There have been countless changes in technology over the past couple of decades: Machine Learning, Cloud Computing, Internet of Things, Artificial intelligence, and Augmented Reality (to name a few). But with all of these advances in technology, the 350 million workers in manufacturing are being asked to perform increasingly complex jobs using technology that has […]
There have been countless changes in technology over the past couple of decades: Machine Learning, Cloud Computing, Internet of Things, Artificial intelligence, and Augmented Reality (to name a few). But with all of these advances in technology, the 350 million workers in manufacturing are being asked to perform increasingly complex jobs using technology that has remained relatively unchanged for 20 years, and, according to Deloitte, manufacturing is already looking at a potential skilled labor shortage of 2.4 million workers in the next decade. Whether this is because enterprise software solutions are expensive, technically complex, difficult to implement, or lack continuous improvement opportunities, these users and processes have been underserved and require a well-planned digital transformation strategy to keep them competitive.
Although there has been a recent trend towards a digital transformation that looks at applying new technologies to improve operational processes, the workers who actually perform these processes are not being considered. Because of this, the frontline worker is largely disconnected from the digital thread of the business, and improvement in productivity seems stagnant.
Key Challenges Manufacturers Face Today
As with any transformational change, adopting a digital transformation strategy is no easy undertaking. We currently see 4 key challenges industrial organizations face when adopting a digital transformation strategy:
1.) Tribal Knowledge and the “Skills Gap”
Senior production workers and subject matter experts have accumulated valuable experience and knowledge, which has been typically hard to capture and convert into an asset that is able to be easily shared and used by others. The younger workforce that is entering the manufacturing sector does not have the knowledge that their senior peers have, but are expected to perform the same jobs, at the same level of productivity and quality.
2.) Lack of Insight
Lack of insight into how workers are performing their jobs on a day-to-day basis is also an issue. There is no fine-grained detail regarding worker activity – how are workers performing vs. benchmarks, are they having trouble on certain steps, what are they doing well, do they have feedback on operational procedures that could help the rest of the workforce? This lack of data and insight has made it extremely difficult to improve the performance of frontline workers. As a result, there is little or no basis for making decisions for improvement across the organization.
3.) Lack of Guidance and Accurate Information
Organizations are struggling with the quality of human-centric processes, as they often suffer from inaccurate, outdated paper-based work instructions. In many cases productivity is also an issue because workers are not equipped with the right tools or instrumented with the appropriate guidance that would help them perform their jobs at peak productivity.
4.) Workers are Disconnected
And lastly, frontline workers are not integrated with their work environment. The human-centric and job-specific workflows are not digitally integrated into the overall business environment and enterprise systems (ERP, CRM) that are critical to the business. The reality of today’s frontline workforce in manufacturing is that workers are not connected to the digital fabric of the business.
Bridging the Digital-Reality Gap
The good news is that there are a number of new strategies and technologies that manufacturing organizations are implementing to solve these problems. In particular, the rise of Enterprise Augmented Reality has lead to a major shift in improving the productivity of the frontline workforce of manufacturing organizations.
Although this is a great first step, Enterprise Augmented Reality alone isn’t enough to deliver sustainable value in manufacturing. In order to see true transformational results, it is key to have a combination of the following:
- Enterprise AR: Delivers initial improvements in productivity and quality for the frontline workforce.
- Consumerization of Software: Enables ease-of-use and ubiquity across the manufacturing landscape.
- Artificial Intelligence: Drives continuous improvement throughout the organization.
Only when these three elements are combined will you see continuous improvements in the productivity of your frontline workforce.
To learn how Enterprise Augmented Reality, Artificial Intelligence, and the Consumerization of Software are delivering transformational value in manufacturing download our white paper, “The Rise of the Augmented Worker.”
