By Trevor Davis FRSA, IBM Distinguished Engineer, November 2017
A good friend of mine who studies the nature of innovation maintains that for something to be innovative it has to be novel, useful and with a design that is somehow representative of the times. So the interesting questions for me are “how do we characterise the times we live in?” and “what does that tell us about innovation going forward?”
Big Data, whether it is from social media, the Internet of Things (IOT) or other sources, can tell us a lot about the zeitgeist. For example, for the large food and beverage companies I work with so often, social media analytics tells me that people want greater personalisation in marketing communications. For scientists, Big Data is providing insights into how we are impacting our biosphere.
Read more: Nov. 13, 2017 Trevor Davis is giving a key note at The Forum for Strategic CSR meeting on Big Data, see full program here
If I had to briefly characterise the times we live in I would say “volatile, uncertain, complex and ambiguous” or VUCA. Hence, I think there are more important uses for Big Data than mining Kim Kardashian’s latest Instagram post. Of course, I am referring to the United Nations Sustainable Development Goals. Surely Big Data has something to offer here, and therefore our focus needs to be on sustainable innovation informed by Big Data rather than following simple commercial imperatives or whim of the crowd.
For example, it seems to me that we are moving from a period where we had very little data about the impact of the choices we make in designing new products to one where we may have too much information for human beings to make sense of. I know there is much anxiety about the impact of artificial intelligence (AI) on areas such as employment, but I am certain that AI is the only way we will truly be able to make sense of an always on, always interconnected world.
Read more: Forum for Strategic CSR
Imagine you are the designer of the new food product and embedded within the product and packaging are sensors that follow that product not just through the value chain but through the human gut and back into the ecosystem. Perhaps those sensors are eaten late in their life-cycle by fish which in turn are eaten by a bird which then re-enters the biosphere anew after the bird dies. Just imagine how much data that produces!
It is precisely this scenario that I think we need to prepare for: AI powered by Big Data helping human beings to make more sustainable choices about innovation in a VUCA world. Behavioural economics has shown that there are limits to the rationality of human beings and that we are quite willing to make choices that harm us: perhaps Big Data and AI can help us escape some of the traps we have made for ourselves which force us to trade profit against social and environmental good. Perhaps we would be more effective in meeting the SDGs if we were guided by machines that could map out poverty from satellite data or outsmart poachers using IoT and machine learning.
Read more: IBM Big Data Analytics
Take another example. It is frequently stated that we will not be able to feed the planet without radical change to food production and distribution systems. Big Data and AI gives us the opportunity to do something about that through real-time resource allocation, hyper-local analysis of demand and micro-targeting of distribution. You can already see examples of what could be achieved by looking at apps such as FoodCloud which redistribute retail and restaurant surpluses to the needy via charities.
The availability of cloud computing, the advances in application of deep learning techniques to pattern recognition and emergence of breakthrough technology such as blockchain have already put in place the foundations for the next leap forward in application of Big Data to business and societal challenges. Blockchain for example is already starting to revolutionise the way that finance works, not just opening up the financial system to those previously denied access but also generating vast amounts of new data about consumption, supply chains and the flow of capital. So how will we make use of all of this for sustainable innovation in the future?
First of all I believe it requires a rethinking of what we think of as innovation best practices-we should be looking for the “next practices”. Historically innovation has grown out of invention, progressing to market through a series of stages and gates that allocate capital and expertise. It’s top-down, slow, and tends to favour the interests of a limited number of stakeholders. What if we could turn that model on its head, make the model more inclusive, faster and less prone to trading sustainability off against short-term profitability? This would be a model of hackers and makers, of co-creation and crowdsourcing, a model of value trickling-up from all of the people involved, rather than trickling down from major corporations, government and NGOs.
Could such a model really work? This brings me to my second point: governance. For such a model to operate in support of sustainable innovation and the SDGs, there is a growing belief that we need Fourth Sector beyond the private sector, public-sector and not-for profits. As an example, there is already a Fourth Sector development initiative from the World Economic Forum for example which focuses on development of for-benefit enterprises that go beyond B Corporations and the like. What shape will these organisations take? Greater employee ownership? More focus on social entrepreneurship?
For me, Big Data is central to sustainable innovation. Big Data offers the prospect of new business and organizational models founded in data science to act on financial and non-financial metrics in ways that truly reflect the impact they have on economic, social and natural systems. Big Data is also fuelling AI in a direction that augments human decision-makers and opens up previously hidden options for sustainable innovation.
Ultimately, Big Data is an unending resource that can be harnessed for self-sustaining, scalable solutions to some of our greatest challenges.