Is the aging workforce a problem or an opportunity for the channel?

"Spend time on a shop floor, in a hospital plant room, or at a logistics hub, and you notice the same pattern. Many of the people who have been keeping assets running have been there for decades. They know every sound a machine makes, can tell when something is wrong without looking at a monitor, and carry an instinct for the job that no training manual can fully capture."

"That kind of experience is not being replaced at the same pace it is disappearing. The latest Ultimo Maintenance Trend Report puts complex numbers to it: nearly two-thirds of respondents say an aging workforce is their biggest maintenance challenge. Half cite recruitment difficulties as their main operational headache. The loss is not theoretical; it is showing up in slower repairs, rising costs, and knowledge gaps that affect day-to-day decisions."

"Together, they make the case for agility, not as a nice-to-have, but as a necessity. This is where enterprise asset management (EAM) platforms have moved beyond simple maintenance tracking. When paired with IoT, AI, machine learning, digital twins, and predictive analytics, they become central to how an organization adapts. The insight they generate can shorten decision-making, target investment more effectively, and keep assets performing at their peak."

Experienced maintenance workers possess tacit knowledge built over decades, and that knowledge base is eroding as the workforce ages and recruitment proves difficult. Surveys report nearly two-thirds of respondents cite an aging workforce as their biggest maintenance challenge, while half identify recruitment difficulties as a primary operational problem. The loss of experienced staff results in slower repairs, higher costs, and knowledge gaps that affect routine decisions. Concurrent pressures from global competition, sustainability reporting, and regulatory change raise the need for organizational agility. Enterprise asset management platforms integrated with IoT, AI, machine learning, digital twins, and predictive analytics deliver insights that speed decisions, target investments, and sustain asset performance, offering an opportunity for IT channel providers to help rebuild maintenance resilience.

Read at ChannelPro