Himanshu Singh.

Time Series Analysis is the kind of trend analysis for for data points observed on a regular time interval.
As this technique helps in understanding the past trend of data points / behaviours being observed, we can also predict the forcast of same data points considering all other factors remaining constant / minimum change.
It is of very high relevance when we need to refer past performance and predict / plan our future actions considering no major policy change / external factors change.

Example we need to predict our people capacity i.e. average people present in office on a monthly basis, by monitoring number of leaves on monthly trend for past few years.
Time series analysis can help predict through seasonal variances for a longer time and understand people taking more leaves during DIWALI or End of Calendar year, hence less capacity is predicted on intervals. 
 
If we need to predict number of calls / request in a BPO from clients by reviewing count of calls / requests recieved on a monthly basis.
This cannot be done through Time series analysis as external factors majorly influence month on month behaviour of the data, hence Time series analysis / seasonal analysis will not support or provide better outcome.