Shelf Life of Trends

Shelf Life of Trends- A concern for big data analytics era

Shelf Life of Trends- A concern for big data analytics era

One the  most grappling challenges for  business in this era  of  big data  is how  long does  each trend remain a  ‘trend’. With the high rate of idea  metabolism , with the increasing rate  of  technology and innovation driven  change , trends get more and more  short lived.

A trend is essentially based on a period of data and more the period the more  reliable it gets. And this period has minimum factors changing be it government policies, economic factors, environmental conditions or technological advancements. But as  and  how these  factors change , this period of consideration gets  sliced and minced .  It gets  difficult to call it a trend. It is no longer  a  function of a long period of constant conditions. In fact, its the rate of  change of change that is more likely to become a trend.

For example –

Trend in the  demand for touch  technology is valid  only as  long as voice recognition is  not developed and  that in turn will not remain no longer relevant than the  invention and mass access to eyeball detection technology .

Question remains, if long-term climatic trend is actionable in project planning today, at what point do you revisit the trends analysis to verify that the projects you have forecasted for your pipeline are still worthy?”

An important step for most companies using long-term trends information garnered from analytics will be to determine how long they can expect the analytics for each trend to remain accurate and usable for business decision making . Organizations have not yet moved forward into long-term trends usage and decision-making, but as more do, they will also need to apply their own analytics to the longevity expectations for the trends data they capture. “It is determinations like this that sit on the doorstep of the next frontier of big data analytics”

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