Automation and robots are not just revolutionizing work in factories and warehouses but also in offices, including insurance companies. According to a study by the McKinsey Global Institute, in around 60% of all occupations, 30% or more of all tasks could be performed by machines—and even 20% of management tasks could be performed by robot workmates.
How will companies change when office work is automated?
If robots and software programs replace human work, this costs on average around 13% of the wage bill paid for work in a developed country like the U.S. At a stroke, moving this work to low-wage economies becomes less attractive because offshoring on average costs almost 40% of the wage bill in developed countries.
A British insurance broker today automatically processes 3,000 claims a day—all managed by a grand total of four employees. And the subsidiary of a major European energy utility has automated several important processes in administration—from billing and collection of consumption data to consumption management. What was previously handled by 250 employees is now managed by 110 robots, overseen by 11 human supervisors. One of the biggest wireless providers has automated 15 complex administrative processes, which is equivalent to 35% of its work volume: 160 robots process around 500,000 transactions a month. And it doesn’t just save costs. Since the results are more reliable than those produced by human employees, sales staff on the front line have more capacity because they don’t keep having to check back with head office to query an incorrect entry.
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Machines, then, are superior both in terms of cost and quality, with robots and computers producing more accurate results. They rigidly follow their programming—errors are not a factor. And even if production is ramped up, the same quality is achieved with large volumes as with smaller volumes. Robots don’t even need breaks—they can work around the clock if necessary. And something else that’s particularly important in times of increased compliance regulations, machines record their activities in seamless logs, and any activity can be verified later.
However, because it will only be possible to fully automate a handful of jobs in the foreseeable future, work content and processes will need to be redefined. For example, if banks use machines to review loan applications, employees have more time to advise customers, thus producing more applications a day. Financial advisers no longer need to analyze the financial data themselves and can therefore work more on creative investment strategies. Robots can even help develop investment strategies—meaning recommendations that were previously only given to the best customers because they tied up so much adviser capacity, can now be granted to every customer as “robo-advice”.
Automation is even relevant for complex jobs
The opinion still persists that automation is only suitable for the work of poorly qualified and low-paid workers. However, the study by the McKinsey Global Institute comes to a different conclusion: Even around 20% of management tasks can be handled by machines. They can analyze reports and presentations for operational decisions, check status reports for compliance with targets and even prepare HR decisions. In turn, managers have more time for thinking, for communicating and for managing—and the time needs to be used wisely. The more intensive the use of data, the more managers can benefit from automation—for example, in investment management where data volumes can be leveraged and turned into recommendations far more systematically using artificial intelligence and machine learning systems than is possible by a human.
Automation is more than a technological decision
Technology is, of course, a key element on the road to intelligent process automation; however, this is primarily a strategic decision that must be made by top management. The management must assess the extent to which the company is affected by the changes and decide whether to develop a specific strength in the area and to be at the forefront of change, or whether to hold back as a follower and avoid the mistakes of the pioneers. Ultimately, managers must decide how to adjust the operational business model of their company—from the organization and culture to the development of talent and skills. Experience shows that companies that selectively automated their processes and reduced costs quickly and easily in those areas with robotic process automation had to redefine all of their processes on the road to intelligent process automation—entirely in the spirit of the business process re-engineering of the 1990s. The key objective isn’t simply far-reaching automation of all processes, but to improve the overarching business system.
It is still uncertain how soon automation will become widely adopted in offices. On the one hand, the timing depends on the pace of technological developments, and on the other how quickly the technological possibilities will be accepted and implemented in companies. Industries with a strong reliance on pure software solutions lead the way. They quickly achieve significant savings with manageable investment—the finance industry, where processes can be automated at relatively little cost, is a good example. The more hardware that is required, or the more security provisions and legal regulations that have to be met, the longer the switch to automation takes.
See also: A Key Misconception on Digitization
Management must have a good overview of how their own industry’s parameters are developing, while at the same time developing a feeling for the economics of automation. This specific IQ of company leadership could become the difference between success and failure in the business world of tomorrow.
Adapted with permission of the publisher, Wiley, from DIGITAL@SCALE: The Playbook You Need To
Transform Your Company
by Anand Swaminathan and Jürgen Meffert. Copyright (c) 2017 by McKinsey & Company. All rights reserved. This book is available at all bookstores and online booksellers.