Leslie Willcocks, London School of Economics,
In late April 2020 Silicon UK contacted me with a range of questions on automation and digitalization. They published my answers in abbreviated form, so here is the full commentary …
>What could work look like in 2030? How will automation and robotics change how we all work? And how will businesses organise their workforces?
I have a study—‘Robo-Apocalypses Cancelled: Reframing The Automation and Future of Work Debate’—coming out soon in the Journal of Information Technology (June, 2020). This shows that the job apocalypse is the stuff of headlines. The majority of studies, including our own, suggest there will be minimal net loss of jobs globally, may be as little as one percent, over the next ten years. However, skills shifts will be dramatic, and skills shortages will be significant in certain areas, and not just in tech-related work.
Frankly, prediction is a losing game with technology, even before you get into present uncertain times, so here is the best I can do, from looking at hundreds of organisations in our database; extrapolating forward from past trends and crises we and others have studied; and applying 35 years of tech experience and a constructive imagination.
I am pretty sure that the take up of digital technologies will continue—even accelerate—over the next ten years, with massive implications for how work is accomplished, for skill sets, processes and the jobs people do. But this can be at a controlled pace, and past experience suggests that deploying these technologies is much more challenging, and that time horizons much longer than people think. There are no plug-and-pay technologies, or ‘fire-and-forget-missiles’, on the road to digital transformation. We think that two thirds of jobs may well be 30 percent or more automated, but that technology enablement process has been ongoing for many years. Combining studies suggest that about nine percent of people will be in occupations that did not exist in 2020. Some 14 percent may well have to switch occupations. A lot of jobs will be restructured so that employees will be retained but doing different, more technology supported work. Distinctive human strengths that machines cannot replicate—for example empathy; leadership; teambuilding; use of experience; tacit knowing, complex decision-making; understanding context; and others—will be even more valuable than today. The big skills shift will also be towards digital; technical; cognitive; medium/high level skills; and non-repetitive complex tasks. The relatively unskilled global workforce that accounts for 54 percent of the global workforce in the G20 countries will probably be only 34 percent of the total by 2030.
As algorithms take over tasks (financial services, for instance), what does the automation roadmap look like for many businesses?
Coming out of the crisis, different organizations will follow different roadmaps. We studied firms coming out of the financial crisis of 2008/9, and are studying firm behavior. Provisional findings suggest that the take up will be across sectors by organisations needing to underpin business recovery quickly, while keeping the lid on labour costs. The winners who went into the crisis some way down the path to digital transformation may well invest more and take up ever more advanced kinds of automation technologies as they become available. Others less advanced but still emerging in quite good shape are likely to slow the digital transformation and automation strategy in order to focus on business recovery. Those hardest hit will try to recover by keeping costs low, not investing in technology, and sweating the existing assets. Others will underpin regaining business performance by investing in the lower levels of automation—especially RPA—and augment these with cognitive technologies, when more benefits can be gained quickly and cheaply.
Will some sectors be more affected by automation and robotics than others?
These are generic technologies—they are not sector specific and, within their limits, can be flexed for multiple uses. RPA, for example can be applied to processes that use structured data; are very repetitive; relatively simple; with short task cycles; and for which a set of rules can be configured. Sectors that fundamentally have information processing factories will adopt automation to scale—that is why banks, insurance companies and utilities are so prominent amongst users already. The easiest things to automate are data collection, data processing, and physical, repetitive office tasks that manipulate data. But note that most large organisations now have to do a large amount of information processing—just look at large retailers like supermarkets, airlines, on-line services—so I am finding it difficult to pinpoint where automation would not spread over the next ten years.
I think the pandemic experience will accelerate the take up of the simpler automation technologies especially if they are not costly, are easy to deploy quickly and produce multiple business benefits. Our research shows that all these things are possible, if automation is managed well. The organisations that come out of the crisis relatively unscathed are likely to rethink their business continuity plans, and invest more in automation, not least to give themselves a technological cushion, in case of future crises. The obvious parallel is with home and remote working technologies that provide a default position and give the organisation additional resilience.
What changes will CIOs and CTOs see to their jobs and their responsibilities as automation expands?
There are already a number of splits in roles. This is partly due to ‘Information Technology’ consisting, in fact, of a massively diverse technology inheritance, as a result of a plethora of technological developments through at least four waves of information and communication technologies. When you add in the emerging technologies today, the traditional CIO role becomes highly challenging even in medium-sized enterprises but impossible in global organisations. One split has been to place more responsibility for the business-focused, and strategic aspects of technology deployment with Chief Operating Officers, or Shared Service Heads. We have also seen more specialising roles develop, such as Chief Innovation Officer; Chief Digital Officer; Chief Automation Officer; Chief Technology Officer; and Chief Data Officer. Basically structure and roles reflect business imperatives, technology and data developments, and where the felt challenges are. On ,pautomation, I see Centres of Automation Excellence eventually merging into centres for digitalisation, as automation increasingly supports moves towards an organisation becoming a digital business.
For tech companies, is automation the conclusion of their digitisation?
Digitisation is about converting analog information into digital form. Digitalisation sees a more impactful conversion—embedding digital technologies and data into processes and roles that make up the operations of a business. Meanwhile digital transformation sees a radical overhaul of the business and its strategy—the outcome being a digital business.
Automation tools like RPA, NLP, machine visioning and those using algorithms and machine learning are only part of an array of technologies that enable digitalisation and digital transformation. Each of ten technologies is set to have a massive impact over the next ten years. I call them ‘SMAC/BRAIDA’ standing for Social media; Mobile; Analytics; Cloud; Blockchain; Robotics; Automation of Knowledge Work; Internet-of-Things; Digital fabrication; and Augmented reality. We have not really seen even the start of what these can achieve for busineses when combined and properly deployed.
Leslie Willcocks is Professor of Technology Work and Globalization at the London School of Economics and Political Science.
His latest book ‘Becoming Strategic With Robotic Process Automation’, is available to purchase onlione at www.sbpublishing.org.
Leslie’s forthcoming title 'Global Business: Strategy in Context' will be published later this year.