- DIMENSIONS (1)Cient: CASE WHEN Case_table.Client = Client1 THEN Client-01 WHEN Case_table.Client = Client2 THEN Client-02 WHEN Case_table.Client = Client3 THEN Client-03 WHEN Case_table.Client = Client4 THEN Client-04 ELSE END
- KPIS (1)Throughput: AVG(CALC_THROUGHPUT(CASE_START TO CASE_END, REMAP_TIMESTAMPS(Case_table.Time stamp, Seconds)))
Question
Thoughputs of each clients are higher than average throughput
Dear community,
I would like to create an OLAP table to calculate throughputs from Process Start to"Process End" of each client.
My data model is single eventlog, Case_table, which consists of Process group, Activity, Time stamp, and Client.
Every records of case table have client name( client1 - 4) in client column.
I tried to make OLAP table like this.
Dear @Sugano,
try this instead of CALC_THROUGHPUT:
AVG(
SECOUNDS_BETWEEN(
PU_FIRST("MAPPING_TABLE", "ACTIVITIES"."EVENTTIME", "ACTIVITIES"."ACTIVITY" = 'CASE_START' ),
PU_LAST("MAPPING_TABLE", "ACTIVITIES"."EVENTTIME", "ACTIVITIES"."ACTIVITY" = 'CASE_END' )
)
)
Best regards,
ChanyutDear Chanyut
Thank you for your support.
I tried a following statement as you mentioned above.
AVG( SECONDS_BETWEEN( PU_FIRST(MAPPING_TABLE, ACTIVITIES.Time stamp), PU_LAST(MAPPING_TABLE, ACTIVITIES.Time stamp) ) )
This statement worked same as CALC_THROUGHPUT.
I assume that the dimensions has a problem.
Hi Sugano
In some cases you might have activities between your process path which its thoughput times are lower than avg throughput times. This might lead to an outlier issue.
(Use Case Explorer to identify if such cases existed)
Possible Solutions:
- Use MEDIAN() instead of AVG() to solves statistical outliers issue.
- Exclude undue activities by using component filter for your OLAP
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