feat: add exp report template
This commit is contained in:
Martin Chan
Родитель
29c485167c
Коммит
6ca6d866cd
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# Employee Experience RMarkdown Report Template
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## Parameters
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The following parameters describe the arguments that will be passed to within the report function.
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- `data`: the input must be a data frame with the columns as a Standard Person Query, which is built using the `sq_data` inbuilt into the 'wpa' package.
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- `report_title`: string containing the title of the report, which will be passed to `set_title` within the RMarkdown template.
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- `hrvar`: string specifying the HR attribute that will be passed into the single plot.
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- `mingroup`: numeric value specifying the minimum group size to filter the data by.
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## Report Type
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This is a **flexdashboard** RMarkdown report.
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The standard YAML header would be as follows:
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```
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output:
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flexdashboard::flex_dashboard:
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orientation: rows
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vertical_layout: fill
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```
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## Report output
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This report contains one single plot and a print out of the data diagnostics.
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## Data preparation
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No data preparation is required as long as it is a Standard Person Query.
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## Examples
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For an example of the report output, see `minimal report.html`.
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To run this report, you may run:
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```R
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generate_report2(
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output_format = rmarkdown::html_document(toc = TRUE, toc_depth = 6, theme = "cosmo"),
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output_file = "minimal report.html",
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output_dir = here("minimal-example"), # path for output
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report_title = "Minimal Report",
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rmd_dir = here("minimal-example", "minimal.Rmd"), # path to RMarkdown file,
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# Custom arguments to pass to `minimal-example/minimal.Rmd`
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data = sq_data,
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hrvar = "Organization",
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mingroup = 5
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)
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```
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#### Wellbeing
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- **Actively Manage Workloads**: % of employees with weekly collaboration under 20 hours and work week span under 45 hours
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- **Promote Switching Off**: % of employees with 2+ quiet days a week (maximum 2 of emails and IMs sent)
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#### Empowerment
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- **Support and Coach**: % of employees with > 15 minute a week of 1:1 meetings with manager (on average)
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- **Empower Employees**: % of employees with < 50% manager co-attendance
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#### Connection
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- **Enable broad connections**: % of employees with an internal network size of over 20
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- **Encourage small-group meetings**: % of employees with at least >2 hour of meetings with 3-8 attendees per week
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- **Encourage small-group meetings without manager**: % of employees with at least >2 hour of meetings with 3-8 attendees per week without manager co-attendance
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#### Growth
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- **Promote skip-level exposure**: % of employees with >30 mins of skip-level meeting hours with maximum 8 attendees
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- **Facilitate external connections**: % of employees with at least 15 minutes of external collaboration per week
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#### Focus
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- **Make time available to focus**: % of employees with at least 4 focus 2-hour blocks per week
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- **Enable 'Deep Work' Days**: % of employees with at least 1 day of <2 hour of meetings excluding weekends
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#### Purpose
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- **Help employees own their time**: % of employees with 25%+ of collaboration time in self-organized meetings
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- **Foster meaningful interactions**: % of employees with at least 30 minutes of 1:1 meetings with peers a week ona verage (excluding line manager 1:1 time and 1:1 coaching time)
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#' @title Create Employee Experience Index from Person Query grouped by Day
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#'
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#' @param data Data frame containing a Standard Person Query grouped by Day.
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#'
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#' @details
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#' Function still under development.
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#' Some `data.table` syntax is used to speed up performance when running daily
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#' data.
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#'
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create_expi <- function(data, hrvar, return = "standard"){
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# HR lookup ---------------------------------------------------------------
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# For joining later
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hr_df <- data %>% select(PersonId, !!sym(hrvar))
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# Daily metrics -----------------------------------------------------------
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# Get `QuietDays` and `DeepWorkDay` based on Daily Data
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# Convert back to the Weekly level
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daily_metrics <-
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data %>%
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mutate(DayOfWeek = lubridate::wday(Date, label = TRUE)) %>%
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mutate(DateWeek = lubridate::floor_date(Date, unit = "weeks",
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week_start = 7) %>%
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as.Date()) %>%
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# QuietDay = at most 2 email or IM sent on the day
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# criterion should change depending whether `IsActive` is on
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mutate(QuietDay = ifelse(Emails_sent <= 2 & Instant_messages_sent <= 2, 1, 0)) %>%
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# DeepWorkDay = Fewer than two meeting hours on the day
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mutate(DeepWorkDay = ifelse(Meeting_hours < 2, 1, 0)) %>%
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group_by(DateWeek, PersonId) %>%
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summarise(
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QuietDays = sum(QuietDay, na.rm = TRUE),
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DeepWorkDay = sum(DeepWorkDay, na.rm = TRUE),
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.groups = "drop"
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)
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# Metrics to sum up by week -----------------------------------------------
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# Sum up each day of a week to the weekly level
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metrics_to_sum <-
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c(
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"Collaboration_hours",
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"Workweek_span",
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"Meeting_hours_with_manager_1_on_1",
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"Meeting_hours_with_manager",
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"Meeting_hours",
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"Meeting_hours_for_3_to_8_attendees",
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"Meeting_hours_for_2_attendees",
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"Meeting_hours_1_on_1_with_same_level",
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"Manager_coaching_hours_1_on_1", # Optional
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"Meeting_hours_with_skip_level",
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"Collaboration_hours_external",
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"Open_2_hour_blocks",
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"Time_in_self_organized_meetings",
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"Meeting_hours_with_manager_with_3_to_8", # New
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"Meeting_hours_with_skip_level_max_8"
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)
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# Metrics summed up by week -----------------------------------------------
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# Grouped by `PersonId` and `DateWeek`
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weekly_metrics <-
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data %>%
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mutate(DateWeek = lubridate::floor_date(Date, unit = "weeks",
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week_start = 7) %>%
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as.Date()) %>%
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as.data.table() %>%
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.[, lapply(.SD, sum, na.rm = TRUE),
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by = c("PersonId", "DateWeek"),
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.SDcols = metrics_to_sum]
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# Metrics averaged up by week ---------------------------------------------
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# Only contains `Internal_network_size` - only one that is not sum-mable
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weekly_metrics_mean <-
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data %>%
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mutate(DateWeek = lubridate::floor_date(Date, unit = "weeks",
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week_start = 7) %>%
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as.Date()) %>%
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as.data.table() %>%
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.[, lapply(.SD, mean, na.rm = TRUE),
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by = c("PersonId", "DateWeek"),
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.SDcols = c("Internal_network_size")]
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# Metrics to convert to Person level --------------------------------------
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# A character vector of metrics with everything calculated so far
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metrics_to_person <-
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c(metrics_to_sum,
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"Internal_network_size",
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"QuietDays",
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"DeepWorkDay")
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# Convert Person-week level to Person level -------------------------------
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# Join the following data frames:
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# - daily_metrics
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# - weekly_metrics
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# - weekly_metrics_mean
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expi_plevel <-
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daily_metrics %>%
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# Join calculations
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left_join(weekly_metrics, by = c("PersonId", "DateWeek")) %>%
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left_join(weekly_metrics_mean, by = c("PersonId", "DateWeek")) %>%
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as.data.table() %>%
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# Average by `PersonId`
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.[, lapply(.SD, mean, na.rm = TRUE),
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by = "PersonId",
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.SDcols = metrics_to_person]
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#TODO: need to replace this once custom metric is available
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# .[, Meeting_hours_cross_level :=
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# Meeting_hours_for_2_attendees -
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# Meeting_hours_with_manager_1_on_1 -
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# Manager_coaching_hours_1_on_1] %>%
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# .[]
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# Calculate EXPI ----------------------------------------------------------
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expi_interim <-
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expi_plevel %>%
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as_tibble() %>%
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mutate(
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# Wellbeing: Actively Manage Workloads --------------------------------
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EXPI_ActiveManageWorkloads = ifelse(
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Collaboration_hours < 20 & Workweek_span < 45, TRUE, FALSE),
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# Wellbeing: Promote Switching Off ------------------------------------
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EXPI_PromoteSwitchingOff = ifelse(QuietDays > 2, TRUE, FALSE),
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# Empowerment: Support and Coach --------------------------------------
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EXPI_SupportAndCoach = ifelse(
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Meeting_hours_with_manager_1_on_1 * 60 >= 15, TRUE, FALSE),
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# Empowerment: Empower Employees --------------------------------------
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EXPI_EmpowerEmployees = ifelse(
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(Meeting_hours_with_manager / Meeting_hours) < 0.5, TRUE, FALSE
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),
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# Connection: Enable broad connections --------------------------------
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EXPI_EnableBroadConnections = ifelse(
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Internal_network_size > 20, TRUE, FALSE
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),
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# Connection: Encourage small group meetings --------------------------
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EXPI_EncourageSmallGroupMeetings = ifelse(
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Meeting_hours_for_3_to_8_attendees > 2, TRUE, FALSE),
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# Connection: Encourage small group meetings w/o manager --------------
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# At least two hours of 3-8 meetings without manager presence
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Temp_EncourageMeetingsWithoutManager = Meeting_hours_for_3_to_8_attendees - Meeting_hours_with_manager_with_3_to_8,
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EXPI_EncourageMeetingsWithoutManager = ifelse(
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Temp_EncourageMeetingsWithoutManager > 2, TRUE, FALSE
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),
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# Growth: Promote skip-level exposure ---------------------------------
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EXPI_SkipLevelExposure = ifelse(
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Meeting_hours_with_skip_level_max_8 * 60 >= 30,
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TRUE, FALSE
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),
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# Growth: Facilitate External Connections -----------------------------
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EXPI_ExternalCollaboration = ifelse(
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Collaboration_hours_external *60 >=15,
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TRUE, FALSE
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),
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# Focus: Make Time Available to Focus ---------------------------------
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EXPI_FocusTime = ifelse(
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Open_2_hour_blocks >= 4, TRUE, FALSE
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),
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# Focus: Enable Deep Work Days ----------------------------------------
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# At least one day excluding weekends with <2 of meetings
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EXPI_DeepWork = ifelse(
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DeepWorkDay >= 3, TRUE, FALSE
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),
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# Purpose: Help employees own their time ------------------------------
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EXPI_OwnTime = ifelse(
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(Time_in_self_organized_meetings / Meeting_hours) > .25,
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TRUE, FALSE
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),
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# Purpose: foster meaningful interactions -----------------------------
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EXPI_MeaningfulInteractions = ifelse(
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Meeting_hours_1_on_1_with_same_level * 60 >= 30,
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TRUE, FALSE
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)
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)
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# Key components ----------------------------------------------------------
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exp_kc <-
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expi_interim %>%
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mutate(EX_KPI_Wellbeing =
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select(.,
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EXPI_ActiveManageWorkloads,
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EXPI_PromoteSwitchingOff) %>%
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apply(1, mean, na.rm = TRUE)) %>%
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mutate(EX_KPI_Empowerment =
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select(.,
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EXPI_SupportAndCoach,
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EXPI_EmpowerEmployees) %>%
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apply(1, mean, na.rm = TRUE)) %>%
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mutate(EX_KPI_Connection =
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select(.,
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EXPI_EnableBroadConnections,
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EXPI_EncourageSmallGroupMeetings,
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EXPI_EncourageMeetingsWithoutManager) %>%
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apply(1, mean, na.rm = TRUE)) %>%
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mutate(EX_KPI_Growth =
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select(.,
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EXPI_SkipLevelExposure,
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EXPI_ExternalCollaboration) %>%
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apply(1, mean, na.rm = TRUE)) %>%
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mutate(EX_KPI_Focus =
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select(.,
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EXPI_FocusTime,
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EXPI_DeepWork) %>%
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apply(1, mean, na.rm = TRUE)) %>%
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mutate(EX_KPI_Purpose =
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select(.,
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EXPI_OwnTime,
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EXPI_MeaningfulInteractions) %>%
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apply(1, mean, na.rm = TRUE)) %>%
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## Calculate EXPI
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mutate(EXPI = select(., starts_with("EX_KPI_")) %>%
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apply(1, mean, na.rm = TRUE))
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# Component summary -------------------------------------------------------
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exp_cs <-
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exp_kc %>%
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left_join(
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hr_df,
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by = "PersonId"
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) %>%
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group_by(!!sym(hrvar)) %>%
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summarise(
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across(
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.cols = c(starts_with("EXPI_"), EXPI),
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.fns = ~mean(., na.rm = TRUE)
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)
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)
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# Key component summary ---------------------------------------------------
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exp_kcs <-
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exp_kc %>%
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left_join(
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hr_df,
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by = "PersonId"
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) %>%
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group_by(!!sym(hrvar)) %>%
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summarise(
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across(
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.cols = c(starts_with("EX_KPI_"), EXPI),
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.fns = ~mean(., na.rm = TRUE)
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)
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)
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# Date extract ------------------------------------------------------------
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dat_chr <- extract_date_range(data, return = "text")
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# Return output -----------------------------------------------------------
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if(return == "standard"){
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expi_interim
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} else if(return == "list"){
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list(
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"standard" = expi_interim,
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"kc" = exp_kc, # key component
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"cs" = exp_cs, # component summary
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"kcs" = exp_kcs, # key component summary
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"date" = dat_chr # date string
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)
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}
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}
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@ -0,0 +1,24 @@
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**Why is Employee Experience important?**
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A positive employee experience is strongly related to company outcomes, predictive of lower turnover and foundational to a strong company culture. Research has shown that companies in the top 25% on employee experience report 3x the return on assets and there was lower turnover within teams that were scoring in the top 25% on employee experience within the company. A positive employee experience can be broken down into 6 core pillars:
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1. **Wellbeing**: You feel uniquely valued, your personal time is respected and are treated with dignity.
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2. **Empowerment**: You are empowered to make decisions about how to best direct your talent and effort with the support of your manager.
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3. **Connection**: You belong as a trusted, integral member of a diverse community. You have high-quality relationships with your colleagues.
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4. **Growth**: You get what you need to maximize your strengths, learn new skills and broaden your exposure.
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5. **Focus**: You know what success looks like, what to prioritize and the time to work towards those goals.
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6. And finally **purpose**: Your work serves a bigger role and you are able to have meaningful impact. You can control your diaries and foster close relationships.
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Use Workplace Analytics metrics to quantify behaviours for each of the 6 employee experience pillars. Find areas of opportunities and growth across the organisation to implement targeted interventions.
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**Read More**
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Read more about how employee experience impacts businesses.
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[How Employee Engagement Drives Growth (gallup.com)](https://www.gallup.com/workplace/236927/employee-engagement-drives-growth.aspx)
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[The financial impact of a positive employee experience](https://www.ibm.com/downloads/cas/XEY1K26O#:~:text=The Financial Impact of a Positive Employee Experience,to recharge and work more flexibly%2C they can)
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[Why the millions we spend on employee engagement buy us so little](https://hbr.org/2017/03/why-the-millions-we-spend-on-employee-engagement-buy-us-so-little)
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@ -0,0 +1,523 @@
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---
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params:
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data: data
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set_title: report_title
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hrvar: hrvar
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mingroup: mingroup
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title: "Org Insights | Employee Experience Report"
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# output:
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# flexdashboard::flex_dashboard:
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# orientation: rows
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# vertical_layout: fill
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---
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```{r setup, include=FALSE}
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knitr::opts_chunk$set(
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echo = FALSE,
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fig.height = 9,
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fig.width = 16,
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message = FALSE,
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warning = FALSE
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)
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```
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<style>
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.navbar {
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background-color: rgb(47,85,151);
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}
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h1, h2, h3, h4, h5, h6, .h1, .h2, .h3, .h4, .h5, .h6 {
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font-family: Arial;
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font-weight: 300;
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line-height: 1.1;
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color: inherit;
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}
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body {
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font-family: Arial;
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font-size: 12px;
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line-height: 1.42857143;
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color: #333333;
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background-color: #FFFFFF;
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}
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</style>
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```{js, echo=FALSE}
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var scale = 'scale(1)';
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document.body.style.webkitTransform = scale; // Chrome, Opera, Safari
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document.body.style.msTransform = scale; // IE 9
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document.body.style.transform = scale; // General
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```
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Introduction
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=====================================
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```{r message=FALSE, warning=FALSE, include=FALSE}
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start_time <- Sys.time() # timestamp
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library(tidyverse)
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library(wpa)
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library(data.table)
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library(flexdashboard)
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expi_df <- params$data # Employee Experience Custom Query
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source("create_expi.R")
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source("vis_exp.R")
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expi_list <-
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expi_df %>%
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rename(Meeting_hours_for_3_to_8_attendees = "Meeting_hours_3_to_8",
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Meeting_hours_for_2_attendees = "Meeting_hours_1_on_1"
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) %>%
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totals_bind(target_col = "full_name_4") %>% # Add Total
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create_expi(hrvar = "full_name_4", return = "list")
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expi_out <- expi_list[["standard"]] # component
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|
||||
expi_out_2 <- expi_list[["kc"]] # key component
|
||||
|
||||
# component summary
|
||||
short_tb <- expi_list[["cs"]] %>% totals_reorder(target_col = "full_name_4")
|
||||
|
||||
# key component summary
|
||||
long_tb <- expi_list[["kcs"]] %>% totals_reorder(target_col = "full_name_4")
|
||||
|
||||
# summary table
|
||||
sum_tb <-
|
||||
long_tb %>%
|
||||
filter(full_name_4 == "Total") %>%
|
||||
select(-EXPI) %>%
|
||||
pivot_longer(cols = starts_with("EX_KPI_"),
|
||||
names_to = "EXP",
|
||||
values_to = "values") %>%
|
||||
mutate(EXP = gsub(pattern = "EX_KPI_", replacement = "", x = EXP)) %>%
|
||||
mutate(EXP = factor(EXP,
|
||||
levels = c("Wellbeing",
|
||||
"Empowerment",
|
||||
"Connection",
|
||||
"Growth",
|
||||
"Focus",
|
||||
"Purpose")
|
||||
))
|
||||
|
||||
create_gauge <- function(filt){
|
||||
gauge(
|
||||
value = round(sum_tb$values[sum_tb$EXP == filt] * 100),
|
||||
min = 0,
|
||||
max = 100,
|
||||
symbol = '%',
|
||||
label = filt,
|
||||
gaugeSectors(
|
||||
success = c(80, 100),
|
||||
warning = c(40, 79),
|
||||
danger = c(0, 39)
|
||||
))
|
||||
}
|
||||
```
|
||||
|
||||
### jumbotron {.no-title}
|
||||
|
||||
```{r results='asis'}
|
||||
xfun::file_string("jumbotron.html")
|
||||
```
|
||||
|
||||
|
||||
Overview {data-orientation=rows}
|
||||
=====================================
|
||||
|
||||
Row
|
||||
-------------------------------------
|
||||
|
||||
### Total
|
||||
|
||||
```{r}
|
||||
gauge(
|
||||
value =
|
||||
long_tb %>%
|
||||
filter(full_name_4 == "Total") %>%
|
||||
mutate(EXPI = round(EXPI * 100)) %>%
|
||||
pull(EXPI),
|
||||
min = 0,
|
||||
max = 100,
|
||||
symbol = '%',
|
||||
label = "EXP Baseline",
|
||||
gaugeSectors(
|
||||
success = c(80, 100),
|
||||
warning = c(40, 79),
|
||||
danger = c(0, 39)
|
||||
))
|
||||
```
|
||||
|
||||
Row
|
||||
-------------------------------------
|
||||
|
||||
### Wellbeing
|
||||
|
||||
```{r}
|
||||
create_gauge(filt = "Wellbeing")
|
||||
```
|
||||
|
||||
### Empowerment
|
||||
|
||||
```{r}
|
||||
create_gauge(filt = "Empowerment")
|
||||
```
|
||||
|
||||
### Connection
|
||||
|
||||
```{r}
|
||||
create_gauge(filt = "Connection")
|
||||
```
|
||||
|
||||
Row
|
||||
-------------------------------------
|
||||
|
||||
### Growth
|
||||
|
||||
```{r}
|
||||
create_gauge(filt = "Growth")
|
||||
```
|
||||
|
||||
### Focus
|
||||
|
||||
```{r}
|
||||
create_gauge(filt = "Focus")
|
||||
```
|
||||
|
||||
### Purpose
|
||||
|
||||
```{r}
|
||||
create_gauge(filt = "Purpose")
|
||||
```
|
||||
|
||||
Column {.sidebar data-width=300}
|
||||
-------------------------------------
|
||||
|
||||
### Definitions
|
||||
|
||||
```{r}
|
||||
preamble_md <- readLines("exp_preamble.md",
|
||||
encoding = "UTF-8")
|
||||
|
||||
wpa:::md2html(preamble_md)
|
||||
```
|
||||
|
||||
|
||||
Baseline
|
||||
=====================================
|
||||
|
||||
Row {data-height=5%}
|
||||
-------------------------------------
|
||||
|
||||
### Title-Placeholder {.no-title}
|
||||
|
||||
```{r results = 'asis'}
|
||||
wpa:::md2html("## Which teams could use further support to improve overall employee experience?")
|
||||
```
|
||||
|
||||
Row {data-height=95%}
|
||||
-------------------------------------
|
||||
### Baseline
|
||||
|
||||
```{r echo=FALSE}
|
||||
long_tb %>%
|
||||
select(-EXPI) %>%
|
||||
pivot_longer(cols = starts_with("EX_KPI_"),
|
||||
names_to = "EXP",
|
||||
values_to = "values") %>%
|
||||
mutate(EXP = gsub(pattern = "EX_KPI_", replacement = "", x = EXP)) %>%
|
||||
mutate(EXP = factor(EXP,
|
||||
levels = c("Wellbeing",
|
||||
"Empowerment",
|
||||
"Connection",
|
||||
"Growth",
|
||||
"Focus",
|
||||
"Purpose")
|
||||
)) %>%
|
||||
ggplot(aes(x = EXP,
|
||||
y = full_name_4,
|
||||
fill = values)) +
|
||||
geom_tile(colour = "#FFFFFF",
|
||||
size = 2) +
|
||||
geom_text(aes(label = scales::percent(values, accuracy = 1)),
|
||||
size = 3) +
|
||||
# Fill is contingent on max-min scaling
|
||||
scale_fill_gradient2(low = rgb2hex(204, 50, 50),
|
||||
mid = rgb2hex(231, 180, 22),
|
||||
high = rgb2hex(45, 201, 55),
|
||||
midpoint = 0.5,
|
||||
breaks = c(0, 0.5, 1),
|
||||
labels = c("Low", "", "High"),
|
||||
limits = c(0, 1)) +
|
||||
scale_x_discrete(position = "top") +
|
||||
scale_y_discrete(labels = us_to_space) +
|
||||
facet_grid(. ~ EXP,
|
||||
scales = "free") +
|
||||
theme_wpa_basic() +
|
||||
theme(axis.line = element_line(color = "#FFFFFF")) +
|
||||
labs(title = "Employee Experience",
|
||||
subtitle = "Baseline by `full_name_4`",
|
||||
y =" ",
|
||||
x =" ",
|
||||
fill = " ",
|
||||
caption = extract_date_range(expi_df, return = "text")) +
|
||||
theme(axis.text.x = element_blank(), # already covered by facet
|
||||
plot.title = element_text(color="grey40", face="bold", size=20))
|
||||
|
||||
# long_tb %>%
|
||||
# create_bar_asis(
|
||||
# group_var = "full_name_4",
|
||||
# bar_var = "EXPI",
|
||||
# title = "Employee Experience Baseline",
|
||||
# subtitle = "Aggregated",
|
||||
# caption = extract_date_range(expi_df, return = "text"),
|
||||
# bar_colour = "darkblue",
|
||||
# percent = TRUE)
|
||||
|
||||
```
|
||||
|
||||
Column {.sidebar data-width=300}
|
||||
-------------------------------------
|
||||
|
||||
### Definitions
|
||||
|
||||
```{r}
|
||||
intro_md <- readLines("components.md")
|
||||
|
||||
wpa:::md2html(intro_md)
|
||||
```
|
||||
|
||||
KPIs
|
||||
=====================================
|
||||
|
||||
Row {data-height=5%}
|
||||
-------------------------------------
|
||||
|
||||
### Title-Placeholder {.no-title}
|
||||
|
||||
```{r results = 'asis'}
|
||||
wpa:::md2html("## Which underlying behaviours are impacting the employee experience pillar scores?")
|
||||
```
|
||||
|
||||
Row {data-height=95%}
|
||||
-------------------------------------
|
||||
|
||||
### KPIs
|
||||
|
||||
```{r echo=FALSE, message=FALSE, warning=FALSE}
|
||||
|
||||
## reg matching nth occurrence
|
||||
# a <- "1, 2, 3, 4, 5, 6, 7, 8, 9, 10"
|
||||
# fn <- ","
|
||||
# rp <- "\n"
|
||||
# n <- 4
|
||||
|
||||
replN <- function(x, fn, rp, n) {
|
||||
regmatches(x, gregexpr(fn, x)) <- list(c(rep(fn,n-1),rp))
|
||||
x
|
||||
}
|
||||
# replN(a, ",", "\n", 4)
|
||||
#[1] "1, 2, 3, 4\n 5, 6, 7, 8\n 9, 10
|
||||
|
||||
short_tb %>%
|
||||
select(-EXPI) %>%
|
||||
pivot_longer(cols = starts_with("EXPI_"),
|
||||
names_to = "EXP",
|
||||
values_to = "values") %>%
|
||||
order_exp() %>%
|
||||
add_component() %>%
|
||||
mutate(EXP = gsub(pattern = "EXPI_", replacement = "", x = EXP)) %>%
|
||||
mutate(EXP = camel_clean(EXP)) %>%
|
||||
mutate(EXP = replN(x = EXP, fn = " ", rp = "\n", n = 2)) %>%
|
||||
# mutate(EXP = gsub(pattern = " ", replacement = "\n", x = EXP)) %>%
|
||||
ggplot(aes(x = EXP,
|
||||
y = full_name_4,
|
||||
fill = values)) +
|
||||
geom_tile(colour = "#FFFFFF",
|
||||
size = 2) +
|
||||
geom_text(aes(label = scales::percent(values, accuracy = 1)),
|
||||
size = 3) +
|
||||
# Fill is contingent on max-min scaling
|
||||
scale_fill_gradient2(low = rgb2hex(204, 50, 50),
|
||||
mid = rgb2hex(231, 180, 22),
|
||||
high = rgb2hex(45, 201, 55),
|
||||
midpoint = 0.5,
|
||||
breaks = c(0, 0.5, 1),
|
||||
labels = c("Low", "", "High"),
|
||||
limits = c(0, 1)) +
|
||||
scale_x_discrete(position = "top") +
|
||||
scale_y_discrete(labels = us_to_space) +
|
||||
facet_grid(. ~ Component,
|
||||
scales = "free") +
|
||||
theme_wpa_basic() +
|
||||
theme(axis.line = element_line(color = "#FFFFFF")) +
|
||||
labs(
|
||||
title = "Employee Experience",
|
||||
subtitle = "KPIs by `full_name_4`",
|
||||
y = " ",
|
||||
x = " ",
|
||||
fill = " ",
|
||||
caption = extract_date_range(expi_df, return = "text")
|
||||
) +
|
||||
theme(
|
||||
axis.text = element_text(size = 8),
|
||||
axis.text.x = element_text(angle = 60, hjust = 0),
|
||||
plot.title = element_text(color="grey40", face="bold", size=20)
|
||||
)
|
||||
```
|
||||
|
||||
Column {.sidebar data-width=300}
|
||||
-------------------------------------
|
||||
|
||||
### Definitions
|
||||
|
||||
```{r}
|
||||
wpa:::md2html(intro_md)
|
||||
```
|
||||
|
||||
|
||||
Opportunities
|
||||
=====================================
|
||||
|
||||
Row {data-height=5%}
|
||||
-------------------------------------
|
||||
|
||||
### Title-Placeholder {.no-title}
|
||||
|
||||
```{r results = 'asis'}
|
||||
wpa:::md2html("## What are the behavioural opportunities for growth within each team?")
|
||||
```
|
||||
|
||||
Row {data-height=95%}
|
||||
-------------------------------------
|
||||
|
||||
### Opportunities
|
||||
|
||||
```{r echo=FALSE, message=FALSE, warning=FALSE}
|
||||
|
||||
vis_list <- vis_exp(x = expi_list, hrvar = "full_name_4")
|
||||
|
||||
vis_list[["plot_1"]]
|
||||
|
||||
```
|
||||
|
||||
Column {.sidebar data-width=300}
|
||||
-------------------------------------
|
||||
|
||||
### Definitions
|
||||
|
||||
```{r}
|
||||
wpa:::md2html(intro_md)
|
||||
```
|
||||
|
||||
|
||||
Distribution
|
||||
=====================================
|
||||
|
||||
Row {data-height=5%}
|
||||
-------------------------------------
|
||||
|
||||
### Title-Placeholder {.no-title}
|
||||
|
||||
```{r results = 'asis'}
|
||||
wpa:::md2html("## Are employees within individual teams sharing a broadly uniform experience?")
|
||||
```
|
||||
|
||||
Row {data-height=95%}
|
||||
-------------------------------------
|
||||
|
||||
### Distribution
|
||||
|
||||
```{r echo=FALSE, message=FALSE, warning=FALSE}
|
||||
|
||||
vis_list[["plot_2"]]
|
||||
|
||||
```
|
||||
|
||||
Column {.sidebar data-width=300}
|
||||
-------------------------------------
|
||||
|
||||
### Definitions
|
||||
|
||||
```{r}
|
||||
wpa:::md2html(intro_md)
|
||||
```
|
||||
|
||||
Notes
|
||||
=====================================
|
||||
|
||||
Column {data-height=650} {.tabset}
|
||||
-------------------------------------
|
||||
|
||||
### Query Spec
|
||||
|
||||
#### Specifications
|
||||
|
||||
Run a single daily person query:
|
||||
|
||||
- Group by `Day`
|
||||
- At least 3 months
|
||||
- Ensure that `IsActive` flag is not applied
|
||||
|
||||
|
||||
#### All metrics
|
||||
|
||||
**Note**: _Custom metrics shown in **bolded italics**_
|
||||
|
||||
1. **_Meeting hours 1 on 1_** [SEE SPEC BELOW]
|
||||
1. **_Meeting hours 1 on 1 with same level_** [SEE SPEC BELOW]
|
||||
1. Time in self organized meetings
|
||||
1. Open 2 hour blocks
|
||||
1. Collaboration hours external
|
||||
1. Meetings with skip level
|
||||
1. Meeting hours with skip level
|
||||
1. ***Meeting hours 3 to 8*** [SEE SPEC BELOW]
|
||||
1. Internal network size
|
||||
1. Meeting hours with manager
|
||||
1. Meeting hours
|
||||
1. Meetings
|
||||
1. Meetings with manager
|
||||
1. Meeting hours with manager 1 on 1
|
||||
1. Instant messages sent
|
||||
1. Emails sent
|
||||
1. Workweek span
|
||||
1. Collaboration hours
|
||||
1. ***Meeting hours with skip level max 8*** [SEE SPEC BELOW]
|
||||
1. ***Meeting hours with manager with 3 to 8*** [SEE SPEC BELOW]
|
||||
|
||||
|
||||
#### Custom metrics
|
||||
|
||||
1. Meeting Hours 1 on 1: where `Total attendees == 2`
|
||||
1. Meeting Hours 1 on 1 with same level: `All attendee's and/or recipient's` where `LevelDesignation == @RelativeToPerson` AND `Total attendees == 2`
|
||||
1. Meeting hours 3 to 8: `Total attendees >= 3` AND `Total attendees <= 8`
|
||||
1. Meeting hours with skip level max 8: `Total attendees <= 8`, using `Meeting hours with skip level`.
|
||||
1. Meeting hours with manager 3 to 8: `Total attendees >= 3` AND `Total attendees <= 8`, using `Meeting hours with manager`. This is used to calculate **small group meetings without manager** by deducting this from `Meeting hours for 3 to 8 attendees`.
|
||||
|
||||
### Table - 1
|
||||
|
||||
```{r echo=FALSE}
|
||||
long_tb %>%
|
||||
set_names(nm = gsub(pattern = "EX_KPI_", replacement = "", x = names(.))) %>%
|
||||
create_dt(rounding = 2)
|
||||
```
|
||||
|
||||
### Table - 2
|
||||
|
||||
```{r echo=FALSE}
|
||||
short_tb %>%
|
||||
set_names(nm = gsub(pattern = "EXPI_", replacement = "", x = names(.))) %>%
|
||||
create_dt(rounding = 2)
|
||||
```
|
||||
|
||||
### Notes
|
||||
|
||||
```{r}
|
||||
end_time <- Sys.time()
|
||||
text1 <- paste("This report was generated on ", format(Sys.time(), "%b %d %Y"), ".")
|
||||
text2 <- expi_df %>% check_query(return = "text", validation = TRUE)
|
||||
text3 <- paste("Total Runtime was: ", difftime(end_time, start_time, units = "mins") %>%
|
||||
round(2), "minutes.")
|
||||
paste(text1, text2, text3, sep = "\n\n" )%>% wpa:::md2html()
|
||||
```
|
||||
|
|
@ -0,0 +1,31 @@
|
|||
<div class="jumbotron" style="background-color:#FFFFFF;">
|
||||
<!--<img src="Microsoft-Viva-Insights-logo.png" style="float:right;width:180px;height:180px;">-->
|
||||
<h1 class="display-4">Employee Experience Report</h1>
|
||||
<p class="lead" style="color:gray;"> <B> Microsoft Viva | Organisational Insights </B></p>
|
||||
<hr class="my-4">
|
||||
<p> <font size="+1"> <em> Based on decades of quantitative and qualitative research, and our own experience working with global customers and here within Microsoft, we have identified six key elements to a great employee experience. These elements are Strongly related to company outcomes, are predictive of lower turnover and are the foundations to a strong corporate culture. </em> </font></p>
|
||||
<br>
|
||||
<p><font size="+0">This is a framework for evaluating Employee Experience. The main components of the baseline are as follows:</font></p>
|
||||
<div class="row">
|
||||
<div class="col-md-6"><!-- first column -->
|
||||
<div class="list-group">
|
||||
<a href="#overview" class="list-group-item"><font size="+1">1. Overview</font></a>
|
||||
<a href="#baseline" class="list-group-item"><font size="+1">2. Baseline</font></a>
|
||||
<a href="#kpis" class="list-group-item"><font size="+1">3. KPIs</font></a>
|
||||
</div><!-- list-group -->
|
||||
</div><!-- end col-md-6 -->
|
||||
|
||||
<div class="col-md-6"><!-- second column -->
|
||||
<div class="list-group">
|
||||
<a href="#opportunities" class="list-group-item"><font size="+1">4. Opportunities</font></a>
|
||||
<a href="#distribution" class="list-group-item"><font size="+1">5. Distribution</font></a>
|
||||
<a href="#notes" class="list-group-item"><font size="+1">6. Notes</font></a>
|
||||
</div><!-- list-group -->
|
||||
</div><!-- end col-md-6 -->
|
||||
|
||||
</div><!-- row -->
|
||||
<p class="lead">
|
||||
<a class="btn btn-primary btn-lg" href="#overview" role="button">Start exploring</a>
|
||||
</p>
|
||||
</div>
|
||||
<br>
|
||||
|
|
@ -0,0 +1,321 @@
|
|||
|
||||
#' @param x List of outputs from `create_expi()`.
|
||||
vis_exp <- function(x,
|
||||
hrvar){
|
||||
|
||||
# Long format data frame -----------------------------------------------
|
||||
|
||||
long_data <-
|
||||
x[["cs"]] %>% # component summary
|
||||
select(-EXPI) %>% # Drop
|
||||
pivot_longer(cols = starts_with("EXPI_"),
|
||||
names_to = "EXP",
|
||||
values_to = "values")
|
||||
|
||||
# Data frame with only EXPI and HR attributes ---------------------------
|
||||
|
||||
expi_results <-
|
||||
x[["kcs"]] %>%
|
||||
select(!!sym(hrvar), EXPI)
|
||||
|
||||
# Data frame with rect specifications -----------------------------------
|
||||
|
||||
bar_data_1 <-
|
||||
long_data %>%
|
||||
group_by(!!sym(hrvar)) %>%
|
||||
summarise(
|
||||
x_max = max(values, na.rm = TRUE),
|
||||
x_min = min(values, na.rm = TRUE),
|
||||
med = median(values, na.rm = TRUE)
|
||||
) %>%
|
||||
mutate(
|
||||
id = 1:nrow(.),
|
||||
y_min = id - 0.4,
|
||||
y_max = id + 0.4
|
||||
) %>%
|
||||
left_join(expi_results, by = hrvar)
|
||||
|
||||
## grouped by EXP
|
||||
## no EXPI joined up
|
||||
bar_data_2 <-
|
||||
long_data %>%
|
||||
group_by(EXP) %>%
|
||||
summarise(
|
||||
x_max = max(values, na.rm = TRUE),
|
||||
x_min = min(values, na.rm = TRUE),
|
||||
med = median(values, na.rm = TRUE)
|
||||
) %>%
|
||||
order_exp() %>%
|
||||
mutate(
|
||||
id = 1:nrow(.),
|
||||
y_min = id - 0.4,
|
||||
y_max = id + 0.4
|
||||
)
|
||||
|
||||
## Clean names
|
||||
bar_data_2b <-
|
||||
bar_data_2 %>%
|
||||
add_component() %>%
|
||||
clean_exp() # %>%
|
||||
# mutate(EXP = paste(Component, "-", EXP))
|
||||
|
||||
|
||||
|
||||
# Long table joined up with rect specifications ------------------------
|
||||
|
||||
pre_plot_df_1 <-
|
||||
long_data %>%
|
||||
left_join(bar_data_1, by = "full_name_4") %>%
|
||||
add_component() %>%
|
||||
mutate(EXP = gsub(pattern = "EXPI_", replacement = "", x = EXP),
|
||||
EXP = camel_clean(EXP)
|
||||
) %>%
|
||||
group_by(full_name_4) %>%
|
||||
mutate(text = case_when(
|
||||
values == max(values) ~ "top",
|
||||
values == min(values) ~ "bottom",
|
||||
TRUE ~ ""))
|
||||
|
||||
pre_plot_df_2 <-
|
||||
long_data %>%
|
||||
left_join(bar_data_2, by = "EXP") %>%
|
||||
add_component()
|
||||
|
||||
# Segments ------------------------------------------------------------
|
||||
|
||||
segment_df_1 <-
|
||||
pre_plot_df_1 %>%
|
||||
group_by(id) %>%
|
||||
summarise(
|
||||
x_med = first(EXPI),
|
||||
y_min = first(y_min),
|
||||
y_max = first(y_max)
|
||||
)
|
||||
|
||||
segment_df_2 <-
|
||||
pre_plot_df_2 %>%
|
||||
group_by(id) %>%
|
||||
summarise(
|
||||
seg_x_med = first(med),
|
||||
seg_y_min = first(y_min),
|
||||
seg_y_max = first(y_max)
|
||||
)
|
||||
|
||||
pre_plot_df_2 <-
|
||||
pre_plot_df_2 %>%
|
||||
left_join(
|
||||
segment_df_2,
|
||||
by = "id"
|
||||
)
|
||||
|
||||
# Generate plot -------------------------------------------------------
|
||||
|
||||
plot_1 <-
|
||||
pre_plot_df_1 %>%
|
||||
ggplot(aes(x = values, y = id)) +
|
||||
geom_rect(
|
||||
aes(
|
||||
xmin = x_min,
|
||||
xmax = x_max,
|
||||
ymin = y_min,
|
||||
ymax = y_max
|
||||
),
|
||||
fill = "#D9E7F7"
|
||||
) +
|
||||
geom_segment(
|
||||
data = segment_df_1,
|
||||
aes(x = x_med,
|
||||
xend = x_med,
|
||||
y = y_min,
|
||||
yend = y_max
|
||||
),
|
||||
colour = "red",
|
||||
size = 0.5) +
|
||||
scale_y_continuous(
|
||||
breaks = unique(bar_data_1$id),
|
||||
labels = unique(bar_data_1[["full_name_4"]])
|
||||
) +
|
||||
geom_jitter(
|
||||
aes(colour = Component),
|
||||
alpha = 0.5,
|
||||
width = 0,
|
||||
height = 0.2,
|
||||
size = 1) +
|
||||
ggrepel::geom_text_repel(
|
||||
aes(
|
||||
label = ifelse(text %in% c("bottom"), EXP, "")), # only label bottom
|
||||
size = 3) +
|
||||
scale_x_continuous(
|
||||
limits = c(0, 1),
|
||||
breaks = c(0, 0.25, 0.5, 0.75, 1),
|
||||
labels = scales::percent,
|
||||
position = "top"
|
||||
) +
|
||||
theme_wpa_basic() +
|
||||
theme(
|
||||
axis.line = element_blank(),
|
||||
panel.grid.major.x = element_blank(),
|
||||
panel.grid.minor.x = element_line(color = "gray"),
|
||||
strip.placement = "outside",
|
||||
strip.background = element_blank(),
|
||||
strip.text = element_blank()
|
||||
) +
|
||||
# geom_vline(xintercept = mean(plot_data_new$values), colour = "red") +
|
||||
labs(
|
||||
title = "Employee Experience",
|
||||
subtitle = paste("Opportunities by", hrvar),
|
||||
caption = paste("Red line indicates EXP Index.",
|
||||
x[["date"]]),
|
||||
y = "",
|
||||
x = ""
|
||||
)
|
||||
|
||||
# Plot 2 ---------------------------------------------------------------
|
||||
|
||||
plot_2 <-
|
||||
pre_plot_df_2 %>%
|
||||
mutate(Component = factor(Component,
|
||||
levels = c("Wellbeing",
|
||||
"Empowerment",
|
||||
"Connection",
|
||||
"Growth",
|
||||
"Focus",
|
||||
"Purpose")
|
||||
)) %>%
|
||||
ggplot(aes(x = values, y = id)) +
|
||||
geom_rect(
|
||||
aes(
|
||||
xmin = x_min,
|
||||
xmax = x_max,
|
||||
ymin = y_min,
|
||||
ymax = y_max
|
||||
),
|
||||
fill = "#D9E7F7"
|
||||
) +
|
||||
geom_segment(
|
||||
aes(
|
||||
x = seg_x_med,
|
||||
xend = seg_x_med,
|
||||
y = seg_y_min,
|
||||
yend = seg_y_max
|
||||
),
|
||||
colour = "red",
|
||||
size = 0.5) +
|
||||
geom_jitter(
|
||||
aes(colour = !!sym(hrvar)),
|
||||
alpha = 0.5,
|
||||
width = 0,
|
||||
height = 0.2,
|
||||
size = 2) +
|
||||
scale_y_continuous(
|
||||
breaks = unique(bar_data_2b$id),
|
||||
labels = unique(bar_data_2b[["EXP"]])
|
||||
) +
|
||||
theme_wpa_basic() +
|
||||
theme(
|
||||
axis.line = element_blank(),
|
||||
panel.grid.major.x = element_blank(),
|
||||
panel.grid.minor.x = element_line(color = "gray"),
|
||||
strip.background = element_rect(
|
||||
fill = "grey60",
|
||||
colour = "grey60"
|
||||
),
|
||||
strip.placement = "outside",
|
||||
strip.text = element_text(
|
||||
size = 8,
|
||||
colour = "#FFFFFF",
|
||||
face = "plain")
|
||||
) +
|
||||
scale_x_continuous(
|
||||
limits = c(0, 1),
|
||||
breaks = c(0, 0.25, 0.5, 0.75, 1),
|
||||
labels = scales::percent,
|
||||
position = "top"
|
||||
) +
|
||||
facet_grid(
|
||||
Component ~ .,
|
||||
scales = "free",
|
||||
switch = "y"
|
||||
) +
|
||||
labs(
|
||||
title = "Employee Experience",
|
||||
subtitle = paste("Distribution by", hrvar),
|
||||
caption = x[["date"]],
|
||||
y = "",
|
||||
x = ""
|
||||
)
|
||||
|
||||
# Return results --------------------------------------------------------
|
||||
|
||||
list(
|
||||
"long_data" = long_data,
|
||||
"plot_1" = plot_1,
|
||||
"plot_2" = plot_2,
|
||||
"pre_plot" = pre_plot_df_2,
|
||||
"bar_data" = bar_data_2b,
|
||||
"segment" = segment_df_2
|
||||
)
|
||||
}
|
||||
|
||||
|
||||
#' Order components
|
||||
order_exp <- function(x){
|
||||
x %>%
|
||||
mutate(EXP = factor(
|
||||
EXP,
|
||||
levels = c(
|
||||
"EXPI_ActiveManageWorkloads",
|
||||
"EXPI_PromoteSwitchingOff",
|
||||
"EXPI_SupportAndCoach",
|
||||
"EXPI_EmpowerEmployees",
|
||||
"EXPI_EnableBroadConnections",
|
||||
"EXPI_EncourageSmallGroupMeetings",
|
||||
"EXPI_EncourageMeetingsWithoutManager",
|
||||
"EXPI_SkipLevelExposure",
|
||||
"EXPI_ExternalCollaboration",
|
||||
"EXPI_FocusTime",
|
||||
"EXPI_DeepWork",
|
||||
"EXPI_OwnTime",
|
||||
"EXPI_MeaningfulInteractions"
|
||||
)
|
||||
)) %>%
|
||||
arrange(desc(EXP)) %>%
|
||||
mutate(EXP = as.character(EXP))
|
||||
}
|
||||
|
||||
#' Clean EXP
|
||||
|
||||
clean_exp <- function(x){
|
||||
x %>%
|
||||
mutate(EXP = gsub(pattern = "EXPI_", replacement = "", x = EXP),
|
||||
EXP = camel_clean(EXP)
|
||||
)
|
||||
}
|
||||
|
||||
#' Add Key Component
|
||||
add_component <- function(x){
|
||||
x %>%
|
||||
mutate(Component = case_when(
|
||||
EXP == "EXPI_ActiveManageWorkloads" ~ "Wellbeing",
|
||||
EXP == "EXPI_DeepWork" ~ "Focus",
|
||||
EXP == "EXPI_EmpowerEmployees" ~ "Empowerment",
|
||||
EXP == "EXPI_EnableBroadConnections" ~ "Connection",
|
||||
EXP == "EXPI_EncourageSmallGroupMeetings" ~ "Connection",
|
||||
EXP == "EXPI_ExternalCollaboration" ~ "Growth",
|
||||
EXP == "EXPI_FocusTime" ~ "Focus",
|
||||
EXP == "EXPI_MeaningfulInteractions" ~ "Purpose",
|
||||
EXP == "EXPI_OwnTime" ~ "Purpose",
|
||||
EXP == "EXPI_PromoteSwitchingOff" ~ "Wellbeing",
|
||||
EXP == "EXPI_SkipLevelExposure" ~ "Growth",
|
||||
EXP == "EXPI_EncourageMeetingsWithoutManager" ~ "Connection",
|
||||
EXP == "EXPI_SupportAndCoach" ~ "Empowerment",
|
||||
)) %>%
|
||||
mutate(Component = factor(Component,
|
||||
levels = c("Wellbeing",
|
||||
"Empowerment",
|
||||
"Connection",
|
||||
"Growth",
|
||||
"Focus",
|
||||
"Purpose")
|
||||
))
|
||||
}
|
||||
Загрузка…
Ссылка в новой задаче