Baby boomers and early-stage Generation-X workers are retiring so quickly that one-third to one-half of all existing employees are predicted to leave the workforce between 2015 and 2022. This great shift change (or crew change) is happening around the world. The most extreme impact will be felt in labor-intensive, asset-intensive industries like oil and gas, utilities, transportation and manufacturing.
While the great shift change is underway, many organizations are also struggling with technological and economic developments. It’s harder to deliver productivity and return on assets (ROA) with current operating models. And it’s a challenge for industry leaders to fully embrace technological advancements such as big data, analytics, mobility and automation. Therefore, they find it difficult to experiment with new capabilities. But this is where the next competitive differentiation lies: in areas such as IoT, AI and augmented reality.
To adopt new operating models, industry leaders will need to re-evaluate their organizational, economic and production strategies. But because the catalyst is this demographic shift, their evaluation needs to start with people.
Preparing for the great shift change: pairing tomorrow’s brawn with today’s brain
Investments are often lost due to the higher attrition rate that exists in physical work environments. Health issues exacerbated by physically demanding field roles—combined with current economic conditions—are accelerating the decision to retire. Many estimates are as high as 15-25 percent attrition in any given year.
But even as they make their plans to leave the workforce, many workers struggle to find a way to segue into retirement. They’re looking for ways to create value and share the experience they’ve accumulated through years of managing their firm’s operations.
What seems to be a perfect storm could actually be a serendipitous event for industries around the world—one which will allow a much-needed transition to occur. One that drives the business model change and engages the new workforce using new technologies that will drive future competitiveness.
A solution to the scalability challenge of mentoring and teaming model
Asset-intensive industries need a way to share, scale and capture tribal knowledge and the wisdom of crowds. Remarkably, the answer to this dilemma is a solution to another. It opens up a great transitional role for aging experts.
Using digital and mobile tools, retiring workers can engage remotely with new technicians. They can help them solve complex repairs, as well as routine challenges around structuring their day; all the way down to having the right tools on the truck to perform preventive maintenance and inspections. Because the approach uses virtual reality and AI to scale limited resources, one senior technician could theoretically provide peer guidance to as many as 10 technicians every day. Add mobile technology like IBM Maximo Mobile and AI-driven assistants, like the IBM Maximo Assist, and you create a more Connected Technician and increase that ability to transfer learning to a much higher power.
Assets are talking. Are you listening?
At the same time that employees are getting smarter, assets becoming more intelligent. Solid-state technologies have evolved to more digital components, and IoT is delivering more real-time operations data than ever before, terabytes worth . So the isolated breakdowns of the past are being replaced by complicated and integrated challenges. IoT, analytics and AI will empower new ways to separate the signals from the noise. But technicians of the future will need to be able to hear and understand those signals. Technicians will require easy-to-master data science techniques, similar to those used by today’s reliability engineers — without the complexity of understanding all the science.
Roles of the future will require massive retraining around new technologies. They will also require the ability to use analytics, and a system-thinking approach to solving problems.
New ways of looking at the workforce of the future, like PTECH and the increasing focus on STEM skills, will make this transition toward using data science a bit easier. But the sheer volume of data will heavily depend on new and advanced tools mining data in operational streams to ensure that technicians focus on the right issues, at the right time.
This will enable technicians to interpret the asset’s situation and bring the right tools and inventory. They’ll know when to respond to (often remote) sites. And they’ll do so only when needed, reducing truck rolls and labor costs. New and old technologies that combine predictive analytics with modelling techniques like digital twins will also play a large role in making sure that the data is interpreted correctly to manage risks.
Man works together with machine
With these changes in the workforce and ability comes the opportunity for organizations to reimagine the workforce…to look at their new challenges in new ways. The leaders of the future will be those who embrace data, AI and IoT on top of their asset management strategy. Many top global enterprises across multiple industries depend on the solutions from IBM Maximo Application Suite to provide essential insights for intelligent asset maintenance and operations.
These organizations use Maximo to combine workforces with new skills and technologies that are powered by IoT capabilities. As they capture more and more data, Maximo analytics and platforms help interpret and identify operating risk. So operating model transformation can be driven from within, and focused on client outcomes.
The timing is right. The transference of new skills using multiple tools and new technologies has already begun. The technician of tomorrow will be empowered with the knowledge of today’s transitional workforce.
To learn more about the full spectrum of technologies affecting field operations, check out this Field Management Guide. And relax. With smarter, connected technicians embracing smarter assets, the great shift change will be great.