What is used of Granularity for Time Series Data in Mongodb?

Hi all,
As per below document,
# Granularity for Time Series Data
It is recommended that " When you create a time series collection, set the granularity to the value that is the closest match to the time span between consecutive incoming measurements that have the same unique value for the metaField field".

“Setting the granularity parameter accurately improves performance by optimizing how data in the time series collection is stored internally.”

“To set the parameter accurately, choose a granularity value that is closest to the ingestion rate for a unique data source as specified by the value for the metaField field.”

Can someone help me to understand how Granularity helps in improving performance here?
Also, what kind of operations will see the performance improvements due to accurate granularity?
What are the drawbacks of having incorrect granularity, meaning, data is injected per second but time series collection is created with granularity “hours”?

Thanks in advance