Learning Ecosystems

This post encompasses a few thoughts on how the future company might learn. It focuses on 4 sections, firstly thinking about an eco-system and then seeing what this could mean for learning in terms of models, systems and culture.

The beauty of an ecosystem is that it is so complex but it still works. It is constantly changing but always exists. Rivers meander, eventually creating new shortcuts which bypass an old route. It creates an oxbow lake as a by-product, but the river never stops and the oxbow lake eventually disappears.

My thinking is simple. If we can build a great learning ecosystem, it will behave just as the river does. It will always exist and always try new paths. It will create by-products which may cater for new habitats and probably will eventually disappear, but the ecosystem itself, like the river, will never disappear. So how can we build this eco-system?

1) Learning from models

I think an important part for any company has to be the fact it can learning from others and not the other way round. In this theory if a learning company is doing just this, learning, surely it will not fail to see new opportunities, new innovations and make great judgements. I’ve been thinking how we can learn from others at an early stage and I think I have some early answers. I have noticed there seems to be new masters programs popping up. For example: Here and here. They might give us clues about their intention. For example on Keios website, the new Master program aims:

To educate creative catalysts and leaders who will design new possibilities in the world through the synthesis of multinational perspectives and approaches.

More and more people with such practical creativity are starting to emerge in society, for example, as Chief Creative Officers (CCO) who create design innovation-led business strategies.

They seem to predict there will be more design leaders and that a multinational approach is crucial  To my their foresight must carry a lot of weight. Especially compared to our individual foresight. I am sure they have evidence of this, that was discussed by experts in the field and they saw a need. I think any sorts of programs like this can tell us a bit about the near future.

Of course, to have fairer judgement I think we shouldn’t just consult the academic realm. I saw this list: The 100 most creative people in business 2012. These people might have different or similar views. I’m not sure exactly, but what I am sure is about the ability to learn from their examples and even meet them. But learning might make us too safe. We have to make sure we are un-learning too and trying to test assumptions. So another question might be how we can unlearn without risks?

2) Systems

The learning models could just a little part of the whole learning eco-system. I think the eco-system can be made up of many little systems. I saw this example of the UK government testing their own app: David Cameron tests real-time economic data app on iPad. But although the example is new, the idea is not. Barack Obama has successfully used systems in his campaign, from backend data which even informed the decision to get George Clooney for the campaign: Inside the Secret World of the Data Crunchers Who Helped Obama Win. I have also read that the campaign used Nationbuilder and in essence much had their own social network which volunteers could see how other volunteers were doing. This progress helped bring a competitive side to signing up people to vote.

And there could be so many other systems in place to create the learning-ecosystem. It does not mater if one is more successful than the other. It is their combined efforts which make one powerful effort. One for collecting learning material and sharing it. Sharing skills or finding them. Tracking and finding other designers or materials.

3) Culture

The last major point I’d like to make is on culture. Above is Nate Silver, a photo found by the internet on election night. Why is he wearing a wizard hat on election night?

He was celebrating. He pretty much beat all the political pundits and predicted every state correctly in the recent US Election using data. He became a celebrity appearing on Jon Stewart’s “The Daily Show” twice in three weeks and appeared on many other TV shows and blogs. This wasn’t a fluke, he predicted 49 out of 50 in the last election and the state he predicted wrong was 0.5% out. Impressively, when you think about it, he had no advantage in private information. He used public polls, the same data we could get and used statistics and own judgement to make his model. It makes me wonder if we can be using the data that’s already out there more logically to make decisions. It was great to see him on this journey.

But the most interesting things I find about him is the way he conducted himself and how he started. On election night when it became clear Obama was winning he tweeted: “This is probably a good time to link to my book,” he’d tweeted at 12:13 a.m. — the closest he came to gloating. He impressively and modestly changed the game for political pundits, many of whom doubted him and even had bad things to say about him. He created a new approach to politics.

And only recently I found out he used to have this blog: The Burrito Bracket. It seems this is how Nate Silver started. Blogging about rating Burritos. His methods were a lot simpler and the topic much less controversial. It makes me think we can start out small, start out fun and even when we get things right (or a bit wrong just as Nate Silver has done) we can always be modest about it, learn and continue.


About duaneharrison

Currently a final year student at the Glasgow School of Art studying Product Design. After having varied but relevant experience in five different countries, I aim to draw from my education and explore how product/services are established and how well they can fit into a whole ecosystem to provide a special experience.

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