Abstract: A computing device can track an operator's head movements and move a lighting system and/or other motor control operations controlled by one or more auxiliary devices according to the operator's head movements via a motor control processor. The motor control processor can facilitate movement by one or more auxiliary devices by continuously monitoring the operator's head movements via camera and moving the auxiliary devices in a manner that mimics the motion of the operator's head. The auxiliary devices may move the lighting system and/or other motor control system in one or more dimensions. The operator can move the lighting system and illuminate a specific area with a head movement. The lighting system can dynamically direct lighting in the direction that the operator is facing while freeing the operator's hands for a primary task.

Abstract: A method may include retrieving metric data on a plurality of groups of users, the metric data including: a value of a performance metric for each of the plurality of groups; and an indication that a first group of the plurality of groups is anomalous with respect to a value of the performance metric of a control group of the plurality of groups; and presenting a user interface, the user interface including: a first portion including a visualization of a comparison of the value of the performance metric for the first group and values of the performance metric of other groups in the plurality of groups; and a second portion including a visualization of trend data of the performance metric for the first group over a period of time.

Abstract: A method may include accessing a plurality of data items, each data item in the plurality of data items having a plurality of stored dimensions; selecting a subset of the data items based on a shared value of a first dimension of plurality of dimensions; identifying an outcome metric for the first group; determining a control group for comparison with the first group with respect to the outcome metric, wherein data items in the control group are determined based on dimensions that influence the first dimension and the outcome metric; determining that the outcome metric of the first group is anomalous with respect to the outcome metric of the control group; and presenting a notification to a computing device indicating the anomaly.

Abstract: A method may include retrieving metric data on a plurality of groups of users, the metric data including: a value of a performance metric for each of the plurality of groups; and an indication that a first group of the plurality of groups is anomalous with respect to a value of the performance metric of a control group of the plurality of groups; and presenting a user interface, the user interface including: a first portion including a visualization of a comparison of the value of the performance metric for the first group and values of the performance metric of other groups in the plurality of groups; and a second portion including a visualization of trend data of the performance metric for the first group over a period of time.