They lead this article with “one view of complexity that holds that it is largely a bad thing- that simplification generally creates value by removing unnecessary costs”. Certainly we all yearn for a more simplified life, structure, organization, approach to systems or just reducing complexity in our daily lives to find time for what we view as improving its ‘quality’.

Within the article they argue there are two types of complexity – institutional and individual.

The former concerns itself with the interactions within the organization, the latter is the way individuals or managers deal personally with complexity.

The real important take away from this article for me was when organizations treat complexity as something they must overcome, reduce or try to ignore they miss opportunities. Complexity, the authors argue, should be seen as a challenge to be managed, managed well, and its full potential exploited, not as a problem to be reduced or eliminated. It is through the nature of these complexities we achieve competitive advantage and can exploit more of the flow of knowledge for those new sources of new profit and wealth creation.

They suggest organizations need to decide on where to hold complexity within any design and build the right capabilities where they matter. I would argue innovation certainly matters, and it is complex and needs to be understood as exactly that, and managed accordingly not in piece meal fashion. Complexity matters in building the right processes, skills and culture but because they don’t behave in linear ways and any ‘messing’ with the complexity and relationships within this can have an awful lot of unintended consequences.

We have choices of complexity

There are different types of complexity to manage. Work conducted by Julian Birkinshaw and Suzanne Heywood suggested four types of complexity. I only summarize these here.  Imposed complexity, those interventions both internally and externally that require ‘higher’ insight. There is the inherent complexity found with any organization and presently managed through striving to be more efficient and effective. There is designed in complexity, where innovation needs to fit more. These are choices about how, where and why an organization sets about its operation. These can be constrained, under invested in, even jettisoned but do have lasting consequences for the future of the organization. This is the area of strategic consequence as these can limit competitive advantaged from the level of innovation intensity chosen as an example. The fourth is unnecessary complexity where increased misalignment resides, it is sometimes easy to recognize but often hard to let go as it sometimes makes up “the way things are run around here” and have a richness in history.

The challenge of complexity within innovation

If you can begin to identify complexity that hampers effectiveness you can begin to remove it. What you have to be very clear upon is having a complete understanding, or a well informed one on all the effects if the complexity part you are removing is not the route to value and often innovation. The more creative side certainly does get constrained and caught up in this often shorter term pursuit of effectiveness for effectiveness sake and you suddenly don’t have the bandwidth for innovation exploration and more.

Do recognize that innovation is complex, recognize it does have to be handled carefully but it needs to also be fully understood for what it is, a complex adaptive system. It cannot be treated in the same way as effectiveness or efficiency can. It  needs ‘actively’ managing differently, for all the future opportunities it holds by placing the emphasis on building greater innovation capabilities to make it ‘dynamically’ work. Otherwise you end up with unexplained consequences to poorer performance from your innovation activities and often at a loss to explain why.

We do need to relate more to complexity as it comes with the turf if you want really lasting innovation.

The post Cracking the complexity code first appeared on Building Your Innovation & Ecosystem Intelligence.

One of my favorite books is “Dealing with Darwin– how great companies innovate at every phase of their evolution” written by Geoffrey Moore. It is well worth a read.

When you work through his other books and connect thinking of “Crossing the Chasm” and “Inside the Tornado” you really appreciate the learning stories coming out of Roger Moore’s studies of the Technology Adoption Life-Cycle.

We all need to rethink a lot as the new challenges come rushing towards us.

In his work, Geoffrey Moore talks about ‘traction’ and I think this is a great word for thinking about how to gain diffusion and adoption in product, service or business models, to gain market and customer acceptance.
Over three posts I am looking at different aspects of “diffusion and adoption”

The first post outlined the different theories and establish their value in our thinking.

The second post relates these theories into their to achieve success in penetrations of our target markets and increasing sales through growing adoption.

This is the third and final post in this series, it looks at how Rogers’ theories relate to us in today’s connected world, and in particular with reference to Apple and finally offers up some of the reasons why diffusion can fail to occur.

Seeking even more than ever, the One-2-One (1to1) of many
Marketing departments talk penetration, “message penetration, market penetration” and so often ‘force’ customers to become aware and then buy. Does this really work today? I doubt it.

Also many organizations hang on to old media ways to get their message across when the use of technology, the internet and social engagement may seem harder but I believe is far more rewarding to engage with the customer on a more personalized basis. I regard this as 1 to 1 of many.

Today we are in an ever-faster world

Connectivity is driving the diffusion rates of nearly everything. Just take a look at the following table:

Even this table is already out of date on the speed to reach critical mass. Companies are not just setting hurdle rates on launch dates but demanding innovations that have critical mass in revenue and when they achieve critical mass.

It is not unusual to set 18 months to achieve critical mass from the inception to settling on the critical factors that make a value proposition to drive penetration. This can only come through engagement and that comes through technology making the connection to the user.

Just study how Apple manages its diffusion and adoption cycle

There are lessons for us all to learn here. Apple has not been the first in markets, they are a classic fast learner and follower.

Yet they master the convergence of ‘breaking’ technology, design, user experience, pushing materials used and providing ease of use within the make-up of the product, and deliver this ‘bundle’ through the sheer generation of excitement and buzz.

The huge difference is their deep understanding of what can be put together that achieves this diffusion and adoption. What can others learn from this integrated approach to product and people?

Take the iPod for example

The first digital music player entered the US market in 1998 and it was not until 2001 Apple released the iPod.

The market had already shown signs of plateauing at the time of Apple’s launch, which must have been worrying.

Yet it was the unique factors of Steve Job’s clear vision of what a musical experience should have, Apple’s superb understanding of design and usage of materials, and its building upon the growing brand recognition and reputation as front edge.

Yet Apple also benefited from previous product releases because the behaviours and expectancies were being understood and were able to be articulated far more to validate and confirm Steve Jobs emerging view on what customers actually wanted- their own unique choice of music in the palm of their hand.

Steve Job’s innate sense of driving a solution to a winning value proposition by demanding all the parts to be incorporated, often taking uncompromising positions, was the additional factor. For example, being determined to offer a progressively growing store of downloadable music provided that incredible ‘complete’ usage experience. It met an un-articulated need but saw the different signals in its convergence of a total package.

Apple gave everyone in the adoption curve something that set their imagination alight.

Recommendations compounded so even late majorities and laggards felt compelled to buy, and the sales simply exploded.
The basic criteria with the theories of Roger’s Diffusion and Adoption were met.

Then look at the Apple iMac

For the consumer, Apple took away complexity. The learning gap became dramatically reduced.

It was quickly understood you took your computer out of the box and plugged it in.

The complexity of most of our past experiences in complicated set ups, the need to download and fiddle with conflicting software, had been taken away.

Apple set about integrating the system and providing a better user experience. It did away with proprietary connections, set USB and CD-Rom drives as their standard, dragging along most in the industry. It again focused on pushing to the maximum from Rogers characteristics of innovation.

The iMac proved to be phenomenally successful, with 800,000 units sold in 139 days. It’s translucent plastic case, originally Bondi blue and later various additional colors, is considered an industrial design landmark of the late 1990s.

Again design, attention to details, focusing on user needs to reduce complexity, offer relative advantage, make the way forward as compatible and integrated, allowing a fast set up to gain immediate experience and a great design or observability ticked all the boxes of Rogers Five Factors.

Then we get to the iPad

Where do you start? The iPad had built-in Wi-Fi and, on some models, cellular connectivity.

An iPad can shoot video, take photos, play music, and perform Internet functions such as web-browsing and emailing.

Other functions—games, reference, GPS navigation, social networking, etc.—can be enabled by downloading and installing apps. As of October 2013, the App Store has more than 475,000 native apps by Apple and third parties.

There have been five versions of the iPad. The first generation established design precedents, such as the 9.7-inch screen size and button placement, that have persisted through all models.

The iPad second generation  added a dual core Apple A5 processor and VGA front-facing and 720p rear-facing cameras designed for FaceTime video calling.

The third generation added a Retina Display, the new Apple A5X processor with a quad-coregraphics processor, a 5-megapixel camera, HD 1080p video recording, voice dictation, and 4G (LTE).

The fourth generation added the Apple A6X processor and replaces the 30-pin connector with an all-digital Lightning connector.

The iPad Air added the Apple A7 processor, the Apple M7 motion coprocessor and reduced the form factor for the first time since the iPad 2. iOS 5.1 added Siri to the third and fourth generations and the iPad Mini.

There have been two versions of the iPad Mini.

Apple were delivering wave upon wave of new technology in a rapidly accepted format.

A story of design, combining technology, understanding the unmet needs of the market, combining revolutionary materials. It filled a need, and it ticked all the boxes again of Rogers Five Factors of Product.

Yet we had by this time the real effect of the People Difference.
Apple have such a powerful body of innovators and early adopters creating such a pre-launch noise, it draws in early and late majorities.

Apple has been a fashion ‘must have’ statement.

Demonstration of products in Apple stores are ready to be put to any user test, the staff are providing you a ‘user experience’ and support structure that understands our needs and provide all your personal reasons to adopt.

The advocates of Apple products are phenomenal. They are nurtured, engaged with and pampered, as they generate such chatter and noise it can’t be ignored. It delivers the powerful messages Apple want to get out there for accelerating sales at mind-boggling speed.

Apple has institutionalized its product and people diffusion, and adoption process – can you?

We can all take away some powerful learning from this by aligning the theories of Rogers, articulated originally in 1962 and see how they seem highly relevant to Apple’s approach to its thinking.

They have added triggering (conversations, user experiences) with contagion and have been working the different tipping points to gain market traction, penetration and constant appeal to stay up to date and in tune with the latest and greatest.

Lastly let’s remind ourselves why diffusion often fails to occur

1. Getting the price wrong and staying stubbornly rigid with it
2. The wrong identification of the target markets
3. The poor selection of channels often because they are known, and they’re the sales forces’ most comfortable point of contact
4. A really poor communication of the product or service benefits
5. The unique attributes are over-hyped and quickly not seen
6. The new product really does not give many benefits over existing products
7. It simply has no innovative advantage, it was more of a cost-reduction exercise
8. The ease of access to the relevant information about the product is complex, difficult, time-consuming and unclear. It becomes complex
9. The real needs and expectations of the consumer were actually ignored, never discovered or just not met
10. The product or service offers no really clear value proposition to switch and buy.
I’m sure you could add a few more but I leave those to you.

The principles of diffusion and adoption I believe are both important in innovation.

Working the diffusion and adoption theories and putting these into your practice is something that needs an integrated approach, it might develop over time, perhaps through serendipity but knowing its principles helps you begin to map out the pathway.

This is the third and final post within the discussion on exploring diffusion and adoption for innovation.

******

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.

The post Exploring Diffusion and Adoption for Innovation – Part 3 first appeared on Building Your Innovation & Ecosystem Intelligence.

The future within our engagements will determine diffusion and adoption

It is all about letting go but also grabbing more at the same time, and then finding ‘it’.

Technology has opened up the door to both scale and fragmentation and social business is the one pushing through this open door.

We are increasingly facing the Collaborative Economy everywhere we turn. Social business is becoming the denominator of success or failure.

We are needing to confront the new questions that are emerging
New rules are emerging – you could say new theories – and where are these fitting within the corporate mindset?
The shift of what our customer means to us, are we still competing with them, pushing them to accept a value proposition that forces them to begin to look elsewhere?

Are we still determined to hang onto control, in the (mistaken) belief we know what is best for our customers?

Are we really bothering to learn the power of networks, cultivating communities, fostering co-creation and optimizing shared value, instead of just creating and selling things?

Are our structures and processes still stuck in the past or are you transitioning to managing a more social business that operates in more dynamic ways?

There are a huge number of new rules and ways to manage. It is the ones that master these that will succeed in diffusion and adoption at very different speeds than we can imagine today.

In three posts I am discussing different aspects and challenges within diffusion and adoption for innovation

The first post outlines the different theories and establish their value in our thinking.

The second post, this one, relates these theories into their to achieve success in penetrations of our target markets and increase sales through growing adoption.

The third and final post in this series looks at how Rogers’ theories relate to us in today’s connected world, and in particular with reference to Apple and finally offers up some of the reasons why diffusion can fail to occur.
Back to this blog……..

We are all in need of answering numerous questions and finding our way.

Social media is for many business organizations, the new kid on the block

It is relentlessly chipping away at the fabric of how organizations have been organized. In less than half a decade societal and cultural shifts through technology, the transfer to global open digital networks have taken us way beyond “just the internet” for connecting.

We are in need to engage in totally different ways. It is really not good enough to sell just products and services anymore. These are basic value propositions. Customers are looking on how these are connected into different “bigger pictures”. 

The questions of your sustainability approaches, environmentalism, corporate social good and responsibility and a growing interest in governance are shifting their thinking.

Your customers are wanting to connect and establish a different level of trust than simply those invested in a brand name, that is becoming table stakes or even irrelevant.

We are moving into a very different territory. Grasping the changes to your business are highly challenging.

Large organizations are being challenged by the sudden rise of self-organizing communities where people come together online and create shared value that often forms an immediate organization to challenge the existing. Traditional business models need to learn to adopt in different ways themselves.

In an era of high-velocity online start-ups, where the next generation of digital businesses are taking up the space as they focus increasingly on the dynamics of social business where does this leave our existing organizations?

Everything has sped up, we diffuse and adapt in seconds

There is an urgent need to “letting go and grabbing more”. Traditionally “we” provide products and services and many of our existing organizations are slowly coming to grips with providing on-line services.

The belief is this is enough to satisfy customers, keep them buying and using the product or service. Is it?

The social connected economy has reversed the relationship. Consumers just want to use and have provided product and services on ‘their’ demand and seek increasingly the platforms where they can easily go to find out and then use the required products and services. Often they don’t want to buy these, they just want to rent them to do the appropriate job.

The whole movement of jobs-to-be-done, identifying customer needs is yet again a place of increased focus. The larger organization still struggles with this as it wants to fit this ‘seen’ need into their structure and system.

They are spending growing time adapting while others are pivoting quickly to capture this fluidness in need.

In many ways diffusion and adoption lies more in the organizations inabilities than the customers. Perhaps the theories of Rogers have reversed.

It is the power of people and how organizations react and determine differences that will determine diffusion and adoption, as explained by Everett Rogers. Dion Hinchcliffe, an expert on next-generation enterprises suggests an Engagement Fabric.

Are we in a reverse situation for diffusion and adoption?

Consumers race to diffuse and adopt, it seems our larger business organizations struggle. The organizations are the ‘laggards’.

We need to think about the organizations ability to engage at scale. Perhaps we need a further theory to add to Rogers ones. The interpretation of the Engagement Fabric goes like this for aiding diffusion and adoption:

The organization as one does need to engage to any, not many. It is the ability to allow information to flow; we learn to aggregate stories or decipher trends to engage back to new groups of audiences that see your diffusion as valuable to their adoption.

The organization continues to throw open its store. The ability to engage and promote self-organizing communities to exchange and extend around our product and services and keep them as engaged stakeholders who you work to keep involved in the evolution that triggers better innovations.

Simultaneous engagement that is constantly synchronized with the evolving story, built more on business and social value, less on your product or service. Constant insights and thinking get captured for its ongoing community value and ability to keep improving on the product or service offered.

Making the space highly visible and user-friendly. By ensuring ‘ease of access to knowledge you are allowing conversations to build and become increasingly valuable to all involved in the community.

The ability to analyse, interpret and filter. Offer the place that captures the many good insights so as to set about the continued building of value into your products and services.

So we need to transform our own internal design to better diffuse and gain increasing adoption

To quote from Dion Hinchcliffe whose future thinking I have drawn heavily upon for this post makes this comment:

We need to rapidly move to an engagement platform

Diffusion and Adoption are even more of a business organization’s challenge to adapt to the most significant set of changes since the internet.

It is the power of all the disruptive technologies, the power of social business and the incredible impact of all the connected networks are accelerating acceptance or rejection.

Diffusion and Adoption is so far more complex but the principles of Rogers theories, offered nearly fifty years ago, can help to understand a single innovation perhaps.

It is today the way you build your platform for engagement which will determine where you stand in any adoption race for the health of your business and its model in the future.
It is the business organization that is in its race for adoption.

******

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.

The post Exploring Diffusion and Adoption of Innovation – Part 2 first appeared on Building Your Innovation & Ecosystem Intelligence.

According to Professor Clayton Christensen and drawn from his book “Seeing What’s Next: Using the Theories of Innovation to Predict Industry Change”, by Clayton M. Christensen, Scott D. Anthony, and Erik A. Roth published by Harvard Business School Press, the only way to look into the future is to use theories.

“The best way to make accurate sense of the present, and the best way to look into the future, is through the lens of theory.” The theory of innovation helps to understand the forces that shape the context and influence natural decisions.

This might not be fashionable for many because as soon as you introduce “theory” into the discussion for many of my practical colleagues they want to dismiss it.

Going back to Christensen “good theory provides a robust way to understand important developments, even when the data is limited. “Theory helps to block out the noise and to amplify the signal”.

Diffusion of Innovation Theory is important for our innovation understanding
One set of theories I believe we simply cannot ignore even more today lies around the work of Everett. M. Rogers where he outlined his thinking in his book Diffusion of Innovations the first edition was published in 1962.

The fifth edition (2003, with Nancy Singer Olaguera) addresses the spread of the Internet, and how it has transformed the way human beings communicate and adopt new ideas.

Over three posts I will look at different aspects of “diffusion and adoption”

The first post, this one, outlined the different theories and establish their value in our thinking.

The second post, relates these theories into their to achieve success in penetrations of our target markets and increase sales through growing adoption.

The third and final post in this series looks at how Rogers’ theories relate to us in today’s connected world, and in particular with reference to Apple and finally offers up some of the reasons why diffusion can fail to occur.

First we need to have a clear grounding or reminder within the theories
By developing our understanding of why some products seem easier to diffuse while others can take longer or often fail, innovators can improve their likelihood of understanding the differences through exploring these different diffusion and adoption theories.

Besides the classic “S-shaped curve” associated with diffusion, it is useful to also reflect on this tougher curve to manage from its development costs into profit requires a greater focus on the commercialization stages.

Product and People determine diffusion and adoption
According to Rogers, the rate of diffusion can be attributed to a combination of “product differences” and “people differences”

Product differences
Research suggests that up to 87 per cent of the variance in an innovation rate of diffusion can be attributed to the following five product characteristics. These are known as Rogers’s Five –characteristics of Innovation.

Relative advantage refers to the degree perceived to be better than the product (or service) it replaces.

Compatibility is the extent to which an innovation is perceived as being consistent with the values, past experiences and needs of potential adopters.

Complexity is the degree to which the new innovation is perceived as being difficult to understand or use.

Trialability is the degree to which the new innovation can be experimented with, piloted and used on a limited basis.

Observability is the degree to which the results of an innovation are visible, observed and communicated to others and where the rate of adoption can often be determined.

People differences
Once the product’s position in relation to the Rogers Five Factors is known, the diffusion process is best managed by focusing on the people’s difference.

The classic bell curve is broken down in the five categories of adopters. 

It is from this initial work of Rogers we then got Geoffrey Moore’s classic on “Crossing the Chasm” which recently has been significantly updated in a recently released book around the Technology Adoption Lifecycle.

The chasm can happen throughout the early adopter’s phase, you have to be alert and responsive enough to find solutions quickly enough to bridge this and ‘cross that chasm.’ Pivoting on the parts that are good, exploring the parts that are needed.

The five adopter categories are:

Innovators– venturesome, risk-taking, information seeking, early seeking status and very experimental, enjoy the degree of early challenge or even uncertainty involved.

Early adopters– Often respected opinion leaders within their social groups, seen often as role models for others.

Early majority – more deliberate before adopting new ideas; interact frequently with peers and trendsetters. They like to merely stay ahead within the curve from that more informed decision-making.

Late majority – Tend to be sceptical, cautious to adopt but ‘feel’ pressure of peers to adopt, tend to need intervention strategies to overcome barriers and see their ‘needs’ resolved by the innovation

Laggards – Traditional , last in the social system, often they pay little attention to opinions of others, they have more a clear point of reference in the past to overcome, are often suspicious of new innovations and their decision process is often lengthy.

Then we have the decision process or stages of adoption:

Awareness and Knowledge – refers to a customer’s acknowledgement of the presence or existence of the new innovation and where they form a general perception of what it might entail and is often driven by the intersection of need recognition through marketing communications. This is the point of being inspired to find out more.

Persuasion and Interest – this occurs when a consumer processes the available information associated with the innovation and considers the product or service’s appeal on this. This positive or negative attitude tends to be based on the five characteristics mentioned above. Here the consumer actively seeks out information and details.

Decision and Assessment – Having considered the persuasion factors the consumer will come to a decision about whether to adopt or reject the innovation. Their activity in seeking out advice, data gathering, comparing or making different assessments happen clearly here. They consider the switching costs and weigh the advantages up. This is the hardest stage to understand.

Implementation and Exploration – These are the series of activities to put the innovation to use. The consumer employs the innovation to a varying learning degree. The usefulness is determined and they may search for further information about it.

Confirmation and Adoption– is mostly concerned with post-adoption behaviour exhibited by the adopter, reinforced by the innovation’s actual delivery against the relative advantage ‘claims,’ its complexity and compatibility on their understandings. The individual finalizes their decision to continue using it or searches for extending its use to its full potential.

So in summary for this opening post:
Diffusion is the manner in which innovation spreads. It is the degree how we facilitate, accelerate, and sustain it.

There are constant difficulties in exploiting these different theories within organizations, the questions are where to place the emphasis and the means of communicating these. The process is contingent upon the structural, cultural and size and scope considerations.

You have to watch for that constantly changing the implementation requirements and lack of sufficient resources or application, as they considerable constrain the innovation outcomes and often you don’t spot these until it is too late

The execution or commercialization stage of any new innovation often fails to address the theories offered by Rogers adequately enough, then organizations often suffer poor diffusion and adoption rates, unaware of the considerable efforts this stage of understanding diffusion and adoption needs to address.

The second part of this post will deal with….

My second post in this diffusion and adoption discussion will deal with managing within a far more fluid set of conditions than we have seen to be facing previously.

The combination of technology, social media and the internet gained a ‘closer’ relationship with final consumers encouraging engagement and feedback has introduced a far more dynamic environment.

Innovation adoption or rejection is getting riskier, and far more complex and we need to bridge the learning gaps far better and smarter. Are Roger’s theories still relevant or even more so today and in the future?

Then the third post provides different examples of diffusion and adoption and offers a starters list of why diffusion can often fail to occur.

******

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, it’s well worth the visit.

The post Exploring Diffusion and Adoption for Innovation – Part 1 first appeared on Building Your Innovation & Ecosystem Intelligence.

They lead this article with “one view of complexity that holds that it is largely a bad thing- that simplification generally creates value by removing unnecessary costs”. Certainly we all yearn for a more simplified life, structure, organization, approach to systems or just reducing complexity in our daily lives to find time for what we view as improving its ‘quality’.

Within the article they argue there are two types of complexity – institutional and individual.

The former concerns itself with the interactions within the organization, the latter is the way individuals or managers deal personally with complexity.

The real important take away from this article for me was when organizations treat complexity as something they must overcome, reduce or try to ignore they miss opportunities. Complexity, the authors argue, should be seen as a challenge to be managed, managed well, and its full potential exploited, not as a problem to be reduced or eliminated. It is through the nature of these complexities we achieve competitive advantage and can exploit more of the flow of knowledge for those new sources of new profit and wealth creation.

They suggest organizations need to decide on where to hold complexity within any design and build the right capabilities where they matter. I would argue innovation certainly matters, and it is complex and needs to be understood as exactly that, and managed accordingly not in piece meal fashion. Complexity matters in building the right processes, skills and culture but because they don’t behave in linear ways and any ‘messing’ with the complexity and relationships within this can have an awful lot of unintended consequences.

We have choices of complexity

There are different types of complexity to manage. Work conducted by Julian Birkinshaw and Suzanne Heywood suggested four types of complexity. I only summarize these here.  Imposed complexity, those interventions both internally and externally that require ‘higher’ insight. There is the inherent complexity found with any organization and presently managed through striving to be more efficient and effective. There is designed in complexity, where innovation needs to fit more. These are choices about how, where and why an organization sets about its operation. These can be constrained, under invested in, even jettisoned but do have lasting consequences for the future of the organization. This is the area of strategic consequence as these can limit competitive advantaged from the level of innovation intensity chosen as an example. The fourth is unnecessary complexity where increased misalignment resides, it is sometimes easy to recognize but often hard to let go as it sometimes makes up “the way things are run around here” and have a richness in history.

The challenge of complexity within innovation

If you can begin to identify complexity that hampers effectiveness you can begin to remove it. What you have to be very clear upon is having a complete understanding, or a well informed one on all the effects if the complexity part you are removing is not the route to value and often innovation. The more creative side certainly does get constrained and caught up in this often shorter term pursuit of effectiveness for effectiveness sake and you suddenly don’t have the bandwidth for innovation exploration and more.

Do recognize that innovation is complex, recognize it does have to be handled carefully but it needs to also be fully understood for what it is, a complex adaptive system. It cannot be treated in the same way as effectiveness or efficiency can. It  needs ‘actively’ managing differently, for all the future opportunities it holds by placing the emphasis on building greater innovation capabilities to make it ‘dynamically’ work. Otherwise you end up with unexplained consequences to poorer performance from your innovation activities and often at a loss to explain why.

We do need to relate more to complexity as it comes with the turf if you want really lasting innovation.

The post Cracking the complexity code first appeared on Building Your Innovation & Ecosystem Intelligence.

He discusses adoption, team practices, ubiquity, networks, language actions, the practice of innovation and other related topics. All are stimulating and worth finding the time to read but one caught my eye and

I’ve gone back to it at least four, maybe five times. It intrigues me.  It is entitled “The idea idea” written in early 2011 and asks the question “What if practices rather than ideas are the main source of innovation?”

I think we all agree “ideas pervade our professional work” and as Professor Denning points out “we borrow them, we apply them, we solve problems with them, we create new ones, and we try to foster more of them in our teams”.

We do put a disproportionately greater emphasis on ideas yet as he points out, all these great ideas and the energy applied to them we still end up with really poor adoption rates, he suggests our success rate in business are around 4%.

All of this ‘idea’ energy seems to be wasting so much time, resources and money. He puts this so well “we are idea rich, selection baffled and adoption poor”

The whole thrust of the article is perhaps that innovation is not ideas generated and I agree so much on this, but practices adopted. We need to spend more efforts on the skills and adoption of new practices and as he suggests “as the framework for new practices”
The two schools of thought
He suggests the two schools; if you believe ideas are the key to innovation you will put your efforts into generating, analysing, selecting and publicizing ideas where the emphasis is on creativity, imagination, borrowing and recombination.

The other is adopting new practice as the key to innovation- the efforts go into selling others the value of doing new practice by building credibility it works, teaching people how to do it, furnishing tools to help them and providing the guidance and leadership to overcome obstacles and resistances.

I’m sitting more and more in the second school, I enjoy the first school of believing in ideas but I feel, well actually place my focus on the second school- the process of new practice. This is why and where I earn my living (or try too) or increasingly so. Also this is why I just keep going back to this article, it resonates so much for me, a confirmation of a confirmation.

He puts both cases well- outlining that “the diffusion model and the pipeline model share this common feature that they both put idea generation as their source. They differ on how ideas move from source to market”

The case of practices he starts by rightly stating “an idea that changes no one’s behaviour is only an invention, not an innovation”. He talks briefly of “the prime innovation pattern” as part of a new theory where innovators goal is to bring about changes of practice to change that “sense of disharmony” detected and they go through different activities to achieve this change.

This gets to the point that the practice suddenly becomes adopted, someone starts doing something different, often in the early stages as improvisation, to overcome something blocking them from doing the job they need to meet. When it is seen as superior others imitate it, the practice spreads.

Where I feel Absorptive Capacity fit here

Many people have offered views on this adoption and promoting its practice as it is aiding making things better for others. I very much wish more people would look a little harder at Absorptive Capacity for many reasons, some of those I’ve previously outlined.

The more we access, anchor and diffuse capability the greater chance for innovation. This links into Absorptive Capacity and for instance Zahra and Georges work on acquisition, assimilation, transformation and exploitation as the four phases of Absorptive Capacity.

Professor Denning rightly suggests it is finding the right balance between cultivating ideas and cultivating (new) practices. Maybe we should all question our balance on this?

He offers three thoughts

The iceberg theory- the visible top part (about 10%) is analogous to the set of ideas, the invisible submerged part (about 90%) relates to the practices of innovation. The practices keep the ideas afloat.

He suggests you beware of the idea- pursuing ideas for the sake of them- and you keep deferring adoption until the idea is perfected. He suggests you need to put 10% of your efforts into explaining the value and principles of your ideas and 90% into fostering the new practices you advocate and it is the work of adoption is from the beginning.

Lastly, it is how  and what you learn from experiments and trial practices. It is then later  how you distil the knowledge gained into the pursuit of the emerging ideas, these emerging new practices. This makes for less value placed on ‘crude’ ideas, more on ‘refined’ ones that do raise the chance of market adoption significantly.

You just keep filtering and improving, experimenting and exploring not just pushing ‘ideas’ simply through the innovation process. You seek to raise the adoption rates of not just translating the idea but the very new practices that get you to that success.

So, it is the connections between ideas and adoption, the idea adopted into practice, and it is the focus on the “dispersing” and “adapting” that accelerates innovation, simply not just the ‘idea’ alone worked through in ‘established’ ways.

What are your thoughts?

The post Making innovation practice spread first appeared on Building Your Innovation & Ecosystem Intelligence.

Maybe I’m taking on more than I can chew here but I’m going to attempt to explain why innovation can be so complex and requires an adaptive system.

I apologise if it does not work for you, or you simply just give up on this but I am going to try to explain innovation as a complex adaptive system.

Why- I like the pain involved!  I’m certainly not in any shape or form an expert or even that much of a student of complex systems, and what it fully consists of, but I do need to explore this more, and a little shared pain helps in this as I go.

This issue is one that I consistently come across many references to innovation being a complex system. The trouble is I’ve never been fully clear on what determines the make up a complex system for innovation. I’m not sure anyone does for complex systems either!

So my aim here is to establish a direct and clear set of links across innovation and complexity without it involving me in ploughing through incredibly ‘dense’ academic papers on this subject.

It is amazing how Wikipedia is becoming rapidly the first call of reference, is it because it takes away all this density found in academic papers, or that the academic papers are written mostly for an informed group and for those of us, obviously sitting on the outside of this ‘elite’ group, we gravitate to where we seem welcome to gain a ‘reasonable’ and quick understanding. So this is my starting point.

Irrespective our starting point has to be definitions

So borrowing from Wikipedia  let’s define:

A complex system is a system composed of interconnected parts that as a whole exhibit one or more properties (behaviour among the possible properties) not obvious from the properties of the individual parts.

A system’s complexity may be of one of two forms: disorganized complexity and organized complexity. In essence, disorganized complexity is a matter of a very large number of parts, and organized complexity is a matter of the subject system (quite possibly with only a limited number of parts) exhibiting emergent properties.

Complex adaptive systems are special cases of complex systems. They are complex in that they are dynamic networks of interactions and relationships not aggregations of static entities. They are adaptive in that their individual and collective behaviour changes as a result of experience

So did that help?

Thankfully whoever wrote the Wikipedia entries kindly gave some examples of complex adaptive systems. These include the stock market, social insect and ant colonies, the biosphere and the ecosystem, the brain and the immune system, the cell and the developing embryo, manufacturing businesses and any human social group-based endeavour in a cultural and social system such as political parties or communities.

There are close relationships between the field of CAS and artificial life. In both areas, the principles of emergence and self-organization are very important.

So does innovation also fit within complex adaptive systems?

If we take the suggested feature list presented on Wikipedia’s entry for complex systems (http://bit.ly/nF5F3G ) I feel innovation fits. Let’s make some comparisons and this is my attempt to quantify innovation for being a complex adaptive system in the table below. It is a work-in-progress.

Components of an innovation complex adaptive system compared.

The source for the features used for a complex adaptive system has been taken from: http://en.wikipedia.org/wiki/Complex_adaptive_system and for the innovation complex adaptive system is my thoughts on where the feature does apply in innovation to fit.  W-I-P 09 02 2012

Do you agree, do you see other ones, or have I lost you?

Cracking the complexity code

There was a good article within the McKinsey Quarterly, published in 2007 entitled “Cracking the complexity code” written by three authors Suzanne Heywood, Jessica Spungin and David Turnbull that leads with “one view of complexity holds that it’s largely a bad thing- that simplification generally creates value by removing unnecessary costs”.

Certainly, we all yearn for a more simplified life, structure, organization, approach to systems or just reducing complexity in our daily lives to find time for what we view as improving its ‘quality’.

Within the article, they argue there are two types of complexity- institutional and individual. The former concerns itself with the interactions within the organization, the latter is the way individuals or managers deal personally with complexity.

The real important takeaway from this article is when organizations treat complexity as something they must overcome, reduce or try to ignore they miss opportunities.

Complexity, the authors argue, should be seen as a challenge to be managed, managed well, and its full potential exploited, not as a problem to be reduced or eliminated. It is through the nature of these complexities we achieve competitive advantage and can exploit more of the flow of knowledge for those new sources of new profit and wealth creation.

They suggest that organizations need to decide on where to hold complexity within any design and build the right capabilities where they matter. I would argue innovation certainly matters, and it is complex and needs to be understood as exactly that, and managed accordingly not in a piecemeal fashion.

Complexity matters in building the right processes, skills and culture but because they don’t behave in linear ways and any ‘messing’ with the complexity and relationships within this can have an awful lot of unintended consequences.

The other correlations that work for me

The late Everett Rogers offered us the diffusion of innovation, which gave us a frame to understand the process by which innovation spreads within social systems.

Complex systems are equally about relationships among the members of a system. You move into more the emergent behaviours that become increasingly adaptive in response to the environment and what interact within it.

Diffusion occurs in complex systems where networks overlap, exchange and learn. Both Diffusion and Complex Systems adapt and adopt with the endpoint of making ‘it’ into more of an ordered system.

The more you work the system, the fitter for the purpose it becomes, the more it diffuses out, the more dynamic it becomes and increasingly valuable from these interactions.

Complex adaptive systems don’t operate in equilibrium conditions

I’ve been also in a set of debates in recent days around management looking for stability, for predictably, looking to take as much complexity out of the system as possible- often sometimes labelled as ‘variance’.

This leads to enforcing business as usual as the modus operandi for innovation to ‘fit’  but we are faced with the very opposite in today’s world, the need to ’embrace’ reoccurring change.

We need to manage complexity and we do need innovation so we do need to obtain as much diversity and non-linear structure in what we do to allow diversity and all possible options. Our innovation systems are being forced ‘open’ making them even more complex and our energies will have to turn from ‘containment’ to more ‘adaptive’ and responsive ones to manage going forward.

We need to not reject complex systems we need to understand them, we need to embrace them and learn to determine what needs to be complex and what doesn’t. This requires a real ‘flow’ of different energies to maintain the organization of the system, it needs active managing. It will only become harder.

For innovation to work, to thrive, and to provide a sustaining payback, it needs to be seen as a complex adaptive system. We can’t keep hiding and pretending the ‘bits and pieces we play with and constantly fiddle with, called our innovation system, will be sufficient. We do need to understand innovation in its entirety.

We have choices of complexity

There are different types of complexity to manage. Work conducted by Julian Birkinshaw and Suzanne Heywood suggested four types of complexity. I only summarize these here.  Imposed complexity, those interventions both internally and externally that require ‘higher’ insight.

There is the inherent complexity found with any organization and presently managed through striving to be more efficient and effective.

There is designed in complexity, where innovation needs to fit more. These are choices about how, where and why an organization sets about its operation. These can be constrained, underinvested in, and even jettisoned but do have lasting consequences for the future of the organization.

This is the area of strategic consequence as these can limit competitive advantages from the level of innovation intensity chosen as an example.

The fourth is unnecessary complexity where increased misalignment resides, it is sometimes easy to recognize but often hard to let go as it sometimes makes up “the way things are run around here” and has a richness in history.

The challenge of complexity within innovation

If you can begin to identify complexity that hampers effectiveness you can begin to remove it but be really clear on the effects if the complexity part you are removing is not the route to value and often innovation, which certainly does seemingly get constrained and caught up in this often shorter-term pursuit of effectiveness for effectiveness sake and you don’t have the bandwidth for innovation exploration.

Recognize innovation is complex, recognize it does have to be handled carefully but it needs to also be fully understood for what it is, a complex adaptive system. It cannot be treated in the same way as effectiveness or efficiency can.

It needs ‘actively’ manage differently, for all the future opportunities it holds by placing the emphasis on building greater innovation capabilities to make it ‘dynamically’ work.

Otherwise, you end up with unexplained consequences to poorer performance from your innovation activities and are often at a loss to explain why.

We do need to relate more to complexity as it comes with the turf if you want really lasting innovation.

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