Dealing with Your Darwin Effect through Innovation


I have been working away, as my labour of love, frustration and sheer determination, on my thinking through the ‘harnessing’ of the dynamics within innovation, to offer organizations their innovation fitness and future landscape design, so as to radically alter their present capabilities and capacity to innovate.

The aim is to relate these to where your organization is in their existing capabilities, where they need to go, in identifying and clarifying the necessary capabilities they need to have, so as to achieve certain strategic goals and then, “we”, together, collectively prioritize the critical ones as ‘must have’ and then set about filling the gaps. This is the innovation fitness journey needed to be travelled.

The building of those more ‘dynamic’ capabilities and competencies are the ones you need so as to provide for a more dynamic innovation environment and deliver unique capacity for your ongoing strategic goals.

This work is covered off partly on this web site but does have its own dedicated site where the articles, post and thinking have been building up over a fairly lengthy period. Go and visit it at

So let me tell you what this is all about and I will describe this with heavy referencing from Geoffrey Moore’s book “Dealing with Darwin”. Without doubt one of my favourite books in how it helped me piece together a large part of my dynamic innovation fitness puzzle.

First you have the internal view.

Critically, you need to take a fresh look at your internal dynamics, at what happens when core competencies cease to differentiate, how resources must be shifted to new areas, how deeply threatening such changes can be, how a protective inertia emerges as the enemy of destabilizing innovation, and finally, what kinds of management responses can best deal with inertia and redirect its energy towards fresh innovation. This is the inward facing dilemma that needs to be addressed.

Then you have the External viewpoint

It is about creating competitive advantage in an increasingly commoditizing world. To lead that effort, you must continually reappraise what role your company is playing in the market ecosystem, how the market landscape of competition is changing and understand where your competitive advantage has come from in the past and where it is likely to come from in the future and with what kinds of differentiation will be most rewarded, and what kinds of innovation are most required. This is the outward facing portion of the story.

Then you have that growing sense of observations

Innovation and inertia: we often get stuck in particular types of innovation, promote given skills to the detriment of others, equally necessary but ignored or not understood fully.
We fail to adapt to market changes, we fund to much of one type of innovation to the exclusion of others and in the process create internal traffic jams of sorts, frustrations and tempers to match.

We squander our scarce resources of time, talent and management attention on initiatives that fail to give us competitive advantage and get constantly impeded by these forces of inertia all around us. Indeed, the more successful we have been in the past, the stronger the resistance to any subsequent change in the innovation course.

Then you have those real world worries

So what does keep management up at night about their performance on innovation? The rising anxieties stem from that worry that perhaps we are losing our ability to innovate, can our people still compete? Do we really get it? And even if we do, can we still get it to the market place at the right time and feed that need? Can we actually see the light of day?

Then Evolutions can happen

Evolution proceeds more gradually but in times of crisis we are forced to make choices that enable you to step back and reflect. I would argue we are all increasingly facing our own types of crisis in today’s volatile world.

If you were able to achieve an understanding that is based on more informed choice, so you can extract yourself from one path that makes you increasingly vulnerable and provides support to commit to a new core focus, one that offers you a more sustaining competitive position on which to compete through innovation. Would you take this different pathway?

Your task, challenges and keys to unlock your dilemma lie here.

1. The task is to develop a suite of core innovation competencies with proven capability to create (unique) competitive advantage.
2. The challenge for management teams is to choose the type of innovation appropriate to their situation and to exploit it deeply enough to create definitive separation from their direct competitors. This can be completed in different ways but through a thorough analysis is recommended
3. The key is to identify and then to extract (scarce) resource from (existing) context and re-channel this into the new core that will differentiate you through the new emerging innovation competencies and systemic approach.
4. A real need is to reposition resources and provide focus on the ‘right’ capabilities to meet new challenges knowing your “Innovation Fitness & the Dynamics in the Landscape”

The sooner you start, the sooner you will be able to extract yourself from the commitments that make you vulnerable and establish those commitments that will strengthen your new position“- Geoffrey A. Moore

Survival of the fittest dominates irrespective.

  • We are all caught in this Darwinian race- all of us it seems.
  • So where do you want to focus your limited resources? The ‘natural selection’ choice to increase your abilities to innovate linked to your needs.
  • Start by mapping out your innovation direction to the tasks and capabilities on hand and those needed or required to get you to certain predefined goals.
  • Chose the path that will leverage and expand your knowledge, capabilities and capacities and start the journey.
  • Start recognizing the opportunity spaces and gaps when you think you should be heading but feel you might have constraints in moving towards.
  • The greater you can identify the need for improving your ‘innovation fitness’ allows you to get closer to accelerating towards the seen and yet unseen opportunities.
  • The greater ‘innovation fitness’ equates to more value creation potential.
  • As you learn to recognize the difference between managing the existing routines and building the new capabilities, the quicker you can absorb these new learnings within the organization, so they can become the new dynamic routines that are needed.
  • You then begin to reduce uncertainties and strengthen the true innovation capabilities you need to thrive and survive in this Darwinian world.

Interested to learn more?

Then simply contact me. I am happy to discuss this and how this can be applied to your organization and what it means in engagement and commitments.

You build progressively the Innovation capabilities and competencies levels to become dynamic and fitter to compete and succeed.

Achieving a higher collaborative gear

Collaborative GearsFor a big majority of us, open innovation is now well established, it is part of our innovation furniture. The quest for many, today, is the search for richer engagements, possibilities and exchanges. We need to move beyond the existing boundaries and go deeper into the collaborative space.

I regard collaboration as the active ingredient, the yeast that allows our ‘daily innovation bread’ to rise. Getting all the parties ‘gathered around’ puts increased vitality, energy and commitment into working together over a project or idea.

As we learn to reach out and collaborate, exchanging perspectives and our different thoughts, it is in these interactions, in the many exchanges on-line and off-line that we move towards a real sense of achievement.

Allowing outside ideas through our doors

Open innovation has literally thrown open the doors, many of our research and development activities are increasingly relying on the input from outside. Open innovation is changing our behaviours.

Yet it can be tough to shift our ingrained habits and patterns of behaviour to accommodate differences of opinion, acceptance that many of the answers lie outside of our building and domain of expertise. The more we look outside for answers the more we are getting closer to the truth, as the truth lies out in the market place.

We need to seek those “moments of truth” and be true to ourselves, in having open, honest dialogues; these strengthen sharing, confidence and trust – all essential to collaborations.

There are certain behaviours to avoid, certain ones to embrace.

I am sure we have all looked at collaborations as more one way, our way, and not made the progress we had originally expected. True collaborating is an art, not a science. It needs constant practice, a freedom to explore and express. You need to have a clear sense of purpose, on why you are talking; otherwise you wander and never get to the point of real value.

The work is around issues / challenges / problems that have the potential for mutual gain. No one enjoys those “black holes” or “long silences” of one way dialogues, those that often feel like “I think this person is sucking out my brain” and expecting that for free.

No, for me collaborations, good collaborations, can move up a gear from those past open innovation experiences. We need to make them human dialogues that appreciate and respect the others’ opinion, otherwise why bother with open innovation, if we already know the answer, we just want you to confirm it?

Designing our collaborative platforms with some suggested principles

  • I like the principles of “demonstrating, validating, sharing and discussing” as you ‘plug’ into each other so you can achieve active dialogue on ‘given’ subjects on a solid ‘give and take’ approach.
  • Often we constrain ourselves in working out the prescribed agenda of needs before we get into any dialogue, I think this is a huge mistake. We should make conversations creative, a rich mix of development techniques that generate good interactions and create that growing bond and identification.
  • We need to allow time to let discussions and exchanges grow and flow and sometimes they can move into unusual directions that lead to even better creative exchanges for value building.
  • We need to seek a bias for action, by simply keeping on asking the basics of “for whom, why are we discussing this, how can we proceed, when and what issues stand in our way?”
  • I like the idea to start off any potential innovation conversation with a belief of its change possibilities; it opens us up to what both parties can truly get out of the collaboration.

The need is for both sides to feel they are gaining from any collaborations

  • We should always start with the belief that we need to gain mutually, and often just simply recognizing that you might ‘just’ simply gain personal knowledge and insights that could offer value somewhere ‘down the line’.
  • Each side constantly needs to track back to a sense of worth and that comes from allowing time for feedback and open thinking. Take your time to really engage in mutual conversations, they prove to be increasingly valuable over time.
  • By the use of design thinking techniques can certainly help in providing a greater dimension to provide ideas to flow, makes exchanges and creative moves towards solutions. Learn the techniques and then try it as an alternative way to work and create together.
  • We need to practice “circles of conversation” where they loop around, move around the parties and you gain increasingly from the positive reinforcing loop of different conversation strands.
  • Lastly, we all bond, sometimes not so much with the problem but far more with the person explaining the problem, so mixing up the expected problem statement with personal experience and your values makes for a far more positive atmosphere, leading to fruitful conversations you might not have initially expected.

Why is collaboration so important to our future?

As we engage, we learn.

We can’t imagine what we don’t often see; others open our minds to new possibilities. We can stay anchored in what we see and do, or if we are prepared to let go and have this ‘freedom’ to look for mutual exchange we can scale new heights. Conversations, exchanges and collaborations give us the experience to learn.

The huge value of collaborative exchanges is how it opens up our minds as we sometimes realise that we were ‘vested’ in selective thoughts that were less informed than we expected. Opinions can fall away as better ones replace them.

We need to let go, unlock the knowledge that comes from collaborations. Just remember outsiders are not insiders, they have different perspectives and do not expect to ‘shoe horn’ their opinions into the one size fits all. 

I’d argue to remain as open as possible, so as to allow yourself to simply open up in a world of mutual collaboration, it can lead to some powerful innovation ideas. Build trust, value your own instincts and permit judgement calls to be pushed off until you have allowed the other party to explain their potential contribution, and then jointly work towards the solutions.

Make your collaborative efforts move just beyond open innovation into relationships that continue the learning process for all sides. Make all your collaborating endeavours stimulating, then you move into that higher creative, co-creating gear and it is a far more rewarding place to be.


Publishing note:  This blog post was originally written on behalf of Hype and with their permission I have republished it on my own site. I recommend you should visit the Hype blog site where they have a range of contributors writing about a wide-ranging mix of ideas and thoughts around innovation, its well worth the visit.


Tackling the Internal Jobs-to-be-done for Improving Innovation


We are constantly nudged towards understanding the needs of customers through the jobs to be done approach. So why do we still seem to not achieve this ‘higher purpose’ of providing solutions to customers’ needs?

Predictable growth has run its course as we live in unpredictable times; we need a better way to identify ALL those unmet needs that our customers have. That need comes from knowing the “job which needs to be done”. We need to sharp shoot to hit clear targets, we need to become a lot more explicit in our knowledge of a customer’s unmet needs, and they need to make the connection of that need with our product (or service).

Mapping the hierarchy of customer needs

We need to map the jobs and generate desired outcome statements that are specific and of real interest to the customer, not our list of multiple ideas generated based on where we are or what we think we know. We need to build the hierarchy of customer needs.

By even attempting to follow a ‘needs first’ approach we are often left to figure out the unmet needs. The flaw lies in not having these fully understood. All needs can be captured but this requires combining a more rigorous, controlled approach, coupled with astute observations.

The key still requires us to accurately quantify the degree to which a proposed solution will increase customer satisfaction – and that means knowing the job’s they want to complete.

We need to segment by jobs and to do this we need to capture this in clear, precise job outcome given statements. We need to become clearer on the product, service or business model ‘job’ it is intended to perform, measured by a customer’s desired outcome.

I really believe our internal processes are letting us down.

There is real scope to do a jobs-to-be-done (JtbD) evaluation internally, let me explain. We can become so intent on finding out the customer JtbD we might be forgetting the internal ones that need addressing as well, they get ignored and continue to ‘undo’ all the hard work of customer need discovery.

We need to fix the internal need for innovation first, the job we are trying to achieve. We are failing on this considerably.

So what is the internal job to be done?

Is it to keep everyone employed in developing and launching new products, to keep our innovation structures humming along or just because it is expected from us?

Surely the job to be done might be “to reduce the product failure rate” – the end need is to get into the innovation pipeline only high-value products that are sustainable, offer clear market differentiation and have a distinct demand. Often we allow products into the development pipeline that are less than stellar.

Actually we have a wide range of reasons for ensuring failure before the product even gets launched. These are the jobs-to-be-UNDONE that need to be eliminated.

Can you spot these happening within your organization? Do you sense you have seen or been part of this set of actions that had the triggering effect of altering the product from its original discovery point.

Failure Points Activity outcome and its potential impact on failure
Inattention Someone decides to deviate from the original detailed specifications and this impacts significantly on the JtbD originally identified but accepted internally as ‘an acceptable’ risk, without any tracking back and validating this ‘internal’ change and how it compromises the original need.
Lack of Ability The skills, conditions or training to execute the JtbD that has been identified, so as to successfully translate this back into a product that delivers on this need are not available within the organization. They are not brought in to offset this lack of internal ability, it becomes ‘let’s reinvent here’ failing to understand critical experience points.
Deviance The internal process suddenly gets short-circuited to speed up the process, the missing ingredient of understanding gets overridden by this need for speed or someone up top overrides the process and the deviance has a knock on effect that (radically) alters the final product intent.
Process Inadequacy The discovery and development process are faulty, they miss critical signs or ignore them and keep pushing on to keep to the prescribed project time line for fear of being singled out. To call stop is bad and indicates weakness not strength, so the process continues regardless
Uncertainty The initial idea lacks the type of real clarity researchers require, gaps begins to be filled in by one person’s assumption, that was ‘best’ judgement and ‘reasonable’ but produces undesired results that are difficult to call a stop too. Actions adjust going forward with future consequences
Task Challenge The task becomes far too difficult to execute reliably every time and the eventual production quality becomes variable and compromised and the products lacks consistency on that final finish and fails to meet the expectancies of the customer
Process Complexity Those well laid out plans, built on a complex final production layout suddenly encounter constant and sometimes novel interactions unexpected and cost overruns, delays, final product rejections all suddenly rise with variable final product results that should have been unacceptable but forced to be acceptable, but on to the consumer.
Hypothesis Testing The hypothesis sounded great, it was heavily backed as a winner but suddenly fails, sometimes when capital commitments have been made. Instead of simply ‘pulling the plug’ it begins to have a momentum of its own, heads go down to prove the hypothesis irrespective.
Exploratory Testing Some adjustments or experimentation made it into the final product, it was meant to be a clever addition to expand knowledge and cater to the JtbD need but has undesired results unforeseen or not thought through.


Tackling the internal JtbD is not easy. While we deviate, while we let internal interpretations into our new product development process we are building in the chance of product failure.

Managing the internal JtbD really does need thinking about.

Knowing the need of our customers and markets is the place that will get us towards growing our business. Yet we do need to focus more often on the failures we have in the internal Job to be Done to actually improve our product success rate. Internal ego’s and the innate wish to constantly meddle along the innovation development process seem to have many jobs that need to be undone.

We need as much internal discipline to stay focused and true to a discovered customer need within our internal processes and pipeline.

How often does a product in its development get altered to accommodate internal wishes? This internally driven perspective, intent on ‘just’ getting the product out of the door, because keeping it in its original state seems simply too hard for all sorts of reasons. The emotional factors kick in and you hear “compromise and cannibalise” and a host of other fear factors to protect existing products, systems or structures that are ‘turf’ driven.

Internally we have this need to identify the true internal jobs-to-be-done and that often centers around deviations from the “customer need discovery point” and it is these which might be causing more failure than you realized, well before any product gets launched. These internal failures need to be undone.


Publishing note:  This blog post was originally written on behalf of Hype and with their permission I have republished it on my own site. I recommend you should visit the Hype blog site where they have a range of contributors writing about a wide-ranging mix of ideas and thoughts around innovation, its well worth the visit.

So Welcome to the Age of Digital Innovation

New age of innovationDigital technology is about to become the precursor for all the changes we have put off for years within our organizations.

We need to radically improve our abilities to engage, relate and discover new innovation opportunities at a completely different level of faster performance.

There are many issues both strategic and tactical to work through, to extract the rich potential from any digital transformation for new innovation growth outcomes

The final part of a seven part series –  a new dawn or your worst nightmare?’

The array of new digital technologies that we are trying to connect organizations into, for the world of digital insights, is going to be highly disruptive or empowering, for all organizations. It has the potential to radically alter our organizations performance.  These are powerful technical forces that are going to connect the digital age inside organizations, these will require a deep thinking through for all the ‘points of impact’ this will have.

Digital is presently moving way ahead for the systems our organizations have presently in place. What does need changing to ultimately yield the innovation returns we will be looking for? Expectations and reality needs resetting, the hard work is not ‘just’ in connecting the technology, it is its impact that it will have across the organization to be able to ‘react, respond and reorganize’ in very different ways from today’s practices.

We are dealing with a completely different set of mindsets, skills, procedures, governance, processes and responsibilities. To gain from the digital evolution taking place we need a robust, comprehensive and radical overhaul of much of what is going on within our organizations.

Many of our existing systems will need a radical redesign

The innovation system is not broken (yet) but it is totally inadequate in its present form to capitalise on this influx of new opportunities digital connecting can bring. It will potentially just choke up and come to a grinding halt unless we seriously step back and re-evaluate the innovation process, its needs, tools, frameworks and its ‘new way of working’. We need to redraw the innovation system and its management structure, procedures and governance.

There is this need to blend technology post digital with people in significantly different ways. Innovation calls for better automation and its management understanding to design all these into its system. Information systems and their data outputs might generate but humans have to frame the challenges and problems they are in search of answers.

So how can digital technology be leveraged more effectively as an engine for innovation and future growth when we are seeing current innovation constraints and impediments?

Is the innovation process fit for the new purpose? Clearly not. It needs a radical overhaul to support the digital technologies and the ‘insights’ coming towards it.

To embrace digital innovation there is a lot to work through, here is my initial attempt.

As we move towards this age of digital innovation, what do we face?

  • We are faced with a truly pervasive global network making more things possible, the biggest value proposition of technology has shifted to the new, deeply super-connected, scalable-to-billions, always-on ways of working that digital business now represents. The upshot: Nearly everyone today is connected to everyone else in the world 24/7, with the devices in their pockets and purses” (View of Dion Hinchcliffe in his article “The internet inside the Enterprise“). Innovation needs to race to catch up and respond, so as to capitalize on it.
  • Equally in Dion Hinchcliffe’s view, which I can recognize: “the Internet has proven itself countless times as that uber laboratory of innovation, trying — quite literally — millions of new ideas in scale, continuously finding the way forward on how best to create value over networks, sustain it, and to relentlessly find new models that have the least friction, cost, the highest velocity, most agility, and best ability to tap into shared innovation.” These observations point towards a very different design and structure within organizations to achieve these ideas to scale.
  • What will be the new management skills and leadership competencies required to achieve continuous innovation and transformation within organizations? What will need to change, what needs to be brought in and equally, thrown away from today’s practices?
  • What are the new forms of organizational design that will be required as ‘adequate’ for an environment of unremitting change? The present innovation system is not ‘fit for digital innovation purpose’ today.
  • To learn to apply the application of technology in support of the business, to cope with the new mantra of making it ‘cheaper, faster, and better‘, combined with the increasingly need to ‘communicate, collaborate, and engage‘ across businesses, customers and stakeholders 24/7, we will need very different, more agile and adaptive systems.
  • Everything about technology is poised to upended the current model in organizations, from architecture, software development, processes, the way to manage and offer a very different level of service delivery in new business models, rates of change, and cooperation and co-creation needs.
  • Boards will need to balance the need for stable, resilient, dependable systems and infrastructure as they go through a ‘state of flux’ in this push for investing in new digital initiatives They must clarify what is essential ‘to make us more agile, innovative and responsive.’
  • The worry of  dealing with increasing risk; cyber risk, organization risk and the organizations ability to capitalize on any discovered insights before others do, all raise the risks and threats. Boards just have a real aversion to risk and how this will play out as we digitally connect will partly determine the winners and losers due to their risk appetite.
  • To help ‘modify’ the risk concerns at board level, the CTO, CIO or CDO or all three, need to stop talking about the potential of these technologies and more the language of business. Frame this not in terms of cost or disruption but in revenue and new organizational opportunity.
  • The need is to establish a digital strategy, which represents all the opinions and the fusion of business and IT, as they are becoming one of the same, as digital is becoming a unifying concept and pervasive and all business has an increasing digital element.
  • There is this need for cognitive alignment as it will be increasingly about sense-making, learning, understanding pattern recognitions, gaining debate, consensus for alignment within the leadership teams.

We certainly need a very different organization design to digitally innovate?

  • The radical shift for the innovator is the need to define the right challenges, in constructing the digital brief, in building the parameters and inputs to be able to ‘extract’ the data that leads to information and knowledge that eventually connects to final valuable insight. Today we are not so good at that.
  • The human part within the new innovation process will still be the framers of the task, interpreters of the information and synthesizers of the result. They will be guided by the digital knowledge and techniques they deploy to help them in this. Framing and synthesizing becomes an essential skill.
  • Developing those abilities and skills in interpreting and synthesizing the data and insights will become essential attributes so to attain the understanding to deliver those “higher scale of richer, more innovative insights” expected .
  • The ‘crunching’ of large data sets, will this be simply be left to the analytic person? Someone deploying different techniques, algorithms and predictive solutions. Will they have the necessary understanding or business experience? Who will have oversight or determine interpretation?
  • Much will rest on the way these new insights can be communicated back into the organization, to be translated and to be turned into new profitable innovation offerings.
  • This ability to align analytics, extract important insights and spot the potential commercial value will become critical. These have the potential to determine the organizations future.
  • There is this need to spot more of those ‘weak signals’ to learn from, using predictive and pattern recognition tools and methods, generating ideas or insights that fit within briefs or parameters that align to the organizations strategic needs.
  • What value judgements will be constructed to rank and grade ideas or insights, so as to begin to formulate the commercial response in new innovation activities.
  • Trending, producing insights, scenarios and patterns of discovery, will need both computer and human power of understanding. Forecasting potential, spotting the breaking needs, segmenting the markets and validating assumptions and trigger points for solutions will become a pivotal role.
  • Listening, filtering, constructing user-experiences that allow interactions and knowledge sharing will be essential. It will be again the analytics, the discovery process and the event management techniques will partly determine the value and richness of these engagements.

What about the need to build new capabilities?

  • There is this increasing need to develop sense-and-response capabilities, increasing ambiguity and uncertainty over time will change our ICT thinking.
  • A constant change or extracting continuously  from the cloud or data lake will require  flexible processes, constant adapting, needing highly agile responses
  • There will be increased demand for visualization and managing decisions in responsive, agile and adroit ways. Constantly communicating the ‘breaking’ story will be essential.
  • The increasing value of purpose-designed intelligent dashboards to allow decision-making and the appropriate information to flow to the decision  maker, as well as the governance trail of where, when and who made what decision becomes important.
  • Whole areas of research, testing, experimentation, modelling will become increasingly automated but the framing parameters will again require growing specialisation and understanding.
  • The ability to test combinations, to work through countless data points will generate new possibilities but these again need clearly framing well, so as to avoid drowning in data, ‘for the sake of it’.
  • The ability to engage in and across different communities will allow for richer understanding. These communities will be internal, business partner ones, customer and other stakeholder communities all contributing and engaging.
  • The emotions, feeling and often unexplained human behaviour will always intervene somehow. It will depend on the robustness and strength and belief in automation on personal as well as organizational levels. This needs careful managing the engagement.
  • Lastly, and I think most important, you do have to keep asking that question of “what are you trying to do, resolve and understand” because data for data’s sake will just simply just let you drown in it, equally change for change sake.

We need to begin to really think though this as a complete redesign.

There are a host more areas to draw out in any digital innovation system we do need to surface and resolve.  To achieve that new position of understanding is a really hard piece of work required to determine and redesign the new digital innovation process.

It cannot be a simple ‘bolt-on’ job, it needs a radical redesign. We should grab this ‘moment of time’ to think what a new innovation system, fit for the post-digital age really should look and operate like.

Organizations will be in their search for understanding what needs to change within their innovation systems as soon as they realize that today’s design can’t cope.

What is needed depends on how each wants to ‘embrace’ digital. It will need a real depth of understanding and working through.

I’m on it, are you? Its BIG and breathing down your neck. Welcome to the age of digital innovation.


*** This is the final part of a seven part exploratory ‘open thinking’ about digital technology and its potential impact on innovation as we know it today. These have been published daily over the last week.

The intent was not to provide definitive answers so much at this stage, it is more about raising our thinking about our lack of providing an adequate innovation system for the changes caused by embracing the digital technologies coming towards us.***





The Need to Automate the Innovation Process

New Technology Dawns 6There has always been a consistent call to automate the innovation process. Now it might turn into a stampede, based on real ‘digital’ need.

We have made solid progress in the use of out-of-the box software for capturing ideas at the ‘fuzzy front end.’

We have developed pipelines and use product life cycle software systems to manage this through to commercialisation.

Yet today we still have a fragmented, often broken innovation process, very reliant on the manual processes, where the human intervention dominates. Can this be changed? Technology must form a greater core of the innovation process.

We still are very reliant on stage gate intervention points, often more due to dogma and imposed oversight by committees occasionally meeting. Decisions are determined by the human, based less on hard knowledge or dynamic intelligence, often these have tended to be thinner on the ground to validate concepts and judgement becomes highly personal and reliant on (past) experience. What can we change within this? There are leading practices to compare and contrast with but we do need to push this automating the innovation process further, in different ways.

Part six of a seven part series

Perhaps all this can know change, with adopting a broader more connected engagement process and take this out, we can constantly engage in community collaborations to test and experiment than before. We can quickly go into the market through digital technology to engage with our communities of interest to confirm or influence a design or concept and shape it. We can gain ‘scale of insights’ quickly all the way through the new product life-cycle, validating, adjusting, adapting through to commercialization.

In the past innovation took a linear route, very reliant on a manual process.

I recently had some different exchanges with Jeffrey Philips, over at Ovo Innovation, a long time sparring partner on innovation thinking.

From his organizations work he suggested top of mind there are five key activities, which are typically completed manually today:

1) Defining a specific challenge or opportunity, 2) Gathering trends and developing alternative future scenarios 3) Understanding/Validating customer needs through research 4) Generating ideas/solutions through brainstorming and from these 5) Developing and Prototyping ideas.

Given some more time I am sure this list would grow. Jeffrey certainly suggests many of these tasks can be accomplished through some form of automating the process, I’d agree.

I’d suggest for many the innovation process in organizations are even more manually conducted in collecting data, validating actions or decisions, communicating the status, working through project tasks, etc.

We are very reliant on manual systems for much within our innovation work.

I don’t think we can afford to let this continue, it often slows decisions and activities significantly down. I know of consumer goods companies that work on 18 to 24 months for incremental products from conception to commercialization. Is this good enough or just comfortable enough for those involved?

Market trends are changing faster and becoming shorter, so opportunity windows are narrowing. Risks of missing out are constantly increasing for those who are not focusing intently on that critical ‘time to market’ and not constantly streaming their innovation system, looking to automate it where ever they can.

Bob Cooper, creator of the Stage-Gate system recently warned, in their ongoing research data “did you know that”…..1) 76% of businesses have already too many development project for the limited resources available. 2) 81% of businesses have unbalanced portfolios full of small bets, 3) 90% of businesses have “few or no” high value projects in their development pipeline and 4) 75% of businesses profess to poor project prioritization.

What happens when all this digital knowledge and insights starts hitting our desks, having to work through a manual or semi-manual system seeking to capitalize on a ‘breaking’ opportunity? It will be a real choke point.

 Opportunity spots where we can speed up this manual process.

Jeffrey suggested some immediate places where there was some clear automating opportunities but we agreed these were ‘just the tip of the innovation iceberg’

• Many innovation teams have gathered and analysed trends by hand, attempting to forecast their impact in the future, to understand emerging needs and alternative future scenarios.
• Also market research has required intensive customer interaction, which has tended to be reliant on face-to-face or observation. Equally the heavy use of surveys and large data sets has tended to have significant human involvement. This is significantly changing through the use of technology and numerous analytical tools and predictive methods.
• Idea Generation has often completely relied on a number of people ‘brainstorming’ or generating ideas and we have learnt this needs to be less random in the event and more specific to problems we believe need to be solved.
• Then we have been reliant on traditional prototyping methods that again reply on people to form a crude representation of a concept or idea. These were reliant on ‘hand-crafting’ prototypes, reliant on people with some skills and schedule the time to complete these but the extensive use of 3D printing is radically altering this..

We can recognize each of these have changed over the recent years. They are being automated wherever possible through pattern recognition methodologies, predictive analysis, trending evaluation methods where there is less human interaction but more interactions with a prototype, simulation.

Now with the recent introduction of 3D printing the designing  a prototype or even a finished product, has become highly valuable, it is shifting  and beginning to disrupt many of the traditional ways of ‘machining’, undertaken in the past. For example, the dentistry business where within the dentist they can make the part using ‘on premise’ 3D fabrication.

We have been seeing better structured approaches, mixed in with unstructured methods and framing techniques to pull out ideas, challenge existing, often entrenched thinking and break through roadblocks to keep moving our innovation work forward. All continue to improve but still miss opportunities to automate in some way or another.

As we have used software to collect information and ideas at the front end (idea management systems) this have made the innovation process far more automated, interesting and participative.

What is needed is to push the thinking on how to automate the innovation process even more.

We see start-ups adopting agile methods, lean processes and new practices, new visualization tools and frameworks, designing techniques as they are unencumbered by a legacy, yet for the most part, large organizations have been slow to adopt these on a wider corporate practice. They still experiment but do not adopt these as organizational practice although this is changing constantly as they value these techniques.

These need pushing deeper into large business organizations. We need a functional group that explores, experiments and seeks broad adoption of many different tools and pioneering methods in our organizations, so they become increasingly part of the daily tool-kits we use. Design thinking, business model design,and lean for example, all should be adopted as everyday tools. Each helps innovation.

Can this be pushed further; can we perhaps become more radical?

Digital technology might be giving us the tools to shape our environments in very powerful and different ways. We can amplify what is going on, we can capture all the interactions, we can discover, explore and extrapolate better and at growing scale.

Less randomness, more of a quest for rational answers but we still need to frame the questions we want answered and that still seems to remain difficult for us humans to do. Even here technology can give us increasing intelligence to spot patterns.

There is so much to be realized, connected and enabled for the higher scale, richer, more innovative business outcomes but it is a massive undertaking that is only just being ‘kicked off’ by the current ‘internet of things’. It will eventually become the ‘integration of everything’ but the disruption and realization of what needs changing is only just dawning on many.

Managing digital knowledge that adds value and growth

External insights coming from market and customer intelligence will not fully take hold as Enterprise knowledge throughout the organization, without real, deep integration of systems designed to ‘receive, translate and diffuse’ valuable knowledge from all this digital information flowing in. A new system of knowledge adoption needs designing in.

Receiving the knowledge alone will not turn these into higher scales, richer, more innovation business outcomes that have real growth value, unless we realize the massive ‘mismatch’ between digital flowing in and the physical attempting to cope with this.

We need to think our innovation system designs a whole lot deeper to allow these new digital technologies and the insights to be worked through the innovation process. Speed is becoming ever more important, for new solutions to be turned out the other end as new innovation.

We need to design a complete innovation system otherwise we will be investing in a front loaded area alone, limiting digital impact and that will not deliver the power of actual growth expected or needed from our innovation activities so as to deliver new valuable outcomes. Approaching the innovation process holistically helps.



*** This is the sixth in 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 is not to offer definitive answers so much at this stage, it is more about raising our thinking.***

The need to respond quickly to new business objectives

New Technology Dawns 5The business objectives will change as we invest heavily in digital technologies, as we increasingly recognize and embrace this changing world where digital knowledge and insights begins to challenge and change our existing frameworks of innovation thinking.

Part five of a seven part series

The outcomes of the investment are expected to provide clear returns and these might include but not limited too: 1) different customization of services 2) quicker response to market trends in new offerings 3) identifying real-time cost optimizations, 4) concentrating on faster, more accurate decision-making to give new competitive edges 5) better and more holistic R&D 6) automate even further the supply chain management, 7) alter you approach to channels to market, 8) move your business into new adjacencies or even white spaces and finally 9) design new business models and value propositions.

There will be lots of new moving parts to grapple with to be future innovation agile.

Equally our senior managers will be digitally challenged

As machine learning or digital inflows occur, the pace will become even more rapid and the leaders will be called upon to create the new innovation forms. The mental capacity and physical adroitness will continue to multiply through digital technologies and the need to be agile in responding. There is going to be significant advances in cognitive work but will this be human or digital brains doing the work?

If we foresee a deeply driven digital world, the new place for human intervention is “where do I actually add value and where do I need to get out-of-the-way and let data take me?”
So we are going to be potentially more data driven, less intuition driven. Your whole domain expertise will eventually be stripped away.

The challenges within the leadership of our organizations are to somehow envision how the physical world and digital world can be ‘pulled’ together. That critical need of applying the different forms of intelligence and experiences and provide the ways to network and build from these ideas and insights into tangible values that fit with the organizations objectives.

The key to leading in a data-driven world recently was suggested in a McKinsey article on the Manager and the Machine will be 1) in learning to ask good questions, 2) attacking exceptions, 3) tolerating more ambiguity and 4) focusing as much as possible on employing ‘soft’ skills where insight gets turned into messages that resonate with the organization to see as innovation potential will require that human touch.

How will digital automation improve and balance our innovation management?

As data flows in we will need to rationalise the decision-making, we will be seeking out for the gathering of data more fact based observations. The intervention of personal opinions and “experience” will become highly challenged and hopefully on the endangered list.

We can look to insights as possibly better predictions of success by lessening the risk factors of no knowledge or very limited understanding and underpin the assumptions with ‘trends’ and rich insights to validate directions and emerging solutions

We will be able to explore the ‘worlds’ trending on those topics relevant to our needs, knowledge and innovation thinking. Exploring consumer behaviours, technology trends, competitor monitoring and significantly granular insights to shifts taking place in real-time and near-time.

We might discover the unexpected and the surprising and not rely on instinct, six sense or ‘our past experiences.’ This may increasingly clash in validating, we need to ensure this increase in insights will yield better ideation. As time goes by and we become more reliant on digital technology our idea management thinking will become distinctly different, less based on hunch, feel or (sadly) experience.

We will be even more under pressure as if the data is ‘open and common’ for all to ‘trawl and gather’ then you are in a race to capitalize on this before your competitors is able to learn or react to it.

Through validation we can constantly confirm or question the business case, we can test hypothesis and experimentation. We can check assumptions for validity far more and across broader communities than the past.

Having data, creating a history you can be equally be more backward looking to judge success and failure and use these different understanding and analysis to design more predictive forward-looking models and framing techniques that capture differently or improve your pattern recognition.

The growing science and value of analytics for innovation

Innovation analytics will become an integral part of the entire innovation life-cycle to make smarter decisions, and to optimise the innovation performance along all its value building chain.

Having clear data-analytic strategies that break down the information into something commercially useful will require more searching for ‘weak signals’ that contain those real nuggets of insight. The early mover has to have speed and pace of decision much higher. The emergence of customized dashboards will dramatically advance but working on the parameters that feed into these will be as real challenge.

The need to analyse, synthesize, transform into actionable events and value enhancing insights will be based more on fact-based decisions but the human interventions become more responding to exceptions not stage-gate managing everything.

Analytics will evolve into providing answers or guiding you to create descriptive answers, situational to why this is happening, predictive in what this might mean or trending towards, prescriptive in validating choice options and finally simply evaluating the risks, the choices of doing something or not due to this data and insights.

Adjusting our thinking on risk

Technology insights can provide a better mitigate risk, it can equally fine tune innovation but it can equally make it far more complicated. Massive amounts of data can complicate decision-making, determining the right decisions and next steps.

Technology will require opening up the present risk mitigation process to capitalize on emerging opportunities at greater speed and higher levels of compromise, to meet that emerging opportunity ‘seen’ requiring it to be turned into commercial offering quickly, so competitive advantage can be gained.

Getting the parameters right, this digital into innovation criteria,  will potentially determine the direction of the organization and where it places its resources. McKinsey talks of democratizing and managing will be determined more by pattern insights, and clear insights, less on waiting for a top manager’s decision as the defined strategy and business development directions become sharper, enabling this ‘decision-making’ to be made much closer to the market or the information source.

The urgency from Leadership

Leadership will have to become far more effective in decision-making and digitally savvy, so as to provide the guidance and strategic frameworks required for the governance and direction digital technology is required to go, to meet organizations stated objectives, and those will change constantly as better insights flow in. Defining those needs and the expected returns does sharpen everyone’s minds.

Tom Davenport of Babson College and MIT made some helpful suggestions about the general use of the phenomenon of big data, add its project attributes so leadership understands its increasing value. He suggests these are 1) describing the data you are using, 2) where the data comes from, 3) the problem you are wanting to solve and 4) where in the company you will use the insights to solve what. This as he suggests “provides clarity” and we all need that with the present easy use of “big data,” that impresses no one.

The changes wrought by applying all the different digital technologies promises far more the adoption of a more fluid core that Haydn Shaughnessy has written about,  as “understanding a new hierarchy of enterprise needs.  Adopting a new, adaptable infrastructure where technology, humans and competitive conditions intersect and can interact in real-time.

Leadership needs to respond quickly to the demands and additional strains this will place on their organization to provide guidance, strategic direction and above all the right resources to capitalize on all the changes this will bring. To expect to achieve a ‘real’ return from the investments being made or asked for in new growth and innovating value.


*** This is the fifth 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 is not to provide definitive answers so much at this stage, it is more about raising our thinking.***

* Sopheon through its software applications have been outlining some of their arguments for improving innovation due to big data and analytics and these helped me kick start part of my own thinking here.

IT is Struggling to be the Digital Technology Master

New Technology Dawns 4There is so much occurring in new applications and alternative solutions, it is a very tough position for most dealing in technology to truly master all  of these breaking options they might have to consider.

It must be a little overwhelming, when many responsible for IT have for years not had any strategic involvement and not been given clear line-of-business oversight.

Business management equally has over the years built up an ‘arm’s distance’ to IT and found ways to overcome barriers they felt were seemingly put in their way, when it came to ‘bringing in’ the technology they deemed as essential.

Something needs to change going forward. Both the business manager and the IT need to find ways to exchange, collaborate and share. It is in their ‘vested’ interest but more importantly for the future health of the business itself.

Part four of a seven part series

Over a number of years IT and the business seem to have grown apart. IT worked on keeping all that surrounds the ‘systems of record’ and tended to push away or outsource many of the ‘systems of engagement’ to others, either third parties or line-of-business. Email for example stayed within their domain but collaborative tools, the building of on-line communities, supply chain systems tended to be handed over to the expert group and they provided the ‘back-end’ support.

Much within IT has been handed over to lines of business to design and manage. Will this need to change back?

Today, the lines of business are rapidly handling increased system designs to meet their own needs and seemingly encouraged to do so. IT often seems to have been assigned the back-end task of ensuring they can work, are safe and don’t corrupt those all important organizational ‘systems of records’.

The changes in customer experiences and the engagement within these communities, the open innovation activities prompted by research and development, the stand alone systems for manufacturing design and improvements, have all seen a massive proliferation of either independent systems with minimum integration, or systems to site upon systems, adding complexity and poor line of corporate oversight.

An awful lot of business intelligence is sitting in silo’s where there is limited ability or even no incentive to explore these in different ways. The Enterprise core is limited and not really connected to much of the value-generating parts as we would wish. Knowledge is not flowing across and up and down organizations unless with some considerable manual effort.

There is a time for real change – technology and business need to be redesigned

We are in need of recognizing this new wave of external connected technology needs to be well-connected within our organizations. There are so many forces of constraint, forces of proliferation that need to come together but this is a massive, significant task for an organization to signal its (final) determination to achieve.

The implementation of ERP for many was a painful experience, not because it was not needed, it seemed such a wrenching change. Any significant technological overhaul will make that set of experiences a ‘walk in the park’ compared to this set of challenges that is being thrown at us today. The changes we will be facing to accommodate new technologies and its realization of value will ned an even greater evolution, ERP will fade into the background as a new Enterprise Innovation Planning (EIP) system evolves

The real need is delivering a new integrated engagement platform

We need not just a new innovation management system, we need a modern engagement platform. We need to integrate and sync so many transaction and stand-alone systems that have been allowed to proliferate over the years to meet specific business needs. The growing pressure will be demanded to find solutions that provide a cohesive and business-focused approach to the new social enterprise where we seek engagement at scale into a multiple array of communities and advocates that has data and innovation as its core.

There is such a business / IT / customer divide where the social push is shifting and still very emergent, where the new competitive advantage will be based on ease of acquisition, ease of use, clarity and diversity of choice and variety so innovations will be more tailored to the individual.

The demand for increased autonomy, personal choice will come up against the organization that is totally unprepared in adapting to this rapidly changing world. Organizations are lacking the right type of resources and comprehensive view of what needs to be connected and integrated, what is presently under way  is going to change many of our current industries today as they all become partly a software business.

How can we connect, enable and deliver better innovative outcomes?

There is so much to be realized, connected and enabled for the higher scale, richer, more innovative business outcomes but it is a massive undertaking that is only just being ‘kicked off’ by the current internet of things. It will eventually become the integration of everything but the disruption and realization of what needs changing is only just dawning on many.

External insights and Intelligence will not become Enterprise knowledge that flows without real, deep integration. Receiving the knowledge alone will not turn these into higher scales, richer, more innovation business outcomes that have real growth value, unless we realize the massive ‘mismatch’ between digital flowing in and the physical attempting to cope with this.

I would think unless the innovation systems within organizations are not dramatically altered and that is calling for a massive investment and some really tough strategic decisions of what and where to place those strategic bets and much of the technology needed is only being designed today that focuses mainly on the incoming part.

A painful and frustrating journey is ahead of us all

Turning big data and its insights into commercial successful innovation outcomes may be a very painful journey for many organizations. Business and IT have got to find radically different ways to collaborate and align. We need new models of work, more community-centric, non-hierarchical, dynamic and fluid, in a sharing economy where the evolution of apps and new devices will all have an increasing impact, based on collaborative technology. I’ve previously written on this as “the proliferation of transitory moments

The enterprise design will be radical in redesign and upheaval.

Much of the hype today about all this big data and the analytics behind it is great but the hand off back into existing infrastructures will mean most of it will never be realizable. It certainly can’t be handled by today’s innovation management system where knowledge is lacking and physical intervention is built on the wrong premise of managing innovation activity.

We need to review organizational engagement. Much has to change, be uprooted and completely revisited to begin to design a new digital and physical integrated innovation system.

To master digital technologies and what that can bring in new innovation and value requires a coordination and collaboration of business and IT, each needs to become involved in what the other is doing, thinking and planning and make these plans integrated through a new organizational set of process and procedural designs.

We need to reconsider enterprise architecture for this 21st digital century where increased autonomy, choice and resources can adapt, disrupt, refine, grow and renew constantly in a digital enterprise collaboration that allows data and voice to be heard….and acted upon.

I liked a comment recently from Beth Comstock, the Senior Vice President of GE in a recent interview on the imperative of speed commented: “If we left it up to each business to figure out their data and software, we would not be taking advantage of the scale of the company”. She is totally right, decisions being made today around digital technology are broad room and highly strategic. IT going forward shapes the organizations future.

Who is going to take the lead in your organization to design digital technologies into the very fabric of the organization. It can’t be left to one person or another, this is a total leadership challenge. IT need to find ways to engage fully within the board room, across all line of business and drive the changes up into each conversation and strategic discussion for the foreseeable future.

How organization design and connect digital technologies with profitable innovation outcomes will decide most organization’s futures going forward, markets, customers and investors will be judging this ability very critically over the next few years.


***This is the forth 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 is not to offer definitive answers so much at this stage, it is more about raising our thinking.***