Performance Tuning :: Options For Querying On The Skewed Data

We have a table with huge data which is skewed on a 'status' column. The 'status' column has 6 distinct values with 1 particular value occupying 80-85% records.

In the batch process we query the data on the status and process the retrieved records. My senior is insisting on partitioning which I see not much feasible considering cost implications just for a part of functionality

See there are 6 status 'A','B','C','D','E','F'

with 'A' occupying 80% records
'B' to 'F' occupies 2% till 14% records in the table(approx)

1) Create a conditional index on status (using case) to have records with all statuses except 'A' Then create If-ELSE structure

IF input parameter is 'A'
select /*+ FULL Parallel(t) */ * from t where status='A';
ELSE
Select /*+ INDEX (t conditional_index) */ * from t where status in ('B','C');
END IF;

I want to create conditional index here for 2 reasons

1] since it will have values for status except 'A' this nullify the chance that this index will be picked up when status='A' will be queried
Thus making the performance worst (status ='A' is for 80% records) - The IF-ELSE is additional protection
2] Less impact on the DMLS as the index will not be on status='A' which contribute to large chunk of records

2)Populate a dummy table which would contain rowid and status. Since the business closes at 21:00 and batch process starts at 21:30
Between these times periods refresh the dummy table every day using merge (to catch business transactions during the day)

Now during the batch process retrieve records from the main table using the rowids in the dummy table depending on the input status value

3)Create index on status
Make sure hard coded status values are used in the database procedures
Gather stats with the histograms
And leave it to the Optimizer to choose the best possible path