This function scans a standard query output to identify employees with consistently low collaboration signals. Returns the % of non-knowledge workers identified by Organization, and optionally an edited dataframe with non-knowledge workers removed, or the full dataframe with the kw/nkw flag added.
identify_nkw(data, collab_threshold = 5, return = "data_summary")
A Standard Person Query dataset in the form of a data frame.
The collaboration hours threshold that should be exceeded as an average for the entire analysis period for the employee to be categorized as a knowledge worker ("kw"). Enter a positive number. Default is set to 5 collaboration hours.
String specifying what to return. This must be one of the following strings:
"text"
"data_with_flag"
"data_clean"
"data_summary"
See Value
for more information.
A different output is returned depending on the value passed to the return
argument:
"text"
: string. Returns a diagnostic message.
"data_with_flag"
: data frame. Original input data with an additional
column containing the kw
/nkw
flag.
"data_clean"
: data frame. Data frame with non-knowledge workers
excluded.
"data_summary"
: data frame. A summary table by organization listing
the number and % of non-knowledge workers.
Other Data Validation:
check_query()
,
extract_hr()
,
flag_ch_ratio()
,
flag_em_ratio()
,
flag_extreme()
,
flag_outlooktime()
,
hr_trend()
,
hrvar_count_all()
,
hrvar_count()
,
identify_churn()
,
identify_holidayweeks()
,
identify_inactiveweeks()
,
identify_outlier()
,
identify_privacythreshold()
,
identify_query()
,
identify_shifts_wp()
,
identify_shifts()
,
identify_tenure()
,
remove_outliers()
,
standardise_pq()
,
subject_validate_report()
,
subject_validate()
,
track_HR_change()
,
validation_report()