Patent ID: 12223467

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings. Wherever possible, the same reference numbers are used in the drawings and the following description to refer to the same or similar parts. While several illustrative embodiments are described herein, modifications, adaptations and other implementations are possible. For example, substitutions, additions, or modifications may be made to the components and steps illustrated in the drawings, and the illustrative methods described herein may be modified by substituting, reordering, removing, or adding steps to the disclosed methods. Accordingly, the following detailed description is not limited to the disclosed embodiments and examples. Instead, the proper scope of the invention is defined by the appended claims.

Embodiments of the present disclosure are directed to systems and methods configured for learning and predicting the sale and delivery patterns of new items and seasonal utilization variations of existing items. A system may gain this intelligence using machine learning models that can handle large amounts of item utilization data as training data to predict item utilization patterns. Item utilization data may include items order processing at sale and delivery centers. The system can also handle limited data availability circumstances by providing the data as input to previously training machine learning models with related item data. By able to predict item utilization patterns the system can understand target inventory estimation of items and make distribution estimates of items.

Referring toFIG.1A, a schematic block diagram100illustrating an exemplary embodiment of a system comprising computerized systems for communications enabling shipping, transportation, and logistics operations is shown. 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, warehouse 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.

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 comprise one or more of these systems, while in another aspect, external front end system103may comprise 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, and1E, 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.)

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. This could include, for example, 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.

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 system100enables 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 comprise one or more of these systems, while in another aspect, internal front end system105may comprise interfaces (e.g., server-to-server, database-to-database, or other network connections) connected to one or more of these systems.

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 comprise 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 of a user (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 warehouse 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 and102B) 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 fulfilment 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 PDD (promised delivery date) for each product. The 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.

In some embodiments, FO system113may determine a PDD 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 on demand.

Fulfilment 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, based on a past demand for products, an expected demand for a product, a network-wide past demand, a network-wide expected demand, a count of 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.

Warehouse 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. 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/PDA1198, computer119C, or the like). WMS119may store each event indicating a scan or a read of a package identifier 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. For example, 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, WMS119, 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 center200is 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, or modified in some embodiments.

Inbound zone203represents an area of FC200where items are received from sellers who wish to sell products using system100fromFIG.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). The picker may then take the item to picking zone209(e.g., by placing it on a cart or carrying it).

Picking zone209may be an area of FC200where items208are stored on storage units210. In some embodiments, storage units210may comprise 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. The device may then prompt the picker to scan a barcode at that location before stowing item202A in that location. 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 device1196.

Once a user places an order, a picker may receive an instruction on device1196to retrieve one or more items208from storage unit210. 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, 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 comprise, 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 comprise 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, 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.

FIG.3is a block diagram of an exemplary target inventory estimation system, consistent with the disclosed embodiments. As illustrated inFIG.3, inventory estimation system310connects with data store320and user device330over network340. Inventory estimation system310components may include forecast module311, service level module312, demand share module313, target inventory module314.

Inventory estimation system310, in some embodiments, may be implemented as a computer system that performs forecasting item target inventory estimation for a specified region. Each component in inventory estimation system310may represent a software program function or the whole software program(s). A processor (for example processors416-417ofFIG.4) can execute software functions and programs representing components in a target inventory estimation system. The processor can be a virtual or physical processor of a computing device. Computing devices executing the software functions or programs may include a single processor or core or multiple processors or cores or maybe multiple computing devices spread across a distributed computing environment, network, cloud, or virtualized computing environment.

Forecast module311may forecast the overall demand for an item based on the data related to the item's orders in data store320. Forecast module311may also consider searches for the item received by front end system103(as shown inFIG.1) to determine the item's overall demand. Forecast module311may receive an item identifier, such as an SKU number or a barcode for an item, as input to determine the overall demand for the item. User device330may share a request with an item identifier to determine the item's overall demand. In some embodiments, user device330may request overall demand data for multiple items. In some embodiments, target inventory module314may request forecast module311to provide the overall demand forecast for an item. Forecast module311may determine the national forecast as overall demand for an item based on the item's previous orders stored as order data322. Inventory estimation system310may utilize the overall demand of the item to compute the target inventory estimation for a specific region at a specific time.

Service level module312may determine service level requirements of various geographical regions served by system100. Service level of a geographical region may be a set of requirements that need to be satisfied by system100serving item orders in that region. Service level module312may manage the target inventory levels at fulfillment centers (e.g., 3rd party fulfillment centers121A-C) in a geographical region. Service level module312may manage inventory levels by balancing between storage capacity of fulfillment centers in the geographical region and the estimated orders of items that may need to be served by the fulfillment centers in the geographical region. Service level module312may need to know the potential orders that may need to be served by the fulfillment centers in the geographical region by reviewing order data322. In some embodiments, service level module312may communicate with shipment and order tracking system111to determine order needs served by a fulfillment center. Fulfillment optimization system113may request service level module312to determine and help maintain highest service levels in all geographical regions for all items and for all service types (such as overnight shipment, fragile item shipment, etc.).

In some embodiments service level module312may determine geographical regions to determine service level of each geographical region. Geographical regions identified by service level module312may be used to calculate inventory estimation of an item at various granularity levels. Granularity level may indicate the size of geographical region served by system100to allow purchase and shipment of items. Granularity levels may define a hierarchy of larger geographical regions at higher levels of granularity which contain smaller geographical regions at lower levels of granularity. For example, granularity levels may include neighborhood, a postal code, a district, state, and country; each region may be included in another larger geographical region where system100may ship purchased items. Hierarchy of geographical regions as served by system100are described in detail inFIG.5description below.

Geographical regions may include portions of overall demand for the item determined by forecast module311. Service level module312may determine the smallest geographical region for service level determination and target inventory estimation calculation which may be associated with a fulfillment center (e.g., FC200ofFIG.2). Service level module312may also determine larger geographical regions that may contain the smallest geographical regions. For example, a larger geographical region may contain all 3rdparty Fulfillment centers121A-C (as shown inFIG.1). Service level module312may determine non-overlapping geographical regions for service level determination and inventory estimation of an item at different geographical granularity levels. Service level module312, upon determining the geographical regions related to inventory estimation requested item or service level of a geographical region, may store the data in data store320. In some embodiments, inventory estimation system310may request service level module312to determine all possible regions.

Demand share module313may determine the share of the overall demand for an item in a geographical region. Demand share module313may determine the share of the overall demand by reviewing orders of the item in the identified region. Demand share module313may request the shipment and order tracking system111(as shown inFIG.1) for the item's total orders. In some embodiments, demand share module313may review order data322directly to identify the order share for each fulfillment center (e.g., FC200) and encompassing geographical regions. Demand share module313uses the total order share data to determine the item's demand share at each geographical region determined by service level module312. Demand share module313may include a machine learning model trained using item order data to estimate the share of overall future orders.

In some embodiments, demand share module313may determine the demand share of a set of items related to each other. Demand share module313may determine the related items using a pre-defined set of categories. In some embodiments, demand share module313may review order data322to identify the related items. For example, demand share module313may review order data to determine the items' purchase patterns, such as items purchased together to determine the related items. Demand share module313may determine each geographical region's share in the overall demand for the item using overall demand data based on past order data from shipment and order tracking system111and expected future orders from forecast module311and geographical regions data from service level module312. Demand share module313may only determine the smallest geographical regions' demand share, such as a fulfillment center (e.g., FC200) alone.

Target inventory module314may determine the target inventory estimation of an item in a particular region. Target inventory module314may compute inventory estimation of an item using demand share estimate of the item in the particular region as computed by demand share module313. Target inventory module314may distribute the overall demand for an item based on each region's demand share estimates to calculate the target inventory estimate of a particular region. Target inventory module314may rely directly on the demand share based on the amount of order data available in calculating demand shares of geographical regions determined by service level module312. In such cases, target inventory module314may rely on a set of items related to the item needing inventory estimation determination. Target inventory module314may need to compute the target inventory estimate of the set of items related to the item requesting target inventory estimation.

Target inventory module314may use segment data324to determine the set of items associated with the item in need of target inventory estimation. Segment data324may include pre-defined segments of item groupings that may be used as sets of related items. In some embodiments, segment data324may be populated dynamically by determining the related items forming a set of items grouping. Target inventory module314may populate segment data324by reviewing order data322to find groupings of items purchased together to identify related items. Target inventory module314may also communicate with shipment and order tracking system111to review item orders to identify related items. For example, items ordered together may be considered related items. In some embodiments, target inventory module314may communicate with front end system103(as shown inFIG.1) to determine searches for items conducted and the items reviewed by users of front end system103to determine related items to be included as a grouping in segment data324.

Target module314, upon determining the related items to a target inventory estimation of a requested item, may calculate target inventory estimation of the related items. Target inventory module314may use demand share estimation of a set of items to compute demand share estimate of a particular item in a particular region. Target inventory module314may compute target inventory estimation of multiple geographical regions comprising the requested item target inventory estimation's particular region. Target inventory module314may aggregate the target inventory estimation of multiple geographical regions to calculate an item's target inventory estimation in a particular region. Target inventory module314may determine inventory estimations of geographical regions that meet the service levels of the geographical regions as determined by service level module312. Target inventory module314may request service level module312to provide the service level of the region in which inventory estimation system310was request for target inventory estimation of an item.

In various embodiments, data store320may take several different forms. For example, data store320may be an SQL database or NoSQL database, such as those developed by MICROSOFT™, REDIS, ORACLE™, CASSANDRA, MYSQL, various other types of databases, data returned by calling a web service, data returned by calling a computational function, sensor data, IoT devices, or various other data sources. Data store320may store data that is used or generated during the operation of applications, such as forecast module311, service level module312, demand share module313, and target inventory module314. For example, if service level module312is configured to identify regions associated with target inventory estimation, data store320may provide item data321and order data322as information about orders and the items ordered in various regions. Similarly, if inventory estimation system310is configured to provide a previously identified segment data324, data store320may generate segment data324associated with an item in data store320. In some embodiments, data store320may be fed data from an external source, or the external source (e.g., server, database, sensors, IoT devices, etc.) may be a replacement.

Item data321may include item related information, including item identifier, item name. Item data321may also include the availability of an item at various geographical regions such as fulfillment center200. SCM system117may provide information about the availability of an item at fulfillment center to data store320to populate item data321. In some embodiments, item data321may include item search data provided by front end system103. Item data321may be tabular data with alphanumeric fields for storing the item identifiers and item names. In some embodiments, item data321may be comma separated alphanumeric values.

Order data322may include item purchase orders as conducted using FO system113. Order data322include information about various items of item data321sold and shipped from various fulfillment centers (e.g., FC200, 3rdParty fulfillment centers121A-C). Order data322may also include tracking data provided by shipment and order tracking system111. Order data322may be tabular data with alphanumeric fields with information about order shipment address, packaging type (for example, special frozen item packaging), and shipment type (for example, overnight shipment). Order data322may be present in other formats such as a comma separated text file or as a JSON file.

Forecast data323may include the overall demand forecast of items listed in item data321. Forecast data323may include demand forecast for various geographical regions supported by fulfillment centers. In some embodiments, forecast data323may be dynamically populated by forecast module311. Forecast data323may be structured in a tabular manner with numeric values representing percentage of overall demand. Forecast data323may also include whole digit fields indicating the amount of an item needed for satisfying all orders in different geographical regions.

Segment data324may include data about sets of items of item data321related to each other. Segment data324may include overlapping sets of items with common items. Segment data324may include sets of data as defined for different geographical regions served by system100. Segment data324may regularly be updated by demand share module313. In some embodiments, service level module312identification of geographical regions may trigger the determination of new sets of data to store in segment data324. Segment data424may include alphanumeric fields of item identifiers that together for a segment. Segment data424may be structured in other formats such as comma separated values in a text file or as a JSON file.

Inventory data325may include details of inventory of each item of item data321. Item details includes inventory data325may include a reference field to the item in item data321. The reference field may be a unique item identifier such as a SKU product number or name. Inventory data325may include details inventory availability in various geographical regions (such as 3rdparty fulfillment centers121A-C ofFIG.1). Inventory data325may be used along with target inventory estimation determined by inventory estimation system310to send the appropriate amount of inventory of an item to a fulfillment center (e.g., 3rdparty fulfillment centers121A-C).

Demand data326may include overall demand estimation of an item that can be ordered using front end103of system100. Demand data326may include the mean and variance (standard deviation) of overall demand estimation of the item. In some embodiments, demand data326may include demand share data of an item of item data321in a geographical region. In some embodiments, demand data326may include mean and variance of demand estimation in a particular geographical region and may be calculated using mean and variance of the overall demand estimation and demand share of the geographical region.

Geo data327may include geographical regions as defined by system100based on distribution of fulfillment centers (e.g., fulfillment centers121A-C). Requirements of a geographical region may include service level to be met by that region is described below. A detailed description of hierarchical geographical regions with differing service levels is defined inFIG.5description below.

Service level data328may include service level requirements for item order fulfillment. For example, in some embodiments, the service level of a geographical region may require a certain number of item orders of the total item order to be fulfilled by fulfillment centers in that geographical region. Service level of a geographical region (e.g., sub region510ofFIG.5) may be defined by a user of inventory system310. Service levels may be defined dynamically by a user of user device330connected to inventory system310over network340. For example, config file350may include the configuration for service level of the geographical region where an item's target inventory estimation is requested. In some embodiments, service level of a geographical region may be based on number of orders of the orders directed to fulfillment centers (e.g., 3rdparty fulfillment centers121A-C) in the geographical region are met and shipped from those fulfillment centers. Service level values may be stored in service level data328and used for future target inventory requests for an item in a geographical region. Service level data328may be associated with the geographical regions defined in geo data327and items in item data321.

Service level of a geographical region defined in service level data328may need to be refreshed at regular intervals of time. The time interval for refreshing service levels may be defined statically or updated dynamically using a configuration (e.g., inventory estimation request350). In some embodiments, the time interval to refresh service level values of geographical regions may include default values. Service level default values may be determined by a machine learning model. The machine learning model may take as input overall storage and throughput capacities in the fulfillment centers (e.g., FC200ofFIG.2) that serve a region. In some embodiments, machine learning model may take as input past order data of order data322for the item in a geographical region and the inventory levels of an item from inventory data325.

System100may have triggers for other events to send requests to update service level data of a geographical region in service level data328. In some embodiments, inventory estimation system310may have the ability to configure target inventory estimation trigger events. A user of inventory estimation system310may configure the trigger event for inventory estimation system310to refresh service level data in a configuration file (e.g., inventory estimation request350). Service level of a geographical region may be defined based on various factors of items, orders and types of service (such as overnight service).

User device330may make a request to access target inventory estimation data for a particular region to the modules in inventory estimation system310. Modules in inventory estimation system310may need to execute one or more functions to retrieve data requested by user device330. The execution of the functions may result in database access requests sent by the modules in inventory estimation system310to other modules within it. The database access requests sent by modules in inventory estimation system310may depend on the type of item or time of day/year. For example, user devices accessing the same item order data may result in different sets of functions of inventory estimation system310's modules executed by a processor to retrieve different item target inventory estimations based on the region and time for target inventory estimations. For instance, if the item is a seasonal item, such as cinnamon flavor, then demand peaks during the holiday season. In addition, in some embodiments, modules in inventory estimation system310may be accessed by other automated applications of system100without the direct involvement of a user. This may occur, for example, in IoT (Internet of Things) environments, virtualized computing environments (e.g., involving instantiated virtual machines, containers, or serverless code instances), or in other environments involving application-to-application communications.

User device330may forward target inventory estimation requests to inventory estimation system310over network340. The requests for information in data store320may also optionally be received via network340. Network340may take various forms. For example, network340may include or utilize the Internet, a wired Wide Area Network (WAN), a wired Local Area Network (LAN), a wireless WAN (e.g., WiMAX), a wireless LAN (e.g., IEEE 802.11, etc.), a mesh network, a mobile/cellular network, an enterprise or private data network, a storage area network, a virtual private network using a public network, or other types of network communications. In some embodiments, network340may include an on-premises (e.g., LAN) network, while in other embodiments, network340may include a virtualized (e.g., AWS™, Azure™, IBM Cloud™, etc.) network. Further, network340may in some embodiments be a hybrid on-premises and virtualized network, including components of both types of network architecture.

User device330may send an inventory estimation request350over network340to inventory estimation system310. Inventory estimation request350may include details of item and region for computing target inventory estimation of an item in a region. In some embodiments, inventory estimation request350may include details of sets of items related to the requested target inventory estimation item. Inventory estimation request350may include other configuration data to configure the behavior of modules of inventory estimation system310. For example, inventory estimation request350may include a configuration of time interval to update overall demand of item in forecast data323and set of related items in segment data324. Inventory estimation system310upon receiving the inventory estimation request350over network begins computation of target inventory estimation of an item in a particular region.

FIG.4illustrates a schematic diagram of an exemplary server of a distributed system, according to some embodiments of the present disclosure. According toFIG.4, server410of distributed computing system400comprises a bus412or other communication mechanisms for communicating information, one or more processors416communicatively coupled with bus412for processing information, and one or more main processors417communicatively coupled with bus412for processing information. Processors416can be, for example, one or more microprocessors. In some embodiments, one or more processors416comprises processor465and processor466, and processor465and processor466are connected via an inter-chip interconnect of an interconnect topology. Main processors417can be, for example, central processing units (“CPUs”).

Server410can transmit data to or communicate with another server430through a network422. Network422can be a local network, an internet service provider, Internet, or any combination thereof. Communication interface418of server410is connected to network422, which can enable communication with server430. In addition, server410can be coupled via bus412to peripheral devices440, which comprises displays (e.g., cathode ray tube (CRT), liquid crystal display (LCD), touch screen, etc.) and input devices (e.g., keyboard, mouse, soft keypad, etc.).

Server410can be implemented using customized hard-wired logic, one or more ASICs or FPGAs, firmware, or program logic that in combination with the server causes server410to be a special-purpose machine.

Server410further comprises storage devices414, which may include memory461and physical storage464(e.g., hard drive, solid-state drive, etc.). Memory461may include random access memory (RAM)462and read-only memory (ROM)463. Storage devices414can be communicatively coupled with processors416and main processors417via bus412. Storage devices414may include a main memory, which can be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processors416and main processors417. Such instructions, after being stored in non-transitory storage media accessible to processors416and main processors417, render server410into a special-purpose machine that is customized to perform operations specified in the instructions. The term “non-transitory media” as used herein refers to any non-transitory media storing data or instructions that cause a machine to operate in a specific fashion. Such non-transitory media can comprise non-volatile media or volatile media. Non-transitory media include, for example, optical or magnetic disks, dynamic memory, a floppy disk, a flexible disk, hard disk, solid state drive, magnetic tape, or any other magnetic data storage medium, a CD-ROM, any other optical data storage medium, any physical medium with patterns of holes, a RAM, a PROM, and an EPROM, a FLASH-EPROM, NVRAM, flash memory, register, cache, any other memory chip or cartridge, and networked versions of the same.

Various forms of media can be involved in carrying one or more sequences of one or more instructions to processors416or main processors417for execution. For example, the instructions can initially be carried out on a magnetic disk or solid-state drive of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to server410can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. An infra-red detector can receive the data carried in the infra-red signal, and appropriate circuitry can place the data on bus412. Bus412carries the data to the main memory within storage devices414, from which processors416or main processors417retrieves and executes the instructions.

Inventory estimation system310or one or more of its components may reside on either server410or430and may be executed by processors416or417. System100or one or more of its components may also reside on either server410or430. In some embodiments, the components of inventory estimation system310and/or system100may be spread across multiple servers410and430. For example, inventory estimation system310components311-314may be executed on multiple servers.

FIG.5illustrates a hierarchical set of geographical regions for inventory management, consistent with the disclosed embodiments. As illustrated inFIG.5, hierarchical set of geographical regions may include an overall region500served by system100. Overall region500may represent all geographical regions from where orders are received by system100.

Overall region500may be served by system100for orders received via external front end system103(as shown inFIG.1). Overall region500may include sub regions510and520. Sub regions510and520may include fulfillment center. In some embodiments, sub regions510and520may include groupings of fulfillment centers530and540. Fulfillment center groups530and540may be grouped by types of service or types of items offered by fulfillment centers part of the group. For example, fulfillment centers533and534may both offer overnight shipping service. In another instance, fulfillment centers547and548of group540may both ship groceries and have same value for service level.

In some embodiments, a fulfillment center may be part of different geographical regions based on the items served by the fulfillment centers. In some embodiments, fulfillment centers groups530and540may be based on the item whose target item inventory estimation was requested by a user of user device (e.g., user device340ofFIG.1).

System100may divide overall region500into sub regions510and520according to fulfillment capabilities and fulfillment costs to different regions510and520. In some embodiments, system100may divide overall region500into sub regions510and520to uniformly distribute types of services offered by fulfillment centers (e.g., FC200ofFIG.2). In some embodiments, sub regions510and520may be prepared based on number of orders and type of orders requested by a user of system100.

FIG.6is an illustrative flow chart of a method for determining target inventory estimation of an item in a region, consistent with the disclosed embodiments. In some embodiments, the steps of method600may be performed by inventory estimation system310for purposes of illustration. It will be appreciated that the illustrated method may be altered to modify the order of steps, or further include additional steps.

In step610, inventory estimation system310may retrieve an item identifier associated with an item. Inventory estimation system310may retrieve item identifier upon receiving a request (e.g., inventory estimation request350ofFIG.1) for target inventory estimation of an item. Inventory estimation system310may receive an automated inventory estimation request for each item at regular intervals of time. For example, inventory estimation system310may receive an inventory estimation request for an item at the end of the day to recompute any changes to inventory estimation of that item in different geographical regions served by system100.

In some embodiments, inventory estimation system310may receive an inventory estimation request upon system100observing a change in orders for the inventory estimation requested item beyond a threshold amount. Inventory estimation system310may receive inventory estimation requests for an item when a percentage change of orders for the item in a geographical region is above a threshold amount. Shipment and order tracking system111may trigger inventory estimation requests for an item and send to inventory estimation system310. System100may have triggers for other events to send inventory estimation requests of an item. In some embodiments, inventory estimation system310may have the ability to configure inventory estimation trigger events. A user of inventory estimation system310may configure the interval and or trigger event for inventory estimation system310to retrieve an item identifier in a configuration file (e.g., inventory estimation request350).

In some embodiments, inventory estimation system310may need to transform the received request to retrieve the item identifier. For example, the transformation of a request may include looking up an item name in item data321to retrieve an item identifier. Item identifier may be an alphanumeric string uniquely representing the item. In some embodiments, the transformation may include identifying a new item identifier. For example, the received request may include an item identifier for a discontinued item, and the transformation may provide an identifier of the new version of the item. Inventory estimation system310may request forecast module311to perform a transformation and/or retrieval of item identifier corresponding to requested target inventory estimation item.

In step620, inventory estimation system310may access the overall demand forecast for an item using the retrieved item identifier. Inventory estimation system310may use order data322to determine the overall demand forecast of an item. In some embodiments, inventory estimation system310may communicate through FMG115to determine past order fulfillment of item orders by FC200and 3rdparty fulfillment centers121A-C to forecast overall demand for the item. Inventory estimation system310may also communicate with WMS119to get live item order fulfillment updates through mobile devices119A-C belonging to FC200.

In step630, inventory estimation system310may calculate mean and variance estimates of overall demand forecast of the item. Inventory estimation system310may review the previously computed overall demand forecast for the item. Inventory estimation system310may retrieve the previously determined overall demand forecast for an item from demand data326. In some embodiments, inventory estimation system310may review order data322to compute the mean and variance demand forecast of the item. In some embodiments, inventory estimation system310may communicate with shipment and order tracking system111to determine mean and variance estimates of the demand forecast of the item.

In step640, inventory estimation system310may evaluate an item's demand share estimate in the geographical region defined in the item estimation request350received in step610. Demand share module313may review order data322associated with fulfillment centers in a geographical region to determine a geographical region's demand share for an item.

Demand share module313may determine a share of orders processed by fulfillment centers in a geographical region using order data322. Demand share module313may consider order data from a defined period to determine the share of orders. In some embodiments, demand share module313may determine a share of the item's orders in a geographical region at regular intervals of time. The time interval may depend on the type of item. For example, a fast-selling item may need share determination at regular intervals, and slow-selling item share determination may occur over a long period of data. In some embodiments, a user may configure the time interval of orders to use to determine demand share. Demand share module313may consider seasonal demand when past order data is used to generate demand share estimation. For example, demand share module313may review past order data from the same time period of previous years in computing demand share estimation for a particular geographical region. Demand share module313may store demand share estimation associated with an item and/or segment of items in data store320.

In some embodiments, inventory estimation system310may determine a set of item identifiers associated with the requested target inventory estimation item's identifier retrieved in step610to generate demand share of the item. Demand share of the item may be generated by generating and combining the demand share estimates of the items associated with the set of identifiers. Demand share estimates of the items associated with the set of identifiers may be combined by computing average or mean of the demand share estimate values. Demand share estimates of the items associated with the set of item identifiers may be computed upon failure to directly compute the demand share estimate of the item associated with the item identifier in step610. Demand share module313may fail to compute the demand share estimate of the item directly if there is very little data for the item. For example, a new item may not have enough sale orders to use it to determine demand share in a geographical region. In another instance, a slow selling or expensive item may not generate enough sale orders to determine demand share estimate directly for the item. In some embodiments, demand share estimates of the items associated with the set of identifiers is aggregated and adjusted to the number of orders of the item associated with the item identifier in step610.

A set of item identifiers associated with an item may represent an item segment. An Identified segment may include items related to the item identified in step610. Item segments may be pre-defined and stored in segment data324of data store320. Segment data324may be updated at regular intervals or may be requested as part of the item inventory estimation request (e.g., inventory estimation request350) received in step610.

Item segment data may be determined based on the similarity of items. Item similarity may be determined using the statically assigned labels of an item. A segment of items may have a set of common labels between the items in the segment. For example, books of various genres may all be meant for children and may include a common children book label and may be considered together as a segment of items. In some embodiments, segment data may be determined dynamically based on order data. For example, items purchased together and/or having the same labels may be considered part of the same segment. In some embodiments, the rules for determining segment data may be configurable as part of an inventory estimation request. A user may provide segmentation configuration rules as part of inventory estimation request350. Upon determination of segmentation rules, demand share module312may determine the share of the total orders of a set of items belonging to a segment in a particular geographical region.

In step650, inventory estimation system310may calculate mean and variance of demand share of item in geographical region determined in step640. Inventory estimation system310may calculate mean and variance of demand share of item in a geographical region by combining mean and variance estimates of the overall demand forecast of the item with the demand share of the item in the geographical region.

In step660, inventory estimation system310may determine the service level associated with the geographical region of the item associated with the item identifier determined in step610. Inventory estimation system610may determine service level requirements from a received request for target inventory estimation (e.g., inventory estimation request350).

Service level requirements may be related to fraction of orders of an item satisfied by a geographical region. For example, service level of a geographical region may require a certain fraction of item orders of the total item order to be fulfilled by fulfillment centers in that geographical region. In some embodiments, service level of a geographical region may be based on number of orders of the orders directed to fulfillment centers (e.g., 3rdparty fulfillment centers121A-C) in the geographical region are met and shipped from those fulfillment centers. In some embodiments, service level requirements are based on the stock rate of the item identified in step610. A detailed description of service levels configuration and computation can be found inFIG.3description of service level data328above.

In step670, Inventory estimation system310may generate target inventory estimation of the item associated. Inventory estimation system310may be generated by combining mean and variance estimates of the item calculated in step630with the demand share estimate of the item in the geographical region determined in step640. In some embodiments, mean and variance estimates of demand share of the item in the geographical reason is also included in the combination to generate the target inventory estimation of the item. The target inventory value, based on mean and variance estimates of demand, may be set equal to the mean demana plus

2⁢c9⁢b
times the standard deviation of the demand, where c is the coefficient of variation of the demand, and b is the desired service level. This method is based on an extension to the Vysochanskij-Petunin inequality (Vysochanskij and Petunin1980). If the probability distribution of the demand for an item has a unimodal distribution, the Vysochanskij and Petunin inequality gives a bound on the probability that the demand exceeds a given target value. Here we extend that result to obtain a bound on the expectation of the lost demand, i.e. the expected value of the overshoot over a certain target: it can be shown that if the demand distribution is nonnegative and unimodal, and the inventory target is set as in the formula above, then the average fraction of the demand lost is no larger than (1-b).

In step680, inventory estimation system310may respond to the received item identifier with the generated target inventory estimation in step670. Inventory estimation system310may respond over network340. Inventory estimation system310, upon completion of step680, completes (step699) executing method600on distributed computing system400.

FIG.7is an illustrative flow chart of a method for determining target inventory estimation of an item at multiple geographical regions offering different services, consistent with the disclosed embodiments. In some embodiments, the steps of method700may be performed by inventory estimation system310for purposes of illustration. It will be appreciated that the illustrated method may be altered to modify the order of steps, or further include additional steps.

In step710, inventory estimation system310may generate target inventory estimation of an item in first set of geographical regions. Inventory estimation system310may employ method600described inFIG.6description above to compute the target inventory estimation of each geographical region of the first set of geographical regions. The first set of geographical regions (e.g., sub region510ofFIG.5with fulfillment centers511,512,533, and534) may be selected from sets of geographical regions (e.g., sub regions510and520) covering all the area (e.g., overall region500) served by system100to satisfy, ship and track item orders. Inventory estimation system310may determine first set of geographical regions which share a common first service type. Inventory estimation system310may represent the first set of geographical regions sharing first service type as a group, such as fulfillment center groups530and540. Inventory estimation system100may select the first set of geographical regions that are part of the geographical region associated with the item estimation request (e.g., item estimation request350ofFIG.3).

In step720, inventory estimation system310may aggregate a second set of geographical regions associated with second service type that form part of the geographical region associated with the item estimation request. The second set of regions are regions which do not form a group such as first set of geographical regions. For example, an inventory estimation request for sub region510may include fulfillment center group530with fulfillment centers533and534acting as first set of geographical regions and the fulfillment centers511and512acting as second set of geographical regions. The second set of geographical regions may include one or more different service types offered by their fulfillment centers and do not form a group. In some embodiments, the lack of grouping may be based on the type of item for which target inventory estimation is requested. For example, a target inventory estimation request for fresh meat may need geographical regions with cold storage facility. In another instance, a target inventory estimation request for fresh produce may need regions with overnight shipping capability. Inventory estimation system310may aggregate second set of geographical regions as a group temporarily for a certain type of item for which target inventory estimation was requested.

In step730, inventory estimation310may generate target inventory estimation for combined demand for first and second types of service offered by first set and second set of geographical regions respectively. Inventory estimation310may determine the target inventory estimations of each geographical region in the second set of geographical regions before combining them with target inventory estimation of the first geographical region. Inventory estimation system310may combine target inventory estimations of first and second set of regions by adding the target inventory estimation values of the two sets of regions. In some embodiments, inventory estimation system310may need to adjust the combined value of target inventory estimation to satisfy service level of the combined geographical region of first and second set of geographical regions. For example, the service level requirements of the combined first and second set of geographical regions may be lower than the individual service levels of first and second set of regions and thus a lower target inventory estimation value would meet the combined region service level requirements.

In step740, inventory estimation system310may respond to received item identifier with generated target inventory estimation for combined target inventory estimation for first and second service type as served by first and second set of geographical regions. Inventory estimation system310, upon completion of step740, completes (step799) executing method700on distributed computing system400.

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.

Computer programs based on the written description and disclosed methods are within the skill of an experienced developer. Various programs or program modules can be created using any of the techniques known to one skilled in the art or can be designed in connection with existing software. For example, program sections or program modules can be designed in or by means of .Net Framework, .Net Compact Framework (and related languages, such as Visual Basic, C, etc.), Java, C++, Objective-C, HTML, HTML/AJAX combinations, XML, or HTML with included Java applets.

Moreover, while illustrative embodiments have been described herein, the scope of any and all embodiments having equivalent elements, modifications, omissions, combinations (e.g., of aspects across various embodiments), adaptations and/or alterations as would be appreciated by those skilled in the art based on the present disclosure. The limitations in 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 or during the prosecution of the application. The examples are to be construed as non-exclusive. Furthermore, the steps of the disclosed methods may be modified in any manner, including by reordering steps and/or inserting or deleting steps. It is intended, therefore, that the specification and examples be considered as illustrative only, with a true scope and spirit being indicated by the following claims and their full scope of equivalents.