Skip to content

A Trip To The Woodshed (Or, “The Nitty Gritty of Data Visualization”)

800px-Schuppen_7235There are no pictures or visualizations here. Well, just the one here to the left – of a woodshed. I use it not per the Wikipedia definition, but rather per that of Wynton Marsalis. “By the time I was sixteen, I understood what the (wood)shed was about – hard, concentrated work.” Data visualization isn’t new, but today’s iteration of it definitely is a leap to a new plane. We should relieve ourselves of the pressure to execute all of the latest and greatest and, instead, take back the driver’s seat to test this and any new tool (especially the digital ones) for best application to the mission at hand.  Iterating and learning are the top priorities. Those are synonyms for “hard, concentrated work.” Jason Hahn of Grameen Foundation provides a case in point for diligent, first-hand learning …”‘shedding.” All best :: Eric

Can data visualization make a difference? Can it improve your programs? In the case of Grameen Foundation, can it make fighting poverty easier? It certainly can. We have seen examples of the impact of visualizations with Hans Rosling’s compelling (and beautiful) work. And, 160 years ago, John Snow demonstrated similar insight when he visualized cholera outbreaks.

Data visualization is important because of the way the human brain is wired. Researchers at the University of Pennsylvania School of Medicine estimate that the human retina can transmit visual input at about the same rate as an Ethernet connection. Further, we know that we remember certain kinds of data better if processed by our brains as pictures rather than as word forms.

At Grameen Foundation we are focused on eliminating poverty. We provide access to essential financial services and information on agriculture and health, assistance that can have wide-scale impact by addressing the specific needs of poor households and communities. We also develop tools to improve the effectiveness of poverty-focused organizations.

We’ve been collaborating with colleagues from Microsoft to use data visualization to better understand our work and improve our programs. We plan on using the results of this collaboration to improve the quality of our programs which empower the poor people we serve to reach their full potential.

Here is some of what we’ve learned along the route:

  • You don’t need to be a programmer to manipulate data visualization software. While it can be a bit complicated to learn, becoming a “super user” on such software as PowerView, PowerBI in Excel, or one of its competitors, it isn’t terribly difficult. In fact, that’s the power of these types of software programs is that they open up data visualization and reporting to all of us. You don’t need to call a programmer when you need a new report or view; you can just pull one on your own.
  • Knowing your plan (and your data!) before you start is critical. On our first joint project the Microsoft team spent a lot of time building a view that tracked the poverty levels of individuals over time only to discover that the records they were using were random samples over time: they weren’t connected to each other. The visualization was great but ultimately we couldn’t draw insights from it. A better written data dictionary and better communication from those collecting the data would have avoided this. In preparing data for analysis it’s a good idea to follow Abraham Lincoln’s advice: “Give me six hours to chop down a tree and I will spend the first four sharpening the axe”.
  • Your investment begins paying off immediately…by enhancing decision-making. Having the ability to analyze and visualize data from the beginning of a program makes all the difference in ensuring you achieve what you set out to do.  As part of our work we confirmed what others had figured out several months previously – that one of our health programs was not consistently collecting a key piece of information for an important metric.  If we had been using visualization we would have discovered the mistake earlier when the “unknown” column for that metric skyrocketed instead of further down the road.

Together with Microsoft we have taken the first steps in bringing data visualization to Grameen Foundation.  We’ve learned the utility of a great visualization program like Microsoft Excel, the need to really drill down and “know” your data before you start analyzing it, and the value that comes from making data easily accessible and understandable.  As we ramp this particular data skill we improve Grameen Foundation’s potential to better its use of data to serve the poor and poorest.

Your Turn

[poll id=’32’]