The Fog of Technology
Technology cycles impact strategy, and in turn investment and talent decisions. The “Fog of Technology" explains the challenge technologists face when assessing new technologies as they move from the initial trigger to adoption. ?
While the market is enthusiastic about technologies at the peak of inflated expectations, very few technologies ever reach mainstream adoption. The number of new technologies, the high failure rate, the lack of visibility and the long duration for winners to emerge makes it difficult to act and react.
To identify technologies likely to reach mainstream adoption, decision makers can get ahead of the game by continuously monitoring developments and tailor investment behavior to each stage of the technology cycle.
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Technology cycles impact strategy, and in turn investment and talent decisions.
Strategy:
Technology evolves in cycles, with new ideas emerging and older ones fading out. Businesses need to understand these cycles to stay competitive. For example, early-stage technologies might require exploration, while mature ones call for scaling. Knowing where a technology sits in its lifecycle helps companies plan their long-term strategies effectively.
Investments:
When and how much to invest in a technology depends on where it is in its cycle. Early on, the risks are high but the rewards could be significant. Later, as the technology matures, the focus shifts to larger, more stable investments. Companies that understand these stages can decide when to invest heavily, hold back, or exit.
Talent:
Every new technology needs people who can work with it. Businesses must hire new talent or train existing employees to keep up. By tracking technology cycles, companies can plan their workforce strategy, ensuring they have the right skills at the right time.
The sheer number of new technologies, the high failure rate, the lack of visibility and the long horizon for winners to emerge makes it difficult to act and to react
New technologies are exciting but unpredictable. They often follow a common pattern called the Hype Cycle:
Take Generative AI as an example:
However, most technologies don’t reach the adoption phase. Research shows:
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This high failure rate and long time horizon make it challenging for businesses to pick winners early.
Decision makers can get ahead of the game by continuously monitoring developments and tailor investment behavior to each stage of the technology cycle
To succeed in a world of rapidly evolving technology, leaders need a clear strategy for managing technology investments:
Steps for Success:
Investment Behavior by Stage:
By tailoring strategies to each stage of the technology lifecycle, decision-makers can cut through the Fog of Technology and mitigate risks, capitalize on opportunities, and stay ahead of competitors.
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Development Architect at SAP
2 个月Christian Dahlen - interesting read. I feel like the #hypercycle is just very dated concept. Even certain technologies have "facets" (or different versions of themselves). Takes "Machine Learning". Over 20 years I took a 4th year University of Waterloo SYS411 (I think) which was called "Machine Intelligence" because the prof refused to call "Artificial". I stayed up multiple nights running training for soft version of "Soccer Bots" to teach them to play soccer on each other (see: https://en.wikipedia.org/wiki/RoboCup). 10 years later I worked with some java-based neural net that could answer natural language text messages. Did the curve really stretch that far back? Or is the hyper with ChatGPT version of AI a totally different curve than either of those before it? If there is a #fogoftechnology' (which honestly believe there is one)... it is that often we group like things together (Gestalt Psychology or Mere-effect?) and over-simply things. I think the quicker companies can get deep understanding of technologies, the better off they will be. Move from marketing to understanding (and possibly application). Those are the companies that will win.