Do you understand that it's the transition, not the trajectory
As someone who studies the history of the future (that is, how organizations have historically tried to prepare themselves for what comes after what comes next), I have learned that it is critically important to differentiate between technology trajectory stories and technology transition realities.
Moore's Law and Ray Kurzweil's Law of Accelerating Returns are technology trajectory stories. Nokia's essential disappearance from the commercial landscape is a technology transition story. Nokia was a 60% market-share leader in a highly technology-intensive business. The consumer phone industry was characterized by high fixed costs and high returns to scale, and was highly regulated, fully global and complex. And yet in less than five years, a competitor with no phone experience came to dominate the global market. Nokia, I think it is safe to assume, did not ask the right questions about the future. Its leaders understood technology trajectories but seemed to miss the point of technology transition.
What should you learn from Google Glass
During the frenzied dot.com era, strategists and planners were told that we had entered a "new normal," where none of the old rules applied. It turns out that some patterns persist. One such persistent pattern is the adoption cycle associated with technology products. Historically, most technology innovations first see the light of day in vertical market applications (for example, video recording devices were prototyped and refined in professional markets before VCRs became available to the public). Google Glass was targeted at consumers at a price -- about $1,500 -- more appropriate for professional markets. As longtime Silicon Valley watcher Tim Bajarin points out, "While Google was playing with Glass, Apple brought out the ideal extension of your smartphone in the form of a watch." One of the questions to ask about the future is what not to do when creating a product for the consumer.
What job are we hiring Products & Services to do
The general consensus is that about 95% of new products fail. Harvard Business School professor Clayton Christensen believes this failure rate can be significantly improved upon if product and service development teams start to look at products as a way to get a job done. In the professor's words, "We actually hire products to do things for us." Christensen suggests migrating away from "segment-the-market" questions and asking "jobs-to-be-done" questions.
"The fact that you're 18 to 35 years old with a college degree does not cause you to buy a product," Christensen says. "It may be correlated with the decision, but it doesn't cause it. We developed this idea because we wanted to understand what causes us to buy a product, not what's correlated with it. We realized that the causal mechanism behind a purchase is, Oh, I've got a job to be done.' And it turns out that it's really effective in allowing a company to build products that people want to buy." (See an illuminating discussion of what we really hire milkshakes to do for us here.)
Coming back to the Google Glass teachable moment, one wonders what job consumers are hiring this product for -- delivering hands-free information from a smartphone
Is your dream big enough
We live in a world of selfies. Will we live in a future of rational self-awareness Identity management -- not the security-related establishment and maintenance of network access, but the existential psychological exercise of determining who we are -- will be a real-time exercise in the future. Self-perceptions can be limiting.
Danuta Hübner, Poland's minister for European affairs, was concerned. "We keep seeing ourselves as a small country. In fact, Poland is a big country. We should have the responsibilities that come with being a big country." How do organizations perceive themselves and their future Is Uber merely a software-enabled replacement for the local taxi monopoly, or is it a logistics software company
Will we have the skills we need
According to the Bureau of Labor Statistics, by 2020, there will be 1.4 million computing jobs and only 400,000 computer science students to fill those roles. According to McKinsey, in the United States alone there is a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data. Should enterprises create "corporate universities" to guarantee a pipeline of appropriate skills
These are just five of at least 20 questions organizations need to be asking themselves about the future.