The present disclosure relates to system and methods for predicting performance caused by software code changes. For this purpose, an augmented machine learning model predicts a latency of software module with updated code executed in a production environment. In some aspects, the latency is predicted based on a change of deviation that is determined by comparing the latency of the software module with updated code and the latency of the software module without updated code, whereas the software modules are executed in environments different from the production environment.

Strategic planning and strategy execution is important in organizations of various sizes and types, such as business and industry, government, and nonprofit organizations. While strategic planning and strategy execution are important, present systems and methods present challenges in providing for a system that links all aspects of strategic planning and strategy execution and communicates strategic planning and strategy execution throughout an organization. The present disclosure provides a system and method with an ability to articulate and align objectives, measures, targets, resources, activities, and outputs with desired outcome(s) and desired impact.

Certain aspects involve building segment-specific executable program code. In one example, a code-building service can execute segmentation logic that assigns different target entity records to different segments based on differences between sets of attribute values among the target entity records. The code-building service can select, for each segment, a set of data assets that is specific to the assigned segment and a set of source code portions that is specific to the selected data assets. The code-building service can order each set of the source code portions based on an identified modeling output type for the target entity records. The code-building service can generate, from the ordered source code portions, a set of program code referencing the selected subset of the data assets. For instance, the generated program code, if executed, can generate and transmit different modeling outputs for different target entity records.

Methods and systems for controlling production resources in a supply chain are described. The system automatically generates predicted supply chain operational metrics across a nodes of a supply chain. The system automatically infers causal factors that impact the predicted supply chain operational metrics. The causal factors include a change to a utilization of the production resource. The system communicates a user interface including production runs being scheduled on the production resource including a user interface element representing the scheduling of the production run associated with a value at risk. The system receives input causing a change to the utilization of the production resource. The change to the utilization of the production resource impacts the predicted supply chain operational metrics including the value at risk associated with the scheduling of the production run.

A system and method for controlling an autonomous vehicle to affect a view seen by an occupant of the autonomous vehicle is described. In one embodiment, a method for controlling an autonomous vehicle to affect a view seen by an occupant of the autonomous vehicle includes determining a navigation route, determining content associated with the navigation route, monitoring current conditions of the autonomous vehicle and the occupant, determining, based on the current conditions, whether to change a position of the vehicle to affect the view seen by the occupant, and when the current conditions permit, moving the autonomous vehicle to affect the view seen by the occupant.

Provided are a computer program product, system, and method for using a predictive model to determine virtual usages of storage spaces in a storage infrastructure. Information on the storage infrastructure indicates storage spaces in the storage infrastructure, including physical boundaries and usages of the storage spaces and a predictive model used to determine storage spaces for items to store in the storage spaces. The predictive model receives as inputs physical boundaries and usages of a selected storage space. The predictive model processes the inputs to output a virtual usage of the selected storage space within the physical boundaries of the selected storage space. The virtual usage is defined by coordinates in the physical boundaries of the selected storage space. Augmented reality representation overlaying the virtual usage at the coordinates within a view of the selected storage space are generated in a computer display.

Data management is disclosed that detects changes in production or potential changes in production to trigger business decisions that inform business spend. Sensor input meant to monitor manufacturing and event correlation data can serve as input to trigger business decisions. The decisions can account for cost structures to ensure automated investments in the interest of the business or other organization. The data management links an early understanding of production data and business decisions to increase the link between manufacturing investment and business spend and to decrease waste including economic waste.

A method for a well intervention program is provided. The method includes selecting, from a number of well intervention mandates generated by a number of originators in an oil and gas industry hierarchy, mid-level mandates based on respectively originator rankings, wherein each of the number of well intervention mandates relates to a well intervention activity of the well intervention program, generating, based on respective pre-defined cycle times of the mid-level mandates, a most frequent timeframe, performing, based on a pre-determined audit criterion and over the most frequent timeframe, an audit of the well intervention program to generate an audit result, and presenting the audit result to the number of originators.

A computing system includes: processor(s), memory(s), storage device(s), and network interface(s) configured to communicate with data source(s) and remotely located computing device(s). The network interface(s) receives data regarding a digital product catalog representation of products from the data source(s). The processor(s): generates a respective score for the digital product catalog representation for each respective product, the score indicative of adherence of the digital product catalog representation for each respective product to at least one criterion; stores the respective score for the digital product catalog representation for each respective product using the at least one storage device; and identifies which products provide the greatest opportunity for sales improvement by improving adherence of the digital product catalog representation to the at least one criterion. The network interface(s) provides an indication of which products provide the greatest opportunity for sales improvement to the at least one remotely located computing device.

Embodiments are directed to managing user associations with service providers. A status value for an association between a user and a service provider may be provided if a user may be non-compliant with one or more terms of the association. Treatment plans for the user may be determined based on the classification of the user. Response information associated with the user may be generated based on execution of the treatment plans such that the user information may be updated based on the response information. During execution of the treatment plans at each evaluation point, result models may be employed to classify the response information or the updated user information. In response to non-compliance by the user with one or more conditions of a current treatment plan, other treatment plans may be determined and executed based on the updated user information.