Welcome to the Journey: Innovation Essentials

A good foundation in the essentials of innovation is, well, essential!

This journey covers how ideas spread – diffusion; how they gain traction – adoption; and the often (mistakenly) ignored topic of resistance.

You’ll get a deeper knowledge of the challenges and solutions to diffusion and adoption (in 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.

Creating an innovation success, in practice, means:

  1. your innovation helps the customer make progress in their life
  2. you have removed resistance to your innovation
  3. you’ve worked out how to spread knowledge about your innovation within your target market (the right network), and
  4. you can scale

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

Reading time <7 mins

Innovations diffuse - knowledge spreads - across a social system through communication channels over time. Your target market is this social system. And a social system is effectively a network. We take a network first look at diffusion in this article.

Some in the social system are innovators, some imitators. And they can be further divided as Rogers' classic 5 Adopter Types:
Innovators, Early Adopters, Early Majority, Late Majority, and Laggards. Gladwell talks of tipping points and connectors, mavens and salesmen. And Bass provides a mathematical basis to all this - which nicely aligns with real-life observations.

Can we influence diffusion speed? Well, we know that one adopter type is rarely influenced the same way as the group to their left. And that for high-tech innovations there is a giant chasm between Early Adopters (EA) and Early Majority (EM). Moore proposes building from a niche beachhead with additional niche markets. Maloney suggests we need to change message and delivery method after 16% have adopted. And what of Gladwell's connectors, mavens and salesmen?

Reading time <13 mins

Innovation adoption is the act of individuals or organisations deciding and starting to use an innovation.

It is closely related to innovation diffusion - spreading knowledge about a particular innovation through a target market (social system / network). And is intricately linked to the often forgotten topic of innovation resistance. As well as having influences with change management, for example, the classic Kotter's 8 steps.

In this article, I explore two main topics.

First, what adoption means for individuals and organisations. Both from the classic product view, as well as for services and platforms (which need both sides of the platform to adopt). And using the perspectives of Rogers' adoption curve, Rogers' Innovation Adoption Decision Process (enhanced to see the role of innovation resistance).

And secondly, how we can speed up rates of adoption through Rogers' adoption variables.

Reading time <11 mins

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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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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Your target market is a network. Can we take advantage of that network's structure to accelerate diffusion? Or can we make simple structure changes to get that acceleration?

We already have seen that diffusion is the spreading of a message through channels of a social system. In the news we always here of social media influencers, which are really individuals who have many people connected to them. And Gladwell talks of Mavens, connectors etc. The number of connections and their directions are just two metrics we can measure of a network. Others, such as density, weak ties, structural holes give us even more information about how well messages are likely to spread.

If we can find out a network's structure, perhaps we can engineer it to make things easier for us.

However, we might find it is easier to do this within organisations - where how people really connect is often different to the stated top down organisation hierarchy. But general public networks can be harder to understand

Reading time <5 mins