More thoughts by Brian Suda
Will big data eat itself? Big data has been the buzz word for a while now. I wonder at what point the term will become so overloaded it will collapse on itself? Maybe that process has started already. Big is relative, both in the size of the data, the size of your operations and the size of your tools. I’ll know the term is empty the day I go through the line at the grocery store and the checkout person swipes my loyalty card and mentions big data. “The Cloud” was so 2012, I fear for what the term of 2013 will be.
I work a lot with data, data mining, network diagrams and visualisations. One day it struck me as I watched someone in Central London get onto a bus with their luggage, this is a massive network of loosely joined pieces. The bus company runs what is best for them, the airport runs what works for them, taxi services fill holes where it is too far to walk. All these tiny services all pieced together create a vast network which covers just about ever square meter of this globe. Those London busses are on a constant move, looping around like little ants following a trail, sometimes one right after the other. To see a person get on a bus with a suitcase would seem like a strange event by itself, but in my head I knew that bus would get her one step closer to her destination. It might be 2-3 more busses, trains, tubes or taxis to get to that airport, but society has created a massive, unstructured, organic transport network that any citizen can take advantage of. What does our future hold as we make the jump from loosely joined physical transportation networks, to more loosely joined digital ones?
Everyone keeps raving about interfaces where you wave your hands around all Minority Report style. I wonder if we go down the road where that is the only way to interact with the system, we’ll have a limiting factor of who can actually use the system. If you don’t have 2 arms, 2 legs and 10 fingers and toes, the system might not work for you. At the moment, accessibility can be achieved through other devices. If a mouse is too hard to use, then keyboard support would suffice, or aural input and output. How come you never seen someone in the future in a wheelchair using these crazy new kinaesthetic interfaces?
There is a wealth of data locked up because existing government organisations are too scared to give it away or their previous business model revolved around the scarcity of the data. Mapping and GPS are prefect examples of information that once set free, multi-billion dollar business have sprung-up. The US is pretty liberal in what they give away after it has been created with tax payers’ money. Other countries are not as lucky. If you look at software to compute travel distances, route planning, address to lat/lon look-ups, these work much better in the US than in Europe and other countries. It isn’t for lack to talent or skills, but for the lack of open data.
I hate gamification. Gamification is unethical, exploitative and counter-productive. Alfie Kohn has written a great book called Punished by Rewards which outlines why extrinsic rewards can ruin the values you are trying to promote by devaluing them to points, stars, coins or credits. If you are thinking about adding gamification to your product, you should really, really consider the consequences. You might get a short-term boost, but any long-term value is lost. These are very important aspects to consider as you are either trying to extract the most money or work out of a player before they quit or trying to build up a community of dedicated fans for a lifetime. Slapping badges on things seems to be what everyone is doing, with detrimental affects. I implore you to think about how this will affect your community and fans.
After dealing with charts, graphs and data visualisations my opinions have softened. There are so many ‘right’ answers to things it becomes hard to see bad work. Even if I personally dislike a design, a good designer can back up their reasoning with sound advice and justifications. So what is left is bad design, built on bad choices. Some of those bad choices are habitual (that’s the way we’ve always done it), inertia (the tool makes it so easy to create these designs) or ignorance (we had no idea the problems with pie charts, everyone else uses them, how bad could they really be?). It takes a lifetime of teaching and training to change all three of these categories, but the designers need to be open to changing. You can never simply walk in and say, ‘this is crap’. That is the last thing people want to hear about their precious design, it is their baby, they did the best they could and you just came in and knocked it over. There needs to be a much better way. Some days I can do it, some days it is hard, but you can never criticise base on your personal opinions.
We tend to think that there is little innovation in the field of atomic charts and graphs. Sure, we see new data visualizations and infographics shared around all the time, but no one ever thinks about a new chart type. We’ve covered all the bases right? Line graphs, bar charts, scatter plots, pie charts etc. These are all the options in Excel and have always existed. That’s not true. The pie chart had to be invented, just like the bar chart. There was a world, pre-line graph. Looking back at history we only remember and use the winners, all the other charts and graphs that didn’t make sense have fallen by the way side. Even today, new chart types are always being invented, the stream graph, tree map, horizon graph… all are new and not widely known about. They aren’t an option in your chart software (yet). So it certainly seems like no new chart types have been invented, therefore it doesn’t seem like there is much innovation, but that’s far from the case. All these new chart types will be tried, tested and many will fail, not because they are bad (well some are), but more likely they fill such a small niche they never get popular support or traction. This is why when we look around we don’t see new atomic chart types all the time, they just aren’t useful in every day examples or if they are, the practitioners haven’t started using them enough yet. There is plenty of innovation and plenty of failures. If you look hard enough, you’ll find them.
Some days I wonder what the future of sports will look like. Many friends hate organised, group sports, I could go either way. But I do know that sports is big business and that technology is constantly creeping in around the seams. Sports like NASCAR, F1, American Football, and Cricket all are using some technologies to track the players or aid the viewers or both. Adding some virtual paint to explain distances or label players in real-time. The term ‘second screen’ is bantered around because we are watching TV with additional devices with us. The question then becomes how do we augment sports to get more value for the viewer, 1) without reproducing data, 2) still working without a second screen, 3) reaching beyond the simple stats, 4) using the additional device to all its capabilities. I think about these ideas in the context of sports because they are data-crazy. How many times have we heard stats about the last time team A beat team B in this type of weather when so-and-so was on the field and the coach was coming off a winning streak at the home stadium. You can slice and dice data any way you want and arrive at any outcome you want to hear. With that data in your own hands anyone can become that annoying stats guy, but at the same time give you a deeper insight into the game itself. How we relate data through our digital devices is ripe for disruption and innovation.
Just listen. After writing, that’s the most important skill you can always improve. I’ve been fortunate in my life to meet some incredibly famous and smart people. Those attributes are not always connected. The best times with these people have been not when I’m trying to brag about my accomplishments, but to simply ask about theirs, then listen. Everyone loves to talk about their ideas, projects, success and failures, some just need to be prodded. You know about your failures and successes, no need to waste their time talking about yourself. Simply ask them a smart question, sit back, listen and learn. You’ll be glad you did.
There is a probably apocryphal story about Abe Lincoln saying if you give him 4 hours to chop down a tree, he’d spend the first 3 hours sharpening his axe. It doesn’t really matter who said it, or what they were going to cut down. Many people ask me about getting into data visualisations, programming or working on the web. The questions usually revolve around, where do I start and how do I get better? It has been so long, I’ve forgotten how to get started — and to be honest, the way I got started and the right way to get started are probably two very different things. I can tell you how to get better — that’s easy. You need to keep an open mind and practice and practice. That final, beautiful design you see probably has more hours than you can count getting to that point. If you want to execute on a job well done, you need to put in a lot of time practicing and sharpening your tools, both mentally and physically.
I love the ‘Everybody votes’ channel on the Nintendo Wii. If you haven’t seen it, go look it up. It is probably one of the best examples of an incredibly simple prediction market all beautifully wrapped-up as a throw-away kids game. Experts toil over game mechanics, exit polls, statistical methods and yet a simple question, asked twice; once from your point of view and again from your neighbour’s makes for an incredibly simple yet robust result. We have a lot to learn from this to improve our data gathering and reporting. Every time I see it, it makes me smile.
When I wrote this, 3D printing was becoming annoyingly overhyped, so by the time you read this I can imagine your disgust already. I get the feeling that people who have grown up post-digital and work in a digital world are yearning for something more physical and tactile. A touch screen that can morph to anything is an entrance into a world where just about anything goes, but at the same time we also want our fancy pens and notebooks with leather-bound cases. There is certainly the pull between atoms and bits, we can rearrange atoms with our bits and our atoms control and save our bits. What will happen when we make the jump from laser cutting plastics, wood and paper and printing plastics and chocolates to actually assembling DNA? We do that now, people have made programs using proteins and DNA, but what does that even mean for our future?