Abstract: A method, computer program product and a computer system for forecasting resource usage is provided. A processor determines a job forecast. The processor determines a probability of a future usage for a first resource, wherein the first resource is currently assigned to a first job. The processor determines an assignment of a second resource to a forecasted job of the plurality of jobs, wherein the second resource is available for assignment to the forecasted job. The processor determines a probable utilization of the second resource, wherein the probable utilization of the second resource indicates the probability that the second resource will be deployed during assignment to the forecasted job. A processor, in response to the probable utilization of the second resource being below a predetermined value, generates a report including the assignment state of the second resource and probable utilization of the second resource by the forecasted job.

Abstract: Computing systems, methods and tools for managing and optimizing the allocation of enterprise resources by automating employee management decision making to align management decisions made on a local level with the goals of the overall enterprise, global economies and emerging market trends. The computing systems, methods and tools use historical data, objective attributes and subjective feedback at the local level to predict employee progression at specific points in time of an employee's career and the effects particular management decisions may have on the employee as an asset of an enterprise, in order to predict, calculate and select the optimal actions that will further improve the employee's value to the enterprise yielding an optimal return on the investment of resources.

Abstract: Selected resources that satisfy a specified technical requirement are entered into a selected pool as a function of a sourcing rate, a screening rate and a selection rate that are each variable over time and applied during a sequence of selection time periods that span a demand forecast time period. Offers for acquisition are iteratively made to the selected pool of resources in a sequence of different offer time periods, wherein the resources are progressively moved into different awaiting offer buffers after each of the offer time periods. The demand number is re-forecast and one or more of the sourcing, screening and selection rates adjusted to minimize a combination of costs of the rates with a cost of acquiring resources to satisfy the gap number as a function of the demand number.

Abstract: From a log of a machine, an entry is selected relating to providing a subservice in processing a service request from a requestor associated with a key. The log entry includes a subsequence of machines used and a cost of providing the subservice. A set of entries is selected from the log, an entry including the subsequence and a second cost of providing the subservice but in processing a different service request from a different requestor associated with a different key. A distance is computed between the cost and the second cost. A number of occurrences of the subsequence with the key is determined. Using the number and the distance for the subsequence, a value pair is computed. Responsive to an aggregate number in the value pair not exceeding a threshold count. The processing of the service request is output as a suspect for using an improper sequence of machines.

Abstract: A method, computer program product and a computer system for forecasting resource usage is provided. A processor determines a job forecast. The processor determines a probability of a future usage for a first resource, wherein the first resource is currently assigned to a first job. The processor determines an assignment of a second resource to a forecasted job of the plurality of jobs, wherein the second resource is available for assignment to the forecasted job. The processor determines a probable utilization of the second resource, wherein the probable utilization of the second resource indicates the probability that the second resource will be deployed during assignment to the forecasted job. A processor, in response to the probable utilization of the second resource being below a predetermined value, generates a report including the assignment state of the second resource and probable utilization of the second resource by the forecasted job.

Abstract: A method, computer program product and a computer system for forecasting resource usage is provided. A processor determines a job forecast. The processor determines a probability of a future usage for a first resource, wherein the first resource is currently assigned to a first job. The processor determines an assignment of a second resource to a forecasted job of the plurality of jobs, wherein the second resource is available for assignment to the forecasted job. The processor determines a probable utilization of the second resource, wherein the probable utilization of the second resource indicates the probability that the second resource will be deployed during assignment to the forecasted job. A processor, in response to the probable utilization of the second resource being below a predetermined value, generates a report including the assignment state of the second resource and probable utilization of the second resource by the forecasted job.

Abstract: A method and system for identifying workplace risk factors is provided. The method includes monitoring via execution of multiple geographically distributed sensor devices, workplace injury based events associated with individuals at a multisite distributed workplace environment. Current injury data describing the workplace injury based events is stored and predicted future workplace injury based events associated with future workplace injury based events with respect to a predicted plurality of individuals at the multisite distributed workplace environment are determined. Injury risk mitigating actions associated with prevention of said predicted future workplace injury based events are generated and an associated cost optimized reduction plan for prioritized implementation of the injury risk mitigating actions is generated.

Abstract: A present risk aversion of a customer is determined. A temporal preference is detected using historical data related to the customer, the temporal preference showing a preference of current utility over a future utility of a product. Using the temporal preference and a negative transaction risk, a future risk aversion of the customer is projected at a future time. A pattern of offer acceptance by the customer is identified in the historical data. A value of an exogenous factor is determined on which a buying ability of the customer depends. The customer is classified in a cluster, where all customers in the cluster have the present risk aversion, the temporal preference, the negative transaction risk, the future risk aversion, and the value. An offer for a product is presented to the cluster, which satisfies the present risk aversion, and where a probability of acceptance of the offer exceeds a threshold.

Abstract: A method and associated systems for automatically identifying a risk that a staffing resource identified by a proposed project-staffing plan will be unavailable. A computerized project-management tool, in response to receiving a proposed project plan, requests, receives, and aggregates information about other past, present, and expected projects and about expected supplies of, and competing demands for, staffing resources required by the proposed plan. The tool infers patterns, business rules, and trends from the received information, with which it adjusts the proposed project's planned start date, expected availabilities of required staffing resources, and expected competition for staffing resources. The tool then determines a likelihood that a sufficient supply of each of the plan's required staffing resources, as adjusted, will be available at the required times, as adjusted. If the risk is too high, the user may fine-tune the proposed plan by repeating the preceding steps with varying project parameters.

Abstract: Aspects model a set of different employee compensation adjustment factors from a locally weighted linear regression function of employee data. Retention probabilities are generated for retaining each of the employees, and employee retention costs modeled as a function of historic employee wage data, the modeled set of employee compensation adjustment factors and the retention probabilities. Costs are modeled for replacing employees as a function of the employee wage data and the historic market data, and revenues are modeled for employee productivity as a function of the retention probabilities and the historic business performance and strategy data. The modeled employee compensation adjustment factors are iteratively optimized to maximize a profit objective value determined as a function of the modeled costs for replacing employees and employee productivity revenues.

Abstract: A decision support tool which takes a high-level view of supply and demand in the realm of labor resources and produces globally-optimal recommendations for assignment of practitioners to open seats. These assignments preferably optimize a utility function composed of different business metrics and can be customizable for different organizations and priorities.

Abstract: A decision support tool which takes a high-level view of supply and demand in the realm of labor resources and produces globally-optimal recommendations for assignment of practitioners to open seats. These assignments preferably optimize a utility function composed of different business metrics and can be customizable for different organizations and priorities.