What is the opportunity cost of not embarking on machine-led decision support?

In earlier blogs, we’ve referenced this great article on SingularityHub to show how the exponentiality of technological progress tends to surprise us as change initially creeps up on us, then overwhelms us in situations like this:
Singularity Hub's power law diagram

But what if we changed the “exponential growth surprise factor” in the diagram above to “opportunity cost?”

Further to yesterday’s blog about the uselessness but value of making predictions, we can use the exponentiality of machines (described by Moore’s Law), to attempt to build our OSS to follow the upper trajectory rather than lower trajectory in the diagram.

But how?
Chances are that you’ve already predicted it yourself.

The industry is already talking about big data analytics, machine learning, IoT, virtualised networks, software like OSS and more. These are machine-led innovations. We’re relatively early in the life-cycle of these concepts, so we’re not yet seeing the divergence of the two trajectories when mapped onto the diagram above.

But if you’re planning your OSS for the next 5-10 years and you’re not seeking to make even little steps into machine-driven decision support technologies now, then I wonder if you may be regretting the missed opportunity years into the future?

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