New thinking for service workforce talent in the digital era

Organizations are predicting major changes in their service teams over the next five years, as the twin trends of increased automation and an ageing skilled workforce start to have an impact. While we shouldn't get too worried about robots taking everyone's jobs, there are some areas where automation in particular will render certain tasks redundant. That, however, does not mean service techs will lose their jobs but what it does mean is that, given the ageing workforce, new skills will need to be learned.

According to a Forrester Consulting study, From Grease To Code: What Drives Digital Service Transformation, 72% of companies say that within just five years, asset equipment will outlive the working life of the engineers who service them. A further 62% say technology will completely automate service technician dispatch, relieving call centre and customer service centre staff of this role. The report emphasizes the importance of skills transfer and data integrity in enabling these changes:

The next five years will bring disruptive and major changes to service workforces globally. With the rise of more digital products in installed bases, simply replicating lost talent will not be sufficient due to the pace of digital skills requirements. Digital transformation demands that organizational workforce strategy should not be independent of a company's service data strategy.

Of course, we've known this has been coming for some time now but that doesn't make it any easier. To some extent, we've all been a little distracted by this idea of robots taking over. The reality is that automation will, in most part, augment existing work. For service techs this means shifting skills, focusing on new and different tasks. Here is four-step plan to help service organizations respond.

1. Prepare for condition-based maintenance

According to the research, 85% of respondents surveyed say that self-healing equipment and remote monitoring will enable field service technicians to focus on more complex specialist work. Better instrumentation of equipment and remote analysis of performance data will target service calls where they are most effective. As a result, 44% of firms are already investing or planning to invest in condition-based maintenance within the next two to three years.

2. Anticipate the 'silver tsunami'

The situation is exacerbated by what is widely referred to as the 'silver tsunami'. Research last year revealed that 53% of field service companies state that replacing an ageing workforce is a challenge for their organization. The prospect of losing a lot of experience and skills in a very short space of time is very real. While this may not seem such a bad idea given the shift in skills requirements, the reality is that it could and probably will leave a skills gap. Knowledge of installed base is still essential and will be for some time.

3. Map talent to service requirements

Training younger workers extensively in old machines and techniques just doesn't make sense. Automation may overcome this issue, at least in the long run, but in the meantime it does highlight the need for organizations to align service talent strategy with installed base strategy. Thankfully, data will come to the rescue here, as long as it is mined and analyzed correctly. Mapping service requirements across the strategies will go a long way to ensuring organizations can resource their teams efficiently and not waste time and money.

4. Optimize operations with service data

As service data continues to mature in organizations, companies should also be able to make better operational decisions around predictive maintenance and customer service. That should help inform workforce strategy and provide added value to customers. As this intelligence helps extend the working life of capital equipment through better service data, organizations will be able to limit capital expenditure without hindering overall machine performance and productivity. Combined with the shift to as-a-service delivery models, this is reframing how businesses best schedule, dispatch and maximize the value from their precious technical service talent.