Item tracking systems and methods for fine tuned delivery scheduling

A computer-implemented system for delivery scheduling from a fulfillment center. The system includes a memory storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include maintaining a first data structure representing a fulfillment center, where the data structure has elements representing portions of the fulfillment center the portions are associated with a plurality of physical locations and a cutoff time. The operations may also include maintaining a second data structure including a mapping between physical locations and product identifiers, receiving a request to provide a delivery time estimate, searching the second data structure to identify at least one physical location associated with the requested product, searching the first data structure to determine cutoff times associated with each of the at least one physical location, and returning, responsive to the request, a fast cutoff time selected from the cutoff times.

TECHNICAL FIELD

The present disclosure generally relates to computerized systems and methods for delivery scheduling. In particular, embodiments of the present disclosure relate to inventive and unconventional item tracking systems and methods fulfillment centers for fine-tuning delivery scheduling based on fulfillment center virtualization.

BACKGROUND

Fulfillment centers (FCs) are warehouses that specialize in warehousing, packing, and shipping orders. There are multiple types of FCs. For example, a fulfillment center may be a large warehouse filling large commercial orders to a retailer or distributor. However, an FC may also encompass centers that strictly focus on shipping small parcels direct-to-consumers (DTC). Additionally, some FCs focus on a niche, such as small or large products, a specific type of product (such as sports goods), or certain number of stock keeping units (SKUs). FCs may also manage inventory and handle returns or exchanges by contracting directly to vendors and/or manufacturers. In such situations, FCs may become responsible for inventory problems such as “mispicks” (in which the wrong product is selected to fill an order) and “misships” (in which the wrong item is sent to the customer). In many cases, FCs must absorb the costs of mistakes.

Recently, FCs, and FC operations, have turned significantly more complex. Some of the current FCs are very large, carry many products (each product with specific conditions for shipping and labeling), and must offer multiple delivery options to provide more options to customers. Further, some FCs are required to fulfill a very large number of orders in short periods of time and must meet very quick promise delivery dates, requiring FCs to strictly coordinate deliveries to minimize liabilities. Thus, FCs are under pressure to improve their delivery times, minimize mistakes, and reduce costs.

The increased complexity of FC operations is compounded by new customer expectations that demand higher personalization of service, putting a heavy burden on FCs to achieve very quick turnarounds at a very low cost. For example, customers now expect very quick deliveries (even deliveries within a few hours) and expect to pay no, or very small, shipping and handling fees. To meet these customer demands, FCs attempt to develop efficient workflows that allow expedited shipping at a minimum cost. However, in large and complex FC's workflows are complex to manage or difficult to implement. Further, in some FC's it is difficult to create independent workflows because they may require diverting from a standard procedure. For example, certain FC's may attempt to keep shipping prices low by using standard procedures that can be implemented cheaply. However, such standard procedures may not fulfill customer demands of personalized and quick shipments, creating a tension between efficiency and customer satisfaction.

The disclosed computerized item tracking systems and methods for fine-tuned delivery scheduling address one or more of the problems set forth above and/or other problems in the prior art.

SUMMARY

One aspect of the present disclosure is directed to a computer-implemented system for delivery scheduling from a fulfillment center. The system may include a memory storing instructions and at least one processor configured to execute the instructions to perform operations. The operations may include maintaining a first data structure representing a fulfillment center, where the data structure stores elements representing portions of the fulfillment center and each of the portions is associated with a plurality of physical locations in the respective portion and a cutoff time for delivery, before a first time period, of products in the physical locations. The operations may also include maintaining a second data structure including a mapping between physical locations and product identifiers, receiving a request to provide a delivery time estimate associated with a requested product, and searching the second data structure to identify at least one physical location associated with the requested product. Moreover, the operations may also include searching the first data structure to determine a cutoff time associated with each of the at least one physical location and returning, responsive to the request, a selected cutoff time.

Another aspect of the present disclosure is directed to a computer-implemented method for delivery scheduling from a fulfillment center. The method may include maintaining a first data structure representing a fulfillment center, where the data structure includes elements representing portions of the fulfillment center and each of the portions is associated with a plurality of physical locations in the respective portion and a cutoff time for delivery, before a first time period, of products in the physical locations. The method may also include maintaining a second data structure including a mapping between physical locations and product identifiers, receiving a request to provide a delivery time estimate associated with a requested product, searching the second data structure to identify at least one physical location associated with the requested product. The method may also include searching the first data structure to determine a cutoff time associated with each of the at least one physical location and returning, responsive to the request, a selected cutoff time.

Yet another aspect of the present disclosure is directed to a non-transitory computer-readable medium storing instructions that, when executed by a processor, perform operations for delivery scheduling from a fulfillment center. The operations may include maintaining a first data structure representing a fulfillment center, where the data structure includes elements representing portions of the fulfillment center and each of the portions is associated with a plurality of physical locations in the respective portion and a cutoff time for delivery, before a first time period, of products in the physical locations. The operations may also include maintaining a second data structure including a mapping between physical locations and product identifiers, receiving a request to provide a delivery time estimate associated with a requested product, filtering the physical locations in the second data structure based on the customer device to identify at least one physical location associated with the requested product, and requesting available inventory from fulfillment centers associated with the filtered physical locations. Moreover, the operations may also include selecting a fulfillment center from the fulfillment centers based on distance between a location associated with a customer device and the fulfillment centers, searching the first data structure for each of the plurality of physical locations to determine a plurality of cutoff times, selecting one of the physical locations based on a comparison between a current time and respective cutoff times and returning (responsive to the request) a selected cutoff time.

Other systems, methods, and computer-readable media are also discussed herein.

DETAILED DESCRIPTION

Embodiments of the present disclosure are directed to systems and methods for delivery scheduling form a fulfillment center (FC). The disclosed systems and methods may employ a tracking system of items that allow to determine the location of items or products in the fulfillment center. Based on the location within the FC, an FC computer system may determine specific delivery dates or cutoff times for each product or item. Thus, the disclosed systems and methods may enhance the efficiency of FC shipping workflows and enable greater personalization of delivery times or options by specifying deliveries dates, times, and options for each product. For example, each item or product in an FC may have a specific cutoff time based on the product's location. The cutoff time may indicate the latest time an order must be processed to meet a promised delivery date (PDD). Thus, disclosed systems and methods may allow determining product or location specific cutoff times based on item locations within the FC, and/or the product distance to the FC's packing and shipping center.

Further, the disclosed systems and methods may also enable automated tracking of product position or location within the FC. For example, the disclosed systems and methods may use wired and wireless sensors to track the location of the products with the FC. In such embodiments, the disclosed systems may include a network of sensors and/or tracking stations that allow the disclosed systems to determine the location of products or items within an FC. Such systems and methods may enable the creation of data structures that store the positioning of items in an FC to create tailored delivery schedules based on the item position. This grater granularization of items within an FC allows the disclosed systems and methods to create personalized shipping flows that allows systems to provide fine-tuned delivery schedules.

Moreover, the disclosed systems and methods for delivery scheduling may enable creating highly personalized websites that specify available delivery options. For example, the disclosed systems and methods may generate personalized websites that specify available delivery options for each product and for each client device. In such embodiments, the disclosed systems and methods may configure HTML or JavaScript files to generate or update a webpages. Moreover, the disclosed systems and methods may enhance accuracy of the delivery date estimation calculations by collecting and analyzing specific date for both preparing the package for delivery and for the delivery address.

Furthermore, embodiments of the disclosed systems and methods may be directed to improving computer operations in an FC. In particular, disclosed systems and methods may result in dynamically produced multi-source hybrid webpages that use information from FC systems, information from delivery addresses, and information from user preferences, to generate personalized websites. For example, the disclosed systems may produce dynamic hybrid webpages that combine information from the retailer (e.g., the availability and location of products), from the FC (e.g., the location of specific items in the FC and estimated time for shipping), information from the shipping agent (e.g., shipping routes and schedules), and information from the customer to (e.g., shipping preferences and postal code). Such multi-sourced arrangement of information may be used to generate multi-sourced webpages that shows products, tailored delivery options, specific delivery date estimates, promised delivery dates, and purchasing options.

Moreover, the disclosed systems and methods may automate the processes used for delivery scheduling using a real-time location system that tracks product location or position within the FC. This system of automated product tracking within the FC may allow to dynamically adjust delivery schedules and offering of available delivery options. For example, the disclosed systems and methods may use indoor real-time positioning systems to fine-tune delivery schedules and provide greater availability of delivery options or have faster turnarounds. Using technologies such as NFC, BLE, or bar code scanning to automate and maintain real time location systems, the disclosed systems and methods may allow FC systems to produce personalized websites and improve shipping and packing workflows.

Reference will now be made in detail to the disclosed embodiments, examples of which are illustrated in the accompanying drawings.

FIG. 1Ashows a schematic block diagram of system100illustrating an exemplary embodiment of a system including computerized systems for communications enabling shipping, transportation, and logistics operations. As illustrated inFIG. 1A, system100may include a variety of systems, each of which may be connected to one another via one or more networks. The systems may also be connected to one another via a direct connection, for example, using a cable. The depicted systems include a shipment authority technology (SAT) system101, an external front-end system103, an internal front-end system105, a transportation system107, mobile devices107A,107B, and107C, seller portal109, shipment and order tracking (SOT) system111, fulfillment optimization (FO) system113, fulfillment messaging gateway (FMG)115, supply chain management (SCM) system117, workforce management system119, mobile devices119A,119B, and119C (depicted as being inside of fulfillment center (FC)200), 3rdparty fulfillment systems121A,121B, and121C, fulfillment center authorization system (FC Auth)123, and labor management system (LMS)125.

SAT system101, in some embodiments, may be implemented as a computer system that monitors order status and delivery status. For example, SAT system101may determine whether an order is past its Promised Delivery Date (PDD) and may take appropriate action, including initiating a new order, reshipping the items in the non-delivered order, canceling the non-delivered order, initiating contact with the ordering customer, or the like. SAT system101may also monitor other data, including output (such as a number of packages shipped during a particular time period) and input (such as the number of empty cardboard boxes received for use in shipping). SAT system101may also act as a gateway between different devices in system100, enabling communication (e.g., using store-and-forward or other techniques) between devices such as external front-end system103and FO system113.

Further, in some embodiments SAT system101may be in communication and control item positioning systems that track and/or store products that are warehoused in the FC. For example, SAT system101may control systems that track the position of products multiple virtual locations of the FC, as further described in connection toFIG. 14.

External front-end system103, in some embodiments, may be implemented as a computer system that enables external users to interact with one or more systems in system100. For example, in embodiments where system100enables the presentation of systems to enable users to place an order for an item, external front-end system103may be implemented as a web server that receives search requests, presents item pages, and solicits payment information. For example, external front-end system103may be implemented as a computer or computers running software such as the Apache HTTP Server, Microsoft Internet Information Services (IIS), NGINX, or the like. In other embodiments, external front-end system103may run custom web server software designed to receive and process requests from external devices (e.g., mobile device102A or computer102B), acquire information from databases and other data stores based on those requests, and provide responses to the received requests based on acquired information.

In some embodiments, external front-end system103may include one or more of a web caching system, a database, a search system, or a payment system. In one aspect, external front-end system103may include one or more of these systems, while in another aspect, external front-end system103may include interfaces (e.g., server-to-server, database-to-database, or other network connections) connected to one or more of these systems.

An illustrative set of steps, illustrated byFIGS. 1B, 1C, 1D, and 1E, will help to describe some operations of external front-end system103. External front-end system103may receive information from systems or devices in system100for presentation and/or display. For example, external front-end system103may host or provide one or more web pages, including a Search Result Page (SRP) (e.g.,FIG. 1B), a Single Detail Page (SDP) (e.g.,FIG. 1C), a Cart page (e.g.,FIG. 1D), or an Order page (e.g.,FIG. 1E). A user device (e.g., using mobile device102A or computer102B) may navigate to external front-end system103and request a search by entering information into a search box. External front-end system103may request information from one or more systems in system100. For example, external front-end system103may request information from FO System113that satisfies the search request. External front-end system103may also request and receive (from FO System113) a Promised Delivery Date or “PDD” for each product included in the search results. The PDD, in some embodiments, may represent an estimate of when a package containing the product will arrive at the user's desired location or a date by which the product is promised to be delivered at the user's desired location if ordered within a particular period of time, for example, by the end of the day (11:59 PM). (PDD is discussed further below with respect to FO System113.)

In some embodiments FO systems113may also be in communication with product position systems of FCs. In such embodiments, FO systems113may have precise information of the product, tentative delivery dates, available delivery options, and cutoff times for each one of the delivery options.

External front-end system103may prepare an SRP (e.g.,FIG. 1B) based on the information. The SRP may include information that satisfies the search request. For example, this may include pictures of products that satisfy the search request. The SRP may also include respective prices for each product, or information relating to enhanced delivery options for each product, PDD, weight, size, offers, discounts, or the like. External front-end system103may send the SRP to the requesting user device (e.g., via a network).

A user device may then select a product from the SRP, e.g., by clicking or tapping a user interface, or using another input device, to select a product represented on the SRP. The user device may formulate a request for information on the selected product and send it to external front-end system103. In response, external front-end system103may request information related to the selected product. For example, the information may include additional information beyond that presented for a product on the respective SRP. Further, the information could include the location of the product within the FC and estimated required time for shipping and delivery. This could include, for example, shelf or pallet position, shelf life, country of origin, weight, size, number of items in package, handling instructions, or other information about the product. The information could also include recommendations for similar products (based on, for example, big data and/or machine learning analysis of customers who bought this product and at least one other product), answers to frequently asked questions, reviews from customers, manufacturer information, pictures, or the like.

External front-end system103may prepare an SDP (Single Detail Page) (e.g.,FIG. 1C) based on the received product information. The SDP may also include other interactive elements such as a “Buy Now” button, a “Add to Cart” button, a quantity field, a picture of the item, or the like. The SDP may further include a list of sellers that offer the product. The list may be ordered based on the price each seller offers such that the seller that offers to sell the product at the lowest price may be listed at the top. The list may also be ordered based on the seller ranking such that the highest ranked seller may be listed at the top. The seller ranking may be formulated based on multiple factors, including, for example, the seller's past track record of meeting a promised PDD. External front-end system103may deliver the SDP to the requesting user device (e.g., via a network).

The requesting user device may receive the SDP which lists the product information. Upon receiving the SDP, the user device may then interact with the SDP. For example, a user of the requesting user device may click or otherwise interact with a “Place in Cart” button on the SDP. This adds the product to a shopping cart associated with the user. The user device may transmit this request to add the product to the shopping cart to external front-end system103.

External front-end system103may generate a Cart page (e.g.,FIG. 1D). The Cart page, in some embodiments, lists the products that the user has added to a virtual “shopping cart.” A user device may request the Cart page by clicking on or otherwise interacting with an icon on the SRP, SDP, or other pages. The Cart page may, in some embodiments, list all products that the user has added to the shopping cart, as well as information about the products in the cart such as a quantity of each product, a price for each product per item, a price for each product based on an associated quantity, information regarding PDD, a delivery method, a shipping cost, user interface elements for modifying the products in the shopping cart (e.g., deletion or modification of a quantity), options for ordering other product or setting up periodic delivery of products, options for setting up interest payments, user interface elements for proceeding to purchase, or the like. A user at a user device may click on or otherwise interact with a user interface element (e.g., a button that reads “Buy Now”) to initiate the purchase of the product in the shopping cart. Upon doing so, the user device may transmit this request to initiate the purchase to external front-end system103.

External front-end system103may generate an order page (e.g.,FIG. 1E) in response to receiving the request to initiate a purchase. The order page, in some embodiments, re-lists the items from the shopping cart and requests input of payment and shipping information. For example, the order page may include a section requesting information about the purchaser of the items in the shopping cart (e.g., name, address, e-mail address, phone number), information about the recipient (e.g., name, address, phone number, delivery information), shipping information (e.g., speed/method of delivery and/or pickup), payment information (e.g., credit card, bank transfer, check, stored credit), user interface elements to request a cash receipt (e.g., for tax purposes), or the like. External front-end system103may send the Order page to the user device.

The user device may enter information on the order page and click or otherwise interact with a user interface element that sends the information to external front-end system103. From there, external front-end system103may send the information to different systems in system100to enable the creation and processing of a new order with the products in the shopping cart.

In some embodiments, external front-end system103may be further configured to enable sellers to transmit and receive information relating to orders. For example, external front-end system103may allow sellers to transmit estimated packing time and/or available delivery options for specific products.

Internal front-end system105, in some embodiments, may be implemented as a computer system that enables internal users (e.g., employees of an organization that owns, operates, or leases system100) to interact with one or more systems in system100. For example, in embodiments where SAT system101enables the presentation of systems to enable users to place an order for an item, internal front-end system105may be implemented as a web server that enables internal users to view diagnostic and statistical information about orders, modify item information, or review statistics relating to orders. For example, internal front-end system105may be implemented as a computer or computers running software such as the Apache HTTP Server, Microsoft Internet Information Services (IIS), NGINX, or the like. In other embodiments, internal front-end system105may run custom web server software designed to receive and process requests from systems or devices depicted in system100(as well as other devices not depicted), acquire information from databases and other data stores based on those requests, and provide responses to the received requests based on acquired information.

In some embodiments, internal front-end system105may include one or more of a web caching system, a database, a search system, a payment system, an analytics system, an order monitoring system, or the like. In one aspect, internal front-end system105may include one or more of these systems, while in another aspect, internal front-end system105may include interfaces (e.g., server-to-server, database-to-database, or other network connections) connected to one or more of these systems. In some embodiments, internal front-end system105may be configured to direct workers for an FC to place items in specific locations. For instance, in some embodiments, SAT system101may be configured to perform predictive algorithms to identify the products that have a greater likelihood to be requested with a special delivery option. For example, SAT system101may be configured to identify the products that are most likely to be requested for dawn delivery or for first time delivery. In such embodiments, internal front-end system105may be in communication with SAT system101and produce websites and/or user interfaces for workers that guide product placement within the FC with the objective of improving delivery times and maximizing the number of products available for dawn, fresh, or first time delivery.

Transportation system107, in some embodiments, may be implemented as a computer system that enables communication between systems or devices in system100and mobile devices107A-107C. Transportation system107, in some embodiments, may receive information from one or more mobile devices107A-107C (e.g., mobile phones, smart phones, PDAs, or the like). For example, in some embodiments, mobile devices107A-107C may include devices operated by delivery workers. The delivery workers, who may be permanent, temporary, or shift employees, may utilize mobile devices107A-107C to effect delivery of packages containing the products ordered by users. For example, to deliver a package, the delivery worker may receive a notification on a mobile device indicating which package to deliver and where to deliver it. Upon arriving at the delivery location, the delivery worker may locate the package (e.g., in the back of a truck or in a crate of packages), scan or otherwise capture data associated with an identifier on the package (e.g., a barcode, an image, a text string, an RFID tag, or the like) using the mobile device, and deliver the package (e.g., by leaving it at a front door, leaving it with a security guard, handing it to the recipient, or the like). In some embodiments, the delivery worker may capture photo(s) of the package and/or may obtain a signature using the mobile device. The mobile device may send information to transportation system107including information about the delivery, including, for example, time, date, GPS location, photo(s), an identifier associated with the delivery worker, an identifier associated with the mobile device, or the like. Transportation system107may store this information in a database (not pictured) for access by other systems in system100. Transportation system107may, in some embodiments, use this information to prepare and send tracking data to other systems indicating the location of a particular package.

In some embodiments, certain users may use one kind of mobile device (e.g., permanent workers may use a specialized PDA with custom hardware such as a barcode scanner, stylus, and other devices) while other users may use other kinds of mobile devices (e.g., temporary or shift workers may utilize off-the-shelf mobile phones and/or smartphones).

In some embodiments, transportation system107may associate a user with each device. For example, transportation system107may store an association between a user (represented by, e.g., a user identifier, an employee identifier, or a phone number) and a mobile device (represented by, e.g., an International Mobile Equipment Identity (IMEI), an International Mobile Subscription Identifier (IMSI), a phone number, a Universal Unique Identifier (UUID), or a Globally Unique Identifier (GUID)). Transportation system107may use this association in conjunction with data received on deliveries to analyze data stored in the database in order to determine, among other things, a location of the worker, an efficiency of the worker, or a speed of the worker.

Seller portal109, in some embodiments, may be implemented as a computer system that enables sellers or other external entities to electronically communicate with one or more systems in system100. For example, a seller may utilize a computer system (not pictured) to upload or provide product information, order information, contact information, or the like, for products that the seller wishes to sell through system100using seller portal109.

Shipment and order tracking system111, in some embodiments, may be implemented as a computer system that receives, stores, and forwards information regarding the location of packages containing products ordered by customers (e.g., by a user using devices102A-102B). In some embodiments, shipment and order tracking system111may request or store information from web servers (not pictured) operated by shipping companies that deliver packages containing products ordered by customers.

In some embodiments, shipment and order tracking system111may request and store information from systems depicted in system100. For example, shipment and order tracking system111may request information from transportation system107. As discussed above, transportation system107may receive information from one or more mobile devices107A-107C (e.g., mobile phones, smart phones, PDAs, or the like) that are associated with one or more users (e.g., a delivery worker) or a vehicle (e.g., a delivery truck). In some embodiments, shipment and order tracking system111may also request information from workforce management system (WMS)119to determine the location of individual products inside of a fulfillment center (e.g., fulfillment center200). Shipment and order tracking system111may request data from one or more of transportation system107or WMS119, process it, and present it to a device (e.g., user devices102A and1026) upon request.

Fulfillment optimization (FO) system113, in some embodiments, may be implemented as a computer system that stores information for customer orders from other systems (e.g., external front-end system103and/or shipment and order tracking system111). FO system113may also store information describing where particular items are held or stored. For example, certain items may be stored only in one fulfillment center, while certain other items may be stored in multiple fulfillment centers. In still other embodiments, certain fulfillment centers may be designed to store only a particular set of items (e.g., fresh produce or frozen products). FO system113stores this information as well as associated information (e.g., quantity, size, date of receipt, expiration date, etc.).

FO system113may also calculate a corresponding cutoff time (maximum time for a specific delivery time) and/or PDD (promised delivery date) for each product. The cutoff time and PDD, in some embodiments, may be based on one or more factors. For example, FO system113may calculate a PDD for a product based on a past demand for a product (e.g., how many times that product was ordered during a period of time), an expected demand for a product (e.g., how many customers are forecast to order the product during an upcoming period of time), a network-wide past demand indicating how many products were ordered during a period of time, a network-wide expected demand indicating how many products are expected to be ordered during an upcoming period of time, one or more counts of the product stored in each fulfillment center200, which fulfillment center stores each product, expected or current orders for that product, or the like. Further, FO system113may calculate a cutoff time based on past deliveries, physical distance between the product location and the shipping center, and available personnel at the location of the FC, among others.

In some embodiments, FO system113may determine cutoff times and PDDs for each product on a periodic basis (e.g., hourly) and store it in a database for retrieval or sending to other systems (e.g., external front-end system103, SAT system101, shipment and order tracking system111). In other embodiments, FO system113may receive electronic requests from one or more systems (e.g., external front-end system103, SAT system101, shipment and order tracking system111) and calculate the PDD or cutoff time on demand. In yet other embodiments, FO system113may determine PDD and cutoff times as a use navigates through one of the webpages. Processes for calculation and transmission of PDD or cutoff times by FO system113are further described in connection toFIG. 7.

Fulfillment messaging gateway (FMG)115, in some embodiments, may be implemented as a computer system that receives a request or response in one format or protocol from one or more systems in system100, such as FO system113, converts it to another format or protocol, and forward it in the converted format or protocol to other systems, such as WMS119or 3rdparty fulfillment systems121A,121B, or121C, and vice versa.

Supply chain management (SCM) system117, in some embodiments, may be implemented as a computer system that performs forecasting functions. For example, SCM system117may forecast a level of demand for a particular product based on, for example, a past demand for products, an expected demand for a product, a network-wide past demand, a network-wide expected demand, a count products stored in each fulfillment center200, expected or current orders for each product, or the like. In response to this forecasted level and the amount of each product across all fulfillment centers, SCM system117may generate one or more purchase orders to purchase and stock a sufficient quantity to satisfy the forecasted demand for a particular product.

Workforce management system (WMS)119, in some embodiments, may be implemented as a computer system that monitors workflow. For example, WMS119may receive event data from individual devices (e.g., devices107A-107C or119A-119C) indicating discrete events. For example, WMS119may receive event data indicating the use of one of these devices to scan a package or that a sensor of the positioning systems has been triggered. As discussed below with respect to fulfillment center200andFIG. 2, during the fulfillment process, a package identifier (e.g., a barcode or RFID tag data) may be scanned or read by machines at particular stages (e.g., automated or handheld barcode scanners, RFID readers, high-speed cameras, devices such as tablet119A, mobile device/PDA1196, computer119C, or the like). Alternatively, a wireless sensor may determine a product has been taken into or out of the shelf. WMS119may store each event indicating a scan, a read of a package identifier, or a sensor event in a corresponding database (not pictured) along with the package identifier, a time, date, location, user identifier, or other information, and may provide this information to other systems (e.g., shipment and order tracking system111).

WMS119, in some embodiments, may store information associating one or more devices (e.g., devices107A-107C or119A-119C) with one or more users associated with system100. For example, in some situations, a user (such as a part- or full-time employee) may be associated with a mobile device in that the user owns the mobile device (e.g., the mobile device is a smartphone). In other situations, a user may be associated with a mobile device in that the user is temporarily in custody of the mobile device (e.g., the user checked the mobile device out at the start of the day, will use it during the day, and will return it at the end of the day).

WMS119, in some embodiments, may maintain a work log for each user associated with system100. For example, WMS119may store information associated with each employee, including any assigned processes (e.g., unloading trucks, picking items from a pick zone, rebin wall work, packing items), a user identifier, a location (e.g., a floor or zone in a fulfillment center200), a number of units moved through the system by the employee (e.g., number of items picked, number of items packed), an identifier associated with a device (e.g., devices119A-119C), or the like. In some embodiments, WMS119may receive check-in and check-out information from a timekeeping system, such as a timekeeping system operated on a device119A-119C.

3rdparty fulfillment (3PL) systems121A-121C, in some embodiments, represent computer systems associated with third-party providers of logistics and products. For example, while some products are stored in fulfillment center200(as discussed below with respect toFIG. 2), other products may be stored off-site, may be produced on demand, or may be otherwise unavailable for storage in fulfillment center200. 3PL systems121A-121C may be configured to receive orders from FO system113(e.g., through FMG115) and may provide products and/or services (e.g., delivery or installation) to customers directly. In some embodiments, one or more of 3PL systems121A-121C may be part of system100, while in other embodiments, one or more of 3PL systems121A-121C may be outside of system100(e.g., owned or operated by a third-party provider).

Fulfillment Center Auth system (FC Auth)123, in some embodiments, may be implemented as a computer system with a variety of functions. For example, in some embodiments, FC Auth123may act as a single-sign on (SSO) service for one or more other systems in system100. Further, FC Auth123may enable a user to log in via internal front-end system105, determine that the user has similar privileges to access resources at shipment and order tracking system111, and enable the user to access those privileges without requiring a second log in process. FC Auth123, in other embodiments, may enable users (e.g., employees) to associate themselves with a particular task. For example, some employees may not have an electronic device (such as devices119A-119C) and may instead move from task to task, and zone to zone, within a fulfillment center200, during the course of a day. FC Auth123may be configured to enable those employees to indicate what task they are performing and what zone they are in at different times of day.

Labor management system (LMS)125, in some embodiments, may be implemented as a computer system that stores attendance and overtime information for employees (including full-time and part-time employees). For example, LMS125may receive information from FC Auth123, WMA119, devices119A-119C, transportation system107, and/or devices107A-107C.

The particular configuration depicted inFIG. 1Ais an example only. For example, whileFIG. 1Adepicts FC Auth system123connected to FO system113, not all embodiments require this particular configuration. Indeed, in some embodiments, the systems in system100may be connected to one another through one or more public or private networks, including the Internet, an Intranet, a WAN (Wide-Area Network), a MAN (Metropolitan-Area Network), a wireless network compliant with the IEEE 802.11a/b/g/n Standards, a leased line, or the like. In some embodiments, one or more of the systems in system100may be implemented as one or more virtual servers implemented at a data center, server farm, or the like.

FIG. 2depicts a fulfillment center200. Fulfillment center (FC)200is an example of a physical location that stores items for shipping to customers when ordered. Fulfillment center (FC)200may be divided into multiple zones, each of which are depicted inFIG. 2. These “zones,” in some embodiments, may be thought of as virtual divisions between different stages of a process of receiving items, storing the items, retrieving the items, and shipping the items. So, while the “zones” are depicted inFIG. 2, other divisions of zones are possible and the zones inFIG. 2may be omitted, duplicated, and/or modified in some embodiments.

Inbound zone203represents an area of FC200where items are received from sellers who wish to sell products using system100(FIG. 1A). For example, a seller may deliver items202A and202B using truck201. Item202A may represent a single item large enough to occupy its own shipping pallet, while item202B may represent a set of items that are stacked together on the same pallet to save space.

A worker will receive the items in inbound zone203and may optionally check the items for damage and correctness using a computer system (not pictured). For example, the worker may use a computer system to compare the quantity of items202A and202B to an ordered quantity of items. If the quantity does not match, that worker may refuse one or more of items202A or202B. If the quantity does match, the worker may move those items (using, e.g., a dolly, a handtruck, a forklift, or manually) to buffer zone205. Buffer zone205may be a temporary storage area for items that are not currently needed in the picking zone, for example, because there is a high enough quantity of that item in the picking zone to satisfy forecasted demand. In some embodiments, forklifts206operate to move items around buffer zone205and between inbound zone203and drop zone207. If there is a need for items202A or202B in the picking zone (e.g., because of forecasted demand), a forklift may move items202A or202B to drop zone207.

Drop zone207may be an area of FC200that stores items before they are moved to picking zone209. A worker assigned to the picking task (a “picker”) may approach items202A and202B in the picking zone, scan a barcode for the picking zone, and scan barcodes associated with items202A and202B using a mobile device (e.g., device119B). Such event may update a real time location system that updates a database to specify the item has been moved into the FC. The picker may then take the item to picking zone209(e.g., by placing it on a cart or carrying it) and the real time location system may request the position of storage for the new item.

Picking zone209may be an area of FC200where items208are stored on storage units210. In some embodiments, storage units210may include one or more of physical shelving, bookshelves, boxes, totes, refrigerators, freezers, cold stores, or the like. In some embodiments, picking zone209may be organized into multiple floors. In some embodiments, workers or machines may move items into picking zone209in multiple ways, including, for example, a forklift, an elevator, a conveyor belt, a cart, a handtruck, a dolly, an automated robot or device, or manually. For example, a picker may place items202A and202B on a handtruck or cart in drop zone207and walk items202A and202B to picking zone209.

A picker may receive an instruction to place (or “stow”) the items in particular spots in picking zone209, such as a particular space on a storage unit210. For example, a picker may scan item202A using a mobile device (e.g., device119B). The device may indicate where the picker should stow item202A, for example, using a system that indicate an aisle, shelf, and location. In some embodiments, the location to stow item202A may be determined based on predictive algorithms that attempt to maximize the availability of special delivery options, such as dawn deliveries. The device may then prompt the picker to scan a barcode at that location before stowing item202A in that location. Alternatively, a wireless sensor or a camera coupled with image recognition, may store the location of the time. In some embodiments, the device may send (e.g., via a wireless network) data to a computer system such as WMS119inFIG. 1Aindicating that item202A has been stowed at the location by the user using device119B.

Once a user places an order, a picker may receive an instruction on device1198to retrieve one or more items208from storage unit210. In some embodiments, as further described in connection withFIG. 11, the picker may receive instructions through a placement or storing guide to stow the products. The picker may retrieve item208, scan a barcode on item208, and place it on transport mechanism214. While transport mechanism214is represented as a slide, in some embodiments, transport mechanism may be implemented as one or more of a conveyor belt, an elevator, a cart, a forklift, a handtruck, a dolly, a cart, or the like. Item208may then arrive at packing zone211.

Packing zone211may be an area of FC200where items are received from picking zone209and packed into boxes or bags for eventual shipping to customers. In packing zone211, a worker assigned to receiving items (a “rebin worker”) will receive item208from picking zone209and determine what order it corresponds to. For example, the rebin worker may use a device, such as computer119C, to scan a barcode on item208. Computer119C may indicate visually which order item208is associated with. This may include, for example, a space or “cell” on a wall216that corresponds to an order. Once the order is complete (e.g., because the cell contains all items for the order), the rebin worker may indicate to a packing worker (or “packer”) that the order is complete. The packer may retrieve the items from the cell and place them in a box or bag for shipping. The packer may then send the box or bag to a hub zone213, e.g., via forklift, cart, dolly, handtruck, conveyor belt, manually, or otherwise.

Hub zone213may be an area of FC200that receives all boxes or bags (“packages”) from packing zone211. Workers and/or machines in hub zone213may retrieve package218and determine which portion of a delivery area each package is intended to go to and route the package to an appropriate camp zone215. For example, if the delivery area has two smaller sub-areas, packages will go to one of two camp zones215. In some embodiments, a worker or machine may scan a package (e.g., using one of devices119A-119C) to determine its eventual destination. Routing the package to camp zone215may include, for example, determining a portion of a geographical area that the package is destined for (e.g., based on a postal code) and determining a camp zone215associated with the portion of the geographical area.

Camp zone215, in some embodiments, may include one or more buildings, one or more physical spaces, or one or more areas, where packages are received from hub zone213for sorting into routes and/or sub-routes. In some embodiments, camp zone215is physically separate from FC200while in other embodiments camp zone215may form a part of FC200.

Workers and/or machines in camp zone215may determine which route and/or sub-route a package220should be associated with, for example, based on a comparison of the destination to an existing route and/or sub-route, a calculation of workload for each route and/or sub-route, the time of day, a shipping method, the cost to ship the package220, a PDD associated with the items in package220, a delivery option, or the like. In some embodiments, a worker or machine may scan a package (e.g., using one of devices119A-119C) to determine its eventual destination. Once package220is assigned to a particular route and/or sub-route, a worker and/or machine may move package220to be shipped. In exemplaryFIG. 2, camp zone215includes a truck222, a car226, and delivery workers224A and224B. In some embodiments, truck222may be driven by delivery worker224A, where delivery worker224A is a full-time employee that delivers packages for FC200and truck222is owned, leased, or operated by the same company that owns, leases, or operates FC200. In some embodiments, car226may be driven by delivery worker224B, where delivery worker224B is a “flex” or occasional worker that is delivering on an as-needed basis (e.g., seasonally). Car226may be owned, leased, or operated by delivery worker224B.

In some embodiments, as shown inFIG. 2, one or more of the sections of FC200may include a positioning system217. Positioning system217may include a plurality of sensors that may be used to determine the position of products within the FC and track their movement through the FC. In such embodiments, sensors of positioning system217may be used for both, tracking the position of products in the FC and also estimating movement between different sections. For instance, sensors of positioning system217may be used to store historic data of time elapsed between the different regions of FC200. This information may then be used for determining distances or estimated times between storing zones and packing zones.

As shown inFIG. 2the positioning system217may include sensors217A in packing zone211, sensors2176in picking zone209, and sensors217C in drop zone205. However, more sensors may be placed in different regions of FC200with the goal of tracking and capturing the position of items FC200and improve the accuracy of estimated deliveries or maximize the availability of delivery options.

FIG. 3is a block diagram of an exemplary system300, consistent with disclosed embodiments. In system300a scheduling system320may process product requests from real-time client device's data streams to, for example, determine whether dawn delivery is available, a PDD, or estimated delivery for a product. The system may also generate instructions to display or modify a webpage to include the estimated delivery data. System300may include scheduling systems320, online resources340, client devices350, third-party systems360, item positioning systems390, and database380. In some embodiments, as shown inFIG. 3, components of system300may be connected to a network370. However, in other embodiments components of system300may be connected directly with each other, without network370. For example, database380may be directly coupled to scheduling systems320.

In some embodiments, scheduling systems320may be implemented with one or more of the components of system100(FIG. 1A). For example, scheduling systems320may include SAT system101, external front-end system103, FO system113, SCM system117, and/or WMS119(FIG. 1A). In other embodiments, scheduling systems320may be implemented with one or more independent servers configured to perform operations for estimating a delivery date, generating a PDD, and/or updating or generating webpages for client devices350.

Online resources340may include one or more servers or storage services provided by an entity such as a provider of webpage hosting, networking, cloud, or backup services. In some embodiments, online resources340may be associated with hosting services or servers that store web pages for authentication services, Domain Name System (DNS), or landing pages. In other embodiments, online resources340may be associated with a cloud computing service. In yet other embodiments, online resources340may be associated with a messaging service, such as, for example, Apple Push Notification Service, Azure Mobile Services, or Google Cloud Messaging. In such embodiments, online resources340may handle the delivery of messages and notifications related to functions of the disclosed embodiments, such as handling digital rights management.

Client devices350may include one or more computing devices configured to perform one or more operations consistent with disclosed embodiments. For example, client devices350may include a desktop computer, a laptop, a server, a mobile device (e.g., tablet, smart phone, etc.), a set-top box, a gaming device, a wearable computing device, or other type of computing device. In some embodiments, client devices350may include the user devices102(FIG. 1A) and be operated as part of system100. In other embodiments, however, client devices350may be independent from system100. Client devices350may include one or more processors configured to execute software instructions stored in memory, such as memory included in client devices350, to perform operations to implement the functions described below. For example, client devices350may be configured to display graphical user interfaces in webpages that include delivery date estimates generated by scheduling systems320. Further, client devices350may be configured for wired and/or wireless communications and may include software that when executed by a processor performs internet-related communication (e.g., TCP/IP) and content display processes. For instance, client devices350may execute browser software that generates and displays interfaces with product information. Thus, client devices350may execute applications that allow client devices350to communicate with components over network370and display content in interfaces via display devices included in client devices350.

In some embodiments, as further disclosed in connection toFIG. 4, client devices350may run applications specifically configured to interact with scheduling systems320. Moreover, client devices350may store one or more accounts. For example, client devices350may store information about a customer's delivery preferences, the customer's location, customer account, and customer identification.

The disclosed embodiments are not limited to any particular configuration of client devices350. For instance, a client device350may be a mobile device that stores and executes mobile applications to perform operations that provide functions offered by scheduling systems320and/or online resources340. In certain embodiments, client devices350may be configured to execute software instructions relating to location services, such as GPS locations. For example, client devices350may be configured to determine a geographic location and provide location data and time stamp data corresponding to the location data. Client devices350are further described in connection withFIG. 4.

Database380may include one or more computing devices configured with appropriate software to perform operations consistent with providing scheduling systems320data for calculating and/or retrieving estimated delivery dates and their respective cutoff times. Database380may include, for example, Oracle™ databases, Sybase™ databases, or other relational databases or non-relational databases, such as Hadoop™ sequence files, HBase™, or Cassandra™. Database380may include computing components (e.g., database management system, database server, etc.) configured to receive and process requests for data stored in memory devices of the database(s) and to provide data from the database(s).

While database380are shown separately, in some embodiments database380may be included in, or otherwise related to scheduling systems320or online resources340.

Database380may be configured to collect and/or maintain data associated with user accounts or products to facilitate delivery date or PDD estimations. For example, database380may store information about user profiles for users of system300. Database380may also store data structures that specify the location of products within an FC, an estimated packing time, and a cutoff time for specific deliveries, such as a cutoff time for dawn deliveries. Database380may also store other information about the location for the previously calculated delivery dates for a specific product and corresponding postal code, to quickly respond to delivery date estimation requests that have similar product and postal code pair. Database380may collect the data from a variety of sources, including, for instance, online resources340or third-party systems360. Further, database380may include information about client devices350operating systems. Database380are further described below in connection withFIG. 5.

In some embodiments, third-party systems360may include one or more elements of system100. For example, third-party systems360may include 3PL systems121A-121C. Additionally, or alternatively, third-party systems360may include one or more servers or storage services provided by an entity related to scheduling systems320, such as a provider of services or a fulfillment center. Third-party systems360may also be connected to system300via network370, but in other embodiments third-party systems360may include direct connections with some elements of system300. For example, to minimize delays or network congestion third-party systems360may be connected in a private network with scheduling systems320. Further, third-party systems360may be configured to provide and/or request information from scheduling systems320, or other elements of system300. In some embodiments, while third-party systems360may also be coupled to network370, they may not be clients of scheduling systems320. Instead, third-party systems360may include systems that include information of users or clients of scheduling systems320. For example, third-party systems360may include servers of delivery contractors such as FedEx®, which may be used by scheduling systems320when a product delivery involves a third-party contractor. Similarly, if a product is not available within fulfillment centers in system100(FIG. 1), third-party systems360may perform their own calculations and inform scheduling systems320about the tentative delivery date or PDD.

Item positioning systems390may include sensors and processors for determining and/or storing the location of products within an FC. For example, item positioning systems390may include sensors217A-217C (FIG. 2). Alternatively, or additionally, item positioning systems390may include cameras that capture images of shelves and use image recognition methods to identify products and determine the position of products in the FC. Further, item positioning systems390may be coupled to scan devices and track the positioning of products in an FC by monitoring scanning events of products. Moreover, item positioning systems390may be in communication with scheduling systems320to provide information that facilitates estimating cutoff times for specific delivery times or to provide more accurate PDDs.

Network370may be any type of network configured to provide communications between components of system300. For example, network370may be any type of network (including infrastructure) that provides communications, exchanges information, and/or facilitates the exchange of information, such as the Internet, a Local Area Network, near field communication (NFC), optical code scanner, or other suitable connection(s) that enables the sending and receiving of information between the components of system300. In other embodiments, one or more components of system300may communicate directly through a dedicated communication link(s). In yet other embodiments, network370may include multiple networks, organizing for example a network or networks.

It is to be understood that the configuration and boundaries of the functional building blocks of system300have been defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent. Such alternatives fall within the scope of the disclosed embodiments.

Referring now toFIG. 4, there is shown a block diagram of an exemplary client device350(FIG. 3), consistent with disclosed embodiments. In some embodiments, client devices350may implement user devices102(FIG. 1A).

In one embodiment, client devices350may include one or more processors402, one or more input/output (I/O) devices404, and one or more memories410. In some embodiments, client devices350may take the form of mobile computing devices such as smartphones or tablets, general purpose computers, or any combination of these components. Alternatively, client devices350(or systems including client devices350) may be configured as a particular apparatus, embedded system, dedicated circuit, and the like based on the storage, execution, and/or implementation of the software instructions that perform one or more operations consistent with the disclosed embodiments. According to some embodiments, client devices350may include web browsers or similar computing devices that access web site consistent with disclosed embodiments.

Processor402may include one or more known processing devices, such as mobile device microprocessors manufactured by Intel™, NVIDIA™, or various processors from other manufacturers. The disclosed embodiments are not limited to any specific type of processor configured in client devices350.

Memory410may include one or more storage devices configured to store instructions used by processor402to perform functions related to disclosed embodiments. For example, memory410may be configured with one or more software instructions, such as programs412that may perform operations when executed by processor402. The disclosed embodiments are not limited to separate programs or computers configured to perform dedicated tasks. For example, memory410may include a single program412that performs the functions of the client devices350, or program412may include multiple programs. Memory410may also include a client application414which may configure client devices350to communicate or execute operations to interact with other elements of system300. For example, client application414may specify instructions to communicate with scheduling systems320and/or generate product information requests, as further described in connection withFIG. 7. In addition, client applications414may interpret instructions for generating graphical user interfaces (GUI) in client devices350or modifying displayed GUI. Memory410may also store data416that may be used by scheduling systems320to assign deliveries estimates or PDDs to the client device.

In certain embodiments, memory410may store instructions for accessing or sending requests to scheduling systems320. For example, memory410may include an application that communicates with scheduling systems320via TCP/IP. Moreover, other software components may be configured to request information from scheduling systems320or determine the location of client devices350. For instance, these software instructions, when executed by processor(s)402, may process information to display available delivery options for the product or PDD in a webpage. The software instructions may also implement scripts to modify webpages being displayed in client devices350.

I/O devices404may include one or more devices configured to allow data to be received and/or transmitted by client devices350and to allow client devices350to communicate with other machines and devices, such as other components of system300. For example, I/O devices404may include a screen for confirming delivery of a parcel or providing information to the user. I/O devices404may also include components for NFC communication. I/O devices404may also include one or more digital and/or analog devices that allow a user to interact with client devices350such as a touch-sensitive area, buttons, or microphones. I/O devices404may also include one or more accelerometers to detect the orientation and inertia of client devices350. I/O devices404may also include other components known in the art for interacting with scheduling systems320.

In some embodiments, client devices350may also include a camera420that capture images and may be used for identification of a product that the user wants. Such identification may trigger the delivery date estimation or PDD calculation. Additionally, or alternatively, client devices350may include a fingerprint sensor430that allows users to unlock client devices350to access their accounts, send request for information, and purchase items. Both camera420and fingerprint sensor430may be operated by processor402and use encryption security to make it impossible for users to externally access fingerprint or camera information.

The components of client devices350may be implemented in hardware, software, or a combination of both hardware and software, as will be apparent to those skilled in the art.

Referring now toFIG. 5, there is shown a block diagram of an exemplary database380(FIG. 3), consistent with disclosed embodiments. In some embodiments, database380may be included in elements of system100. For example, database380may be part of the FO system113or the WMS119(FIG. 1A).

Database380may include a communication device502, one or more database processors504, and database memory510including one or more database programs512and data514. Database380may include NoSQL databases such as HBase, MongoDB™ or Cassandra™. Alternatively, database380may include relational databases such as Oracle, MySQL and Microsoft SQL Server.

In some embodiments, database380may take the form of servers, general purpose computers, mainframe computers, or any combination of these components. In some embodiments, database380are included within other elements of system300, such as scheduling systems320. Other implementations consistent with disclosed embodiments are possible as well.

In some embodiments, database380may include both non-relational and embedded databases. For example, database380may include a non-relational database, such as an Hbase, and an embedded database, such as a RocksDB (e.g., a key-value store database).

Communication device502may be configured to communicate with one or more components of system300or system100, such as online resources340, scheduling systems320, or SCM system117. In particular, communication device502may be configured to provide scheduling systems320order information, user preferences and privileges, position of products within the FC, and/or historic previous estimations for similar postal codes and products inquiries.

The components of database380may be implemented in hardware, software, or a combination of both hardware and software. For example, although one or more components of database380may be implemented as computer processing instruction modules, all or a portion of the functionality of database380may be implemented instead in dedicated electronics hardware.

Database memory510may include programs512, which may include instructions to update webpages based on delivery estimates, PDDs received or generated by scheduling systems320, or cutoff times associated with different zones in an FC. Further, database memory510may include instructions for communications between elements of system300. For example, database memory510may include instructions for communications between client devices350and scheduling systems320. Further programs512may include instructions to store information in real-time as it is processed by scheduling systems320.

Data514may also be data associated with webpages, such as online resources340, or user accounts from client devices350. Data514may include, for example, information relating to previous delivery estimation calculations, available delivery options for products in an FC, or previous PDDs associated with postal codes. Data314may also include content files and accumulation variables to evaluate capacity of fulfillment centers and order availability.

FIG. 6is a process flow diagram of an exemplary delivery estimation distribution, consistent with disclosed embodiments. In some embodiments, system100, or portions of system100, may perform calculations to determine an estimated delivery. System100may then transmit PDD information to online modules600that generate webpages for client interaction.

In some embodiments, as shown inFIG. 6, elements of system100may communicate with each other to generate an estimated delivery date or to identify the available delivery options. For example, external front-end system103may receive a request for a delivery estimate from user devices102A-102B (FIG. 1A). The request may then be transmitted to an FO system113that may determine a selected fulfillment center and an estimated delivery time, as further described in connection toFIG. 9. Then FO system113may send the selected fulfillment center and estimated delivery date to fulfillment messaging gateway115. In turn fulfillment messaging gateway115may send the information to the online modules600.

Online modules600may include a search result page (SRP) module604, a single display page (SDP) module606, an order management module608, and a shopping cart module610. Each one of the modules may generate different webpages for display to consumers. For example, SRP module604may generate result pages (like the one described in connection withFIG. 1B) for user devices102, while SDP module606may generate single product webpages (like the one described in connection withFIG. 1C) for user devices102. Similarly, order management module608may generate or update order pages (like the one described in connection withFIG. 1E) while shopping cart module610may generate or update cart pages (like the one described in connection withFIG. 1D). Therefore, each one of online modules600may incorporate hypermedia elements in webpages to display the estimated delivery date, display delivery options, PDDs received from system100, or cutoff times associated with delivery options.

Moreover, each one of online modules600may perform different operations when receiving estimated delivery dates. For example, after receiving a PDD SRP module604may store PDDs and/or delivery cutoff times for similar products and/or similar locations in cache memory for future searches. Then, when SRP module604receives a search request—within the cutoff time associated with the PDD or estimated delivery—that has the same or similar postal code and product, SRP module604does not need to query system100. Instead, SRP module604may immediately update the search webpage based on previous information. Conversely, SDP module606may generate files for updating product webpages when receiving a PDD or delivery estimate. For example, SDP module606may generate a JavaScript or HTML file that updates the product webpage. Further SDP module606may initiate a clock or timer to determine if the delivery date estimation has expired. In such embodiments, SDP module606may generate a second file to update the single product webpage if necessary (e.g., the estimated delivery time has expired).

Further, order management module608may also react to receiving PDDs or estimated delivery dates from system100. For example, in response to receiving estimated delivery date, order management module608may prepare an electronic message for a selected fulfillment center. This preparatory message may be configured to be deployed if an order is received. In this way, online modules600may prepare for potential orders and facilitate meeting the a PDD by minimizing delays between order and transmission to fulfillment centers. In some embodiments, order management module608may be coupled to SAT system101(FIG. 1A) and the preparatory message may be forwarded to SAT system101as soon as an order is received. Moreover, shopping cart module610may generate a script for updating cart webpages using the delivery date information. For example, shopping cart module610may modify cart webpages to include timers and/or counters based on the expiration times of the estimated delivery dates. Alternatively, or additionally, shopping cart module610may modify websites to indicate cutoff times for multiple delivery options based on the product locations within the FC.

FIG. 7is a flow chart of an exemplary process700for handling a request for product delivery estimate, consistent with disclosed embodiments. In some embodiments, elements of system300may perform process700. For example, as disclosed in the description below, scheduling systems320may perform process700. This is just an illustrative example of process700, however, and in other embodiments system100, or parts of system100, may perform process700. For example, Shipment Authority Technology System101, FO System113, and/or order tracking system111(FIG. 1A) may perform one or more of the steps in process700.

In step702, scheduling systems320may receive a request for product information from a remote device. For example, as a user of client devices350navigates in a webpage, client devices350may send a request for product information to scheduling systems320. Moreover, the request may include a username, a postal code, and a physical location. Alternatively, or additionally, scheduling systems320may receive the request from online resources340. Online resources340may communicate with scheduling systems320to request product and estimated delivery information to prepare webpages. Further, online modules600may send requests for product information, estimated delivery, and/or product availability.

In step704, scheduling systems320may send a request for delivery estimate based on the information received from the request in step702. Scheduling systems320may prepare and send a request to other elements of system300or system100. For example, scheduling systems320may prepare a request for estimated delivery and PDD for FO system113. In such embodiments, the FO system113may act as a second system that includes in-memory storage including multiple delivery dates for different products that have been previously calculated. Alternatively, or additionally, FO system113may also include records of products locations and associated cutoff times for delivery options. Further, scheduling systems320may include front-end and a back-end portions. In such embodiments, the front-end may be configured to receive and process requests while the back-end may be configured to compute PDD or estimate delivery cutoff times. Like with FO system113, the back-end portions of scheduling systems320may include multiple delivery dates for different products to minimize calculations whenever a request is similar to a previous request that has not expired.

In some embodiments, the request for delivery estimate of step704may be directed to a specific type of fulfillment center. For example, the product information received with the request in step702may be associated with a fresh product (e.g., products such as fruits, vegetables, other type of produce and/or other perishable items). If the request for product information is associated with fresh products, scheduling systems320may tailor the request for delivery estimate for the fresh product and send it to a specific fulfillment center. For instance, when scheduling systems320determine the client is requesting information for a fresh product, scheduling systems320may associate a customer region with the remote device and determine a fresh fulfillment center (i.e., a fulfillment center that carries fresh products) that serves the customer region. Scheduling systems320may then transmit the request for delivery estimate to the fresh fulfillment center.

Moreover, in some embodiments the request for delivery estimate of step704may be directed to a specific fulfillment center based on the fulfillment center location or capacity. For example, some requests may be associated with specific delivery types. The specific delivery types may include “Fresh” deliveries, for products that may expire quickly, or “Dawn” deliveries. Fresh and Dawn deliveries may be services for specific customer accounts that allow users to get a perishable product or receive items by dawn next day. For example, when a dawn delivery is available for a user, the delivery may be guaranteed by a predefined time, such as 7 AM. Thus, if the request for product information is associated with a dawn delivery service, scheduling systems320may create a specific request directed to fulfillment centers based on location.

Specific delivery types, such as fresh or dawn deliveries, may trigger a delivery process or mechanism that differ from nonspecific delivery types. For example, for dawn deliveries scheduling systems320may select fulfillment centers in system300based on a dawn cutoff time. In such embodiments, scheduling systems320may determine that products ordered from a fulfillment center before the dawn cutoff time can be delivered by dawn next day. Further, scheduling systems320may use tracking systems to determine specific cutoff times for each product based on the product time and its location in the FC. However, scheduling systems320may determine that products ordered from the fulfillment center after the product's or FC location cutoff time cannot be delivered by dawn. Further, fulfillment centers in system300may have a designed coverage area. Based on fulfillment centers dawn cut off times and coverage area, scheduling systems320may route the request for product information to a specific fulfillment center in step704. For example, scheduling systems320may identify fulfillment centers that may accept a dawn delivery request based on the distance between the fulfillment center and the remote device. While fulfillment centers that are far away may have an early cutoff, fulfillment centers that are close may have a later cutoff. Thus, scheduling systems320may direct request for delivery estimate only to fulfillment centers that may complete the order by dawn in step704.

Arranging fulfillment centers with cutoff times and service regions for dawn deliveries, may allow scheduling systems320to minimize network congestion when resolving dawn delivery requests. By performing determinations before transmitting requests to fulfillment center brokers, scheduling systems320may be able to minimize the number of communications when handling dawn deliveries, which may be highly time sensitive. Moreover, having cutoff times for specific regions in the FC and/or for specific products, allow greater level of shipping customization or fine-tuning without affecting the overall's FC workflow.

In step706, scheduling systems320may receive a delivery estimate, PDD, or delivery cutoff. For example, scheduling systems320may receive a cutoff time for dawn delivery from FO system113. Alternatively, scheduling systems320may receive the PDD from database380or FO system113. Further, in embodiments where the scheduling systems320has a back-end calculator and a front-end gateway, the front-end portion of scheduling systems320may receive the calculated estimated delivery from the back-end portions. The delivery estimate or PDD received in step706may include an expiration or cutoff time that specifies when the order needs to be received in order to meet the PDD or have a valid predicted delivery date. This cutoff time may be determined based on the position of the product within the FC as determined by, for example, item positioning system390(FIG. 3). Thus, the estimated delivery may include a conditional expiration or cutoff time for each product that specifies when is the deadline to guarantee the delivery of the product.

In step708, scheduling systems320may generate an electronic message including the estimated delivery date or the cutoff time for a delivery option. The electronic message may be formatted specifically for the remote systems that generated the query in step702. For example, scheduling systems320may generate an electronic message for client devices350when they request the product information. The electronic message may include a TCP/IP message, SMS message, or other similar electronic communications. The electronic message generated in step708may include an HTML File or JavaScript with product information and delivery information, as further described in connection toFIG. 16. In some embodiments, the HTML file may include the product information, the delivery date estimate, and instructions to modify the webpage. In such embodiments, the modification instructions may include identifying the webpage's type (the webpage's type being one of a search result page, a single detail page, a cart page, or an order page) and modifying the webpage based on the webpage's type.

Moreover, the electronic message of step708may specify instructions to generate or modify a webpage in the remote device. In some embodiments, the HTML File or JavaScript may be configurable to modify webpages instead generating a new one. For example, when a user of client devices350is browsing a webpage that displays products, like described inFIG. 1B, the electronic message may include instructions to modify the webpage; instead of sending updated versions of the webpage as estimated deliveries are computed. Such embodiments may improve the technical field of generating dynamic webpages by minimizing network congestion. Moreover, in some embodiments the instructions to modify the website may include modifying product icons to include fresh, dawn, first-time delivery, or non-fresh dawn indicators based on the product information.

In step710, scheduling systems320may transmit the electronic message of step708to the remote device. For example, the HTML or JavaScript files generated in step708may be transmitted to client devices350when client devices350request the product information. In embodiments that employ dawn delivery options, scheduling systems320may perform specific instructions to communicate with users in step710. For example, when a user of client devices350is set to receive a dawn delivery, scheduling systems320may activate two settings. First, scheduling systems320may identify products going to be delivered by dawn and issue a promise of dawn delivery, for example delivery by 7 AM. Further, scheduling systems320may modify graphical user interfaces, as further described in connection withFIG. 12, to indicate the dawn delivery promise. Second, when fulfilling dawn deliveries, scheduling systems320may program a messaging service (such as Google Cloud Messaging (GCM) or Apple Push Notification service (APNs)) to send a push notification at a predefined time to customers. In such embodiments, scheduling systems320may program push notifications to include delivery info, photos of the delivered package, and/or data associated with delivery. Further, scheduling systems320may program and generate push/text notifications based on user preferences that can be set during checkout. For example, a user may select the time of the push notification, or whether the user wants an SMS in addition to the push notification. An alternative user selection may include receiving both push notifications and SMS immediately after the package is delivered, even if the delivery is scheduled at, for example, 4 AM.

In step712, scheduling systems320may receive an acknowledgement. For example, scheduling systems320may receive an acknowledgement from client devices350that the electronic message was received. Further, based on receiving the acknowledgement, scheduling systems320may initiate a timer based on the cutoff time associated with the product time. With this configuration, scheduling systems320may save resources on the number of timers that need to be employed to monitor expiration of estimated delivery dates. Instead of immediately starting timers for estimated delivery dates or PDDs, scheduling systems320may minimize utilization of computational resources by only initiating timers when client devices350acknowledge they received and/or displayed the estimated delivery.

In step714, scheduling systems320may determine whether an order for a product has been received. For example, scheduling systems320may review order requests in order data streams to determine if the customer associated with the remote device has completed the order. If scheduling systems320determine an order has been received (step714: Yes), scheduling systems320may continue to step716an initiate a fulfillment process. Thus, scheduling systems320may send instructions to a one or more FCs shipping zone to ship the product or initiate the process to fulfill the order. For example, scheduling systems320may engage with SAT system101to begin processing the order.

However, if scheduling systems320determine an order has not been received (step714: No), scheduling systems320may continue to step718. In step718, scheduling systems320may determine whether the time has expired or that the cutoff passed. For example, if the delivery estimate received in step706was associated with an expiration time of one hour, in step718scheduling systems320may determine whether an hour has lapsed since the delivery estimate was received. Similarly, if the cutoff assigned for the product in the FC is 4 PM, in step718scheduling systems320may determine whether the order was received after 4 PM. If scheduling systems320determine that the expiration time has not lapsed (step718: No), scheduling systems320may return to step714and continue monitoring whether an order has been received for the product and cycle between steps714and step718. However, if scheduling systems320determine the expiration time lapsed (step718: Yes), scheduling systems320may continue to step720and send a new request for updated delivery estimate. For example, scheduling systems320may send a request for updated delivery estimates to the fulfillment centers or to a back-end portion of the scheduling systems320.

In some embodiments, requesting an updated PDD or cutoff time estimate in step720may include identifying FCs based on the remote device information, requesting available inventory from identified FCs, and selecting an FC from the identified fulfillment centers based on a match between corresponding available inventory and the product identification.

In step722, scheduling systems320may receive an updated delivery estimate from fulfillment center or back-end calculator portion of the system. For example, because the cutoff time lapsed or the PDD estimate expired, scheduling systems320may receive an updated cutoff time for a different delivery type or PDD that is later than the first delivery estimate received in step706. If the initial delivery estimate was “Monday at 20:00” the second delivery estimate may be “Tuesday at 10:00.” If the earliest cutoff time was “4 PM for dawn delivery,” the later cutoff time may be “8 PM for before lunch delivery.” This second delivery or cutoff may also include an expiration time. Nevertheless, in some situations the second delivery estimate received in step722may be the same but include an updated expiration time.

In some embodiments, steps720and722may be executed by performing operations of determining the estimate expiration for the first delivery estimate lapsed, providing (to a second system such as FO systems113) a third request for a second delivery date estimate, receiving (from the second system) the second delivery date estimate, and generating a second electronic message with instructions to modify the webpage by substituting the first delivery date estimate with the second delivery date estimate.

In step724, like in step712, scheduling systems320may receive an acknowledgement and initiate a timer based on the new expiration time. Moreover, scheduling systems320may return to step714to monitor the order, cutoff times for specific products, and delivery date estimates to initiate fulfillment process or request, again, an update for the delivery estimate when the expiration lapses.

FIG. 8is a flow chart of an exemplary process800for handling estimate requests of products fulfilled by third parties, consistent with disclosed embodiments. In some embodiments, elements of system300may perform process800. For example, as disclosed in the steps description below, scheduling systems320may perform process800. Alternatively, or additionally, third-party systems360may perform process800, or parts of process800. Further, in other embodiments system100, or parts of system100, may perform process800. For instance, FO system113and 3PL systems121may perform process800.

In step802of process800, scheduling systems320may receive a request for product information including product, customer, and timestamp information. For example, scheduling systems320may receive a request for product information from client devices350. The request may also include customer information, such as a postal code, and a timestamp of when the request was generated.

In step804, scheduling systems320may determine whether the product would be fulfilled by a third party. For example, scheduling systems320may determine the product is unavailable in local inventory and would need to be fulfilled by a third party. Alternatively, scheduling systems320may determine the product is normally fulfilled by third parties by default, without requiring an inventory query.

If scheduling systems320determine the product is not fulfilled by a third party (step804: No), scheduling systems320may continue to step806and initiate the process to determine a selected fulfillment center. For example, as further described in connection toFIG. 9, based on the postal code of the customer, product availability, and fulfillment center capacity, scheduling systems320may identify a fulfillment center that has a priority to complete an order. In step808, scheduling systems320may send an estimated delivery and cutoff time based on the selected FC. For example, once a FC is identified in step806, scheduling systems320may request a product location within the FC, determine a delivery date estimate, and send it to client devices350for display to customers.

However, if scheduling systems320determine the product is fulfilled by a third party (step804: Yes), scheduling systems320may continue to step810and prepare a request for estimated delivery or PDD from the third party. For example, in step810scheduling systems320may prepare and send a request for PDD to third-party systems360or 3PL systems121. The request sent to the third party may include the product information and customer information (e.g., customer's postal code).

In step812, scheduling systems320may receive the estimated delivery date from third parties that may fulfill an order for the product requested in step802. For instance, scheduling systems320may receive a PDD and delivery estimate information from one of third-party systems360. Further, in step812scheduling systems320may receive a cutoff time that depends on the positioning of the requested item within the third party facilities.

In step814, scheduling systems320may prepare an electronic message including a JavaScript or HTML file to update or generate webpages including the estimated delivery date and/or time. The electronic message may then be submitted to the requester of product information in step802.

Steps in process800may be stored in a memory device of scheduling systems320, which may include instructions to determine, by consulting a database (such as databases180), whether delivery of the product will be fulfilled by a third party. Scheduling systems320may also, based on determining that the delivery of the product will be fulfilled by a third party, provide the request for a delivery date estimate to a system associated with the third party. Further, based on determining that the delivery of the product will not be fulfilled by a third party, scheduling systems320may provide the request for a delivery date estimate to a system that pre-stores a plurality of delivery date estimates in memory.

FIG. 9is a flow chart of a retail website modification process900, consistent with disclosed embodiments. In some embodiments, elements of system300may perform process900. For example, as disclosed in the steps description below, scheduling systems320may perform process900. However, in other embodiments system100, or parts of system100, may perform process900. For example, FO System113and/or FC Auth123(FIG. 1A) may perform one or more of the steps in process900.

In step902, scheduling systems320may receive a request for product information from a client device. The request may include product, time, and postal code information. Based on the information in the request, scheduling systems320may identify relevant geographical regions in step904to associate at least one fulfillment center based on the client's device id and the product. For example, scheduling systems320may identify regions that may fulfill a potential order for the product based on the customer's postal code. Alternatively, or additionally, scheduling systems320may identify FCs that are capable of fulfilling orders under specific delivery options, such as dawn delivery.

In step906, scheduling systems320may retrieve first data structures indicating locations within FCs and production locations. For example, scheduling systems320may query servers or databases that include FC information to retrieve data structures that include information of the specific position or location of the requested products withing the FC identified in step904. The data structures may include matrixes, arrays, tables, or maps. Further the data structures may also be implemented with resizable arrays of multi-type variables (depending on the language, individual elements may either all be forced to be the same type or may be of almost any type). Moreover, the data structures may include linked lists with a linear collection of data elements of any type, called nodes, where each node has itself a value, and points to the next node in the linked list. The data structures may also include records (also called tuples or structs), unions (a data structure that specifies which of a number of permitted primitive types may be stored in its instances), or a tagged union (also called variant). Further, the data structures may include objects, an in-memory instance of a class from a taxonomy.

In step908, scheduling systems320may retrieve one or more second data structures, which may indicate cutoff times for FCs locations. The second data structures may be implemented like the first data structures. That is, second data structures may also be implemented with, for example, arrays, matrices, lists, or unions. However, unlike the first data structures, the second data structures may not have information about the product in the FC, but information about cutoff times for deliveries based on locations in the FC. For example, as further described in connection toFIG. 14, FCs may be divided in virtual regions each region having its own cutoff time for certain delivery methods. For example, FCs may be divided in multiple zones with different cutoff times for dawn deliveries. The second data structure of step908may specify this information.

In step910, scheduling systems320may identify locations of the product based on first data structures. For example, scheduling systems320may determine a location of the requested product by searching entries in the first data structure that match the requested location. In step912, scheduling systems320may determine cutoff times based on the location of products by correlating the product location with the cutoff times stored in the second data structure. For example, scheduling systems320may determine first time delivery cutoff times based on location retrieved from the first data structures by correlating the location with a cutoff time in the second data structure.

In step914, scheduling systems320may determine whether the request of step902was received within cutoff time for a specific delivery. For example, scheduling systems320may determine whether the product request was received before the cutoff time for a first time delivery by comparing the cutoff time retrieved form the second data structure and the time stamp in the received order.

If scheduling systems320determine that the request was delivered before the cutoff time (step914: Yes), scheduling systems320may continue to step916. In step916, scheduling systems320may calculate remaining time before the cutoff. For example, if the cutoff time is 4 PM and the request was received at 2 PM, scheduling systems320may calculate a remaining time before the cutoff of 2 hours. Further, scheduling system320may continue to step918and generate an interactive icon for first time delivery. In step918scheduling system320may also generate instructions to include the remaining time before the cutoff in the website. For example, when requests are generated by client devices, scheduling system320may, determine a fulfillment center and associated physical location for the product and send cutoff times associated with the physical location to the system for displaying web pages. Hence, in some embodiments, each cutoff time may be inversely proportional to respective ones of the calculated distance for each of the associated physical locations.

If, however, scheduling systems320determine that the request was not received before the cutoff time (step914: No), scheduling systems320may continue to step920. In step920, scheduling systems320may calculate estimated delivery for a standard delivery. For example, using a PDD determination process, as further described in connection toFIG. 7, scheduling systems320may calculate an estimated delivery for the product under standard shipping. Further, scheduling systems320may also generate instructions to modify website indicating estimated delivery in step922. For example, scheduling system320may generate HTML or JavaScripts to display the available delivery options, respective cutoff times, and respective icons for the delivery types.

FIG. 10is a process flow diagram of an exemplary product location identification process1000, consistent with disclosed embodiments. Process1000may be performed by system300, or parts of system300. For example, as described below scheduling systems320may perform process1000. This is just an illustrative example of process1000, however, and in other embodiments system100, or parts of system100, may perform process1000. For example, Shipment Authority Technology System101, FO System113, and/or order tracking system111(FIG. 1A) may perform one or more of the steps in process1000.

In step1002, scheduling systems320may receive a scan or sensor event. For example, scheduling systems320may receive a signal from sensors217A-217C (FIG. 2) indicating that a product was placed or removed from a shelf. Alternatively, or additionally, scheduling systems320may receive a notification that a product has been scanned in the picking zone triggering the product positioning system. Moreover, in step1002scheduling systems320may receive an electronic message from item positioning system390(FIG. 3) indicating a product was relocated within an FC. The electronic message may be generated when with the scan event and/or the sensor event.

In step1004, scheduling systems320may determine whether the scan or sensor event is associated with the shelving of a product. For example, scheduling systems320may determine whether a sensor got triggered because a product was placed in the shelf or because a new pallet was placed in the picking zone. If scheduling systems320determine that the scan or sensor event is associated with shelving a product (step1004: Yes), scheduling systems320may continue to step1006, in which scheduling systems320may calculate a distance of product to the packing center. The distance calculated in step1006may be a physical distance (a distance in meters from product's location to the packing center). However, the calculated distance or distance score may be an equivalent distance measured in units different from length. For example, the calculated distance may be expressed in time and in step1006scheduling system may calculate a distance in minutes from the product to the packing center. Alternatively, or additionally, the distance between the product and the packing center may be determined in arbitrary units that include, for example, a unit that combines physical distance and travel time. When calculating the distance between the product and the packing center, scheduling systems320may take into account the floor in which the product is located, availability of elevators or conveyer belts, number of employees in the location of the product, among other factors.

In step1008, scheduling systems320may estimate cutoff for first time delivery based on the distance. For example, if the calculated distance is long, the distance may indicate the product is far away from the packing center or that it is difficult to take the product from the shelf to the packing center (e.g., there are not enough employees and there are delays in bringing products to packing centers). Thus, the cutoff time for first time delivery may need to be early to guarantee that the product will be delivered to the packing center on time. Alternatively, if the calculated distance is short, the distance may indicate that the product is close to the packing center and the FC may afford to wait until later for first time deliveries (i.e., have a later cutoff time). Using a distance to packing center to determine cutoff times for each product or location in the FC allows a greater level of specificity that enables providing first time deliveries for longer and later cutoffs. Thus, the determination of distances for packing centers facilitates creating workflows for shipping and improve computerized scheduling.

In step1010, scheduling systems320may update database and/or data structures. For example, scheduling systems320may update database380to store the cutoff calculated for the location identified in step1008. Further, scheduling systems320may update the database of inventory and product locations based on the information received in steps1006-1008. In some embodiments, scheduling systems320may update the first data structure of step906which includes FC virtual zones and the product locations within the FC.

If in step1004scheduling systems320determine that the scan or sensor event is not associated with shelving a product (step1004: No), scheduling systems320may infer that the even was triggered by a removed item and continue to step1012.

In step1012, scheduling systems320may determine whether additional items remain in the same shelf. For example, using sensors data or image recognition techniques, scheduling systems320may determine whether additional items of the same product remain in the shelf. Alternatively, or additionally, in step1012scheduling systems320may retrieve inventory information from an FC server and determine whether additional elements remain in the shelf. Furthermore, scheduling systems320may determine whether additional items remain in the shelf using sensors, like wireless BLE sensors, weight sensors, and/or RFID tags.

If scheduling systems320determine that additional items do not remain in the same shelf (step1012: No), scheduling systems320may continue to step1014and update the FC inventory. In some embodiments, updating the FC inventory may include re determining the cutoff time for first time delivery associated with the product. Because the product is no longer available in the location that was used for the cutoff time determination, in step1014scheduling systems1014may update first data structures (to indicate the product is no longer available in the previously store location) and the second data structure (to indicate the product should no longer be associated with previously computed cutoff time).

However, if scheduling systems320determine that additional items remain in the same shelf (step1012: Yes), scheduling systems320may continue to step1016.

In step1016, scheduling systems320may initialize a packing timer. With the goal to have more precise information about travel times between shelfs and packing centers, scheduling system320may initialize a timer once a product is removed from the shelf. This information may be used to train predictive algorithms that determine the distance described in step1008. For example, times between shelfs and packing centers may be used to train a machine-learning algorithm that use Random Forest or Non-Linear Regressions to determine or adjust the distance that is used to estimate travel times between shelfs and packing centers and, in turn, fine tune the cutoff times.

In step1018, scheduling systems320may receive scan event at packing center. This may occur when the product that triggered the event in step1002is delivered in the packing center. Thus, in step1020, scheduling systems320may stop timer and store lapsed time. This lapsed time is the actual travel time between shelf and packing center and may be used to fine tune cutoff time for the location and product.

In some embodiments, after stopping the timer in step1020, scheduling system320may return to step1010and update database and/or data structures. For example, scheduling systems320may update the second data structure to update the cutoff time associated with a region based on the measured travel time.

FIG. 11is a flow chart of a placement guide generation process1100, consistent with disclosed embodiments. In some embodiments, elements of system300may perform process1100. For example, as disclosed in the steps description below, scheduling systems320may perform process1100. However, in other embodiments system100, or parts of system100, may perform process1100. For example, FO System113and/or FC Auth123(FIG. 1A) may perform one or more of the steps in process1100.

In step1102, scheduling systems320may retrieve records of first time deliveries by FC. For example, scheduling systems320may query database380to obtain records of first time deliveries by an FC. The records may include order time, item description, time to packing center, and successful or unsuccessful first time delivery.

In step1104, scheduling systems320may perform statistical analysis of first time deliveries by FC. The statistical analysis may include a model summarizing relationships between data and underlying population, averages analysis, predictive analysis, and/or event frequency analysis. For example, scheduling systems320may determine the products that are most commonly ordered for first time delivery or the products that normally have unsuccessful first time deliveries. Further, the statistical analysis may determine which products take longer to go from shelfs to packing center.

In step1106, scheduling systems320may categorize products based on number of successful and unsuccessful first time deliveries. For example, based on the statistical analysis of step1104, scheduling systems320may identify the product that is more frequently requested for first time delivery. Further, based on the statistical analysis, scheduling systems320may identify products that are frequently requested for first time delivery but are not successfully delivered because it is unable to meet the cutoff.

In step1108, scheduling systems320may identify prioritized products and second priority products. For example, scheduling systems320may determine that categories of step1106associated with multiple unsuccessful deliveries should be prioritized to prevent future unsuccessful deliveries. Alternatively, or additionally, scheduling systems320may identify products that are frequently requested for first time delivery as prioritize products to facilitate work flows in the FC for first time deliveries. In contrast, products that are not frequently requested for first time delivery may be categorized as low priority.

In step1110, scheduling systems320may generate shelving or placement guides using the prioritization. For example, scheduling systems320may generate a shelving guide in which products classified as low priority can be placed further away from the packing center then products classified as high priority. The shelving or placement guide may use the calculated distance of step1006(FIG. 10) to guide the selection of where products should be stowed in the FC based on the priorities. Thus, in some embodiments, scheduling systems320may retrieve first and second data structures to determine distances of locations of the FC with the packing center. For example, from the first data structure scheduling systems320may determine the location of products within the FC. Then scheduling systems320may determine distance from locations to packing center from the second data structures. Correlating information from the first and second data structure scheduling systems may determine the distances of FC locations to the packing center. With this information, scheduling systems320may generate a shelving or placement guide for workers of an FC. The guide may be configurable to be displayed in devices of workers and/or machines in hub zone213(FIG. 2).

FIG. 12is a flow chart of a distance score calculation process1200, consistent with disclosed embodiments. In some embodiments, elements of system300may perform process1200. For example, as described below scheduling systems320may perform process1200. However, in other embodiments system100, or parts of system100, may perform process1200. For example, FO System113and/or FC Auth123(FIG. 1A) may perform one or more of the steps in process1200.

In some embodiments, process1200may allow systems100or300to determine a distance score that indicates travel time, physical distance, and/or overall required time to transport packages from specific locations of an FC to a packing center.

In step1202, scheduling systems320may initialize process1200by assigning a distance score based on physical distance to packing center. For example, current FC's normally have multiple floors and large layouts. Particularly FCs that are located in high population density areas may spread multiple products in several locations and levels within the FC. Thus, in step1202scheduling systems320may assign a distance score based on a physical distance to a packing center in the FC. For example, scheduling systems320may assign a score where one score point represents one meter of distance between the physical distance to the packing center. Alternatively, or additionally, scheduling systems320may assign a number of points (e.g., 10 points) to the distance score when the physical location is in a different level than the packing center. Overall, if the physical distance is long, scheduling systems320may assign a high distance score, indicating that it will take a long time to transport the product from the location in the FC to the packing area. However, if the physical distance is short (e.g., the product is in a location nearby the packing center), scheduling systems320may assign a low distance score, indicating that it will not take a long time to transport the product from the location in the FC to the packing area.

In step1204, scheduling systems320may modify the estimated distance score based on available transportation methods. For example, if conveyor belts are available between the location of the product and the packing center. The score may be reduced to a lower score to indicate that, even if the location is far away from the packing center, the product or item may nonetheless arrive quickly to the packing center through the conveyor belt. For example, the distance score assigned in step1202may be multiplied by ½×, ⅓×, and/or ⅚× to take into account the availability of a transportation system. If, however, the product can only be transported by a worker, the distance score may get increased to indicate that the transportation method may cause delays. For example, the distance score assigned in step1202may be multiplied by 2×, 3×, and/or 5× to take into account the unavailability of a transportation system Similarly, scheduling systems320may include availability of elevators, automated packages delivery, or transportation method congestion when modifying the estimated distance score in step1204.

In step1206, scheduling systems320may modify the estimated distance score based on personnel availability in portions of the FC. Delivery of products may be limited by the availability of personnel in the location of the product. Regardless of the transportation velocity or the distance between the location and the packing center, if there are no workers available to select and distribute the product, the time required to transport the product or item to a packaging center may be high. Thus, in step1206scheduling systems320may modify the distance score based on personnel availability. For example, scheduling systems320may review LMB115(FIG. 1) records to determine availability of employees in a certain zone and at a certain time. If scheduling systems320determines that only a few employees are available in the product's zone, scheduling systems320may increase the distance score because it is likely the product will take a long time to reach the packing center. In some embodiments, scheduling systems320may increase the score number of points that is inverse to the number of workers. For example, scheduling systems320may increase the score by 10 points for each employee below 10 employees in the FC. However, if scheduling systems320determines that many employees are available in the product's zone, scheduling systems320may decrease the distance score. For example, scheduling systems320may decrease the score by 10 points for each employee above 20 employees in the FC

In step1208, scheduling systems320may modify the distance score based on date and time of orders. In some embodiments, scheduling systems320may include date and time of orders in the computation of the distance score. Based on historic of order density, retrieved for example from SAT101, scheduling systems320may predict dates and times when the FC is busy (i.e., fulfilling multiple orders) and dates and times when the FC is not busy (i.e., low density of orders). In such embodiments, scheduling systems320may adjust the order delivery to account for date and time. In some embodiments, scheduling systems320may increase the score number of points proportionally with the density of orders at the specific date. For example, scheduling systems320may increase the score by one point for each 100 orders per minute. Thus, if for the date and time there are 1000 orders per minute, scheduling systems320may add 10 points to the score. For example, for dates and times when the FC is generally busy, with a high density of orders, scheduling systems320may increase the distance score because the likelihood of delays in a busy FC is higher. In contrast, for dates and times when the FC is generally not busy, scheduling systems320may decrease the distance score. In some embodiments, the score may also be adjusted down if the density of orders is below the FC normal capacity. For example, if the FC has the capacity to handle 100 orders per minute, scheduling system320may reduce the score when the FC has an order density of less than 100 orders per minute.

In step1210, scheduling systems320may adjust the distance score based on historic analysis of previous deliveries to packing center in the FC. During process1200scheduling systems320may query databases to determine historic trends or averages of travel time between product locations and packing centers. For instance, scheduling systems320may retrieve information of the timers of step1016to adjust the distance score of the location based on previous deliveries. Based on the historic information, scheduling systems320may adjust the score. For example, scheduling systems320may compare scores of different locations and their measured travel times in historic records. In such embodiments, scheduling systems320may decrease the distance score when historic information of travel time indicates that the location frequently delivers faster than their peers (i.e., similar distanced location). Alternatively, if the historic information indicates that the location delivers later than peers, scheduling systems320may adjust up the score.

Process1200describes a process with an initial assignment and multiple score modifications and adjustments. This is an exemplary embodiments and steps1204-1210are optional. Thus, in some embodiments, only some of the modifications of process1200may be performed. For example, some embodiments may not perform steps1204and/or1206. Alternatively, or additionally, process1200may be limited only to steps1202and1204.

In some embodiments, scheduling system320perform process1200using scan events from employee devices. For example, scheduling system320may receive, from a first employee device, a first scan event including an identifier associated with a first physical location stored in the first data structure. Further, as part of process1200, scheduling system320may receive, from a second device, a second scan event specifying a product identifier associated with the requested product and determine a time period based on the first scan event and the second scan event. In such embodiments, scheduling systems320may modify, based on the determined time period, the cutoff time associated with the portion containing the first physical location in a first data structure.

Additionally, or alternatively, scheduling system320may analyze a plurality of first scan events and a plurality of second scan events during process1200. In such embodiments, scheduling system320may calculate or modify the distance score based on the plurality of first scan events (such as de-shelving products) and the plurality of second scan events (such as scanning at the packaging center).

FIG. 13is a flow chart of an exemplary cutoff time determination process1300, consistent with disclosed embodiments. In some embodiments, elements of system300may perform process1300. For example, as disclosed in the description below, scheduling systems320may perform process1300. This is just an illustrative example of process1300, however, and in other embodiments system100, or parts of system100, may perform process1300. For example, Shipment Authority Technology System101, FO System113, and/or order tracking system111(FIG. 1A) may perform one or more of the steps in process1300.

In step1302, scheduling systems320may maintain a first data structure representing a fulfillment center. For example, scheduling systems320may store and update a first data structure that includes zones of a fulfillment center and the product location with respect to the zones in the fulfillment center.

In step1304, scheduling systems320may maintain a second data structure including a mapping between physical locations and product identifiers. For example, scheduling systems320may manage a database storing and updating a second data structure that includes distance scores, physical distance, routes, and transportation systems between physical locations (such as a packing center) and products. In some embodiments, the first data structure is stored in a first database, the second data structure is stored in a second database different from the first database, and the second database is stored in a server within the fulfillment center.

In step1306, scheduling systems320may receive a request to provide a delivery time estimate associated with a requested product. For example, one of client devices350may send a request to provide a delivery estimate as the user navigates in a product website. Alternatively, or additionally, a mobile device may generate a request for delivery time estimate when a user selects a product.

In step1308, scheduling systems320may search and filtering the second data structure to identify at least one physical location associated with the requested product. In step1310, scheduling systems320may request available inventory from fulfillment centers associated with the filtered physical locations. For example, scheduling systems320may contact internal front-end system105(FIG. 1) to request the inventory of the FC.

In step1312, scheduling systems320may select a fulfillment center from the fulfillment centers based on availability of the product and a distance between the client deice and the FC. In step1314, scheduling systems320may search the first data structure, maintained in step1302, to determine cutoff times associated with each of the at least one physical locations in the FC.

In step1316, scheduling systems320may select one of the physical locations based on a comparison between the current time and respective cutoff times. For example, scheduling systems320may compare distance scores between different locations to select a physical location to fulfill the order. The selection may be based on identifying the location with lowest distance score, which may correlate with the latest cutoff time. In step1318, scheduling systems320may return, in response to the request, a first cutoff time selected from the cutoff times. In some embodiments, the first cutoff time may be associated with a faster delivery estimate than other cutoff times in each of the physical locations. For example, scheduling systems320may return a selected cutoff time of 4 PM for the product requested in step1306when such cutoff time has the faster delivery estimate in the related locations. Other cutoff times of 5 PM or 6 PM associated with the location may be discarded based on having a later delivery date or time. In such embodiments, scheduling systems320may be configured to find the fastest possible delivery time from among the available cutoff times. For example, scheduling system320may query first data structures to associate each cutoff time with a delivery date and time.

Process1300may allow scheduling systems320to provide enhanced consumer experience when placing online orders. For example, through process1300scheduling systems320may not only determine the available delivery options but also select delivery options that would result in faster delivery dates and times. Thus, understanding cutoffs and their respective estimated deliveries may allow scheduling systems320to figure out the ideal delivery time that can be offered to the customer for fastest delivery time. In other embodiments, however, scheduling system320may perform the selection of cutoff times based on other optimization other than the fastest possible delivery time. For example, scheduling systems320may select cutoff times based in optimizing the number of packages that can be delivered at a first time or based on grouping shipments to minimize shipping costs.

FIG. 14is graphical representation of an exemplary FC1400divided in virtual zones with specific cutoff times. As shown inFIG. 14, may include multiple levels and each level may be divided in virtual zones with specific cutoff times. Further FC1400may include a packaging center1430, which may be similar or part of transportation system107(FIG. 1).

FC1400may include multiple virtual zones. Each of the virtual zones may be associated with shelf locations or pallet locations inside of an associated FC. For example, FC1400may include a first virtual zone1401which may be in the top most floor of the FC. Because first virtual zone1401is far away from the packing center1430, first virtual zone1401receives an early cutoff time of 7 PM for first time delivery. Because products in first virtual zone1401are far away from packing center1430, it may be necessary to start the order early to be able to meet first time delivery. Similarly, virtual zones1402,1414, and1412, may also have early cutoff times because they are far away from packing center1430.

Virtual zones that start to be closer to packing center1430, such as virtual zones1404,1406,1418, and1416may start having later cutoff times (e.g., 8:30 PM). Because they are physically closer to packing center1430, FCs may afford to have later cutoff times and still meet the first time delivery option. Nonetheless, as shown inFIG. 14, virtual zones even in the same level of the FC may have different cutoff times, based on distance, availability of personnel, and/or transportation method.

As shown inFIG. 14, Virtual zones that are close or in the same level as packing center1430may receive the latest cutoff times. Because products in these zones can be delivered to the packing center quickly, virtual zones1408and1420may be assigned later cutoff times.

The virtualization of an FC allows systems FC1400to provide first time deliveries for longer. Particularly for products closer to the packing center, the different zones with specific cutoff assignments enables FC1400to offer first time, dawn, or fresh deliveries with later cutoffs.

As shown inFIG. 14, FC1400may include sensors1450in each one of the virtual zones. As previously disclosed in connection toFIGS. 2 and 10, sensors may be used as part of an item positioning system to determine whether a product is in one of the virtual zones and update first and second data structures. Sensors1450may be implemented with sensors217A-217C (FIG. 2) and include wireless, image, scan, or weight sensors to determine the position of items within the FC. Thus, in certain embodiments virtual zones or physical locations may have optical or wireless tags attached, as sensors1450, and the optical or wireless tags may be associated with a physical location identifier stored in a data structure such as the first data structure described in connection withFIG. 9.

FIG. 15is a front view of a sequence of Single Display Page exemplary graphical user interfaces in a mobile device, consistent with disclosed embodiments.FIG. 15shows three graphical user interfaces (GUIs) that may be displayed in client devices350and/or user devices102.

GUI1510shows a single product with a graphical description, text description, order information, and a dynamic text box. The dynamic textbox1512in GUI1510is empty. In some embodiments, dynamic textbox1512may be empty awaiting for calculations by scheduling systems320.

GUI1520shows the same single product information but dynamic textbox1512has been substituted by dynamic text box1522, which now specifies both estimated delivery date and expiration, displaying “Arrival by 1 pm, if ordered in 10 min.” In some embodiments, electronic messages generated by scheduling systems320may include instructions to update dynamic textbox1512to dynamic textbox1522. Moreover, in GUI1520the product display may be modified to include additional icons to indicate available delivery service. For example, the product displayed in GUI1520may be updated to show a first time delivery icon1524, to show the product is available for dawn delivery based on cutoff and proximity to fulfillment centers. In some embodiments, first time delivery icon1524may include information specific to the product or the tentative delivery date/time. For example, first time delivery icon1524may include a message such as “before dinner,” based on determinations from scheduling systems320.

GUI1530shows the single product information but dynamic text box1522has been updated to dynamic textbox1532. For example, the expiration time of 10 min may have lapsed from GUI1520to GUI1530. Thus, scheduling systems320may have sent instructions to update the delivery estimate from 1 pm to 8 pm. Moreover, GUI1530may also show dawn delivery icon1534displayed on products that can be delivered by dawn next day.

FIG. 16is an exemplary source code of a script configurable to generate or modify a webpage with delivery date estimates and/or available delivery options. Exemplary source code1600shows exemplary instructions and functions that may be employed to generate or modify a webpage to display available delivery options and estimated delivery times, as described in connection withFIGS. 9 and 11. For example, electronic messages generated and transmitted by scheduling systems320may include exemplary source code1600. The syntax and instructions used in exemplary source code1600is exemplary and different syntaxis and functions can be also employed and/or substituted.

Exemplary source code1600may include headers1601including the html headers to identify and/or modify a webpage. Headers1601are examples of operations and headers that could be used. Exemplary source code1600may also include a document type identification portion1602. Portion1602may include functions to evaluate whether a webpage is a cart page, order page, search page, or single product page. The functions detailed in portion1602show exemplary functions.

Exemplary source code1600may also include a dynamic textbox generation portion1604. Functions and routines in portion1604may specify the messages and modification instructions, as discussed in connection toFIGS. 9 and 11. Further, exemplary source code1600may include a modification portion1606including options for modifications of the different webpages. Moreover, exemplary source code1600may include a timer portion1608, which may include instructions to display a timer on the webpage that is correlated with expiration times, or remaining times, of the estimated delivery times for products.

Routines in portion1604, modification portion1606, and timer portion1608describe exemplary implementations and different or alternative implementations are possible.

While the present disclosure has been shown and described with reference to particular embodiments thereof, it will be understood that the present disclosure can be practiced, without modification, in other environments. The foregoing description has been presented for purposes of illustration. It is not exhaustive and is not limited to the precise forms or embodiments disclosed. Modifications and adaptations will be apparent to those skilled in the art from consideration of the specification and practice of the disclosed embodiments. Additionally, although aspects of the disclosed embodiments are described as being stored in memory, one skilled in the art will appreciate that these aspects can also be stored on other types of computer readable media, such as secondary storage devices, for example, hard disks or CD ROM, or other forms of RAM or ROM, USB media, DVD, Blu-ray, or other optical drive media.

Thus, the foregoing description has been presented for purposes of illustration only. It is not exhaustive and is not limiting to the precise forms or embodiments disclosed. Modifications and adaptations will be apparent to those skilled in the art from consideration of the specification and practice of the disclosed embodiments.

The claims are to be interpreted broadly based on the language employed in the claims and not limited to examples described in the present specification, which examples are to be construed as non-exclusive. Further, the steps of the disclosed methods may be modified in any manner, including by reordering steps and/or inserting or deleting steps.