The New York Times recently posted an article about robots taking work from white-collar workers, who felt their positions were relatively safe from automation. Machines, it seems, can take work from doctors, lawyers, accountants and bankers. At the same time, we know machines and automation haven’t necessarily meant fewer jobs, but new kinds of jobs. But we easily underestimate how these things impact our jobs, and the winners are those companies that look for growth, not only savings with automation.
A common statement is that machines and automation remove routine and let people focus on more demanding tasks. This is true in the big picture, but details are often much more complicated. I wrote earlier automation and digitization not done right – like lipstick on a pig! A retailer doesn’t become the new Amazon because their current employees automate some routines. It takes a much more fundamental change.
It is common for companies to look for efficiency and cost savings with automation, and there are many reports that automation projects lead to layoffs. Understandably, many companies want to get quick wins. Often, layoffs are not the result of automation but actions like outsourcing or downsizing. Companies could and should focus on how to grow their businesses, not just look for short term savings.
This also depends on the technologies used for automation. If you only use a tool for copy-pasting or organizing data fields, it is quite clear, it is about immediate savings, not transforming your business. Growth means automating and building more mission-critical automated processes. It also means better and smarter automation than copy-paste solutions, preferably solutions that can process data and make conclusions.
There are at least three critical areas to get business growth from automation:
- Processes and operations must be designed based on real business needs and opportunities for technology use, not automating the old way of doing things; it is not just about enhancing existing processes but designing new methods that make sense.
- Tools must support automation that enables relevant work, not small routines of the old way.
- It is demanding to automate white-collar work, and it requires top-level operations and technology professionals.
It is a paradox that many automation and RPA solutions have only targeted simplified solutions when building robots to automate white-collar work, typically done by well-educated, professional people. How is it possible to automate their work with very simplified tools and solutions when robots to automate blue-collar work are created by top-level professionals with top-level design tools?
I also wrote earlier about AI’s hands and how the insurance claim process is an excellent example of AI-aided automation. Too often, companies think automation only involves small routines, like scanning a claim form and adding the data to an old system, just as a person previously did manually. This does not get full value from automation and is only an interim solution anyway. It doesn’t free these people to work on some more demanding tasks when significant parts of the process are still based on old systems. At best, it reduces headcount, as fewer people are needed to enter data manually. But fully automated solutions would free people to investigate suspicious cases that machines would identify and give them more time to develop and sell new products.
A Deloitte study found that only 8% of organizations were at the stage to scale up automation. There is considerable evidence that companies start automation and RPA processes but cannot scale them to get the full value. Those cases are most often focused on the small routines with simplified tools mentioned above. It doesn’t mean all issues need to be addressed in the first instance, but there must be a clear direction involving the right tools, competence and capability to scale up.
It is like underestimating the work of many professional people. White-collar robots are coming, but their implementation needs professional tools and top professionals to design processes and robots. Only then can we enable these white-collar workers to move to more demanding, creative and productive work.