Many industrial producers are facing a perfect storm of accelerating change and the pressing demand to become more agile.
With Adaptive Microlearning your organization can harness these gale-force winds of change to power digitization of core processes and industrial work.
Talent losses and gains
Research of industrial operations reveals four change drivers for better, faster and less expensive ways to manage an industrial workforce.
- Most baby boomers will retire soon, taking with them a tremendous amount of institutional and tribal knowledge with no effective way of transferring that knowledge to younger workers.
- Many of the younger workers resist using stale, lame, and antiquated tools and systems, especially common corporate training and knowledge base systems.
Compounding costs, many of the younger workers continue to leave their corporate employers every two or three years. This adds higher costs to the recruitment, onboarding and training of short-haul replacements.
- Chronic shortage of trained technicians with skills and domain knowledge requires that industrial organizations invest more heavily in remedial training, retraining of existing employees, and aggressive poaching of scarce replacement workers.
- Most of the younger digital-native workers learn in ways markedly different than their older counterparts.
Digital natives demand always-on mobile short-form lessons and job-cycle refreshers that are directly related to the work at hand, emphasizing the importance of fast, low-cost production of short-form explainer and how-to videos.
Hindering digital transformation
The pace of innovation and change on the factory or shop floor, in the field or at remote stations further widens worker knowledge gaps, putting more pressure on a step-change improvement of worker training.
Regulatory compliance for greater transparency and traceability, especially for Environmental Social Governance, Health, Safety and Wellness, also increases the requirement of more if not continuous supervision and training.
Taken together, talent shortages, inefficient training systems, and demand for greater traceability, can thwart the digitization and industrial IoT transformations.
We believe that Adaptive Microlearning can and will play a critical role in speeding digital transformations of industrial operations.
We believe that Adaptive Microlearning will produce safer, more productive, more meaningful, and transparent work environments
We believe that Adaptive Microlearning enables you to the last remaining area of the industrial operations: industrial workers and related job cycles.
What distinguishes Adaptive Microlearning from traditional learning and development
When compared and contrasted with traditional methods of training, seven factors differentiate Adaptive Microlearning Workspaces from SmarTECHS.
1 Adaptive Microlearning happens in real time on the job as well as at home or while traveling.
2 Adaptive Microlearning provides contextual information, content, and live collaboration as well as interactive software applications and data collection that a worker needs to complete a job.
3 Adaptive Microlearning molds itself to
- Individual’s competencies
- Jobs orders and tasks to be performed
- Accessible performance support, online or offline/embedded
- Edge computers that the worker uses, and
- Internet connectivity including offline store-and-forward recorded
4 Adaptive Microlearning enables multimodal interactions
- Self-directed or guided learning in …
- Individual or small groups sessions focused on …
- Training, apprenticeships, or monitored job cycles using …
- Manuals, guidebooks, helper videos created by …
- Experts from the industrial organization, OEMs or service providers
5 The learning and performance analytics of Adaptive Microlearning provides an interactive dashboard for visualizing the verified competencies of each profiled worker, the current position with a worker competency-skills maturity matrix, time-series plots of learning activities and attainments, and next-best learning modules to master.
6 The SmarTECHS Adaptive Microlearning platform integrates data from a customer’s
- Legacy learning management systems
- HR and people analytic systems
- Enterprise content management systems
- Digital asset management
- Business process and work management systems
- Enterprise asset management systems
- Enterprise AI data lakes
7 The SmarTECHS Adaptive Microlearning drives a close-loop optimization cycle of field work efficiency with continuous improvement of the job cycle and continuous upskilling of workers.