Every innovation is a recombination of older innovations. Even the lowly paperclip is only possible to produce because previous inventors understood how to make steel, not to mention the machine tools used to make every paperclip identical. But making new technologies work often requires innovations in older, established technologies. The Model T allowed Ford Motorcar to capture 50% of the automobile market in 1920, but making the Model T required the development of precision machine tools, new factory organization with a moving assembly line, and new human resource practices: Ford’s $5 day which doubled the effective wage of factory workers, and the elimination of foremen’s power to evaluate workers.
Similarly, the advent of information technology has created profound changes to organizations, as the distribution of information within organization can fundamentally change the nature of jobs themselves. For example, the introduction of word processors eliminated typing pools and now middle and senior management compose their own memos. Email reduced the need for individual administrative assistants as management it became more efficient for management to manage their own communication. Breakthrough technologies such as email, word processing, computers and the internet make the workplace of yesteryear difficult to imagine.
Today, new technologies, such as blockchain, artificial intelligence and machine learning are threatening to change the office environment in the same way that an earlier generation of information technology changed the meaning of computer from “worker who does complex and long calculations by hand” to, well, a computer. Such changes are exciting! But they take a long time to affect organizations. This is because technological innovations require complementary organizational innovations to provide useful solutions to problems.
Take, for example, IBM’s Watson. Here we are 20 years in, and mostly we are just playing an awesome game of chess – a well defined game with a strict set of rules. It is another thing to consider how artificial intelligence will interact with people and existing structures in organizations. We’ve all lost important emails to spam filters as that machine learning technology was evolving. And while we can guess at a few of them, there will be many surprises as we adopt machine learning to help evaluate job applicants. We should expect this project to be exceptionally long, complicated, and full of problems that nobody right now can imagine.
This does not mean that these technologies should be ignored. They will have profound effects on the organizations we all work in. and because we cannot know how these new technologies will work, organizations should experiment with these new trends. To do this, they will require new knowledge and capabilities. This will be a difficult process, fraught with experimentation and failure. But through this experimentation and failure, the organization will learn and be prepared to adopt and implement these new technologies. But this process of learning will take time. Panic is not necessary – and hype should be recognized as hype.