Automation and digitization should increase the productivity of work. But productivity growth has been flat or declining in most developed countries during the past 20 years. This has been visible in countries where most jobs, and especially new jobs, are not in manufacturing, but in services and information work. So, it would be fair to assume that technology and digitization don’t help improve productivity. Henry Ford, Jeff Bezos and Larry Page didn’t win big because they optimized old operations; it’s because they created totally new operating models. Opportunity lies in developing new ways to do things, not optimizing old ones.
World-famous economists, like Daron Acemoglu, Greg Mankiw and advisors of many governments, try to understand reasons for slower productivity growth. I won’t attempt to understand all the macro-economic factors, but to focus on small practical questions like what could be the bottlenecks with digitization and automation of information work.
I wrote earlier about how we need real digitalization, not consulting projects. The problem of many automation and digitization projects is that they just try to optimize the existing processes and implement them in legacy IT systems. Both those processes and systems were developed before the current opportunities of digital services were readily available. The optimal model would be to build new processes with the latest technology focusing on the company’s real value to its customers. If you automate old processes that are unnecessary to offer customers value, it doesn’t improve productivity. That’s why genuinely digital companies like Amazon, Facebook, Google, Netflix, Alibaba and many startups win business from old companies.
It takes quite a lot of courage from management and investors to disrupt old models instead of just trying to ‘optimize’ them. The reality is that to fine-tune old models with old IT could give you a small percentage improvement in productivity, but if you want to achieve much more, maybe 100 or 1,000 per cent gain, you must create new models to operate with the latest technology.
I also wrote earlier about the trending low-code and citizen-development, and how it can rarely help implement robust well-planned solutions. This is another example, why automation of processes doesn’t always bring significant value when citizen-development is trending in automation. Suppose a company must create new models to operate so that customers can communicate digitally with it, and they digitize all internal and supplier interactions. In that case, it doesn’t work if each employee (i.e. citizen-developer) starts to automate their routines from the pre-digital era.
It’s a sad fact that real automation also makes some work unnecessary. If you just let employees automate something they don’t like, it doesn’t make a company significantly more effective. Of course, by getting rid of boring routines, each individual and department can become more effective. But in reality, significant changes need much more fundamental changes. A record shop doesn’t become a new Spotify simply because employees automate some of their routine work. And a bricks-and-mortar retailer doesn’t become a new Amazon when employees automates their routines. Those companies need a new way to operate with new processes and new roles for their employees. Uncovering existing processes and automating them might bring some savings, but if you create new ways to operate based on new tools, you can create a whole new business.
AI, digitization and automation (including RPA, robotic process automation) are at the heart of these changes. They are hype terms nowadays, and it is easy to make fun of them. Their reputations suffer if those technologies are not appropriately utilized; they become window-dressing, like lipstick on a pig. Suppose you put a little bit of AI and a little bit of automation on top of your old processes and systems. In that case, it is not making them more digital or intelligent, and it’s just adding one more layer of complexity and arguably, technical problems. Some companies would like to use machines to observe people and use AI to create automation to perform the same tasks. It sounds like an exciting tech vision, but it’s a strange idea that the optimal model for machines would be to copy how people have done something traditionally.
Henry Ford didn’t build a car for everyone by asking old-style workshop car builders to automate some of their routines. Jeff Bezos didn’t digitalize retail by asking guys who receive telephone orders and fill paper order forms to use VoIP calls and scan order papers. Google founders didn’t revolutionize the online ad business by making an online copy of the yellow pages. They created new models from scratch, how they could offer the best value to their customers with the latest technology. But many companies still try to develop their operations by adding new tricks to old models.
Automation, AI, and digitization will change most businesses, and they will significantly change the way information works. Improving existing processes is a multibillion-dollar opportunity, but creating new, more effective models to operate in hundreds of billions or trillions. Improvements bring short term wins; new operating and business models create companies that prevail in the future.
All these require courage from management and investors. They must be brave enough to discard old models to operate and old systems. It is nice to promise each employee that nothing will change or promise two per cent stable growth to investors. Still, as we have seen in retail, this model leads to huge collapses, significantly when competitors change the business and market rules. Those leaders who want to create big successes should start to build their operations based on software robots, AI and digital processes, not just hope the old models can be done a little bit better. And they should start today.
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