Anyone with young kids will marvel at their ability to spend hours drawing. I’m about as far from being an artist as you could find. My ability to draw anything is frankly pretty embarrassing. It’s not that my kids (7, 5 and 2 years old. To be fair, 2-year old is some way off) are gifted either, despite how hard I try to convince myself. But how they love it. The feeling of making something. How they love to create. The lack of fear of failure. The sense of satisfaction when they give their masterpieces to all and sundry. Imagine a world where working with data felt as nice, as free, and as appreciated by the receiver.
For most people, data work is hard work. It is miserable. Most don’t get out of bed and think – “Wow, finally a chance to get into some good old data cleansing. Oh, how much fun to finally have the time to build some organisational analysis.”. I am totally convinced that every single reader of this post is now finally reaching the conclusion that I’ve finally lost the plot. That in fact, I am actually destined for the cuckoo house. To even dare to suggest it could be anything other than the most painful of all exercises, and should be left to contractor database people or outsourced to a part of the world where the alternative is a textile sweat shop.
But, I’m not mad. Or at least, not totally mad. We have finally found a way to make working with data fun. To make it feel like you are painting with it. The trick is universal drag & drop; it is parking lots; it is turning our filter control into a data cleaning machine. In order to make something really enjoyable, a state of flow needs to be achieved. Flow is characterised by absorption, work enjoyment and intrinsic motivation. For this to occur, there are a number of pre-conditions as described by the seminal work of Csikszentmihalyi.
And now I’ve spelled his name there is no way I’m going to go into detail about flow. Experienced readers of this blog will know all about it. The point is you need immediate feedback; no worry of failure; a balance between the challenge and your skill levers with clear goals. Once the pre-conditions are achieved: action and awareness merge; distractions are excluded from your consciousness; the activity becomes “autotelic” or done for its own sake. It becomes fun in the same way that playing golf or the piano or a game of rugby becomes for those that are passionate about those things.
We achieve this by making the visual environment in which you explore the data; in which you gain insight from it also the same environment in which you manipulate the data; clean the data and add to it. We make it instantly easy to see where there are issues AND even easier to fix them. The best example of this is the filter control.
You can see, instantly, that the data is messy Female and female for “female”.
You can point to the errors. Those ought to be over there. And that instinctive reaction is what we want to capture. Your instincts are right. You just take all that data from where it’s wrong and put it where it ought to be. You drag, you drop, the whole group in one go. And hey presto – it’s fixed. We want to help you trust your instincts on data and see instantly whether you’re getting it right.
So just drag the 2 wrong elements directly onto the right one and hey, presto, it is fixed.
Here’s another example. You want to explain who does what. Mathematically, that means mapping people onto their roles. But you don’t need to think of it like that. You want to see who the people are, see what the roles are and simply connect those people to those roles. And if you colour the data in by a dimension, and one of the roles isn’t coloured the way it should be, you simply drag them on to the right colour. And it’s done. The place you see the data is the same place you fix it. Intuitively and directly. Fixing it up actually becomes a pleasure.
Another example is the ability to map all roles onto a N x N grid. See where each person sits, move them about and have all the data instantly updated. In addition, you can colour each element by another dimension, and drag these onto a colour as a way of changing it.
The point is, all elements are drag-able and can instantly be updated. All elements can be presented in all manner of shapes and sizes on what is a free flowing canvass. This functionality is only becoming a reality in v2.10. I only saw it for the first time today and just needed to write about it. It has blown my mind. It is such fun. It is so productive. I believe thousands of souls (if not millions – but I shouldn’t get ahead of myself… too much) who currently hate working with data will just find it a doodle. They will generate so much insight and impact, it will be one of those things they actually enjoying doing at work and even outside work. Chris Barrett, OrgVue’s product director, told me today that you can “Paint with Data”… oh how on the money he is.
Latest posts by Rupert Morrison (see all)
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- Is workforce planning supply chain management? - June 19, 2014