By Carole Gunst, Director of Marketing, AIoT Solutions, Aspen Technology, Inc.
The workforce is experiencing turbulence. The world was witness to a “Great Resignation”, a trend which originated in the USA and saw 47 million Americans voluntarily quit their job in 2021. The Middle East also felt the aftershocks of the phenomena, with organisations scrambling to retain staff by offering pay hikes and other incentives.
When combined with other market forces, such as baby boomers retiring and millennials growing into new roles; a global pandemic which forces pharma companies to run their plants around the clock and refineries needing to pivot oil production to respond to volatility, uncertainty, complexity, and ambiguity (VUCA) environments, new solutions are required to adapt to the current environment so that business can thrive.
This starts with embracing technology that can attract and retain the next generation of workers as well as empowering them with the skills they need to reimagine manufacturing. This means upscaling and upskilling the organisation. In addition to leveraging new industrial data, placing employees on cross-functional teams, which include people of different viewpoints and experiences, will allow organisations to benefit from this knowledge more broadly.
Enter: “Industrial AI.” This is not just artificial intelligence (AI), but, artificial intelligence that is specific to the manufacturing space, because it is important to understand the industry in addition to understanding data analytics.
Transition in the workplace is a huge challenge. If reports are to be believed, 50% of the MENA region’s population is below 25 years old and millennials account for 77% of the national workforce in the UAE. This exodus of boomers from the workplace with all the knowledge, deep domain knowledge of manufacturing processes, is causing an urgency for organisations to begin capturing this knowledge. The age-old debate on whether AI is better than people got it wrong. How about we focus on how do we capture that knowledge from the plant floor that’s leaving as people are retiring?
The risk isn’t limited to people who have been in a manufacturing job for a long time that are retiring and leaving with their knowledge. It can be disruptive to an organisation when people in manufacturing roles leave the organisation, taking their knowledge and experience with them. This is where technology and AI can help. When industrial data can be captured and utilised in a smart way, it can make workforce transitions easier. There’s also a need to simplify the way software is built and deployed so that workers can become effective in their jobs quickly. Another way to capture knowledge is to have cross-functional teams, made up of people with different set of eyes and experiences, work together so that knowledge is shared.
We’re all living 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 marketplaces, workforces and to changing customer demands as they arise by asking “do we presently have the systems and structures to enable us to respond in real-time?” By keeping these in mind, we can identify the technology and the workplace knowledge needed to keep the workforce productive and the enterprise competitive.