsystem, a customer’s intent and a logistics partner’s intent received through a plurality of communication channels.

10. The method (300) as claimed in claim 8, further comprising notifying, by the post-dispatch return to origin notification subsystem, a seller a chance of the package to return to origin (RTO) based on an identified intent of the customer and an identified intent of the logistics partner.