U.S. patent application number 17/101370 was filed with the patent office on 2021-03-11 for systems and methods for real-time order delay management.
This patent application is currently assigned to Walmart Apollo, LLC. The applicant listed for this patent is Walmart Apollo, LLC. Invention is credited to Michael Gilbert Ebener, Arnon Katz, Vidyanand Krishnan, Pratosh Deepak Rajkhowa, Austin Lee Smith.
Application Number | 20210073717 17/101370 |
Document ID | / |
Family ID | 1000005237403 |
Filed Date | 2021-03-11 |
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United States Patent
Application |
20210073717 |
Kind Code |
A1 |
Smith; Austin Lee ; et
al. |
March 11, 2021 |
SYSTEMS AND METHODS FOR REAL-TIME ORDER DELAY MANAGEMENT
Abstract
Systems and methods including one or more processors and one or
more non-transitory storage devices storing computing instructions
configured to run on the one or more processors and perform
receiving one or more orders from one or more customers, each
respective order of the one or more orders comprising one or more
respective items for sale at a store; and for each respective order
of the one or more orders from each respective customer of the one
or more customers: determining a respective order completion time
based on at least one of: (1) respective availabilities of one or
more store associates of the store; and (2) a respective pick time
estimation for the respective order as determined by a regression
analysis performed on respective historical data for available
associates of the one or more store associates; and facilitating
displaying, on a respective electronic device of the respective
customer, the respective order completion time. Other embodiments
are disclosed herein.
Inventors: |
Smith; Austin Lee;
(Burlingame, CA) ; Krishnan; Vidyanand;
(Sunnyvale, CA) ; Ebener; Michael Gilbert; (San
Francisco, CA) ; Rajkhowa; Pratosh Deepak;
(Bangalore, IN) ; Katz; Arnon; (San Mateo,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Walmart Apollo, LLC |
Bentonville |
AR |
US |
|
|
Assignee: |
Walmart Apollo, LLC
Bentonville
AR
|
Family ID: |
1000005237403 |
Appl. No.: |
17/101370 |
Filed: |
November 23, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
15582319 |
Apr 28, 2017 |
10846645 |
|
|
17101370 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 10/083 20130101;
G06Q 30/0635 20130101 |
International
Class: |
G06Q 10/08 20060101
G06Q010/08; G06Q 30/06 20060101 G06Q030/06 |
Claims
1. A system comprising: one or more processors; and one or more
non-transitory storage devices storing computing instructions
configured to run on the one or more processors and perform:
receiving one or more orders from one or more customers, each
respective order of the one or more orders comprising one or more
respective items for sale at a store; and for each respective order
of the one or more orders from each respective customer of the one
or more customers: determining a respective order completion time
based on at least one of: (1) respective availabilities of one or
more store associates of the store; and (2) a respective pick time
estimation for the respective order as determined by a regression
analysis performed on respective historical data for available
associates of the one or more store associates; and facilitating
displaying, on a respective electronic device of the respective
customer, the respective order completion time.
2. The system of claim 1, wherein the one or more non-transitory
storage devices storing the computing instructions are further
configured to run on the one or more processors and perform:
assigning the respective order of the one or more orders to one or
more associates of the one or more store associates of the store
for collection of the one or more respective items of the
respective order at the store.
3. The system of claim 1, wherein the one or more non-transitory
storage devices storing the computing instructions are further
configured to run on the one or more processors and perform:
automatically updating, in real-time, the respective order
completion time based on at least one of: (1) automatically
assigning the respective order to one or more associates of the one
or more store associates; (2) detecting a delay of one or more
associates of the one or more store associates; or (2) one or more
associates of the one or more store associates becoming available
earlier than previously estimated when determining the respective
order completion time for the respective order.
4. The system of claim 1, wherein receiving the one or more orders
from the one or more customers comprises: receiving the one or more
orders for delivery of the one or more respective items of each
respective order of the one or more orders to the one or more
customers.
5. The system of claim 1, wherein receiving the one or more orders
from the one or more customers comprises: receiving the one or more
orders for pickup of the one or more respective items of each
respective order of the one or more orders by the one or more
customers.
6. The system of claim 1, wherein the one or more non-transitory
storage devices storing the computing instructions are further
configured to run on the one or more processors and perform: for
each respective order of the one or more orders, determining a
respective picking start time and a respective picking end time
using the respective pick time estimation for the respective
order.
7. The system of claim 1, wherein the one or more non-transitory
storage devices storing the computing instructions are further
configured to run on the one or more processors and perform:
splitting the respective order of the one or more orders between
two or more associates of the one or more store associates of the
store for collection of the one or more respective items of the
respective order at the store.
8. The system of claim 1, wherein the respective availabilities of
the one or more store associates of the store are determined, at
least partially, by a forecasting computer system using a feedback
loop comprising feedback from the one or more store associates
about real-time updates to their respective availabilities.
9. The system of claim 1, wherein the regression analysis is
further based on one or more of: (1) one or more respective
locations in the store of the one or more respective items for the
respective order; (2) a number of commodity switches in the store
required to collect the one or more respective items for the
respective order; (3) a time of day when the respective order is
collected in the store; or (4) whether any of the one or more
respective items for the respective order need to be kept in a cold
environment.
10. The system of claim 1, wherein the one or more non-transitory
storage devices storing the computing instructions are further
configured to run on the one or more processors and perform:
placing each respective order of the one or more orders in an order
queue as each respective order is received.
11. A method comprising: receiving one or more orders from one or
more customers, each respective order of the one or more orders
comprising one or more respective items for sale at a store; and
for each respective order of the one or more orders from each
respective customer of the one or more customers: determining a
respective order completion time based on at least one of: (1)
respective availabilities of one or more store associates of the
store; and (2) a respective pick time estimation for the respective
order as determined by a regression analysis performed on
respective historical data for available associates of the one or
more store associates; and facilitating displaying, on a respective
electronic device of the respective customer, the respective order
completion time.
12. The method of claim 11 further comprising: assigning the
respective order of the one or more orders to one or more
associates of the one or more store associates of the store for
collection of the one or more respective items of the respective
order at the store.
13. The method of claim 11 further comprising: automatically
updating, in real-time, the respective order completion time based
on at least one of: (1) automatically assigning the respective
order to one or more associates of the one or more store
associates; (2) detecting a delay of one or more associates of the
one or more store associates; or (2) one or more associates of the
one or more store associates becoming available earlier than
previously estimated when determining the respective order
completion time for the respective order.
14. The method of claim 11, wherein receiving the one or more
orders from the one or more customers comprises: receiving the one
or more orders for delivery of the one or more respective items of
each respective order of the one or more orders to the one or more
customers.
15. The method of claim 11, wherein receiving the one or more
orders from the one or more customers comprises: receiving the one
or more orders for pickup of the one or more respective items of
each respective order of the one or more orders by the one or more
customers.
16. The method of claim 11 further comprising: for each respective
order of the one or more orders, determining a respective picking
start time and a respective picking end time using the respective
pick time estimation for the respective order.
17. The method of claim 11 further comprising: splitting the
respective order of the one or more orders between two or more
associates of the one or more store associates of the store for
collection of the one or more respective items of the respective
order at the store.
18. The method of claim 11, wherein the respective availabilities
of the one or more store associates of the store are determined, at
least partially, by a forecasting computer system using a feedback
loop comprising feedback from the one or more store associates
about real-time updates to their respective availabilities.
19. The method of claim 11, wherein the regression analysis is
further based on one or more of: (1) one or more respective
locations in the store of the one or more respective items for the
respective order; (2) a number of commodity switches in the store
required to collect the one or more respective items for the
respective order; (3) a time of day when the respective order is
collected in the store; or (4) whether any of the one or more
respective items for the respective order need to be kept in a cold
environment.
20. The method of claim 11 further comprising: placing each
respective order of the one or more orders in an order queue as
each respective order is received.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of application Ser. No.
15/582,319, filed Apr. 28, 2017, which is herein incorporated by
this reference in its entirety.
TECHNICAL FIELD
[0002] This disclosure relates generally to systems and methods for
real-time management of order changes of delivery and/or pick up
orders.
BACKGROUND
[0003] Many customers of retail or grocery stores now desire the
convenience of having their orders delivered to their homes and/or
picking up their already-collected orders at a designated area of
the store. These orders are often made by the customers online
using a website or mobile application for the store. If, however,
the customer has a narrow window of time in which to pick up the
order or be at home for delivery of the order, and/or the store has
numerous orders to fulfill, a problem with these online orders is
providing accurate order completion times to the customer when the
customer makes the order on the website or mobile application.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] To facilitate further description of the embodiments, the
following drawings are provided in which:
[0005] FIG. 1 illustrates a front elevational view of a computer
system that is suitable for implementing various embodiments of the
systems disclosed in FIGS. 3 and 5;
[0006] FIG. 2 illustrates a representative block diagram of an
example of the elements included in the circuit boards inside a
chassis of the computer system of FIG. 1;
[0007] FIG. 3 illustrates a representative block diagram of a
system, according to an embodiment;
[0008] FIG. 4 is a flowchart for a method, according to additional
embodiments; and
[0009] FIG. 5 illustrates a representative block diagram of a
portion of the system of FIG. 3, according to an embodiment.
[0010] For simplicity and clarity of illustration, the drawing
figures illustrate the general manner of construction, and
descriptions and details of well-known features and techniques may
be omitted to avoid unnecessarily obscuring the present disclosure.
Additionally, elements in the drawing figures are not necessarily
drawn to scale. For example, the dimensions of some of the elements
in the figures may be exaggerated relative to other elements to
help improve understanding of embodiments of the present
disclosure. The same reference numerals in different figures denote
the same elements.
[0011] The terms "first," "second," "third," "fourth," and the like
in the description and in the claims, if any, are used for
distinguishing between similar elements and not necessarily for
describing a particular sequential or chronological order. It is to
be understood that the terms so used are interchangeable under
appropriate circumstances such that the embodiments described
herein are, for example, capable of operation in sequences other
than those illustrated or otherwise described herein. Furthermore,
the terms "include," and "have," and any variations thereof, are
intended to cover a non-exclusive inclusion, such that a process,
method, system, article, device, or apparatus that comprises a list
of elements is not necessarily limited to those elements, but may
include other elements not expressly listed or inherent to such
process, method, system, article, device, or apparatus.
[0012] The terms "left," "right," "front," "back," "top," "bottom,"
"over," "under," and the like in the description and in the claims,
if any, are used for descriptive purposes and not necessarily for
describing permanent relative positions. It is to be understood
that the terms so used are interchangeable under appropriate
circumstances such that the embodiments of the apparatus, methods,
and/or articles of manufacture described herein are, for example,
capable of operation in other orientations than those illustrated
or otherwise described herein.
[0013] The terms "couple," "coupled," "couples," "coupling," and
the like should be broadly understood and refer to connecting two
or more elements mechanically and/or otherwise. Two or more
electrical elements may be electrically coupled together, but not
be mechanically or otherwise coupled together. Coupling may be for
any length of time, e.g., permanent or semi-permanent or only for
an instant. "Electrical coupling" and the like should be broadly
understood and include electrical coupling of all types. The
absence of the word "removably," "removable," and the like near the
word "coupled," and the like does not mean that the coupling, etc.
in question is or is not removable.
[0014] As defined herein, two or more elements are "integral" if
they are comprised of the same piece of material. As defined
herein, two or more elements are "non-integral" if each is
comprised of a different piece of material.
[0015] As defined herein, "real-time" can, in some embodiments, be
defined with respect to operations carried out as soon as
practically possible upon occurrence of a triggering event. A
triggering event can include receipt of data necessary to execute a
task or to otherwise process information. Because of delays
inherent in transmission and/or in computing speeds, the term "real
time" encompasses operations that occur in "near" real time or
somewhat delayed from a triggering event. In a number of
embodiments, "real time" can mean real time less a time delay for
processing (e.g., determining) and/or transmitting data. The
particular time delay can vary depending on the type and/or amount
of the data, the processing speeds of the hardware, the
transmission capability of the communication hardware, the
transmission distance, etc. However, in many embodiments, the time
delay can be less than approximately one second, two seconds, five
seconds, or ten seconds.
[0016] As defined herein, "approximately" can, in some embodiments,
mean within plus or minus ten percent of the stated value. In other
embodiments, "approximately" can mean within plus or minus five
percent of the stated value. In further embodiments,
"approximately" can mean within plus or minus three percent of the
stated value. In yet other embodiments, "approximately" can mean
within plus or minus one percent of the stated value.
DESCRIPTION OF EXAMPLES OF EMBODIMENTS
[0017] A number of embodiments can include a system. The system can
include one or more processors and one or more non-transitory
computer-readable storage devices storing computing instructions.
The computing instructions can be configured to run on the one or
more processors and perform acts of receiving one or more orders
from one or more customers, each respective order of the one or
more orders comprising one or more respective items for sale at a
store; and for each respective order of the one or more orders from
each respective customer of the one or more customers: determining
a respective order completion time based on at least one of: (1)
respective availabilities of one or more store associates of the
store; and (2) a respective pick time estimation for the respective
order as determined by a regression analysis performed on
respective historical data for available associates of the one or
more store associates; and facilitating displaying, on a respective
electronic device of the respective customer, the respective order
completion time.
[0018] Various embodiments include a method. The method can
comprise receiving one or more orders from one or more customers,
each respective order of the one or more orders comprising one or
more respective items for sale at a store; and for each respective
order of the one or more orders from each respective customer of
the one or more customers: determining a respective order
completion time based on at least one of: (1) respective
availabilities of one or more store associates of the store; and
(2) a respective pick time estimation for the respective order as
determined by a regression analysis performed on respective
historical data for available associates of the one or more store
associates; and facilitating displaying, on a respective electronic
device of the respective customer, the respective order completion
time.
[0019] A number of embodiments can include a system. The system can
include one or more processing modules and one or more
non-transitory storage modules storing computing instructions
configured to run on the one or more processing modules. The one or
more storage modules can be configured to run on the one or more
processing modules and perform an act of receiving a plurality of
orders from a plurality customers. Each order of the plurality of
orders can comprise one or more items for sale at a store. The one
or more storage modules can be further configured to run on the one
or more processing modules and perform an act of, for each order of
the plurality of orders from each customer of the plurality of
customers, determining an order completion time based on at least
one of: (1) availabilities of one or more associates of the store
to collect the one or more items of the order at the store or (2) a
dynamic pick time estimation for the order. The one or more storage
modules can be further configured to run on the one or more
processing modules and perform an act of, for each order of the
plurality of orders from each customer of the plurality of
customers, coordinating displaying the order completion time on an
electronic device of the customer. The one or more storage modules
can be further configured to run on the one or more processing
modules and perform an act of, for each order of the plurality of
orders from each customer of the plurality of customers, assigning
the order to one associate of the one or more associates of the
store for collection of the one or more items of the order at the
store. The one or more storage modules can be further configured to
run on the one or more processing modules and perform an act of,
for each order of the plurality of orders from each customer of the
plurality of customers, automatically updating, in real-time, the
order completion time based on at least one of: (1) automatically
reassigning the order to a different associate of the one or more
associates or (2) the one associate of the one or more associates
becoming available earlier than previously estimated when
determining the order completion time for the order.
[0020] Various embodiments include a method. The method can include
receiving a plurality of orders from a plurality customers. Each
order of the plurality of orders can comprise one or more items for
sale at a store. The method also can comprise, for each order of
the plurality of orders from each customer of the plurality of
customers, determining an order completion time based on at least
one of: (1) availabilities of one or more associates of the store
to collect the one or more items of the order at the store or (2) a
dynamic pick time estimation for the order. The method also can
comprise, for each order of the plurality of orders from each
customer of the plurality of customers, coordinating displaying the
order completion time on an electronic device of the customer. The
method also can comprise, for each order of the plurality of orders
from each customer of the plurality of customers, assigning the
order to one associate of the one or more associates of the store
for collection of the one or more items of the order at the store.
The method also can comprise, for each order of the plurality of
orders from each customer of the plurality of customers,
automatically updating, in real-time, the order completion time
based on at least one of: (1) automatically reassigning the order
to a different associate of the one or more associates or (2) the
one associate of the one or more associates becoming available
earlier than previously estimated when determining the order
completion time for the order.
[0021] Additional embodiments can include a system. The system can
include one or more processing modules and one or more
non-transitory storage modules storing computing instructions
configured to run on the one or more processing modules. The one or
more storage modules can be configured to run on the one or more
processing modules and perform an act of receiving a plurality of
orders from a plurality customers. Each order of the plurality of
orders can comprise one or more items for sale at a store. The one
or more storage modules can be further configured to run on the one
or more processing modules and perform an act of, for each order of
the plurality of orders from each customer of the plurality of
customers, determining a picking start time, a picking end time,
and an order completion time based on at least one of: (1)
availabilities of one or more associates of the store to collect
the one or more items of the order at the store or (2) a dynamic
pick time estimation for the order. The one or more storage modules
can be further configured to run on the one or more processing
modules and perform an act of, for each order of the plurality of
orders from each customer of the plurality of customers. The one or
more storage modules can be further configured to run on the one or
more processing modules and perform an act of, for each order of
the plurality of orders from each customer of the plurality of
customers, coordinating displaying of the order completion time on
an electronic device of the customer. The one or more storage
modules can be further configured to run on the one or more
processing modules and perform an act of, for each order of the
plurality of orders from each customer of the plurality of
customers, assigning the order to one associate of the one or more
associates of the store for collection of the one or more items of
the order at the store. The one or more storage modules can be
further configured to run on the one or more processing modules and
perform an act of, for each order of the plurality of orders from
each customer of the plurality of customers, automatically
adjusting, in real-time, the picking start time and the picking end
time without adjusting the order completion time based on at least
one of: (1) automatic reassigning the order to a different
associate of the one or more associates or (2) the one associate of
the one or more associates becoming available earlier than
previously estimated when determining the order completion time for
the order.
[0022] Turning to the drawings, FIG. 1 illustrates an exemplary
embodiment of a computer system 100, all of which or a portion of
which can be suitable for (i) implementing part or all of one or
more embodiments of the techniques, methods, and systems and/or
(ii) implementing and/or operating part or all of one or more
embodiments of the memory storage modules described herein. As an
example, a different or separate one of a chassis 102 (and its
internal components) can be suitable for implementing part or all
of one or more embodiments of the techniques, methods, and/or
systems described herein. Furthermore, one or more elements of
computer system 100 (e.g., a monitor 106, a keyboard 104, and/or a
mouse 110, etc.) also can be appropriate for implementing part or
all of one or more embodiments of the techniques, methods, and/or
systems described herein. Computer system 100 can comprise chassis
102 containing one or more circuit boards (not shown), a Universal
Serial Bus (USB) port 112, a Compact Disc Read-Only Memory (CD-ROM)
and/or Digital Video Disc (DVD) drive 116, and a hard drive 114. A
representative block diagram of the elements included on the
circuit boards inside chassis 102 is shown in FIG. 2. A central
processing unit (CPU) 210 in FIG. 2 is coupled to a system bus 214
in FIG. 2. In various embodiments, the architecture of CPU 210 can
be compliant with any of a variety of commercially distributed
architecture families.
[0023] Continuing with FIG. 2, system bus 214 also is coupled to a
memory storage unit 208, where memory storage unit 208 can comprise
(i) non-volatile memory, such as, for example, read only memory
(ROM) and/or (ii) volatile memory, such as, for example, random
access memory (RAM). The non-volatile memory can be removable
and/or non-removable non-volatile memory. Meanwhile, RAM can
include dynamic RAM (DRAM), static RAM (SRAM), etc. Further, ROM
can include mask-programmed ROM, programmable ROM (PROM), one-time
programmable ROM (OTP), erasable programmable read-only memory
(EPROM), electrically erasable programmable ROM (EEPROM) (e.g.,
electrically alterable ROM (EAROM) and/or flash memory), etc. In
these or other embodiments, memory storage unit 208 can comprise
(i) non-transitory memory and/or (ii) transitory memory.
[0024] In various examples, portions of the memory storage
module(s) of the various embodiments disclosed herein (e.g.,
portions of the non-volatile memory storage module(s)) can be
encoded with a boot code sequence suitable for restoring computer
system 100 (FIG. 1) to a functional state after a system reset. In
addition, portions of the memory storage module(s) of the various
embodiments disclosed herein (e.g., portions of the non-volatile
memory storage module(s)) can comprise microcode such as a Basic
Input-Output System (BIOS) operable with computer system 100 (FIG.
1). In the same or different examples, portions of the memory
storage module(s) of the various embodiments disclosed herein
(e.g., portions of the non-volatile memory storage module(s)) can
comprise an operating system, which can be a software program that
manages the hardware and software resources of a computer and/or a
computer network. The BIOS can initialize and test components of
computer system 100 (FIG. 1) and load the operating system.
Meanwhile, the operating system can perform basic tasks such as,
for example, controlling and allocating memory, prioritizing the
processing of instructions, controlling input and output devices,
facilitating networking, and managing files. Exemplary operating
systems can comprise one of the following: (i) Microsoft.RTM.
Windows.RTM. operating system (OS) by Microsoft Corp. of Redmond,
Wash., United States of America, (ii) Mac.RTM. OS X by Apple Inc.
of Cupertino, Calif., United States of America, (iii) UNIX.RTM. OS,
and (iv) Linux.RTM. OS. Further exemplary operating systems can
comprise one of the following: (i) the iOS.RTM. operating system by
Apple Inc. of Cupertino, Calif., United States of America, (ii) the
Blackberry.RTM. operating system by Research In Motion (RIM) of
Waterloo, Ontario, Canada, (iii) the WebOS operating system by LG
Electronics of Seoul, South Korea, (iv) the Android.TM. operating
system developed by Google, of Mountain View, California, United
States of America, (v) the Windows Mobile.TM. operating system by
Microsoft Corp. of Redmond, Wash., United States of America, or
(vi) the Symbian.TM. operating system by Accenture PLC of Dublin,
Ireland.
[0025] As used herein, "processor" and/or "processing module" means
any type of computational circuit, such as but not limited to a
microprocessor, a microcontroller, a controller, a complex
instruction set computing (CISC) microprocessor, a reduced
instruction set computing (RISC) microprocessor, a very long
instruction word (VLIW) microprocessor, a graphics processor, a
digital signal processor, or any other type of processor or
processing circuit capable of performing the desired functions. In
some examples, the one or more processing modules of the various
embodiments disclosed herein can comprise CPU 210.
[0026] Alternatively, or in addition to, the systems and procedures
described herein can be implemented in hardware, or a combination
of hardware, software, and/or firmware. For example, one or more
application specific integrated circuits (ASICs) can be programmed
to carry out one or more of the systems and procedures described
herein. For example, one or more of the programs and/or executable
program components described herein can be implemented in one or
more ASICs. In many embodiments, an application specific integrated
circuit (ASIC) can comprise one or more processors or
microprocessors and/or memory blocks or memory storage.
[0027] In the depicted embodiment of FIG. 2, various I/O devices
such as a disk controller 204, a graphics adapter 224, a video
controller 202, a keyboard adapter 226, a mouse adapter 206, a
network adapter 220, and other I/O devices 222 can be coupled to
system bus 214. Keyboard adapter 226 and mouse adapter 206 are
coupled to keyboard 104 (FIGS. 1-2) and mouse 110 (FIGS. 1-2),
respectively, of computer system 100 (FIG. 1). While graphics
adapter 224 and video controller 202 are indicated as distinct
units in FIG. 2, video controller 202 can be integrated into
graphics adapter 224, or vice versa in other embodiments. Video
controller 202 is suitable for monitor 106 (FIGS. 1-2) to display
images on a screen 108 (FIG. 1) of computer system 100 (FIG. 1).
Disk controller 204 can control hard drive 114 (FIGS. 1-2), USB
port 112 (FIGS. 1-2), and CD-ROM drive 116 (FIGS. 1-2). In other
embodiments, distinct units can be used to control each of these
devices separately.
[0028] Network adapter 220 can be suitable to connect computer
system 100 (FIG. 1) to a computer network by wired communication
(e.g., a wired network adapter) and/or wireless communication
(e.g., a wireless network adapter). In some embodiments, network
adapter 220 can be plugged or coupled to an expansion port (not
shown) in computer system 100 (FIG. 1). In other embodiments,
network adapter 220 can be built into computer system 100 (FIG. 1).
For example, network adapter 220 can be built into computer system
100 (FIG. 1) by being integrated into the motherboard chipset (not
shown), or implemented via one or more dedicated communication
chips (not shown), connected through a PCI (peripheral component
interconnector) or a PCI express bus of computer system 100 (FIG.
1) or USB port 112 (FIG. 1).
[0029] Returning now to FIG. 1, although many other components of
computer system 100 are not shown, such components and their
interconnection are well known to those of ordinary skill in the
art. Accordingly, further details concerning the construction and
composition of computer system 100 and the circuit boards inside
chassis 102 are not discussed herein.
[0030] Meanwhile, when computer system 100 is running, program
instructions (e.g., computer instructions) stored on one or more of
the memory storage module(s) of the various embodiments disclosed
herein can be executed by CPU 210 (FIG. 2). At least a portion of
the program instructions, stored on these devices, can be suitable
for carrying out at least part of the techniques and methods
described herein.
[0031] Further, although computer system 100 is illustrated as a
desktop computer in FIG. 1, there can be examples where computer
system 100 may take a different form factor while still having
functional elements similar to those described for computer system
100. In some embodiments, computer system 100 may comprise a single
computer, a single server, or a cluster or collection of computers
or servers, or a cloud of computers or servers. Typically, a
cluster or collection of servers can be used when the demand on
computer system 100 exceeds the reasonable capability of a single
server or computer. In certain embodiments, computer system 100 may
comprise a portable computer, such as a laptop computer. In certain
other embodiments, computer system 100 may comprise a mobile
electronic device, such as a smartphone. In certain additional
embodiments, computer system 100 may comprise an embedded
system.
[0032] Turning ahead in the drawings, FIG. 3 illustrates a block
diagram of a system 300 that can be employed for real-time order
delay management, as described in greater detail below. System 300
is merely exemplary and embodiments of the system are not limited
to the embodiments presented herein. System 300 can be employed in
many different embodiments or examples not specifically depicted or
described herein. In some embodiments, certain elements or modules
of system 300 can perform various procedures, processes, and/or
activities. In these or other embodiments, the procedures,
processes, and/or activities can be performed by other suitable
elements or modules of system 300.
[0033] Generally, therefore, system 300 can be implemented with
hardware and/or software, as described herein. In some embodiments,
part or all of the hardware and/or software can be conventional,
while in these or other embodiments, part or all of the hardware
and/or software can be customized (e.g., optimized) for
implementing part or all of the functionality of system 300
described herein.
[0034] In some embodiments, system 300 can include a communication
system 310, a web server 320, a display system 360, and an
assignment system 370. Communication system 310, web server 320,
display system 360, and/or assignment system 370 can each be a
computer system, such as computer system 100 (FIG. 1), as described
above, and can each be a single computer, a single server, or a
cluster or collection of computers or servers, or a cloud of
computers or servers. In another embodiment, a single computer
system can host each of two or more of communication system 310,
web server 320, display system 360, and/or assignment system 370.
Additional details regarding communication system 310, web server
320, display system 360, and assignment system 370 are described
herein.
[0035] In many embodiments, system 300 also can comprise user
computers 340, 341. In some embodiments, user computers 340, 341
can be mobile devices. A mobile electronic device can refer to a
portable electronic device (e.g., an electronic device easily
conveyable by hand by a person of average size) with the capability
to present audio and/or visual data (e.g., text, images, videos,
music, etc.). For example, a mobile electronic device can comprise
at least one of a digital media player, a cellular telephone (e.g.,
a smartphone), a personal digital assistant, a handheld digital
computer device (e.g., a tablet personal computer device), a laptop
computer device (e.g., a notebook computer device, a netbook
computer device), a wearable user computer device, or another
portable computer device with the capability to present audio
and/or visual data (e.g., images, videos, music, etc.). Thus, in
many examples, a mobile electronic device can comprise a volume
and/or weight sufficiently small as to permit the mobile electronic
device to be easily conveyable by hand. For examples, in some
embodiments, a mobile electronic device can occupy a volume of less
than or equal to approximately 1790 cubic centimeters, 2434 cubic
centimeters, 2876 cubic centimeters, 4056 cubic centimeters, and/or
5752 cubic centimeters. Further, in these embodiments, a mobile
electronic device can weigh less than or equal to 15.6 Newtons,
17.8 Newtons, 22.3 Newtons, 31.2 Newtons, and/or 44.5 Newtons.
[0036] Exemplary mobile electronic devices can comprise (i) an
iPod.RTM., iPhone.RTM., iTouch.RTM., iPad.RTM., MacBook.RTM. or
similar product by Apple Inc. of Cupertino, California, United
States of America, (ii) a Blackberry.RTM. or similar product by
Research in Motion (RIM) of Waterloo, Ontario, Canada, (iii) a
Lumia.RTM. or similar product by the Nokia Corporation of
Keilaniemi, Espoo, Finland, and/or (iv) a Galaxy.TM. or similar
product by the Samsung Group of Samsung Town, Seoul, South Korea.
Further, in the same or different embodiments, a mobile electronic
device can comprise an electronic device configured to implement
one or more of (i) the iPhone.RTM. operating system by Apple Inc.
of Cupertino, Calif., United States of America, (ii) the
Blackberry.RTM. operating system by Research In Motion (RIM) of
Waterloo, Ontario, Canada, (iii) the Palm.RTM. operating system by
Palm, Inc. of Sunnyvale, Calif., United States, (iv) the
Android.TM. operating system developed by the Open Handset
Alliance, (v) the Windows Mobile.TM. operating system by Microsoft
Corp. of Redmond, Wash., United States of America, or (vi) the
Symbian.TM. operating system by Nokia Corp. of Keilaniemi, Espoo,
Finland.
[0037] Further still, the term "wearable user computer device" as
used herein can refer to an electronic device with the capability
to present audio and/or visual data (e.g., text, images, videos,
music, etc.) that is configured to be worn by a user and/or
mountable (e.g., fixed) on the user of the wearable user computer
device (e.g., sometimes under or over clothing; and/or sometimes
integrated with and/or as clothing and/or another accessory, such
as, for example, a hat, eyeglasses, a wrist watch, shoes, etc.). In
many examples, a wearable user computer device can comprise a
mobile electronic device, and vice versa. However, a wearable user
computer device does not necessarily comprise a mobile electronic
device, and vice versa.
[0038] In specific examples, a wearable user computer device can
comprise a head mountable wearable user computer device (e.g., one
or more head mountable displays, one or more eyeglasses, one or
more contact lenses, one or more retinal displays, etc.) or a limb
mountable wearable user computer device (e.g., a smart watch). In
these examples, a head mountable wearable user computer device can
be mountable in close proximity to one or both eyes of a user of
the head mountable wearable user computer device and/or vectored in
alignment with a field of view of the user.
[0039] In more specific examples, a head mountable wearable user
computer device can comprise (i) Google Glass.TM. product or a
similar product by Google Inc. of Menlo Park, Calif., United States
of America; (ii) the Eye Tap.TM. product, the Laser Eye Tap.TM.
product, or a similar product by ePI Lab of Toronto, Ontario,
Canada, and/or (iii) the Raptyr.TM. product, the STAR 1200.TM.
product, the Vuzix Smart Glasses M100.TM. product, or a similar
product by Vuzix Corporation of Rochester, N.Y., United States of
America. In other specific examples, a head mountable wearable user
computer device can comprise the Virtual Retinal Display.TM.
product, or similar product by the University of Washington of
Seattle, Wash., United States of America. Meanwhile, in further
specific examples, a limb mountable wearable user computer device
can comprise the iWatch.TM. product, or similar product by Apple
Inc. of Cupertino, Calif., United States of America, the Galaxy
Gear or similar product of Samsung Group of Samsung Town, Seoul,
South Korea, the Moto 360 product or similar product of Motorola of
Schaumburg, Ill., United States of America, and/or the Zip.TM.
product, One.TM. product, Flex.TM. product, Charge.TM. product,
Surge.TM. product, or similar product by Fitbit Inc. of San
Francisco, Calif., United States of America.
[0040] In some embodiments, web server 320 can be in data
communication through
[0041] Internet 330 with user computers (e.g., 340, 341). In
certain embodiments, user computers 340-341 can be desktop
computers, laptop computers, smart phones, tablet devices, and/or
other endpoint devices. Web server 320 can host one or more
websites. For example, web server 320 can host an eCommerce website
that allows users to browse and/or search for products, to add
products to an electronic shopping cart, and/or to purchase
products, in addition to other suitable activities.
[0042] In many embodiments, communication system 310, web server
320, display system 360, and/or assignment system 370 can each
comprise one or more input devices (e.g., one or more keyboards,
one or more keypads, one or more pointing devices such as a
computer mouse or computer mice, one or more touchscreen displays,
a microphone, etc.), and/or can each comprise one or more display
devices (e.g., one or more monitors, one or more touch screen
displays, projectors, etc.). In these or other embodiments, one or
more of the input device(s) can be similar or identical to keyboard
104 (FIG. 1) and/or a mouse 110 (FIG. 1). Further, one or more of
the display device(s) can be similar or identical to monitor 106
(FIG. 1) and/or screen 108 (FIG. 1). The input device(s) and the
display device(s) can be coupled to the processing module(s) and/or
the memory storage module(s) communication system 310, web server
320, display system 360, and/or assignment system 370 in a wired
manner and/or a wireless manner, and the coupling can be direct
and/or indirect, as well as locally and/or remotely. As an example
of an indirect manner (which may or may not also be a remote
manner), a keyboard-video-mouse (KVM) switch can be used to couple
the input device(s) and the display device(s) to the processing
module(s) and/or the memory storage module(s). In some embodiments,
the KVM switch also can be part of communication system 310, web
server 320, display system 360, and/or assignment system 370. In a
similar manner, the processing module(s) and the memory storage
module(s) can be local and/or remote to each other.
[0043] In many embodiments, communication system 310, web server
320, display system 360, and/or assignment system 370 can be
configured to communicate with one or more user computers 340 and
341. In some embodiments, user computers 340 and 341 also can be
referred to as customer computers. In some embodiments,
communication system 310, web server 320, display system 360,
and/or assignment system 370 can communicate or interface (e.g.,
interact) with one or more customer computers (such as user
computers 340 and 341) through a network or internet 330. Internet
330 can be an intranet that is not open to the public. Accordingly,
in many embodiments, communication system 310, web server 320,
display system 360, and/or assignment system 370 (and/or the
software used by such systems) can refer to a back end of system
300 operated by an operator and/or administrator of system 300, and
user computers 340 and 341 (and/or the software used by such
systems) can refer to a front end of system 300 used by one or more
users 350 and 351, respectively. In some embodiments, users 350 and
351 also can be referred to as customers, in which case, user
computers 340 and 341 can be referred to as customer computers. In
these or other embodiments, the operator and/or administrator of
system 300 can manage system 300, the processing module(s) of
system 300, and/or the memory storage module(s) of system 300 using
the input device(s) and/or display device(s) of system 300.
[0044] Meanwhile, in many embodiments, communication system 310,
web server 320, display system 360, and/or assignment system 370
also can be configured to communicate with one or more databases.
The one or more databases can comprise a product database that
contains information about products, items, or SKUs (stock keeping
units) sold by a retailer. The one or more databases can be stored
on one or more memory storage modules (e.g., non-transitory memory
storage module(s)), which can be similar or identical to the one or
more memory storage module(s) (e.g., non-transitory memory storage
module(s)) described above with respect to computer system 100
(FIG. 1). Also, in some embodiments, for any particular database of
the one or more databases, that particular database can be stored
on a single memory storage module of the memory storage module(s),
and/or the non-transitory memory storage module(s) storing the one
or more databases or the contents of that particular database can
be spread across multiple ones of the memory storage module(s)
and/or non-transitory memory storage module(s) storing the one or
more databases, depending on the size of the particular database
and/or the storage capacity of the memory storage module(s) and/or
non-transitory memory storage module(s).
[0045] The one or more databases can each comprise a structured
(e.g., indexed) collection of data and can be managed by any
suitable database management systems configured to define, create,
query, organize, update, and manage database(s). Exemplary database
management systems can include MySQL (Structured Query Language)
Database, PostgreSQL Database, Microsoft SQL Server Database,
Oracle Database, SAP (Systems, Applications, & Products)
Database, and IBM DB2 Database.
[0046] Meanwhile, communication between communication system 310,
web server 320, display system 360, assignment system 370, and/or
the one or more databases can be implemented using any suitable
manner of wired and/or wireless communication. Accordingly, system
300 can comprise any software and/or hardware components configured
to implement the wired and/or wireless communication. Further, the
wired and/or wireless communication can be implemented using any
one or any combination of wired and/or wireless communication
network topologies (e.g., ring, line, tree, bus, mesh, star, daisy
chain, hybrid, etc.) and/or protocols (e.g., personal area network
(PAN) protocol(s), local area network (LAN) protocol(s), wide area
network (WAN) protocol(s), cellular network protocol(s), powerline
network protocol(s), etc.). Exemplary PAN protocol(s) can comprise
Bluetooth, Zigbee, Wireless Universal Serial Bus (USB), Z-Wave,
etc.; exemplary LAN and/or WAN protocol(s) can comprise Institute
of Electrical and Electronic Engineers (IEEE) 802.3 (also known as
Ethernet), IEEE 802.11 (also known as WiFi), etc.; and exemplary
wireless cellular network protocol(s) can comprise Global System
for Mobile Communications (GSM), General Packet Radio Service
(GPRS), Code Division Multiple Access (CDMA), Evolution-Data
Optimized (EV-DO), Enhanced Data Rates for GSM Evolution (EDGE),
Universal Mobile Telecommunications System (UMTS), Digital Enhanced
Cordless Telecommunications (DECT), Digital AMPS (IS-136/Time
Division Multiple Access (TDMA)), Integrated Digital Enhanced
Network (iDEN), Evolved High-Speed Packet Access (HSPA+), Long-Term
Evolution (LTE), WiMAX, etc. The specific communication software
and/or hardware implemented can depend on the network topologies
and/or protocols implemented, and vice versa. In many embodiments,
exemplary communication hardware can comprise wired communication
hardware including, for example, one or more data buses, such as,
for example, universal serial bus(es), one or more networking
cables, such as, for example, coaxial cable(s), optical fiber
cable(s), and/or twisted pair cable(s), any other suitable data
cable, etc. Further exemplary communication hardware can comprise
wireless communication hardware including, for example, one or more
radio transceivers, one or more infrared transceivers, etc.
Additional exemplary communication hardware can comprise one or
more networking components (e.g., modulator-demodulator components,
gateway components, etc.).
[0047] Turning ahead in the drawings, FIG. 4 illustrates a flow
chart for a method 400, according to an embodiment. Method 400 is
merely exemplary and is not limited to the embodiments presented
herein. Method 400 can be employed in many different embodiments or
examples not specifically depicted or described herein. In some
embodiments, the activities of method 400 can be performed in the
order presented. In other embodiments, the activities of method 400
can be performed in any suitable order. In still other embodiments,
one or more of the activities of method 400 can be combined or
skipped. In many embodiments, system 300 (FIG. 3) can be suitable
to perform method 400 and/or one or more of the activities of
method 400. In these or other embodiments, one or more of the
activities of method 400 can be implemented as one or more computer
instructions configured to run at one or more processing modules
and configured to be stored at one or more non-transitory memory
storage modules 512, 562, 572, and/or 574 (FIG. 5). Such
non-transitory memory storage modules can be part of a computer
system such as communication system 310, web server 320, display
system 360, and/or assignment system 370 (FIGS. 3 & 5). The
processing module(s) can be similar or identical to the processing
module(s) described above with respect to computer system 100 (FIG.
1).
[0048] One or more embodiments of method 400 can be utilized to
provide and update a service level agreement or order completion
time for an order placed by a customer. Embodiments of method 400
also can adapt assignments for order collection and/or order
completion times based on real-time changes, such as but not
limited to store associates completing collection of an order
earlier than expected, delays in collecting an order, and/or
reassignment of an order to a different store associate.
[0049] In many embodiments, method 400 can comprise an activity 405
of receiving a plurality of orders from a plurality of customers.
Each order of the plurality of orders can comprise one or more
items for sale at a store. In some embodiments, the store can
comprise one or more brick and mortar stores. In other embodiments,
the store can comprise one or more online stores, one or more
warehouses, and/or one or more distribution centers for one or more
online stores, one or more brick and mortar stores, or both.
[0050] In many embodiments, each order of the plurality of orders
can be received at different times from electronic devices of the
plurality of customers. For example, at least a portion of the
plurality of customers can place an order online using his/her
electronic device. In other examples, an order may be made by the
customer by calling the store and speaking with an associate or
leaving a message with the order. Moreover, in some embodiments,
activity 405 can comprise: (1) receiving, from a first electronic
device of a first customer, a first order comprising one or more
first items for sale at the store, and also (2) receiving, from a
second electronic device of a second customer and after the first
order is received, a second order comprising one or more second
items for sale at the store. In such an embodiment, for example,
the first order would be placed before the second order in a queue
of orders to be collected at the store.
[0051] In various embodiments, the orders placed by customers can
comprise orders for delivery or orders for pickup. For example,
activity 405 can comprise receiving the plurality of orders for
delivery of the one or more items of each order of the plurality of
orders to the plurality of customers. In these embodiments, system
300 (FIG. 3) also can receive a delivery address for the order
and/or coordinate delivery of the order by an associate of the
store or third-party delivery service. In an order for delivery of
the one or more items, the one or more items are collected at the
store by a store associate, and then a store associate, a
third-party delivery driver, a drone service, or a self-driving car
delivers the one or more items to the agreed upon location for
delivery.
[0052] In other embodiments, activity 405 can comprise receiving
the plurality of orders for pickup at the store of the one or more
items of each order by the respective customer. In an order for
pickup of the one or more items, the one or more items are
collected at the store by a store associate (or "picker"), and the
customer goes to a predetermined location in the store or the
parking lot of the store to pick up the one or more items of the
order.
[0053] In some embodiments, activity 405 and other activities in
method 400 can comprise using a distributed network comprising
distributed memory architecture to perform the associated activity.
This distributed architecture can reduce the impact on the network
and system resources to reduce congestion in bottlenecks while
still allowing data to be accessible from a central location. In
some embodiments, activity 405 and other activities in method 400
can comprise using a distributed network comprising distributed
memory architecture to perform the associated activity. This
distributed architecture can reduce the impact on the network and
system resources to reduce congestion in bottlenecks while still
allowing data to be accessible from a central location.
[0054] In many embodiments, method 400 can further comprise an
activity 410 of, for each order of the plurality of orders from
each customer of the plurality of customers, determining an order
completion time for the order. The order completion time can be a
time at which the order is ready for pickup at the store by the
customer, or can be a time at which the order should be delivered
to the customer. In some embodiments, the order completion time is
a window of time, such as a 15-minute window, a 30-minute window, a
1-hour window, and so on.
[0055] In some embodiments, the order completion time can be based
on at least one of: (1) availabilities of one or more associates of
the store to collect the one or more items of the order at the
store and/or (2) a dynamic pick time estimation for the order.
Thus, in some embodiments, the order completion time is not a
static determination, but rather a dynamic determination that
considers various real-time factors. For example, availabilities of
the one or more associates of the store can be based on a total
number of associates assigned to collect items for orders at the
store, scheduled breaks for the associates assigned to collect
items for orders at the store, and/or any currently pending or
in-progress orders at the store. By way of an additional example,
the order completion time for a new order can be based not only on
the dynamic pick time estimation for the new order, but also the
dynamic pick time estimation for any currently pending or
in-progress orders at the store. Moreover, the order completion
time for a new order also can be based on the availability of one
or more associates to collect not only the new order but also any
currently pending or in-progress orders.
[0056] The dynamic pick time estimation for the order the dynamic
pick time estimation can be based on one or more of the following:
(1) one or more locations of the one or more items in the store,
(2) a number of commodity switches required to collect the one or
more items at the store, (3) a historical performance of the
associate of the store assigned to collect the one or more items of
the order and/or the one or more associates available to collect
the one or more items of the order, (4) a time of day when the
order is collected at the store by the associate, and/or (5)
whether any of the one or more items need to be refrigerated or
kept frozen. The number of commodity switches can include the
number of times an associate must switch between different
commodities in the store to collect the one or more items. For
example, a number of times a user must switch from the refrigerated
or frozen section of the store to the room temperature section of
the store. In some embodiments, the number commodity switches can
comprise a number of isle switches of how many isle must be
traversed in the store based on the item locations within commodity
for an associate to collect the order.
[0057] In some embodiments, the dynamic pick time estimation can be
determined using a regression analysis for estimating the
relationships among variables. The regression analysis used can use
the relationship between a dependent variable and one or more
independent variables (or "predictors"). The regression model can
determine how picking time (or the dependent variable or "criterion
variable") can be modeled changes when any one of the independent
variables is varied for each order. The independent variables can
include, for example, a number of: (1) a total number of ambient,
chilled, and/or frozen products; and/or (2) a total number of
ambient, chilled, and/or frozen products.
[0058] In some embodiments, linear regression can be used where the
relationships are modeled using linear predictor functions whose
unknown model parameters are estimated from data. For example,
given a variable y and a number of variables X.sub.1, . . . ,
X.sub.p that may be related to y, linear regression analysis can be
applied to quantify the strength of the relationship between y and
the X.sub.j, to assess which X.sub.j may have no relationship with
y at all, and to identify which subsets of the X.sub.j contain
redundant information about y.
[0059] In a non-limiting example, the following was used to
determine with all values of A based on historical data, and then
used to estimate picking time based on order related variables:
Estimated Picking Time=A1X1, A2X2, A3X3, A4X4, A5X5 . . .
AnXn+Constant+Error
[0060] where constant is a required value for each estimation, A
are coefficients, and X are order related variables that impact
picking. Independent variables or order related variables that
impact picking time can be determined through techniques of feature
selection, and then reducing the independent variables or order
related variables to the features that impacted the picking time
the most. Information gain for feature selection can be used to
select features that are most important to picking time and discard
irrelevant or redundant features.
[0061] In some embodiments, factors considered in determining the
order completion time can vary dependent upon whether the order is
an order for pickup or an order for delivery. For example, if the
order is an order for delivery, determining the order completion
time can comprise, for each order of the plurality of orders,
determining the order completion time based on: (1) the dynamic
pick time estimation for the order and (2) a distance of the
customer from the store. The distance of the customer from the
store can include an actual road distance from the store to the
location for delivery, the time of day, and/or current or
forecasted traffic conditions. In some embodiments, if the order is
an order for a scheduled delivery, determining the order completion
time does not factor in real-time availability of store associates
for collecting the one or more items at the store. In other
embodiments, if the order is an order for express or on-demand
delivery, determining the order completion time can factor in
real-time availability of store associates for collecting the one
or more items at the store. Similarly, if the order is an order for
pickup, determining the order completion time can factor in
real-time availability of store associates for collecting the one
or more items at the store.
[0062] In many embodiments, activity 410 also can include, for each
order of the plurality of orders, an activity of determining a
picking start time and a picking end time for the order. The
picking start time and the picking end time can be based on (1) the
availabilities of the one or more associates of the store to
collect the one or more items of the order at the store, and/or (2)
the dynamic pick time estimation for the order.
[0063] Method 400 can further comprise an activity 415 of, for each
order of the plurality of orders from each customer of the
plurality of customers, coordinating displaying the order
completion time for the order on an electronic device of the
customer. In some embodiments, activity 415 can comprise
coordinating displaying a plurality of order completion times on
the electronic device of the customer, and method 400 also can
comprise an activity receiving a selection of one of the plurality
of order completion times from the electronic device of the
customer. In these embodiments, the plurality of order completion
times for an order can be determined as a plurality of possible
order completion times according to activity 410, and the customer
can select which order time of the plurality of order times he/she
prefers.
[0064] Method 400 can further comprise an activity 420 of, for each
order of the plurality of orders from each customer of the
plurality of customers, assigning the order to one associate of the
one or more associates of the store for collection of the one or
more items of the order. Thus, activity 420 can comprise activities
of assigning the first order to a first associate for collection of
the one or more first items at the store, and assigning the second
order to a second associate for collection of the one or more
second items at the store.
[0065] Assignment of each order to certain associates of a
plurality of associates at a store can be based on one or more
factors. For example, system 300 (FIG. 3) can estimate or forecast,
in real-time, when an associate will be available for collection of
a new order based upon application of one or more of the factors
described above in relation to activity 410 to each pending or
in-progress order made before the new order. In some embodiments,
system 300 (FIG. 3) can automatically split a single order into two
or more lists for two or more different associated to collect the
order simultaneously. Splitting of the order can be based on any of
the factors described elsewhere in this disclosure, such as but not
limited to associate availability, pick time estimation, and so on.
In many embodiments, method 400 can comprise an activity of, for
each order of the plurality of orders, transmitting the order to an
associate electronic device of the associate assigned to collect
the order. Transmitting the order to the associate electronic
device can occur when the assignment of the order is initially
made, and/or when the associate is available to collect the
order.
[0066] In many embodiments, method 400 can further comprise an
activity 425 of, for each order of the plurality of orders from
each customer of the plurality of customers, automatically
updating, in real-time, the order completion time. Automatically
updating, in real-time, the order completion time can be based on
at least one of: (1) automatically reassigning the order to a
different associate of the one or more associates or (2) the one
associate initially assigned the order becoming available earlier
than previously estimated when determining the order completion
time for the order.
[0067] For example, if the associate initially assigned to collect
the order takes longer on a different order that is earlier in the
order queue, takes a break, or is otherwise delayed, system 300
(FIG. 3) can automatically reassign the order to a different
associate of the store associates and automatically update, in
real-time, the order completion time if the order completion time
has changed due to the reassignment of the order. Thus, method 400
can optionally comprise an activity of automatically reassigning
the order to the different associate if the one associate initially
assigned the order is delayed or unavailable for collection of the
order at the originally assigned time. Activity 425 can then
comprise, for each order of the plurality of orders, automatically
updating, in real-time, the order completion time based on
reassigning the order to the different associate.
[0068] Alternatively or additional, the associate initially
assigned to collect the order may become available earlier than
previously estimated when determining the order completion time,
and thus may begin collecting the order earlier than expected,
resulting in an earlier order completion time. Method 400 can thus
optionally comprise an activity of automatically reassigning a
second order or later order to a different associate than
originally assigned if the different associate becomes available
for collection of the one or more second items before the initially
assigned associate. Activity 425 can then comprise an activity of
automatically updating, in real-time, a second order completion
time for the second order based on reassigning the second order
from the second associate to the first associate.
[0069] In embodiments where picking start times and picking end
times for each order have been determined, activity 425 can
comprise, for each order of the plurality of orders, automatically
adjusting the picking start time and the picking end time based on
(1) reassigning the order to the different associate of the one or
more associates or (2) the one associate of the one or more
associates becoming available earlier than previously estimated
when determining the order completion time for the order. In many
embodiments, any time a change in associate availability to collect
an order occurs, system 300 (FIG. 3) can automatically reassign all
orders of the plurality of orders that are currently pending and
adjust the picking start time and the picking end time for each
order.
[0070] For example, every time any order of the plurality of orders
is reassigned, system 300 (FIG. 3) can review all pending orders in
system 300 (FIG. 3) and all active or available associates in
system 300 (FIG. 3), and then reassign or re-queue all pending
orders to the available associates with an adjusted estimated
picking start time and picking end time for each order. In some
embodiments, this reassignment of all pending orders can change the
order completion time for one or more orders of the plurality of
orders. If the order completion time is changed or updated, method
400 can optionally comprise an activity of transmitting, to the
electronic device of the customer, a message comprising the order
completion time as updated. In other embodiments, this reassignment
of all pending orders can be accomplished without changing any
order completion time for the plurality of orders or without
notifying the customer of the earlier order completion time.
[0071] FIG. 5 illustrates a block diagram of a portion of system
300 comprising communication system 310, web server 320, display
system 360, and assignment system 370, according to the embodiment
shown in FIG. 3. Each of communication system 310, web server 320,
display system 360, and assignment system 370, is merely exemplary
and not limited to the embodiments presented herein. Each of
communication system 310, web server 320, display system 360, and
assignment system 370, can be employed in many different
embodiments or examples not specifically depicted or described
herein. In some embodiments, certain elements or modules of
communication system 310, web server 320, display system 360,
and/or assignment system 370, can perform various procedures,
processes, and/or acts. In other embodiments, the procedures,
processes, and/or acts can be performed by other suitable elements
or modules.
[0072] In many embodiments, communication system 310 can comprise
non-transitory memory storage module 512. Memory storage module 512
can be referred to as communication module 512. In many
embodiments, communication module 512 can store computing
instructions configured to run on one or more processing modules
and perform one or more acts of method 400 (FIG. 4) (e.g., activity
405 of receiving a plurality of orders from a plurality of
customers (FIG. 4)).
[0073] In many embodiments, display system 360 can comprise
non-transitory memory storage module 562. Memory storage module 562
can be referred to as display module 562. In many embodiments,
display module 562 can store computing instructions configured to
run on one or more processing modules and perform one or more acts
of method 400 (FIG. 4) (e.g., activity 415 of coordinating
displaying the order completion time for each order on an
electronic device of the customer (FIG. 4)).
[0074] In many embodiments, assignment system 370 can comprise
non-transitory storage module 572. Memory storage module 572 can be
referred to as assignment module 572. In many embodiments,
assignment module 572 can store computing instructions configured
to run on one or more processing modules and perform one or more
acts of method 400 (FIG. 4) (e.g., activity 420 of assigning the
order to one associate of the one or more associates of the store
for collection of the one or more items of the order (FIG. 4)).
[0075] In many embodiments, assignment system 370 can comprise
non-transitory storage module 574. Memory storage module 574 can be
referred to as order completion module. In many embodiments, order
completion module 574 can store computing instructions configured
to run on one or more processing modules and perform one or more
acts of method 400 (FIG. 4) (e.g., activity 410 of determining an
order completion time for each order, and activity 425 of
automatically updating, in real-time, the order completion time
(FIG. 4)).
[0076] Although systems and methods for real-time order delay
management have been described with reference to specific
embodiments, it will be understood by those skilled in the art that
various changes may be made without departing from the spirit or
scope of the disclosure. Accordingly, the disclosure of embodiments
is intended to be illustrative of the scope of the disclosure and
is not intended to be limiting. It is intended that the scope of
the disclosure shall be limited only to the extent required by the
appended claims. For example, to one of ordinary skill in the art,
it will be readily apparent that any element of FIGS. 1-5 may be
modified, and that the foregoing discussion of certain of these
embodiments does not necessarily represent a complete description
of all possible embodiments. For example, one or more of the
procedures, processes, or activities of FIG. 4 may include
different procedures, processes, and/or activities and be performed
by many different modules, in many different orders.
[0077] All elements claimed in any particular claim are essential
to the embodiment claimed in that particular claim. Consequently,
replacement of one or more claimed elements constitutes
reconstruction and not repair. Additionally, benefits, other
advantages, and solutions to problems have been described with
regard to specific embodiments. The benefits, advantages, solutions
to problems, and any element or elements that may cause any
benefit, advantage, or solution to occur or become more pronounced,
however, are not to be construed as critical, required, or
essential features or elements of any or all of the claims, unless
such benefits, advantages, solutions, or elements are stated in
such claim.
[0078] Moreover, embodiments and limitations disclosed herein are
not dedicated to the public under the doctrine of dedication if the
embodiments and/or limitations: (1) are not expressly claimed in
the claims; and (2) are or are potentially equivalents of express
elements and/or limitations in the claims under the doctrine of
equivalents.
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