94% of executives have an innovation problem

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Innovation Essentials
What is Innovation?
Understanding Service
Making S-D logic Approachable

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Welcome to the Innovation Essentials Journey


Any writing on innovation needs to cover some essentials. And that is exactly what this journey does – with some extras! We’ll look at how innovations spread – diffusion; how they gain traction – adoption; the often missed aspect of resistance; and how to avoid innovation theatre.

We’ll get a deeper knowledge of the challenges and solutions to diffusion and adoption. And do so in a different from normal way: a network-first manner. Bass, Rogers, Moore, Gladwell (the tipping point) and the big/little hire of Christensen’s jobs to be done theory are all looked at. As well as a grounding on the types of resistance and what can cause it. Just remember the first version, and ultimate failure, of Google Glass.

First, we’ll expose a new definition of innovation. One that is built out from service-dominamt logic and a new view of value.  Focused around helping beneficiaries make progress (functional and non-functional) better than they can currently.

And, we’ll explore something that many of us miss. Or simply don’t know of. Innovation resistance. We tend to believe that all innovation is good and we just need to get it diffused and adopted. But beneficiaries often resist innovation. Why? And What can we do? We’ll find out.

Moreover, we need to make sure our innovation activities don’t descend into innovation theatre. That is, performing activities that ultimately lead to no tangible outcome. You’ll recognise the feel good factor of running an innovation campaign across your enterprise but really the tangible returns have been low? That’s innovation theatre.

As we close this journey we’ll look at some of the maths behind Bass’ diffusion model. You don’t need to dig into this. But it’s kind of fun, and has all sorts of applications. And finally, we’ll take a quick peek on how network structures can alter the diffusion rates. Which implies we can harness network theory to our advantage (influencers, anyone?)

Evolving the definition of innovation
beneficiary-focussed helps make progress improves minimised-resistance offering resource coordination scalable sustainable co-creation of value value proposition
An updated view of what is innovation - built from a new definition of value (progress sought, progress offered and progress achieved) and insights from service-dominant logic.
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Work in Progress

Let's define innovation, avoiding the trap of value-in-exchange (that normal definitions have) and open our thinking up for wider success.

Innovation is creating and offering a new (to the organisation, market/industry, or world) value proposition:

  1. that helps a beneficiary make progress better than they can currently
  2. that improves during, or as a result of, the naturally occurring value co-creation
  3. which is delivered through the scalable and sustainable co-ordination of skills and resources (often across an ecosystem)
  4. and where resistance is minimised

Note, in particular, how our service-dominant logic lens steers us to focus differently on value. compared to normal old-school definitions

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Diffusion of Innovation
adopter types crossing the chasm diffusion early group imitators influence majority mavens moore bass people rogers social network tipping point
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Innovations diffuse - knowledge spreads - across a social system through communication channels over time.

We'll take a network-centric view of diffusion and see how Bass' model and Rogers' adoption curve help us understand diffusion

Then we'll look at Moore's crossing the chasm and Maloney's 16% rule to understand some issues. And finally look at the tipping point, and Gladwell's mavens, connectors and salesmen.

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Innovation adoption
change management adoption decision diffusion social-network early adopters knowledge-step perceived-attributes early majority adoption rate rejection resistance relative-advantage step laggards
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Innovation adoption is when individuals or organisations decide and start using an innovation.

We'll look at the classic adopter types, the adoption decision steps, and how adoption can be accelerated

But also we'll put the adoption decision in the context Christensen's Job theory (big and little hires). And see how resistance to innovation should be included in the classic adoption steps

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Innovation Theater
action activities ambition change needle moving ienterprise innovation = change execution ideas organisation structure performance innovation problems resistance complexity vision
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Innovation = change.

And if your enterprise can't handle, or resists, those changes, then your innovation activities are simply innovation theater (activities that deliver few/no tangible results)

Worse, the outcome of those activities are likely increasing that resistance to change

Calls to action, hackathons, open innovation, innovation spaces/rooms, appointing chief innovation officers, claiming to be an accelerator, building silicon valley outposts - all these, and more, are at risk of being innovation theatre

Here's why....

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Innovation Resistance
economic functional traditions usage patterns norms opposition perceived image physical postponement social rejection resistance
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Innovation resistance – users postponing, rejecting, or even objecting/demonstrating against – is the sadly neglected child.

We are all familiar with its sisters: diffusion and adoption. Yet, we see innovations failing again and again. And not addressing innovation resistance is a candidate for why this is so. As well as for why 94% of executives are disappointed with innovation performance. Why? Well, in order to get adoption we have to:

  1. address Rogers’ classic adoption variables, and
  2. remove resistance (opposition, rejection and postponement) to the innovation
Too often we only see and address the point 1. Yet:
  • “innovation resistance seems to be a normal, instinctive response of consumers” (Sheth and Ram, 1989)
  • "customer resistance is usually one of the greatest risks to innovation" (Heidenreich & Kraemer, 2015).

In this article, we look at innovation resistance and why it occurs.

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Diffusion of Innovation II – Bass Diffusion, let’s get Mathematical…
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How should you build up your supply chain? What are the real market sizes of Rogers' adopter types? When is best to launch the next generation of your innovation?

To answer those, we take a deeper look at the mathematics behind Bass' Diffusion Model

The maths helps us understand the split of innovator and imitator types - captured as two co-efficients in the formula. That allows us to understand where to apply internal and external influence. We can use existing sales (or a comparator) to derive these two co-efficients and therefore predict adoption. That helps us manage supply chains and real market size. Additionally, we can determine when it is best to launch the next generation of the innovation (and see what happens when we lauch to early or late)

And, best of all...it all fits real life!

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Innovation: Diffusion, and What Network Topology can tell us
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Work in Progress Early Thoughts

Diffusion happens across a social network. Can we take advantage of that network's structure to accelerate diffusion?

To do so, we look at the network's topology. Its centricity, density, weak ties, structural holes etc

Which. in plainer speak, are the influencers, and Gladwell's Mavens, connectors etc. And where we might need to target a few innovator types, or many

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