Is the digital technology we see emerging today going to be able to provide the positive tension between rational and randomness that takes place in our innovation activities today?
Will digital begin to dominate our innovative thinking, will we lose this randomness, this spark of human creativity or will it be allowing this to connect multiple strands in new, more exciting ways? How are we going to adjust to the changing way technology will impose itself on our innovation activities and needs?
How will all this Mobile Connectivity, Cloud Computing, Social Media, Crowdsourcing, Internet of Things, Industrial Internet, Big Data, Analytics, 3D Printing and Scanning be presented and managed as a part of successful business scenarios and intertwined with changes in social behaviour?
Are our existing innovation systems ready for this potentially set of sweeping changes in knowledge inflows and translation, so they can be successfully commercialized into new innovation?
Part two within the series of seven
It is through searching for and seeking engagement in the ‘wider’ world we will begin to make greater connections and receive potentially enormous amounts of (raw) data, about interactions, performance, possible issues and connecting, previously fragmented and dispersed information and through analytics turn this into emerging valuable knowledge.
Rational and Random thinking can be accommodated with digital technologies.
Technology has spawned operating systems that are set up to be searching for the rational, by setting up the system hierarchy, by ensuring a coherent input of facts and data, you can automate the process and generate greater outcomes that give you scale, make considerable processing saving, and gain increasing efficiencies by the constant quest for improvement and automation.
We are equally seeing more random pattern recognition, matching, and ‘crunching’ data to offer up multiple scenarios. Then we begin to see equally a big move in where you store this data, those ‘data lakes’ where you can constantly revisit and drawdown raw data, in new and different ways. For managing significant data the cloud offers a significant alternative to on-premise.
Thankfully the quest to extract intelligence out of the raw data has equally kept the randomness side moving along in equal measure. It is this side that is making the big leap through these emerging technology changes of social media, smart mobility, sensors and other machine intelligence that is generating vast new levels of data.
This big data requires analysis and the analytical aspects coming from exploiting different algorithms, will allow for greater insights into all the activities taking place.
There is even more of a promise that artificial intelligence can combine with human intelligence in significantly different ways, to generate new growth and deliver those richer, higher scale, more innovative business outcomes, that this investment being undertaken will be required to bring.
What needs changing is the innovation process to accommodate these changes
The arrival of big data is full of bytes, both terabytes but also strategic bites! We seem to be in a really evolutionary period, with the explosion of change taking place in the post-digital world of cloud, big data, and social and interconnected devices.
The discovery of insights from all this embedded intelligence, social activity and data analytics is leading us to potentially manage a significant wave of new innovation opportunities from this digital knowledge.
Managing this transformation is a real strategic and operational challenge.
We will need to transform much within our systems but more importantly to orientate our skills to receive, translate and diffuse new knowledge, in significantly different ways.
It is through this combination of people and ‘things’ connecting to our businesses that we will be able to extract new observations, to give us insights that can lead to completely different innovation opportunities.
That is the promise of this ‘fat juicy carrot’, providing fresh growth, new innovation opportunities, that have real value and worth.
Insights and ideas will become a real log jam attempting to enter the innovation pipeline
As it stands I can see a potentially damaging build-up, or a log jam of promising concepts all desperately trying to work themselves through the innovation funnel. Either decisions or the existing disciplines have to be radically altered, where we take on a much higher risk profile to enable these to move from idea to finished product or new service, or we accept the consequences of different failures, growing frustrations or variable revenue metrics against the cost invested.
Cranking up the innovation throughput needs different approaches than at present. The innovation pipeline today is very manual, it needs human intervention, in decisions, in inputs, in what is communicated, what is approved or dropped. Innovation gets often weighed down by human intervention.
Will this change, if so what is required is for the innovation process to become more automated where predictive decisions or probability ratings are presented more from technology design and digital information? What changes are needed, who will be willing to invest in this radical redesign of the innovation system?
Radical smart-connected and digitally discovered concepts will radically alter the value proposition as I have outlined before. These will need the internal business structures to alter and deliver new business models to respond in unique market ways.
That will call for bold leadership and radical redesigns of much within our organizations to allow greater innovation to flow out to the market to capitalise on these increasing levels of insights coming from a more digitally connected front end.
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***This is the second part of a seven-part exploratory ‘open thinking’ about digital technology and its potential impact on innovation as we know it today. These will be published daily over the next week. The intent at this stage is more about raising our thinking on what might need changing or at least re-orientation within our innovation management approaches.***
Dear Paul,
First of all, congratulations, I follow with attention and admiration your innovation postings.
I have been involved in innovation management at enterprise level for a long time, and always pursued a framework for the front end definition, in order to take out the innovation randomness and properly channel creativity, in line with the company´s competitive strategy.
Regarding the digital revolution impact on that framework, you are correct, it will enhance its effectiveness, but I sincerely cannot see one sole software taking care of all the variables the framework entails. Just as an example, big data and analytics will certainly make competitive intel easier and more effective, and related microsegmentation is revolutionizing innovation needs identification and marketing. Maybe this is shortsightedness, but I do not see, at least in the short run, analytics providing the complete integration of the above with social, economic, political, geopolitical, technological and other trends, patent data mining, resource requirements and feasibility considerations and other parts of the framework, as, in each of them, human criativity is called upon.
Cheers
Fernando Machado
Fernando, Thanks for your compliments. I think it is do-able. Lets start by saying it will not be one software provider but it can be on one platform where a number of providers come, more than likely in the cloud, so you can go in, use, save, bring back down information into your ‘secure’ on premise’ site for protecting your intellectual property and when you need to work on this again, sometimes continuously, you can ‘toggle^between keeping in in secured clouds or bringing it back within the organization. I think all the ‘app’s’ sitting on the cloud can cover off the needs. It starts with building a platform.
What do you think? Make (improving) sense?
Paul, very interesting post – I just stumbled over your blog today while connecting with people about year-end planning. Good time to learn from others practicing innovation management.
With regard to a Platform for Innovation, I’ve done some study and practice in that area, and have a working model. There are a few different types of clouds involved, for different types of digital information. The goal is to promote using the data in a manner that supports a desired outcome, which could be either strategic or tactical. Reducing the feedback loop between the CEO and the front lines is part of the challenge, so as to become data-driven toward specific objectives.
The platform provides a framework for enforcing Lean and Repeatability Principles, but these are just two types of principles that may be desirable. My hypothesis is these are great principles to start with for building a new business around a scalable innovation of some kind . However, the platform doesn’t really care what about the principles used – it’s job is to translate objectives into action according to a certain set of rules that can be tested and improved.
With the technology advances as they are, everything will have a user interface, and everything will be customized – in a “personal cloud” that will be configured to inter-operate with other personal clouds. Platforms will connect users across multiple channels and markets and serve as a “lingua franca” for collaborating members of any innovation initiative.
Anyway, my 2 cents – thanks for the article.