In the most recent issue of the Harvard Business Review we saw an article that we just had to read: Visualizations That Really Work.
Being pretty obsessed with all things data visualization everyone in the office read the article and we were immediately impressed with everything that we read, but we also had a few questions and insights of our own that we could share.
We have been at this data visualization game for pretty much one reason: we realized a long time ago that using data to make smarter decisions and improve your business was going to be a key competitive advantage in the future. It’s just nice to have some third-party confirmation that we were right all along.
by The VisualCrew
We’ve written a lot about the amazing human visual system, and what a shame it is that we don’t use it more often in data visualizations.
But frankly that is just one small (albeit awe-inspiring) part of the amazing, interconnected system that is your body.
When you think about it, your body is the ultimate source of streaming data. It is constantly providing you with feedback: it tells you when it’s hungry, thirsty, tired, cold, hot or doing just fine. This data is streaming from dozens of different sources and is processed and analyzed by the best data analytics processor in the business: your own mind.
Today we’re looking at different, innovative ways that clever people out there have come up with to visualize the data that’s coming from your own body… probably right now.
It all started with an article we found about robot shepherds on large Australian cattle farms.
As with any new implementation of technology, the cattle farmers had a problem. According to the article, on a particularly large cattle farm the cows were too spread out for the ranchers to adequately monitor them and they were losing many animals to injury and illness as a result.
The robot shepherds used advance thermal imaging and other methods “to detect changes in body temperature and walking gait” in an effort “to improve the quality of animal health and make it easier for farmers to maintain large landscapes where animals roam free” according to the robot’s designer.
That got us thinking: what kind of data does a cow generate?
At VisualCue we have a couple of specialities: industries that we have worked with time and again and have consistent success in implementing amazing data visualization solutions for them. Sales, marketing, operations and contact centers are just a few.
But one of the industries that often yields the most amazing visualizations and consistently sees the highest return on their investment into a data visualization platform is logistics: the business of moving people and material from one place to another. We have implemented data visualization solutions in dozens of logistics companies around the world.
So believe us when we say that whenever someone moves, whether it’s themselves or a physical asset, there is a lot of data generated. And where there’s data, there’s cool visualizations.
It’s one of those clichés everyone knows: you ask someone wise for answers and they respond with “you should first learn to ask the right questions.”
This might cryptic and confusing but, believe it or not, there is wisdom in learning to ask the right questions: asking the right questions can lead to the right answers. But if you don’t have the right questions then you could be spinning your wheels endlessly searching for the answers to questions that might not even lead to the most benefit.
There is something undeniably amazing about seeing data stream at you in real time. Something about seeing the numbers change really hits home the fact that data is not just an abstract concept but a numerical reflection of real things happening in real time.
So why is it that sometimes we forget that data reflects reality? because numbers in a spreadsheet are so abstracted: so far removed from the data they represent that it’s easy for us to disconnect them in our minds. Real-time streams help bridge that gap, but not entirely.
That’s why this week we are focusing on data visualizations that not only are updated in near real time, but also directly represent the thing they are measuring. It’s the best way to realize that streaming data is like seeing the world as it happens.
It’s a pretty common trope in media today, probably because it’s such a romantic figure: the lone wolf. Just thinking about it conjures up sentiments of independence, ferocity, determination and power. The lone wolf is master of all he or she surveys, successfully carving out a place of dominance in an unforgiving wilderness.
What a lot of baloney.
Anyone who’s read Kipling’s The Jungle Book will know that the strength of the wolf is in the pack, and that without their pack a lone wolf would starve before too long.
But the idea of the lone wolf is even more pernicious when you take that mentality and place it into a business scenario. Yet, unfortunately, that is precisely what we are creating with sales representatives when we evaluate, judge and compensate them based on only one or two KPIs. An entire sales force of lone wolves, each of them slowly starving to death.
Languages- we all speak them. A lot of us speak more than one. We read it, write it, speak it. Many of the planet’s smartest people are convinced that the languages we speak inherently alter our perception of the world around us.
Given how important languages are it’s little surprise, then, that we have been studying them for a long time. We’ve classified, codified and put them in dictionaries and with all of that work, of course, comes a lot of data.
Using data to study language, whether it’s spoken or written, has picked up speed in recent years and we’ve gathered some of the best ways we’ve found to gain insight into the languages we speak.
In the October 1987 Journal of Marketing an article appeared that has since come to inform, in very large degree, how modern organizations manage and motivate their sales forces. The article, written by Erin Anderson and Richard Oliver, introduced the world to the concept of “control systems.”
What they discovered should change the way you think about how you manage your sales team, and it should. They discovered two main approaches to organizing, motivating and compensating a sales force and, as usual, both systems are not created equal.