Generating user level productivity intelligence is extremely important for enterprise management teams. Measuring and improving digital information management has the potential to greatly influence the success real-time operations such as medical billing, supply chain, network administration, display controls or any interaction in a digital domain. Effective enterprise managers can now measure reactions to unexpected and unanticipated changes across their business while remaining focused on resolving problems. Empower your employees or users to identify problems and integrate shared tasks to accomplish team goals.

vHumanMetrics is a multi-faceted tool that can be customized to understand the effectiveness of human interaction within any digital domain. It is not a tool to rate employees or displace human workforces, it is simply a software measurement tool used to conduct team performance diagnostics by gathering human alalytics. This new tool provides data about training inefficiencies, interface design issues, cognitive limitations under stress, or building an overall human workforce health score.

Demonstrating the value of a knowledge graph and its engine is no trivial task especially when the domain is large. To facilitate system evaluation, we developed a real-time graph analysis tool. Customer’s use our graph metrics to evaluate both individual and team performance while interacting with large complex graphs. Essentially this provides a window into the working components of our technology.

Our engine traverses the graph model and records the systems beliefs about the world, human-computer goals to be achieved, and required plans to be executed. The essential idea behind the metrics tool is to capture real-time instances of graph pathways to document what is happening in the world and what its human users intend to do about what they know. By measuring what is happening in the graphs, we can make inferences about employee and team performance.

The underlying activation of the knowledge graph structures can provide a dynamic real-time model of ‘human intention’, human analytics, that has the potential to support the analytical community with novel classes of metrics. Some of these novel metrics might be:

• Cognitive workload (number of concurrently active goals across time)
• Current active plans and goals in the DA Graph
• Time and predicted time to complete ongoing tasks
• Predict collaborations between users based on shared plans & goals
• Force synchronization (timeliness of distributed sub-goal satisfaction)