Judging by the plethora of images we see in the media of individuals wearing Augmented Reality (AR) sets in all aspects of their work-life, one could assume that Enterprise AR has been widely adopted amongst many companies. However, the reality of Enterprise AR is that most industrial companies have had difficulty creating sustainable value when attempting to implement the technology. One reason being is that most early AR vendors were overly focused on delivering information and digital work instructions to industrial workers via wearable devices, which has not produced the expected efficiency benefits.
Since many of the early adopters of AR solutions failed to justify cost and complexity compared to the minimal gains in efficiency, they got stuck in “pilot purgatory” where they weren’t able to successfully emerge from an initial proof-of-concept initiative.
First Wave of AR Solutions Failed to Find Widespread Adoption
But why is it, that a technology that promised to generate overall success and savings in resources, costs and time has failed to deliver? If we take a step back and examine the first wave of enterprise AR, we can pinpoint some of the reasons why Enterprise AR alone has been unable to provide the value that manufacturers are looking for causing a lack of widespread adoption:
- Early AR solutions are characterized by high costs and long implementation cycles, which made them accessible only to the largest manufacturing enterprises that have high innovation budgets and significant resources.
- Solutions were not tailored to small and mid-market manufacturing companies.
- Poorly implemented software solutions and early hardware that didn’t perform to the comfort, safety, and reliability expected by the users
- Existing solutions only deliver information to frontline workers and with that have not been able to provide value beyond the initial one-time gain in productivity.
Most importantly though, once the solutions were finally deployed, it became obvious that the software failed to provide value beyond the initial one-time gain in productivity, which was frequently seen in use-cases where hands-free operation was the real source of the benefits derived.
Expanding the Value Proposition of Enterprise AR by Focusing on the Connected Worker
But just because the first wave of AR implementations have mostly failed, doesn’t mean that the technology doesn’t have the potential to generate great efficiency gains for industrial companies. We simply need to take a new approach.
What’s been overlooked so far is the potential derived from collecting data about the work from this newfound connectivity to the worker.
If you could envision workers as a new source of information to improve your processes, and if you used AI to analyze that data to create insights into every aspect of their productivity and training, you could benefit the entire organization.