A colleague told me about Makeover Monday, and ever since, I’ve been interested in attempting a “Makeover” of my own.
The latest data published was Week #46 November 11, 2019 – Youth and Adult Literacy Rates. This sounded like an interesting topic to learn more about and I decided to take the plunge.
Although, I wasn’t going to submit a final work for review, I thought it would be worth the effort to go through the creative process. This included time-boxing the work to a maximum of 4 hours.
Below is an image and link to the original visualization for the Makeover published by UNESCO:
After a review of the dashboard, it became clear that this was intended as an exploratory tool on the global literacy rate.
I thought of a couple people who may find a tool like this useful:
- Governmental analyst; to help inform policy decisions
- Supporting role at an NGO; advocating for funds, resources and campaigns
A downside of an exploratory tool is that it does not efficiently provide an actionable insight for an end user to make an informed data-driven decision.
For this reason, I focused on creating an actionable insight told with simple data viz charts.
The insight –
Recommend to increase health and educational investments targeting female youth in Afghanistan and Pakistan.
Now, let me explain you how I got to this outcome.
As a start, I recognized the strategic goal of the United Nations (UN) Sustainable Development Goal (SDG) for youth and adult literacy.
By 2030, ensure that all youth and a substantial proportion of adults, both men and women achieve literacy and numeracy.UNESCO SDG
A few thoughts on this goal to aid in the segmentation effort:
- Clearly identified youth as important; target of all or 100%
- Specific mention for both men and women to equally achieve literacy
- Target to reach the goal is by 2030
Side Note: I find it most effective when data visualizations are connected directly to the why or purpose, which is why I think this is a good place to start.
In my fictional case, an end user (a leader or decision-maker) needs to know if we need to increase or maintain current investments to achieve the goal.
Now, a look into the data and approach –
Instead of creating a dashboard through Tableau/PowerBI, I used Data Wrapper. Data Wrapper is commonly used by journalists to embed data viz directly into their stories and content. This was my first time using this tool, and felt that it was a good fit.
I asked myself three questions to help structure my approach:
- Current: How are we currently tracking in relation to the target?
- Trends: What is working well and not so well with prior investments?
- Future: How can we make more productive investments to lift the literacy rate?
How are we currently tracking in relation to the target?
By segmenting age and gender, I identified female youth as the opportunity aligned to the UNESCO goal. Youth has a higher target in the goal, than adult.
Currently, Central and Southern Asia as well as Sub-Saharan Africa are regional opportunities for the female youth literacy rate.
What is working well and not so well with prior investments?
At this point in the discovery process, it’s helpful to have opinion from a stakeholders or subject matter experts to add context to the data and fill in knowledge gaps on the topic. For instance:
- Did investments cease in 2012 and after 2016? Or, what drove an increase in 2011 and 2013-2016?
- Is there incomplete data or data collection inconsistencies that speak to fluctuations in the rate?
As an alternative without context of the data, I grouped the two regions to compare against the overall.
Then, took a look at a 8/year CAGR growth rate across the regions. I found that while Central and Southern Asia was down slightly, Sub-Saharan Africa was just above 0.
Since the growth rate trend for Central and Southern Asia was down slightly, a next step was to explore this region at the country level to identify opportunities.
How can we make more productive investments to lift the literacy rate?
At this point, I’m able to visualize the data in a map and identify the specific countries that have a comparatively lower than average literacy rate.
For sake of time, I did average the rate across all the years due to lack of data. I’m not sure if this was caused by data collection issues or other geopolitical factors…
With the available data and time, I’ve reached an actionable insight by identifying an opportunity among this segment:
- Gender: Female
- Age: Youth
- Region: Central and Southern Asia
- Countries: Afghanistan and Pakistan
By focusing on this targeted segment, it will help provide for a more productive investment to lift the global literacy rate aligned to UNESCO’s strategic goal.
Some further thoughts on next steps –
Since, this insight work is entirely based on trends and assumptions. An example of how I would look at continuing this work is testing the hypothesis of a strong correlation between literacy rate and family size.
Do reproductive health education investments help improve literacy rates? My understanding is that child rearing is an opportunity cost with educational opportunities for the female population. Especially, within areas where there has been turmoil/war, and reproductive health and birth control options may be limited exacerbating the issue.
Another idea is to look at forecasting health and educational investment needs for this segment, which would require sourcing and matching in other data (demographic, population, etc.) to tell an interesting insight.