It used to be that robots were distinct from their human bosses, but ‘bots and bosses are blending today. Thanks to rapid advances in intelligent automation (IA), jobs are changing – some drastically – in terms of the tasks humans do versus those done by machines.
In “The Future Of Jobs, 2027: Working Side By Side With Robots,” Forrester Research, Inc. predicted that by 2018, automation will change every job category by at least 25 percent.
Early movers who have begun to implement intelligent automation within their organizations have discovered that it’s a more complex undertaking than originally thought.
They’ve found that the most fundamental conversations posed by IA turn on these issues:
- How can businesses profit from new economic opportunities while safeguarding the wellbeing of employees and other stakeholders?
- How do businesses capture the cost savings and other bottom-line benefits of automation while releasing the potential of human capital to do other, more valuable things?
- How should organizations manage the transition to the workforce of the future?
- How will automation impact the customer experience, and how can businesses ensure that they are prioritizing customers (internal and external) over cost-cutting?
KPMG clients adopting IA confirm they are automating tasks within a job but rarely entire jobs, a development we think will continue for a few more years. In the meantime, however, jobs, work teams, processes and functions need to be redesigned to create a more intelligent, higher-performing enterprises.
Shaping the workforce of the future
Creating an agile workforce strategy is not just about embedding the right technology but also about empowering the workforce with the right skillsets, structure and culture to be successful. This is what we mean by workforce shaping.
It differs from more traditional workforce planning in seven key respects:
- The impact of IA on the workforce and required skills must be analyzed continuously, rather than over a three- to five-year time horizon.
- This analysis must be based on new job families. Required capabilities must be based on “to-be” tasks and critical skills for end-to-end processes, not on discrete tasks and existing job families.
- Workforce shaping should be owned and conducted by business units and end-to-end process owners and facilitated by human resources (HR), not owned and conducted by HR alone in consultation with the business.
- Workforce strategy must consider human workers both employed and not employed as well as automation owned and not owned, rather than focusing solely on employed workers.
- Traditional top-down work structures – with critical roles driven by hierarchy – must give way to a team-based and end-to-end process view of how work is organized. Critical roles should be driven by skill scarcity and value-add to the business.
- A bias for scenarios with probabilities attached – based on horizon scanning and an outside-in mindset – should be preferred over the bias for “an answer” based on the existing organization mindset.
- The workforce model must be continually reexamined to help ensure a more multidisciplinary approach to forecasting.
As organizations react to the challenges of intelligent automation, their ability to transform themselves with a nimble and productive workforce will be central to their ability to grow and survive.