Abstract: A mobile Quality Management/Control system for performing mobile product inspections is provided. A mobile device, such as a tablet, is configured to communicate with one or more databases and allow for real time entry (and subsequent access) of the details of product inspections for quality control and management purposes. The details of such inspections are maintained and available for all subsequent inspections. The mobile device is further configured to provide inspectors with inspection procedures and/or tutorials associated with the inspections being performed.

Abstract: A system and method schedule work within a workflow with defined process goals. A plurality of work queues are defined that comprise work items. The plurality of work queues are associated with one or more links between a parent work queue and at least one child work queue to form at least one work process. At least one work process goal is defined for each work process. A work schedule to achieve the work process goals is generated.

Abstract: In embodiments of the present invention, improved capabilities are described for a virtualization environment adapted for development and deployment of at least one software workload, the virtualization environment having a metamodel framework that allows the association of a policy to the software workload upon development of the workload that is applied upon deployment of the software workload.

Abstract: A validation engine validates product demand data using novel supply-demand imbalance data. Validating the product demand data provides confidence that the demand data is accurate. Confidence in the demand data allows manufacturers, distributors, and others involved in commerce to rely upon the demand data for product manufacture and ordering. The validation engine correlates determined product demand data with product supply data to generate ‘imbalance data’. The product supply data represents data for the same time period as the time period of the product demand data. The imbalance data is, in one embodiment, a difference between the product supply data and the product demand data. In one embodiment, the validation engine generates the imbalance data by subtracting product demand data from the supply data associated with the same product. Negative imbalance data indicates undersupplied products, and positive imbalance data indicates oversupplied products.

Abstract: A device for managing material handling productivity is disclosed. The device may receive information identifying a moving zone for a job site, a quantity of loads for the moving zone, and a material for the moving zone, and may identify a first machine, from multiple machines, to assign to the moving zone, the quantity of loads, and the material. The device may provide, to a first user device associated with the first machine, information indicating that the moving zone, the quantity of loads, and the material are assigned to the first machine. The device may receive, from the first user device, location information associated with the first user device and the first machine, and may provide the location information to a second user device, associated with a second machine, to enable the second machine to travel to the first machine.

Abstract: Disclosed in some examples is a question platform which matches survey creators with survey takers (entities) referred by publishers. In some examples, the match can happen in real-time or near real time based upon a number of match criteria. Match criteria may include survey creator criteria submitted by the survey creators that describe desired entity attributes, a bid price (e.g., maximum price they are willing to pay), and survey content information. Match criteria may also include publisher criteria that describe entity information, an ask price (minimum price that the publisher is willing to accept for providing access to the entity), and content criteria (e.g., restrictions on the types of survey, the number of questions, and the like).

Abstract: A dynamic supply chain planning system for analysis of historical lead time data that uses machine learning algorithms to forecast future lead times based on historical lead time data, weather data and financial data related to locations and dates within the supply chain.

Abstract: A system may include a processor that receives tasks to be performed, determines ordering rules associated with the tasks, and identifies a first set of employees to perform the one or more tasks based on schedule data associated with the employees and the ordering rules. The processor may then identify one employee of the first set of employees to perform the tasks based on a current schedule for the one employee and the ordering rules, identify scheduled tasks to remove from the current schedule based on un-assignment rules, and generate an adjusted current schedule to include the tasks and remove the scheduled tasks from the current schedule. The processor may then send a notification indicative of an adjusted current schedule to a computing device associated with the one employee.

Abstract: A method includes receiving hierarchy data indicating a capability hierarchy associated with a customer network, the capability hierarchy indicating that a first capability is a sub-capability of a second capability. The method further includes receiving application data from a MID server of the customer network, the application data associated with an application utilized by the customer network for the first capability. The method further includes determining, based on the application data, an application score indicating an effectiveness level of the application for the first capability. The method further includes determining, based on the application score, a first capability score associated with the first capability. The method further includes determining, based on the first capability score and the capability hierarchy, a second capability score of the second capability, the second capability score indicating a health metric of the second capability within the customer network.

Abstract: A dynamic supply chain planning system for analysis of historical lead time data that uses machine learning algorithms to forecast future lead times based on historical lead time data, and to divide historical lead time data into clusters based on seasonality and linearity. The machine learning results are further processed to adjust future planned lead times and to identify sources in the supply chain that contribute to large deviations between historical planned lead times and actual lead times.

Abstract: A system comprises one or more modules to access a business rule, deconstruct the business rule into a condition and an associated action, determine a set of questions relevant to the condition, place the set of questions into a question queue, order the question queue, and present the question queue to a user. A system comprises one or more modules to determine a subject of the request received from a user, use the subject to obtain a set of relevant questions, examiner each question and determine whether an answer to a current question is available in a storage area, and present the current question when the answer is not available. A system comprises one or more modules to access a decision tree, determine a current node, determine an estimated number of nodes between the current node and a leaf node, and present a representation using the estimated number of nodes.

Abstract: Features related to a system and method for dynamic resource prediction simulation are described. The predictions consider historical data collected by the organization or user revisions to planning inputs to predict the amount of a resource needed for a certain task and the amount of the resource able to perform the tasks. The system and method displays the predictions in a visual representation including control elements allowing a user to simulate a variety of scenarios and situations to allow the organization to properly reallocate resources or acquire an appropriate amount of the resource.

Abstract: A workflow management system for managing the storage, retrieval, and transport of items in a warehouse includes a voice-directed mobile terminal. The system also includes a server computer in communication with the voice-directed mobile terminal. The server computer includes a tasking module for transmitting task data to the voice-directed mobile terminal. The server computer also includes a workflow-analysis module for generating, based at least in part upon an analysis of workflow dialog between the voice-directed mobile terminal and the user, performance data relating to the performance of tasks associated with the storage, retrieval, and/or transport of the items.

Abstract: Systems, methods, and other embodiments associated with a shortest path engine for warehouse management are described. In one embodiment, a method determines a shortest path between a first location and a second location. The method includes receiving a request for a shortest path between a first location and a second location and accessing a first data structure. The first data structure maps the first location to a first reference point and the second location to a second reference point. A shortest path between the first reference point and the second reference point is determined and the determined shortest path is returned.

Abstract: Embodiments provide a computer-executable method, computer system and non-transitory computer-readable medium for programmatically generating an association among two or more purchase categories based on purchase data of a plurality of consumers. The method includes programmatically accessing, from a dataset via a network device, prior purchase data associated with purchases of a plurality of commercial objects by a plurality of consumers. The method also includes programmatically identifying a plurality of categories associated with the plurality of commercial objects. The method also includes, for each consumer in the plurality of consumers, programmatically generating a total number of purchases by the consumer in each category in the plurality of categories.

Abstract: Disclosed subject matter relates to data analytics including a method of evaluating performance of employees of an organization. A performance evaluating system provides a review matrix corresponding to one of plurality of review contexts to recommenders for receiving their feedback including recommender's review score and review comments in the review matrix for the employees. Further, the performance evaluating system generates a system review score for each employee by analysing the review comments and computes a compound review score for each employee and each of the plurality of review contexts using the recommender's review score and the system review score. Furthermore, cumulative evaluation score for each employee is computed using the compound review score, predefined organizational weights and historical evaluation score. Finally, the cumulative evaluation score of is analysed to evaluate performance of the employees and reward them objectively.

Abstract: An operating procedure generation support apparatus according to embodiments of the present invention includes a property acquirer, an additional operating procedure candidate generator, and an output device. The property acquirer acquires non-associated properties, according to product description specifications including a product family and properties of the product family, standard operating procedures pre-associated with the product family and the properties, and a basic operating procedure specified from among the standard operating procedures, the non-associated properties being the properties of the product family and having values not updated by the basic operating procedure.

Abstract: A computing system and method dynamic multi-factor ranking for prioritizing tasks, and in particular, tasks relating to servicing of problem reports in a managed network, is disclosed. The computing system may be disposed within a remote network management platform and be configured for management of problem report sent from reporting stations in the managed network. The computing system may thus receive a plurality of problem report messages from one or more reporting stations, and may then compute a multi-factor ranking of the messages based on dynamically selected factors associated with each message. The multi-factor ranking may then form the basis of a prioritized list of the messages, and the prioritized list may be displayed on a display device of the computing system. The prioritized list may thus provide a basis for prioritizing tasks related to servicing the reported problems.

Abstract: A system and method schedule work within a workflow with defined process goals. A plurality of work queues are defined that comprise work items. The plurality of work queues are associated with one or more links between a parent work queue and at least one child work queue to form at least one work process. At least one work process goal is defined for each work process. A work schedule to achieve the work process goals is generated.

Abstract: Systems and methods for optimizing outcomes in multi-factor systems are described. Business process management, consulting intelligence, business intelligence, mobile intelligence, artificial intelligence, machine learning, and transportation management are integrated, as discussed herein, for optimizing transportation and logistics processes. Users may input legacy knowledge and data such as text, numbers, formulas, algorithms, and automated processes into a computing system for providing the system with industry insights for intelligently analyzing situation contexts, or the system may leverage third-party data. The system may suggest recommended actions based on analyzed situation contexts, and the system may furthermore execute various actions for responding to the situation contexts. The system may be configured to automatically analyze situation contexts and furthermore automatically execute various actions for responding to the situation contexts.