The rate of change keeps galloping faster
In this connected world where speed and quality are important, competition has increased a lot. It is not only among the big players but also with the small startups using technology and innovation. Basically to bring digital disruption in the citadels of business established just a couple of decades ago.
The largest companies today did not even exist in garages a couple of decades ago and the largest names of yesterday are fighting a problem of their own creation – command, and control to cater to scale and quality that brought along with it a complexity that reduced the speed of movement considerably.
Classic nature of digital disruption
Organisations today need a 360-degree periscope to look around. To beware of the next disruptive threat to their business. When a team of 19 people created WhatsApp, they brought a digital disruption. They rummaged a billion dollar of SMS revenues 8000 miles away and caught the settled giants napping.
Such was the power of disruption. Such was the speed that companies staring at green fields were looking down a ravine.
Smaller companies are digital by objective
They have no baggage or legacy of the past and are very fast in entering new markets because of their very nature. They are online and cloud hosted so they can almost scale real-time and cater to any spike in demand. Gone are the days of the 5-year plan in business. Here we measure the rate of change at new age digital tech companies in factors of 10x in a year.
At this rapid pace and setting up new territory, there is hardly a notion of what is going to be the landscape 5 years down the line. Nimbleness is in – pivoting and fail fast are part of business and management philosophy and vocabulary.
It’s like a tottering drunk sailor
A sailor with no idea where his ship is – punch drunk growth and the free spirit of adventure without a compass. And the machines are taking over day jobs. This world of digital disruption is the prediction of some while others believe a new era of disruption is just beginning. I tend to support the former since the prevalence of computing power, data to run deep end analytics and train machines is under the control of today’s digital giants. This data is increasingly being used to study, recommend, personalise and predict the actions and behaviour of individuals.
The rate of change and improvement in prediction indexes is going up by the day. How do humans adapt to this constantly increasing rate of change? How do we benefit from the machines while at the same time not get replaced by them professionally? Some topics to explore in the next set of blogs.