Insight

Talent in the age of automation and other trends to watch in 2019

KPMG's 4Q18 Global Insights Pulse Survey report explores top service delivery trends for 2019 with the biggest positive and negative impact.

Ensuring access to a skilled talent base is a perennial challenge for most organizations. Talent shortages and talent management challenges are the most often cited trends with a negative impact on business operations. 

Though a perennial challenge, talent issues are even more acute than in the past, with tight labor markets and high demand for skills required to adopt intelligent automation making talent management challenges the top negative factor for organizations’ business operations in 2019.

Given the pace of technological change, the HR organization needs to become a partner to the business to help them decide not just how many heads are required, but what types of skills will be needed to support new technologies.
David J. Brown, Principal and Global Lead, Shared Services & Outsourcing Advisory, KPMG in the U.S.

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Talent in the age of automation and other trends to watch in 2019

Explore the 4Q 2018 KPMG Global Survey report for the top service delivery trends for 2019 with the biggest positive and negative impact.

 

Beyond talent, the 4Q18 Global Pulse Survey explores these trends to watch:

 

The ongoing adoption of IA and other innovative technologies continues to have an enormously positive impact on organizations’ business operations. But most organizations have yet to adjust their business processes and talent strategies to fully exploit these technologies.

While cost reduction continues to be a primary corporate focus, its relative importance has waned as organizations seek to deliver more value-added, strategic benefits from new technologies. 

Socioeconomic and political factors such as protectionism, populism, Brexit disruptions, and weak global/regional economies remain key market concerns, though somewhat less so than in the past two years.

Operating models and processes have not yet evolved to accommodate the potential of intelligent automation, with dysfunctional operating models and organizational processes presenting the single greatest challenge to organizations achieving their most important initiatives.

Though investing in robotic process automation continues to be the most common way to harness intelligent automaton, organizations have increasingly turned to artificial intelligence and machine learning as a means to enhance the quality of business outcomes.

 

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