AR will not change the future of Service, Augmented Operations will.
Aug 27, 2019 • Features • Augmented Reality • future of field service • Augmentir
Russ Fadel, CEO and Co-Founder, Augmentir outlines why the next wave of AR implementations in our sector must harness Artificial Intelligence as well...
Much has been said and written about Augmented Reality (AR) and its benefits n the field service arena – from improved field technician performance to reductions in field service operating costs. However, these early success stories masked the reality of Enterprise AR in the industrial sector – companies have been slow to adopt this technology and have had difficulty moving beyond the experimentation and pilot phase
The first wave of vendors in the Enterprise AR space were overly focused on wearable technology, believing the early predictions that there would be millions of sets of smart glasses deployed in the enterprise by 2018. This directed their efforts to getting work instructions running on a variety of wearables, and many also invested solely in using AR to present information to technicians in the field with rich content and 3D CAD overlays.
It has become clear that these investments have not delivered the value expected to the enterprise, which is reflected in the lack of mainstream adoption. What has been overlooked is the real opportunity of leveraging the new found connectivity to service workers to create sustainable value throughout the organization. Not only by delivering personalized information to each worker, in the ideal format, but also using artificial intelligence and machine learning to augment the intelligence of the organization relative to how it engages, empowers, and continually improves its human workforce.
This is the beginning of a new era, an era not of Enterprise Augmented Reality, but of Augmented Operations where AR is but one of many ways to present data, support, and guide field workers. Augmented Operations has the opportunity to transform human worker productivity much like automation has done in the past 30 years.
This transformation is driven by the combination of two key technology trends – Enterprise AR and Artificial Intelligence/Machine Learning.
Artificial Intelligence and Machine Learning (AI/ML) has been around for a long time and has historically been applied against external data sets. A recent trend is to embed AI in software platforms, and have it act on the internal data, eliminating the estimated 80% of AI/ML project efforts around labelling and cleansing external data. This is frequently being applied to solutions focused on improving outcomes in business processes where the human worker is at the center. Artificial intelligence and machine learning (AI/ML) is ideally suited to understanding patterns in the noisy data sets generated by humans workers.
At Augmentir, we are using our AI engine to identify patterns in the data generated by field technicians and highlight areas that can then be used to improve overall worker performance, as well as act in real-time to provide personalized procedures based on the proficiency of each worker. The AI engine is able to help continually deliver insights and recommendations based on that human worker data – this is valuable intelligence that can be used to help drive continuous improvement across the entire organization – from operations to training to quality.
• AI can help each worker perform at their peak – dynamically changing the instruction to one that allows each worker to perform their job as fast as possible, while meeting quality and safety targets;
• AI understands the patterns and outliers in the vast instruction/job execution data to identify the largest capturable opportunities in the areas of: productivity,. worker effectiveness, training materials effectiveness, and instruction effectiveness – and provide insights and recommendations on how to capture these opportunities. This is the only way to deliver the actionable information required for industrial organizations to drive continuous improvement on a year-over-year basis;
• With AI, companies can optimize troubleshooting/ diagnostic procedures by observing the attempts and results of technicians in the field;
• With AI, companies will be able to capture tribal knowledge from participating in the interactions between Experts and frontline workers, over time making the expertise/tribal knowledge a scalable corporate asset.
With this concept of Augmented Operations (using AI/ML to deliver intelligence across the organization from your augmented workforce), we are seeing a step change in how organizations are making informed decisions, empowering workers, and improving the productivity of humans in the workplace.
What has been ignored is a real opportunity to create sustainable value throughout the organization – not only giving workers the ability to consume information and apply knowledge, but also augmenting the intelligence of the organization relative to how it engages empowers, and continually improves its human workforce. At Augmentir, we are calling this Augmented Operations, and we believe that this will transform the service workforce of the future.
Much has been said and written about Augmented Reality (AR) and its benefits n the field service arena – from improved field technician performance to reductions in field service operating costs. However, these early success stories masked the reality of Enterprise AR in the industrial sector – companies have been slow to adopt this technology and have had difficulty moving beyond the experimentation and pilot phase
The first wave of vendors in the Enterprise AR space were overly focused on wearable technology, believing the early predictions that there would be millions of sets of smart glasses deployed in the enterprise by 2018. This directed their efforts to getting work instructions running on a variety of wearables, and many also invested solely in using AR to present information to technicians in the field with rich content and 3D CAD overlays.
It has become clear that these investments have not delivered the value expected to the enterprise, which is reflected in the lack of mainstream adoption. What has been overlooked is the real opportunity of leveraging the new found connectivity to service workers to create sustainable value throughout the organization. Not only by delivering personalized information to each worker, in the ideal format, but also using artificial intelligence and machine learning to augment the intelligence of the organization relative to how it engages, empowers, and continually improves its human workforce.
This is the beginning of a new era, an era not of Enterprise Augmented Reality, but of Augmented Operations where AR is but one of many ways to present data, support, and guide field workers. Augmented Operations has the opportunity to transform human worker productivity much like automation has done in the past 30 years.
This transformation is driven by the combination of two key technology trends – Enterprise AR and Artificial Intelligence/Machine Learning.
Why is Artificial Intelligence and Machine Learning Important?
Artificial Intelligence and Machine Learning (AI/ML) has been around for a long time and has historically been applied against external data sets. A recent trend is to embed AI in software platforms, and have it act on the internal data, eliminating the estimated 80% of AI/ML project efforts around labelling and cleansing external data. This is frequently being applied to solutions focused on improving outcomes in business processes where the human worker is at the center. Artificial intelligence and machine learning (AI/ML) is ideally suited to understanding patterns in the noisy data sets generated by humans workers.
At Augmentir, we are using our AI engine to identify patterns in the data generated by field technicians and highlight areas that can then be used to improve overall worker performance, as well as act in real-time to provide personalized procedures based on the proficiency of each worker. The AI engine is able to help continually deliver insights and recommendations based on that human worker data – this is valuable intelligence that can be used to help drive continuous improvement across the entire organization – from operations to training to quality.
• AI can help each worker perform at their peak – dynamically changing the instruction to one that allows each worker to perform their job as fast as possible, while meeting quality and safety targets;
• AI understands the patterns and outliers in the vast instruction/job execution data to identify the largest capturable opportunities in the areas of: productivity,. worker effectiveness, training materials effectiveness, and instruction effectiveness – and provide insights and recommendations on how to capture these opportunities. This is the only way to deliver the actionable information required for industrial organizations to drive continuous improvement on a year-over-year basis;
• With AI, companies can optimize troubleshooting/ diagnostic procedures by observing the attempts and results of technicians in the field;
• With AI, companies will be able to capture tribal knowledge from participating in the interactions between Experts and frontline workers, over time making the expertise/tribal knowledge a scalable corporate asset.
With this concept of Augmented Operations (using AI/ML to deliver intelligence across the organization from your augmented workforce), we are seeing a step change in how organizations are making informed decisions, empowering workers, and improving the productivity of humans in the workplace.
Augmenting the Service Workforce of the Future
Despite some early momentum, Enterprise AR alone isn’t enough to deliver sustainable value in the field service sector.What has been ignored is a real opportunity to create sustainable value throughout the organization – not only giving workers the ability to consume information and apply knowledge, but also augmenting the intelligence of the organization relative to how it engages empowers, and continually improves its human workforce. At Augmentir, we are calling this Augmented Operations, and we believe that this will transform the service workforce of the future.
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