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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