Great interview with Stephen Few, founder of Perceptual Edge who specialise in data visualisation in simple, practical ways to help people to understand and communicate the important stories to be found in data. We interviewed Stephen about his latest book, Signal, and also about his upcoming visit to deliver his workshop in Dublin to an Irish audience on October 6th to 8th which is hosted by the Analytics Store @analyticsStore.
Who is the workshop aimed at?
This course is for anyone who works with quantitative business data as part of their job. Some key titles include:
- Analytics Professionals
- Business Intelligence Professionals
- Reporting Specialists
- Data Scientists
- Business Analysts.
These workshops are for a limited audience (max 70) to allow engaging with the audience and taking questions during the workshop break out sessions.
What key takeaways can attendees look forward to getting out of the workshop?
Both courses that I’ll be teaching in Dublin—Show Me the Numbers and Now You See It—focus on the fundamental data visualization skills that are needed to analyze and present quantitative data visually. Even though these skills are fundamental and essential, relatively few of the people who analyze and present quantitative data have ever been trained in them. This is often because of a mistaken assumption that data visualization is something you are automatically capable of doing if you know how to use a software product that produces charts. This is far from true.
Knowing how to create charts in Excel, for example, does not mean that you know how to select an appropriate chart type and design it in a way that tells the story clearly and accurately. Analyzing and presenting information visualization requires an understanding of concepts, principles, and practices that must be learned. The good news is that these skills are easy to learn, but they don’t come naturally.
A large part of the book, Signal, is about reading the data correctly, with only a relatively short section for part 2 ‘Watch over the land’ – is this level of diligence still necessary?
Part 1 of Signal, which comprises most of the book, teaches the skills that are needed for exploratory data analysis (EDA). EDA is what we do initially to become acquainted with a data set. When done well, we examine the data from every useful perspective, resulting in a thorough understanding of that data—a mental model—that is needed before we can do anything else useful with it. If we try to answer specific questions about a data set without first becoming familiar with it in this way, we will often draw the wrong conclusions because we lack sufficient context to interpret what we find. And, more central to the book, Signal, we cannot begin to separate signals in our data from the noise without first understanding its routine behavior.
Most signals are unusual events that are not random. Until we understand routine variation in our data, we have no means to spot when something unusual is happening. Most of the work that’s required for effective signal detection is preparation. Abraham Lincoln once said, “Give me six hours to chop down a tree and I will spend the first four sharpening the axe.” Exploring the data from every meaningful perspective to become intimately familiar with it what we do to sharpen the axe. Most people who are tasked with data analysis are wearing themselves out swinging dull axes.
What future trends in data analysis are you excited about?
We, including experts, are notoriously bad at predicting future trends, so I refrain from doing so. What I will do, however, is say what I would like to see in the future. More than any other one thing concerning data analysis, I would like to see a shift in focus from expecting technologies to save the day to relying primarily on human beings to address our analytical challenges. Data sense-making requires the human brain. Technologies can at best assist us, doing things that computers do well but we don’t, such as fast mathematical calculations. Technologies can help us work around the limitations of our brains, such as by placing a great deal of data in front of our eyes in visual form to expand the amount of information that we can handle at once beyond the limited capacity of working memory.
Technologies, however, cannot do our thinking for us. Our brains are equipped for data sense-making, given the proper training. For this reason, I would like to see much more attention given to the development of skilled data analysts rather than to the acquisition and implementation of technologies. No analytics technologies will make a difference unless they are being used by skilled data analysts. Investing in the development of human beings isn’t nearly as sexy as investing in over-hyped technologies that promise salvation. It’s hard work and it takes time, but it’s the only real solution.
What tech do you wish was already invented to make your life easier?
Most of the technologies that excite people today don’t actually make our lives easier. We’re living in a time when many technologies are pursued and celebrated simply because they seem new, cool, and innovative, not necessarily because they improve our lives. To be honest, I don’t find myself longing for specific technologies that don’t already exist. Instead, I find myself constantly wishing that the essential technologies that potentially add value to our lives were better designed. Bad design is pervasive.
A good example that often annoys me as I travel is found in showers. I’m a fairly smart guy, but I’ve stood in showers for up to a minute trying to figure out how to get the water to come out in the volume and at the temperature that I desire, sometimes getting scalded or frozen during the process, because the controls are unfamiliar and confusing. So, to answer your question, rather than wishing for any new technology in particular, I wish that we would start focusing more on creating only those technologies that are really useful and taking the time to design them well. Our lives would be so much better if we would.
What are your strategies for managing a work/life balance in an ever more connected world?
There were times when I struggled to maintain a healthy balance between the personal and professional parts of my life. At various times during my career in Silicon Valley, I put in 80-hour weeks because that’s what everyone in high tech thought they must do to survive. In fact, that was the clear message from our employers. Those times were stressful and less productive than they would have been had I worked less but smarter. Today, I work only as much as I want, which at times is quite a bit, but that’s fine because I love the work and am able to do it precisely as I see fit. I no longer draw a firm line between the personal and professional parts of my life because my work is an intimate part of me, no longer just something that I do to earn a living.
The “ever more connected world” that we live in today has little effect on me because I don’t participate in it. I don’t engage in social media, unless you put email in this category. I avoid Facebook, Linked-In, and Twitter, and I even do my best to refrain from texting. I try to train my friends and colleagues to reach out to me via email rather than by texting because email isn’t disruptive or distracting. When I need to concentrate, which is often given the nature of my work, I turn off email, which leaves nothing to interrupt me, except for my dogs who occasionally ask for attention.
The work of data sensemaking requires concentration. Contrary to popular opinion, our brains are not capable of multi-tasking. We can only do one thing at a time that requires attention. People who think they’re multi-tasking are actually serially tasking, shifting back and forth between activities, which undermines their productivity. To concentrate on our work, we usually need a quiet, comfortable place with no distractions. Even though this is contrary to the way that many workplaces are currently designed, it is essential to concentration. For tips on reducing distraction, I highly recommend the book The Distraction Addiction by Alex Soojung-Kim Pang.
In Stephen’s own words in the books Epilogue. Zen Stewardship,
p195 “Our world is full of noise and it’s getting noisier everyday”
Any readers wishing to find out more about The Analytics Store, see the website. See here for information on Stephens workshop in Dublin in October, pricing & booking information.
This is Stephen’s first time to deliver one of his workshops in Ireland, delegates are travelling from all over Europe to see him. The workshop is based around two of Stephen’s books, “Show Me the Numbers: Table and Graph Design” and “Now You See It: Visual Data Analysis” Each delegate will receive a complete set of Stephen’s books, including Signal