Rolling Out An Idea

Posted: December 5, 2012 in CRM, social marketing

Has the emergence of social technology been faster than the roll out of other advanced technologies like CRM and ERP and why?
 

I have recently been reading a dense technical book from 1990 with the improbable title (for CRM), The Rise and Fall of Infrastructures — Dynamics of Evolution and Technological Change in Transport, by Arnulf Grübler.  It’s a well researched examination of some of the social and economic trends that influence adoption of new transportation paradigms such as rail and autos.  But it also has some nuggets applicable to CRM today.

I have lately wondered if our industry has speeded up in adopting innovation.  That was my hunch, and I am pleased to say that Grübler confirmed it.  His book was published in 1990, well before so much of what we take for granted such as the ubiquitous Internet and social media, were even close to business reality.  But it has a lot to say about those topics even now.

Grübler quoted other researchers and sources, most notably, Everet M. Rogers and his 1962 book, Diffusion of Innovations.  It is hard for me to say definitively, but many of the ideas from Grübler and Rogers appear to have found their way into our consciousness through popularizers such as Geoffrey Moore and Clayton Christensen.  That’s not to discount Moore’s and Christensen’s work; it is only to show that their ideas spring from deep sources.

Interestingly, while they and we are familiar with the bell curve segmentation of innovation adoption (Early Adopters etc.) the original concept of adoption was actually that of diffusion, as in the diffusion of an idea through a market or social network.  I think we lost something when we began thinking in terms of adoption rather than diffusion.

The change represents the commercialization of an academic idea and the concept became one of vendors persuading adopters and we lost the connotation of a natural rhythm.  The concept of diffusion carries with it the idea of a rate by which adoption takes place by more or less organic means — someone you trust gives you an idea that you validate for yourself and later you may influence others just as you were initially influenced.

I found two ideas under Rogers in Wikipedia that I think are relevant to this discussion.  The first one defines three types of innovation-decisions (my comments in Italics)

  1. Optional Innovation-Decision — made by an individual who is in some way distinguished from others in a social system.  This individual might be the “cool” kid in school that everyone wants to emulate, such as the quarterback or someone who has distinguished him or herself.  It could also be the class rebel.  When this kid does something, others take it up to be like him or her.
  2. Collective Innovation-Decision — made collectively by all individuals of a social system.  It is hard to distinguish this as a cause or as an effect of the decision above.  When “everyone” is doing something, the original seed crystal — the cool kid — might be lost to history.  Regardless, this decision appears to be a driving force behind exponential growth of an idea.
  3. Authority Innovation-Decision — made for the entire social system by a few individuals in positions of influence or power.  This is typically how big organizations buy and why salespeople try so hard to reach the C-level.  When the idea becomes institutionalized, i.e. everyone has to have it and the adoption is taken over by management.  This is especially noted in business adoption of large or expensive systems such as CRM.  Social media is right at the interface of a Collective Decision and an Authority Decision.

The second concept defines the intrinsic characteristics that influence an individual’s decision to adopt (or reject) an innovation.

  1. Relative Advantage — How improved an innovation is over the previous generation.  Vendors of new category items always score high here because there’s little to compare with.
  2. Compatibility — The level of compatibility that an innovation has to be assimilated into an individual’s life.  In software this issue is often dealt with by the CIO who can over rule a purchase if it conflicts with the established order.
  3. Complexity — If the innovation is perceived as complicated or difficult to use, an individual is unlikely to adopt it.  Departmental buyers often have the say here, even after a purchase as anyone who has ever tried to get sales people to use a difficult SFA package knows.
  4. Triability — How easy an innovation may be experimented with.  If a user is able to test an innovation, the individual will be more likely to adopt it.  SaaS and subscriptions have a big advantage here, no wonder they are in the ascent.
  5. Observability — The extent that an innovation is visible to others.  An innovation that is more visible will drive communication among the individual’s peers or personal networks and will in turn create more positive or negative reactions.  We use case studies to fill this need but also, late adopters need good observability to make a positive decision.

We see much of these five characteristics woven into sales and marketing strategies aimed at helping a new idea become diffused in a market.  In fact if you take these five characteristics and apply them to the bell curve of adoption —including Innovators, Early Adopter, Early Majority, Late Majority, Laggards — you can reasonably show a one to one correlation demonstrating these characteristics as the dominant features for an adoption (or diffusion) phase.

If you apply this knowledge you can begin answering the question I posed at the beginning, namely, has our marketplace speeded up somehow?  I say the answer is “yes” in large part due to social media.  What’s interesting to me is that social media  is also the best mode of promoting itself to the marketplace.

As an innovation decision, social began as an Optional-Innovation Decision.  Recall that only kids at Ivy League colleges were able to join Facebook initially but then the phenomenon quickly spread to other schools (a Collective-Innovation Decision).  When Facebook and other social technologies let down their barriers to entry the rest of the market, from high school kids to adults, joined in to the point that if Facebook were a country it would be one of the most populous on the planet.

But, back to the speed up.  It took, by my estimate well over a decade for CRM to become mainstream.  If you go back to the first release of ACT! in the mid-1980s to 2000, the year that Siebel’s revenues surpassed the $1 billion mark, it took about fifteen years for CRM to become prominent. By 2002 Siebel (founded in 1993) was cresting because of persistent rumors that it was hard to use (the Complexity characteristic).  Also Salesforce was out flanking Siebel with the Triability characteristic of its SaaS model.

Now take a look at social.  The signal event of the social revolution in the front office is the fourth edition of Paul Greenberg’s magisterial study, CRM At The Speed Of Light, published in 2009, just five years after Facebook was founded in a dorm room at Harvard.

So as we turn the corner into 2013, we can look back on a very rapid adoption of social media, and it’s not an illusion.  It happened in part because the medium became the message in the same way that Marshal McLuhan described TV.  But more to the point, as a network, social had the advantage of bi-directional communication and instant feedback that TV never had and that only accelerated things.

What this rapid adoption, thus far, says about the future is somewhat puzzling.   Social adoption is now at the level of an Authority Innovation-Decision but at the same time, entrepreneurs continue innovating on their original innovations and popularizing them through the same channel that has already demonstrated a propensity for truncating adoption and refining innovations with record speed.

But innovation is proceeding down numerous smaller pathways as we discover more uses in segmentation, sentiment and all the other ways there are to analyze customer and market behavior.  Will these permutations drive a round of complexity or will vendors skip over that and drive Triability and Observability?  They will if they’re smart but maybe they all don’t read my column.  Ha!

Comments
  1. studentforce says:

    Hey Denis,

    One of your best post’s I believe. Thanks for this. It’s inspiring – especially to me. Happy holidays!

    Ed

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