A Human-Centric Approach to the Industrial Internet (of Things)
What's Next is what matters
Global industries with remote or mobile assets are losing money through workforce-related inefficiency. Existing enterprise software and equipment automation solutions do not effectively engage, leverage or address the field workforce component.
Warm hands still touch cold steel
All the analyzing, optimizing and distribution of operational information will not succeed if the people doing the work do not have the skills and contextualized information required to execute effectively.
Big Data Should be Small
What the industrial employee does not need is more sensors, more complexity and more dashboards – they simply need to know when and where to execute. Providing automated actionable data at the point of service will reduce unplanned downtime, increase productivity and save lives.
Skilled is a State of Mind
There exist massive employment gaps and massive unemployment – how can this happen? We believe that all people are skilled and they are simply not presented with the right information and technology to apply those skills.
contextere solves that problem by presenting the right information at the right time on the right device with the right context. We weave together this environment using human-centric machine learning, curation algorithms, sensor integration and mobile technology.
Extracting and understanding systemic human error
Although there has been great progress in identifying and resolving systemic error with equipment, there is virtually nothing to capture and address systemic human error. Understanding the common ways in which groups of individuals function correctly and incorrectly can refine automated guidance and avoid equipment redesign.