Making over a chart from the Singapore Labour Force (2019) report.

This was written as part of the requirements for the Visual Analytics module for MITB.

For my first DataViz makeover, I have used data from the Ministry of Manpower of Singapore, which analyses Singapore’s labour force to understand shifts in the labour market to facilitate better decision making.

1) The original visualisation

Figure 1: Chart 6 of Labour Force in Singapore 2019 report (page 22)

Notes:

• LFPR refers to the proportion of working-age population that engages actively in the labour market, either by working or looking for work. Source: MOM
• Share of residents refers to the age distribution of the labour force.

Before making over the selected visualisation, it is important to have a clear understanding of the context of the visualisation and its key takeaways which are dependent on:

• Who: Individuals, businesses and primarily policy-makers, to help improve the well-being and optimisation of workers.
• What: Understanding the shift in Singapore’s labour force from the respective age bands over the past 10 years (2009 to 2019).
• How: Showing that labour force distribution and participation rate of older workers (55 and over) has increased, which resulted in the increase in labour force’s median age.

2) Critiques and suggestions for current visualisation

2.1 Clarity

2.2 Aesthetics

3) Proposed Design

3.1 Sketch

Figure 2: Sketch of proposed design

3.2 Advantages of proposed design

i) Clear title – shows how the participation rate and distribution of Singapore’s labour force has shifted by age bands from 2009 to 2019.
ii) Chart titles tell the big picture story, followed up with short commentary to provide more context.
iii) Shows how labour force has changed across the 10 years instead of 2 year points as shown in the original visualisation.
iv) Figures and age bands per commentary and chart are consistent for easy cross referencing.
v) Axis are properly labeled – LFPR% and share of labour force.
vi) Only selected figures (2009 and 2019) are shown to highlight the shift.
vii) Colours are consistent throughout the dashboard.

4) Data visualisation steps

In remaking the existing visualisation, I used
i) Table 5 (Resident Labour Force Participation Rate by Age and Sex, 2009 - 2019), and
ii) Table 7 (Resident Labour Force Aged Fifteen Years and Over by Age and Sex, 2009 - 2019)
from the Ministry of Manpower of Singapore.

4.1 Data preparation

Data: Table 5 - LFPR

1. Remove unnecessary columns
   Delete columns A, B, D, F, H, J, L, M, N, P, R, T, V, X, Z.
   Figure 3: Remove unnecessary columns

2. Remove empty rows
   Delete rows 1 to 4 and 19. Figure 4: Remove empty rows

3. Rename header
   Rename header from “Age (Years)” to “Age band”. Figure 5: Rename header

4. Delete unnecessary tabs
   Remove tabs T5_F and T5_M.
   Save and rename file as T5_T_clean.

Data: Table 7 - Labour force

1. Tidy data
   Repeat steps 1 to 4 as done for Table 5 above.

2. Pivot data
   Import file into Tableau, select all the years, right click and select “Pivot”. Figure 6: Pivot data

3. Rename headers
   Rename ‘Pivot Field Names’ to ‘Year’. Rename ‘Pivot Field Values’ to ‘Labour force’. Figure 7: Rename headers

4. Change data type
   Change Year data type to “Date”.

5. Export file to csv
   Save file as “T7_T_pivot”.

4.2 Data visualisation

Import both T5_T_clean and T7_T_pivot into Tableau.

Data source tab - T5_T_clean

1. Import into Tableau & create flat file
   Inspect imported data: Upon importation, the LFPR from 2009 to 2019 are spread across multiple columns. As such, we want to create a flat file - select the columns from 2009 to 2019, right click and select pivot. Figure 8: Pivot data

2. Rename headers
   Rename ‘Pivot Field Names’ to ‘Year’.
   Rename ‘Pivot Field Values’ to ‘LFPR%’.
   Figure 9: Rename headers

3. Change data type
   Change ‘Year’ data type from string to Date.
   Figure 10: Change data type

4. Import T7_T_pivot
   Inspect imported data to ensure data is in flat file format and data types are correct.

LFPR% tab

1. Create line chart
   Drag [Year] and [LFPR%] to Columns and Rows respectively.
   Figure 11: Create line chart

2. Apply filter
   Drag [Age band] to Filters panel, and check these 4 values: 15- 24, 25-54, 55-64, 65+.
   Figure 12: Appy filter

3. Apply colour
   Drag [Age band] to colour, change colours according to figure 13.
   Update ‘Automatic’ to ‘Line’.
   Figure 13: Apply colour

4. Update view
   Update view from ‘Standard’ to ‘Entire View’.

5. Add annotation
   I only want to highlight points on 2009 and 2019. Hence for points on

   • 2009: Right click on each of the points (4 in total) and select Annotate > Point. In the “Edit Annotation” panel, write “<SUM(LFPR%)>%” and colour font according to the age band colour done previously.
   • 2019: Right click on each of the points (4 in total) and select Annotate > Point. In the “Edit Annotation” panel, write “ <SUM(LFPR%)>%” and colour font according to the age band colour done previously.

6. Format annotation
   Remove borders and shading.

7. Rename y-axis
   Rename y-axis to “Labour Force Participation Rate (LFPR%)”.

8. Add title
   Add title: More Singapore residents across all age groups work. <font size 14>
   However, the increase in older workers' (55-64 and 65+) participation rate of 9ppt and 11.6ppt was triple that of younger workers' (15 - 24 and 25 - 54) of 3.6ppt and 3.3ppt! <font size 10>

Share of LP

1. Create new age band group
   Right click [Age band] > Create > Group.
   Group and rename according to figure below.
   Figure 14: Group age bands

2. Apply filter Filter out “Total”
   Add colour Drag [Age band] to colour.
   Check and ensure that colour is consistent with tab “LFPR%”.
   Reduce opacity to “60%".

3. Create stacked bar chart
   Drag [Labour force] and [Year1] to Columns and Rows respectively.
   Convert to percentage : Right click [SUM(Labour force)] > Quick Table Calculation > Percent of Total.
   Convert to stacked bar : Right click [SUM(Labour force)] > Compute using > Age band (group).

Figure 15: Create stacked bar chart

4. Change view
   From “Standard” to “Fit height”.

5. Rename x-axis
   Rename to “Share of labour force (%)”.
   Remove y-axis Right click > Hide field labels for row.

6. Remove grid lines
   Using Format Lines panel.

7. Add annotation
   Drag mouse pointer and select the 2009 and 2019 bars > right click > Mark labels > Always show.

8. Add title
   Add title : Singapore’s labour force gets older.The median age has increased from 41 in 2009 to 44 in 2019 due to the gradual shift towards older workers (55-64 and 65+ band) over the past 10 years.

Dashboard 1

1. Add title
   Add title : “The shift in Singapore’s labour force distribution and participation rate by age bands 2009 to 2019” with grey background, white text and font size 23.

2. Add commentary
   Using Objects > Text > drag to bottom of title and add:
   “Although labour force participation rate (LPFR) across all age groups has increased from 2009 to 2019, the significant increase in older workers' (55-64 and 65+) participation has shifted the labour force’s distribution towards an older labour force. This shift is due to multitude of reasons, namely aging population due to low birth rates, extended retirement age, longer average lifespan, etc.”

3. Add sheets
   Add sheet “LFPR%” to the left and “Share of LF” to the right. Retain one age band legend, place it at the bottom of “share of LF”.

4. Add source
   Using Objects > Text > drag to bottom left and add :
   “Source: Ministry of Manpower Singapore (https://www.mom.gov.sg/)
   Original report:https://stats.mom.gov.sg/Pages/Labour-Force-In-Singapore-2019.aspx
   The raw data: https://stats.mom.gov.sg/Pages/Labour-Force-Tables2019.aspx”

5. Add author
   Add text to bottom left corner and add text : “DataViz Makeover #1 by @suyiinang” align left.

5) Final visualisation

5.1 Snapshot of dashboard

Figure 16: Dashboard Full visualisation available at Tableau Public

5.2 Main observations

• Labour force participation rate (LFPR) has increased across all age bands since 2009. While younger workers (15 – 24 and 25 – 54) experienced a slight increase of 3.6ppt and 3.3ppt since 2009, the increase in older workers’ (55-64 and 65) participation was triple that of younger workers, increasing by 9ppt and 11.6ppt since 2009.
• Participation rate of 15 - 24 workers tended to fluctuate more than the other age bands.
• LFPR for older workers (55-64 and 65) seemed to have experienced a steep increase in 2011.
• The shift in labour force’s distribution was mainly due to shift from the 25-54 age band to the 55-64 and 65+ age band. While the share of labour force for the 15 -24 age band was quite stable (share of 8-9%) across the 10 years.
• Given that the financial crisis happened in 2008/2009, 2009 may not give the best numbers to use as a base comparison as is it historically lower compared to other years. As such, the increase in participation of old workers may be due to workers re-joining the workforce as the economy recovers, of which leads to the shift in the share of labour force towards older workers.

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