Systems and methods are described for managing a supply of building blocks for one or more products. An example method includes: obtaining demand data for each building block from a plurality of building blocks; obtaining substitution data for the plurality of building blocks; providing the demand data and the substitution data as input to a predictive model; receiving as output from the predictive model a predicted optimal production quantity for each building block; and facilitating a production of the plurality of building blocks according to the predicted optimal production quantities.

A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events.

A method for improving performance of a computer procurement application includes using the procurement control system computer, determining a peer group associated with a first entity; using a procurement control system computer, obtaining, from client computers respectively associated with the entities, configurations that instruct a procurement application how to perform procurement tasks for the respective entities of the entities in the peer group; using a procurement control system computer, obtaining, from a first client computer associated with the first entity, a first configuration that instruct the procurement application how to perform procurement tasks for the first entity; obtaining a desired end result from the first entity; using the procurement control system computer, using a machine learning algorithm, determining configurations of the peer groups that have a causal relationship to the desired end result; providing a description of the configuration value to the client computer associated with the first entity.

A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events. Furthermore, the system utilizes a virtual agent engine and various predictive models to schedule and execute callbacks between a person in a virtual queue and a virtual agent based on predictive model results.

Systems and methods for measuring a brand health of a brand in real-time and the subsequent allocating of resources. The system comprises at least one device having at least one processor, at one least memory device storing instructions that are executable on the at least one processor, and a non-transitory, computer-readable medium embodying computer program code to implement a method for measuring the brand health of the brand in real-time. The method entails obtaining unique IDs who engage with both the brand and competing brands during a period of time; determining a set of real-time coefficients of the brand; calculating a market share of the brand via the use of the coefficients; calculating the brand health of the brand in real-time via the use of both the market share and real-time coefficients of the brand, and allocating, based on the brand health of the brand, marketing resources for the brand.

Generating a model for evaluating organizational skills to determine cost of entering a new market includes training a machine learning model to define business capabilities, processes and required skills of an organization based on a current business strategy, training the machine learning model to define a plurality of skill classes of the required skills of the organization using the cognitive computing processor device, training the machine learning model to define skill profiles of the available talent of the organization based on the plurality of skill classes, determining skill gaps of the available talent of the organization by analyzing the required skills of the organization and the skill profiles, assessing skills required for a new business strategy for the organization, and determining a cost of the organization executing the new business strategy based on the skill profiles, the at least one skill gap and the new business strategy skills.

A processor may estimate uncensored demand from historical supply chain data. The processor may ingest historical data. The processor may convert the historical data to a dataset of multiple time series corresponding to sales for different products and locations and channels across multiple time points that is usable by an uncensored demand estimation machine learning model. The processor may train the uncensored demand estimation machine learning model by applying optimization solver techniques for deep learning.

A method for identifying stakeholders relative to an issue is disclosed. In one embodiment, the method may include accessing first data associated with a plurality of individuals associated with an organization; generating first nodes representing the plurality of individuals within an issue graph model; accessing second data associated with one or more policies; generating second nodes representing the one or more policies within the issue graph model based on the second data; receiving an indication of a selected agenda issue; generating links within the issue graph model representing relationships between the first nodes and the second nodes; determining importance scores for the first nodes in the issue graph; identifying a node of the plurality of first nodes associated with the at least one selected agenda issue based on the importance scores; and outputting node properties associated with the identified node.

A system for generating and analyzing organizational influence data is disclosed. In one embodiment, at least one processor is configured to access first data associated with a plurality of policymakers; generate first nodes representing the plurality of policymakers within an issue graph model; generate a second node representing an organization; receive a selection of an agenda issue of interest to the organization; access second data associated with the organization; generate links within the issue graph model representing relationships between the first nodes and the second node; determine an organizational influence factor comprising a measure of how likely the second node is to affect a property of each of the first nodes; identify at least one node of the first nodes associated with the selected agenda issue based on the organizational influence factor; and output node properties associated with the identified node.

Methods, systems, and computer-readable storage media for extracting, by a multi-experience runtime engine and from a metadata file, metadata that is descriptive of an analytics UI for display on a display of a computing device, the metadata including instructions for a binding to a service providing inference using one or more ML models, in response to the binding, transmitting an inference request to the service through a predictive data adapter, the inference request including data representative of a workflow task that is to be executed in a digital workplace, receiving inference results that are responsive to the inference request, and displaying, within the analytics UI, the inference results and at least a portion of the data representative of the workflow task.