This is the opening presentation I gave at Open Innovation in Action, a major conference for the biotech and pharma sector. It was held at the UK's first open innovation biomedical campus, Stevenage Bioscience Catalyst, in November 2012. As the first presenter I had two objectives - giving a definition of open innovation to set the tone for the rest of the day, and sharing some thoughts on the future of open innovation in the bioscience sector.
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3. Connectivity
The root of all
innovation.
Connectivity
Collaboration
Open
Open Takes innovation where
Innovation
Innovation Collaboration
it needs to go.
Challenge Challenge
Turns a good idea into a
great one.
19. Thank You
Twitter: @clare_oneill
www.original-ventures.com
Notes de l'éditeur
First of all I’m going to get something out of the way right at the start, and that’s a definition of Open Innovation (OI). We don’t want to get too hung up on definitions, because today is about moving beyond that and learning from other people’s experience of OI.
I like to think of it as a form of collective intelligence across multiple organisations. It is often characterised by: (1) extensive or even radical use of connections and networks to share ideas, knowledge and expertise. The classic activity here in OI is a crowdsourcing – an open innovation challenge to anyone who’s out there to come up with a solution to a specific question. (2) In-house and outside ideas and knowledge being integrated – this is not just about hoovering up other people’s ideas. (3) The nature of relationships are more like collaborations than supply-demand transactions, and (4) all this means that new business models are sometimes needed to help to maximise the value of IP and other assets There are examples coming up, but in general: if a company is keeping all its R&D in-house, it’s not doing open innovation; if it is using crowdsourcing to gather ideas, or sharing data for free in order to stimulate the next stage of research, then it is doing OI. There’s always a certain amount of subjectivity in how we define any type of innovation, but this is our starting point for open innovation.
I want to expand on 3 aspects of working that I believe are fundamental in OI. (1) CONNECTIVITY: we’re inspired by what we see others are able to do, or not able to do, and we can translate problem-solving methods from one sphere of work to another. People who are connected with several different, diverse networks are at higher risk of having a good idea (ref: Prof Ron Burt at University of Chicago). (2) COLLABORATION: Innovation is a contact sport (Annalee Saxenian). One person might have an idea on their own but it takes a collaborating team to turn it into a product – researchers, investors, advisors and so on. The better connected we are, the more likely we are to find the right collaborators each time. (3) CHALLENGE: Firstly, open innovation challenges to generate ideas. Secondly, the fact that if you’re connected to a diverse network then an idea can be challenged from multiple angles, and that’s how we turn a good idea into a great one. This is all about increasing your risk of having a good idea and making it work.
Now that companies are using open innovation, so what? What different does it make? Other sectors have seen the benefits in terms of improved innovation success rates and increased revenues. Well-known examples range from gold-mining to space tourism, from toy building bricks to Formula 1 software algorithms being translated over to national air traffic control systems. And in bioscience we have the early adopters already making bold moves into open innovation methods.
Procter & Gamble: famous for radically changing how many of their ideas for new products came from outside the company, and doubling their revenues in the process. Lilly: a strong leader on OI - a current example is their Open innovation challenge for new TB drugs. AstraZeneca: making 22 key compounds available free of charge, with clinical data, to researchers in a very interesting partnership with the MRC. GlaxoSmithKline: with their Tres Cantos open lab and other initiatives (ref Patrick Vallance’s presentation). Antabio: this is an antimicrobials start-up that has successfully used crowdfunding as its first round of finance. Then there are the multi-partner collaborations where many big pharma get together to share data and expertise at pre-competitive stages – Transcelerate; Pistoia; and SGC which determines 3D structures of potential drug targets and openly publishes the results. Stevenage Bioscience Catalyst: literally and metaphorically, the door that normally exists between big pharma and biotechs is now open on this campus.
OI is not a panacea. But it is underused throughout the sector – and that means that opportunities are being missed.
There will be a great deal more open innovation in the bioscience sector – the train has left the platform and it’s moving faster. Open Innovation will transform problem-solving in this sector and that will play an important part in maintaining viable businesses and affordable medicines. We will see an expansion of crowdsourcing not just aimed at researchers but also aimed at customers, patients and carers to help identify unmet healthcare needs and possible solutions. We will also see open innovation increasingly being used as a tool to support cross-sector, multidisciplinary innovation as technologies converge.
Here’s an example from the digital sector just to make a point about the future in bioscience. This is from Bran Ferren of Applied Minds. Bran talks about a presentation he seems to have seen many times at digital conferences. The speaker shows a graph like this black line to represent the digital revolution – it’s the number of people in the world who own a mobile phone, the number of bits of information moving around the world every day, and so on.
The speaker will then add the red line and say ‘that’s your business’. And whatever the units are on this graph, you know that the point where the lines cross over isn’t a good place to be.
Then the speaker will say we’re in trouble because where we are in this time line is here (blue line 1).
Then a member of the audience will say “That’s nonsense. It’s all OK because we’re really at this point in the timeline” (blue line 2).
Then a much younger member of the audience will say “You’re all wrong. Where we are is here (blue line 3) – all your companies are dead already, you just don’t know it yet.”
But a real visionary will say that we are still near the start of the digital revolution (the blue arrow). The past 20 years have seen an utter transformation of work and leisure – but we’re only just starting to realise what we can do with big data, and things like quantum computing are expected to be a practical reality on consumer goods in 30-40 years. One such visionary is Alan Kay, the originator of one of my most favourite quotes on innovation: “The best way to predict the future is to invent it.”
That’s enough about digital – here’s a new graph, a completely different one. It’s open innovation in bioscience. It’s the number of big pharma using crowdsourcing to answer a research problem; it’s the number of biotechs reaping the benefits of working with big pharma in that way. More cynically, it’s the number of companies putting out publicity about how they’re doing open innovation, when in fact they’re not doing anything new and probably won’t until most of their competitors have done it first. But back to the positive stuff: it’s the number of start-ups looking at equity crowd-funding for early stage finance; it’s the number of multi-company alliances that share data and knowledge at pre-competitive stages; it’s open innovation in bioscience. Now, there’s another line on this graph, and that’s your company....
It starts up here. So where does it go next?
But of course we are right at the start of this timeline. It’s true that 10 years have passed since one or two of the very early adopters starting ringing the changes, but for the vast majority of the bioscience sector, open innovation is a new thing in the experimental stages. That means it’s up to you: you get to decide where that red line goes. For your own organisation that red line will depend – more than it does today - on how much you lead on open innovation, and how much your organisation improves its skills level on collaboration, on idea-spotting, and exploring the very boundaries of the company to see what competitive advantage can be found by doing things differently.
Because the truth is that innovation is a mindset more than a process. If you look at the really innovative companies, it’s the corporate and individual mindset that really makes them buzz. It’s about the way you work; the nature of the collaborations you’re prepared to have; the way you spot opportunities; the way you solve problems; the way you manage change; the way you fail and learn from it; the way you make things happen. This is true of innovation, and doubly so of Open Innovation. So bearing that in mind, I’m going to leave you with a question.
What’s your risk of having a good idea and making it happen? What are doing today, and tomorrow, to improve your risk of having a good idea and making it work?
