The 5 Challenges to Workplace Automation

Article by Tania Armstrong | Published on July 6, 2017

No one really does a great justice of defining exactly what Automation is, but according to McKinsey the newest sense of the word pertains to the convergence of machine learning, AI and robotics. Arguably there is a wider technological landscape that makes up 'automation'. Established technologies like Business Intelligence will also have a part to play. And its safe to say that everyone and their dog has an opinion on it. McKinsey, Boston Consulting Group, Gartner and academics have been pumping out their opinions on who and what its going to impact as automation technology impacts businesses and workplaces. The end result being that there are some definite attention grabbing key takeaways relating to the acceleration and adoption of automation technology. For example - 45% of all jobs in the US are vulnerable to replacement by current technology, or technically 'automatable' activities could affect a possible 1.2 billion employees globally, with at least 60% of ALL jobs having at least 30% of tasks suitable for automation, and closer to home… 40% of all Australian jobs at risk of automation over the next 10-15 years.

But this is not the full story. What the commentators and researchers also tend to agree on, and what does not seem to make the same impact is that there is also a looming workforce labour crisis coming as well. The simple fact is we, globally, don’t have enough skilled workers entering the workforce to replace our retiring ‘baby boomers’ who are inconveniently taking their years of experience out of the market. The headlines are somewhat driven by businesses accelerating their need to compensate for a shrinking labour market along with the reducing cost of the technology. (I mean who wouldn't by a Baxter robot for highly repetitive work? At a paltry $22K, Baxter never tires, doesn't sleep, need holiday or sick pay. The ROI is no-brainer). However, the down side is the acceleration and impact of displacement and polarisation on work.

Arguments relating to workforce displacement (where labour is replaced by machinery) - aren't new. Previous technical advancements have faced opposition and criticism with every step-change since the industrial loom. However, historically, as new technology has reduced or retired manual work, new jobs and industries have been created. After the Industrial Revolution, the new looms still needed skilled workers to build and maintain them, and so to will those developing and purchasing driver-less cars. Every technology advancement needs its experts.

The polarisation of the labour market is complex. Research indicates that both ends of the work spectrum, where automation is difficult to deploy, workers will be continually sought. Those working in physically demanding and highly variable roles (e.g.truck drivers) or those with highly skilled knowledge-based jobs (e.g. big data, data analytics, cyber security) will continue to be in demand. Industries with high predictability and repetition is where automation will accelerate, such as manufacturing and the retail trade where it is thought up to 81% of tasks could be automated. Jobs high in data collection and automation are also vulnerable. It is thought that up to 64% of data collection and 69% of data processing could be automated. This will hit the wider job market and possibly impact middle-skill workers disproportionately. Accountants, for example, have found their traditional models of operation challenged by software vendors such as Xero. The answer will be to move up the 'value chain' as technology automates the grunt* work. Add value.

The answer will be for businesses to move up the 'value chain' as technology automates the grunt* work.

So what are the challenges to automation taking over everything?

  1. The first is technical feasibility. Machines outperform humans in ‘information retrieval, gross motor skills and optimisation and planning’ (Manyika, et al. 2017. P10). Developing technical capability in more complex areas such as natural language understanding, emotional and social reasoning will assist with automating advanced human tasks, however those capabilities are not here yet. Businesses need to realise a return on investment for the cost for developing and deploying software and hardware needed for automation. Quite simply - it won't always make sense.
  2. Depending on the industry, current labour market dynamics also have a part to play. Restaurant cooks may have a high replacement potential, but with hourly wages being low and cooks being numerous it is unlikely that there is an industry appetite or need for automation, although highly skilled jobs in manufacturing may be automated earlier than later due to demand
  3. Wider economic benefits also need to be considered, ‘including performance gains such as increased profit, increased throughput and productivity, improved safety, and higher quality, which sometimes exceed the benefits of labor (sic) substitution’ (Manyika, et al. 2017). Automation may not be about saving money, but saving lives.
  4. Regulation plays a part. While the demand for automation may be there, government regulation may be required to slow down the adoption of the technology to transition workers into other jobs and reduce the negative economic impact of increased unemployment. Bill Gates has argued that a ‘robot tax’ might be needed to achieve this. Arguably and controversially it may be economic policy which may impact the unemployment rate more than the introduction of automation.
  5. Social Acceptance. Technology which has an ultimate say in life or death decisions such as in hospitals with dying patients or driverless cars where ethical considerations need to be apart of the underlying algorithms - people may feel uncomfortable at not having a human connection. It will be the intended end user that will decide, at least in the short term, if they are willing to use technology in such situations and if they add to the demand for automated services.

Wide spread automation is replacing jobs and New Zealand will face the same challenges that other countries will encounter. On a global stage, we are no different. Government, businesses and employees will need to flex and upgrade their skills sets as change comes to both vulnerable industries and repetitive tasks found in most jobs. Although employees may be exposed to displacement and possible polarisation, new jobs and industries will be created, and with a world-wide shortage of highly skilled talent, expectations are high that those jobs replaced by automation will open up opportunities and new industries. What will ultimately decide New Zealand’s future is the rate of this change and how we decide to embrace it.

Tania is the Client Relationship Manager and a Director of DATAMetrics Business Intelligence and Data Solutions. She has worked extensively with corporate and large businesses in Australia, UK and New Zealand in business development and sales roles. A self-professed data evangelist, Tania specialises in building relationships while she builds businesses.

* Terrible word but I couldn't think of anything better.

 


 

 

References.

Aho, K. (2015) The Robotics Industry: Creating Jobs, Closing the Skills Gap. Techniques: Connecting Education & Careers p.22-25.

Autor, D. H. (2015) Why Are There Still So Many Jobs? The History and Future of Workplace Automation. Journal of Economic Perspectives 29(3) p 3-30

Boesel, D. B. O. and Liepert, B. (2016) 4 Robotic Revolutions - Proposing a holistic phase model describing future disruptions in the evolution of robotics and automation and the rise of a new Generation ‘R’ of Robotic Natives. Proceedings of the International Conference on Intelligent Robots and Systems (pp. 1262-1267) Daejeon, Korea

Brown, A. (2012) Automation v Jobs: Mechanical Engineering

Dan, L. (2016) Prepare Your Kids for the Robot Revolution. Retrieved from http://m.nzherald.co.nz/business/news/article.cfm?c_id=3&objectid=11683100

Davenport, H. D and Kirby, J. (2017) Beyond Automation. HBR’s 10 Must Reads. Boston, Massachusetts: Harvard Business Review Press.

Frey, T. (2013) Hi, I’m a Robot and I’m here to Take Your Job. Journal of Environmental Health 72(2) pp 46-47.

Fitzgerald, J. (2017) retrieved from https://amp-weforum-org.cdn.ampproject.org/c/amp.weforum.org/agenda/2017/05/robots-and-jobs-this-is-the-impact-theyre-having-in-the-us

McCauley, D. (2017) Robots threaten ‘millions’ of jobs. Retrieved from http://www.nzherald.co.nz/business/news/article.cfm?c_id=3&objectid=11849335

Mlot, S. (2014) Will a Robot Revolution Lead to Mass Unemployment? PC Magazine.P20-22

Manyika, J.; Chui, M.; Miremadi, M.; Bughin, K.; George, K.; Willmott, P.; and Dewhurst, M. (2017) A Future that Works: Automation, Employment and Productivity. Retrieved from http://www.mckinsey.com/~/media/McKinsey/Global%20Themes/Digital%20Disruption/Harnessing%20automation%20for%20a%20future%20that%20works/MGI-A-future-that-works-Executive-summary.ashx

Maras, E. (2016 August 23) Robotics and Automation: Evolution Not Revolution. Food Logistics 179. p54-57

Robots Online Marketing Team (2016, ) Impact of the Robotics Revolution (2016) Retrieved from https://www.robotics.org/blog-article.cfm/Impact-of-the-Robotics-Revolution/3

Tati, M. (2017) A robot tax to save human jobs? Retrieved from https://www.newsroom.co.nz/2017/04/19/19714/a-robot-tax-to-save-human-jobs

Thibodeau, P. (2013) Gartner's dark vision for tech, jobs. Retrieved from https://www.cio.co.nz/article/528841/gartner_dark_vision_tech_jobs/?fp=4&fpid=2117013136

Tamvakologos, M. and Canaough, A. (2016) Back to the future? Digital disruption and its impacts on work. Governance Directions, 68(11), p663-665