These articles are part of exploration that started in late 2015 and early 2016. It was a confusing time: autonomous vehicles and Boston Dynamics were frequently in the news and OpenAI was just formed to make sure that the “march towards AGI was safe.” UBI was actively being discussed by Sam Altman and Ray Kurzweil was promoting 10x / exponential thinking. At the same time, economists like Robert Gordon were arguing that we were actually living in a time of low progress.
I tried to develop my own perspective on what was happening, with key conclusions presented at this link. Greater detail supporting other conclusions can be found in Part I and Part II.
Labor Challenge: Today’s digital technologies have only had a marginal effect on worker productivity.
Many of the consumer benefits from smartphones, Google searches, and Facebook do not lead to direct commercial growth in the economy: consumers are now more productive in how they use their personal time. Likewise, many of the current advancements being made in CS today (e.g., natural language processing, computer vision) support discovery and search—that is, they primarily strengthen existing ICT value propositions for technology businesses. IT has not been as meaningful for what people do with their time at work as we might have hope.
“The things at which Google and its peers excel, from Internet search to mobile software, are changing how we work, play and communicate, yet have had little discernible macroeconomic impact.…Transformative innovation really is happening on the Internet. It’s just not happening elsewhere.” – Greg Ip, Wall Street Journal, August 12, 2015
For a macroeconomic perspective, McKinsey researchers recently examined 22 industries to measure “digital potential”— including both investment and the use of technology to change how work is done. Some industries, like technology, media and financial services, were well along, while others, like healthcare and hospitality, trailed. Only 18 percent of the American economy is living up to its “potential,” the report concluded. “…And if lagging industries do not catch up, we will not see much of a change in national economic statistics,” said James Manyika, a director of the McKinsey Global Institute.
This concept of “digital potential” implies that the use of technology will provide new services and features that consumers value, and that corporations can provide at a profit over today’s operating models. Often, neither of these assumptions prove true:
- New technology isn’t implicitly better. Most new digitization efforts need to fit into the pre-existing user workflow to have a chance at adoption. Technology changes generally stick best when they have a “pull mechanism”; as an example of this, interactive whiteboards (in 45% of schools in 2013) largely failed to be adopted by teachers even with significant investment from school administrators.
- Half-efforts may fail and be worse than having done nothing at all. Many legacy businesses are required to completely rethink their operations to take advantage of digital opportunities — companies need to be designed to solve these problems. This level of systems thinking is difficult to do: there are personnel problems, workflow problems, organizational problems, regulatory problems, amongst others. Taking advantage of IT in a company is really, really hard.
What does it all mean
Of course, none of this is to say that digital transformation isn’t possible. Industries throughout the supply chain from factory to retailing have already been substantially reorganized to reduce inventory, waste, and headcount; and IT-supported efficiencies in middle management and administrative support have been exploited.
“Needle-moving” changes require deep shifts in how businesses operate - for example, enabling experimentation, building internal software teams focused on removing “toil”, and Agile planning methodologies. These efforts often require a leap of faith from decision makers who have historically been successful without requiring any of those tools. It is a huge challenge to find the leadership, political will, and talent that can guide an organization through the pain of transformation.
Additional research, perspective, and detail can be found in the following supporting articles:
- Intro: Creating a general framework for current opportunities and challenges.
- Part I: We are in a time of slow productivity and strong incumbents.
- Part II: Aging & unproven learning models are headwinds to growth.
My goal in putting this together was to clarify my own thinking - and to present it in a way that can be challenged and deepened by others. I would be grateful to learn what may resonate (or differ) from your personal perspectives and work.