track_HR_change: Sankey chart of organizational movement between HR attributes...

In wpa: Tools for Analysing and Visualising Viva Insights Data

Sankey chart of organizational movement between HR attributes and missing values (outside company move) (Data Overview)

Description

Creates a list of everyone at a specified start date and a specified end date then aggregates up people who have moved between organizations between this to points of time and visualizes the move through a sankey chart.

Through this chart you can see:

• The HR attribute/orgs that have the highest move out

• The HR attribute/orgs that have the highest move in

• The number of people that do not have that HR attribute or if they are no longer in the system

Usage

track_HR_change(
  data,
  start_date = min(data$Date),
  end_date = max(data$Date),
  hrvar = "Organization",
  mingroup = 5,
  return = "plot",
  NA_replacement = "Out of Company"
)

Arguments

data	A Person Query dataset in the form of a data frame.
start_date	A start date to compare changes. See end_date.
end_date	An end date to compare changes. See start_date.
hrvar	HR Variable by which to compare changes between, defaults to "Organization" but accepts any character vector, e.g. "LevelDesignation"
mingroup	Numeric value setting the privacy threshold / minimum group size. Defaults to 5.
return	Character vector specifying what to return, defaults to "plot". Valid inputs are "plot" and "table".
NA_replacement	Character replacement for NA defaults to "out of company"

Value

Returns a 'NetworkD3' object by default, where 'plot' is passed in return. When 'table' is passed, a summary table is returned as a data frame.

Author(s)

Tannaz Sattari Tabrizi [e-mail]

See Also

Other Data Validation: check_query(), extract_hr(), flag_ch_ratio(), flag_em_ratio(), flag_extreme(), flag_outlooktime(), hr_trend(), hrvar_count_all(), hrvar_count(), hrvar_trend(), identify_churn(), identify_holidayweeks(), identify_inactiveweeks(), identify_nkw(), identify_outlier(), identify_privacythreshold(), identify_query(), identify_shifts_wp(), identify_shifts(), identify_tenure(), remove_outliers(), standardise_pq(), subject_validate_report(), subject_validate(), validation_report()

Examples

dv_data %>% track_HR_change()

wpa documentation built on Aug. 21, 2023, 5:11 p.m.