By Carole Gunst, Director of Marketing, AIoT Solutions, Aspen Technology, Inc.
The staff is experiencing turbulence. The world witnessed a “Great Resignation,” a trend that originated in the US and saw 47 million Americans voluntarily quit their jobs by 2021. The Middle East was also feeling the aftershocks of the phenomenon, with organizations scrambling to hire staff. by offering wages for hikes and other incentives.
Combined with other market forces, such as baby boomers retiring and millennials growing into new roles; a global pandemic that forces pharmaceutical companies to run their factories around the clock and refineries that must run oil production to respond to volatility, uncertainty, complexity and ambiguity (VUCA) environments, new solutions are needed to adapt to the current environment so that businesses can thrive.
This starts with embracing technology that can attract and retain the next generation of workers and give them the skills they need to reshape manufacturing. This means scaling up and retraining the organization. In addition to leveraging new industry data, placing employees in cross-functional teams, including people with different viewpoints and experiences, allows organizations to take advantage of this knowledge more broadly.
Enter: “Industrial AI.” This is not just artificial intelligence (AI) but also artificial intelligence specific to the manufacturing space as it is important to understand the industry in addition to understanding data analytics.
Transition in the workplace is a huge challenge. If we are to believe the reports, 50% of the population of the MENA region is under the age of 25 and millennials make up 77% of the national labor force in the UAE. This exodus of boomers from the workplace with all knowledge, deep domain knowledge of production processes, means that organizations urgently need to start capturing this knowledge. The age-old debate about whether AI is better than humans is wrong. How about if we focus on how we capture that factory floor knowledge that leaves when people retire?
The risk is not limited to people who have worked in a manufacturing job for a long time and who retire and leave with their knowledge. It can be disruptive to an organization when people in production positions leave the organization and take their knowledge and experience with them. This is where technology and AI can help. When industrial data can be captured and used in a smart way, it can make the transition of personnel easier. There is also a need to simplify the way software is built and deployed so that employees can quickly become effective at their jobs. Another way to capture knowledge is to have cross-functional teams, made up of people with different eyes and experiences, work together so that knowledge is shared.
We all live in a VUCA environment. It’s more important than ever to not just run operations as we’ve always known them, but to have the flexibility to respond to changing markets, workforces and changing customer demands as they arise by asking, “Do we currently have the systems in place? and structures to enable us to respond in real time?” By taking this into account, we can identify the technology and knowledge in the workplace needed to keep the workforce productive and the business competitive.