Who will transform the transformers?
Part 1: Process model

What happens when the transformation practice becomes commoditised? Is this a good thing or a bad thing? Does it become vulnerable to disruption like any other business? Recent re-orgs at leading global consultancies beg these questions.

Highly regarded ground breaking facilitation programmes were once untouchable revenue generating machines. These "tough economic times" have since forced these programmes either down the P&L to the lowly cost section or off the P&L altogether.  Innovation, collaboration and transformation now reside in the same pool as facilities-management and stationary or they are gone entirely. To paraphrase a leader in the field, that’s the death of that.

Process model vs business model

How did this happen? Is it indeed these “tough economic times” or is it something else? Has the once highly successful transformation programme failed to jump the S-Curve? Does the innovative programme require innovating? 

I'll attempt to answer these questions by distinguishing between the process model and the business model.

On the process side, there are plenty of old and new ideas around facilitation, innovation, collaboration and transformation. Older processes include attempts to innovate through painstaking scientific research and analysis as well as through group genius by way of facilitation and collaboration. The latest efforts, on the other hand, centre around leveraging the electronic social network [the subject of this blog post].

On the business side, a transformation practice has to generate sufficient value to justify continuing or it becomes a cost centre. Looking at the sales process linearly this should include marketing followed by the sale of the service and thereafter by continuing services [the subject of Part 2].

Examining these two things, the process and the business, just might allow us to transform the transformation practice and give us next-gen facilitation, innovation, collaboration and transformation.  I'll refer to this as "FICT 2.0".

Old and New Models

Efforts to bottle problem solving as a process over the last seventy-years reveals two principle approaches. These evolved almost simultaneously on opposite sides of the world: TRIZ in the USSR and the DesignShop in the USA. There have been many attempts to place process around problem solving but these two stand out because they share the explicit goal of finding new ways of doing things - divergence.

Using the idea of divergence to help discover what FICT 2.0 might look like reveals a nice little irony: we’re using a tool common to both innovation processes on those very processes themselves to innovate and develop a new innovation process!

We don’t have to diverge very far, on the other hand, to run into the social networking phenomenon. Collaboration is the fountain of innovation and social interaction is the bedrock of collaboration.  Surely, mixing an e-social interaction capability into the collaboration process is a necessity.

One way we might do this, depending on how you look at it, is to either tackle the huge headache or exploit the fantastic opportunity of all those mountainous reams of raw data. The social network has given us a junk pile, or a treasure trove, of electronic data that’s just waiting to be analysed.

Continuing our divergence we might find inspiration in DARPA. There task, in the name of National Security, is to glean useful and relevant information from overwhelming (and growing) volumes of raw data.  This data comes from people communicating with each other electronically. The CIA calls this “chatter.”

Our working theory will be that our new innovative FICT 2.0 process lies within a Venn diagram at the intersection of TRIZ, The DesignShop, social networking and data analytics.

A Brief History - The USA vs the USSR:  ASE & TRIZ

In 1946, 20-year old Russian scientist Genrisch Altshuller began developing TRIZ (Russian acronym roughly meaning the Theory of Inventive Problem Solving). He viewed the problems of engineering and innovation in terms of technical contradictions; for example, making something strong yet light. Solve this contradiction and you have a new invention. This led to the creation of a knowledge base of inventions that he analysed and distilled into a series of invention principles. In 1995 the Altshuller Institute for TRIZ Studies was established in Boston, Mass.

In 1952, at 13 years old, American architect Matt Taylor produced his first work and considered why everything in a floor plan was the way it was. This relation of physical architecture to group learning & creativity formed the foundation of his later work. With his wife Gail, an educator, he developed processes, tools and environments to facilitate the release of "group genius" to solve problems. In 1996 Ernst & Young licensed the DesignShop and created the Accelerated Solution Environment (ASE).

Underpinning TRIZ is the idea that somebody, somewhere has already solved our problem. We just don’t know about it because it was solved in another industry or domain that uses a different lexicon to our own. We simply have to find it, hence the knowledge base.

Then, when faced with a transformation assignment or in need of an improvement or of a step-change that solves a problem we can find the solution in someone else’s earlier solution to a similar problem. We simply query the database. 

Underpinning the DesignShop, on the other hand, is a 3-day workshop where facilitation meets process, meets environment. The intense three days starts with the Scan phase where facilitators guide stakeholders to reach out and explore ideas far outside their usual range of expertise. Sound familiar? On the second day stakeholders Focus on the problem and on the final day they break through the problem and Act.

Fundamental to the success of the DesignShop is the physical layout and design of the environment where deliberate attention is paid to details such as space, room sizes, lighting and props.

Consider the similarities between TRIZ and the DesignShop: 
  • both ideas germinated post-war in 1946 and 1952; 
  • crossover from academia to consultancy occurred in 1995 and 1996; 
  • TRIZ is high-speed R&D and the Design Shop is accelerated problem solving; 
  • TRIZ finds solutions elsewhere from previous inventions and the DesignShop participants Scan outside of their usual range of expertise to discover new ways of doing things.
Now the differences:
  • how the scientist went deep into research and painstakingly created a knowledge base vs the architect and the educator who created a physical environment where they could facilitate solutions through people’s interactions;
  • TRIZ is scientific, detailed and technical whereas the DesignShop is social, interactive and emotional.
Social Networking, Social Business Software, Social Business Solutions (SBS)

In an era of globalisation where we are electronically connected yet physically separated social networking solutions bring people back together. Think of the DesignShop: it’s not so easy in a global company to bring stakeholders stationed around the world into the same physical environment for three days. Electronic social networking solutions fill this gap.

Much of the attention in the social networking sphere has focused on external or consumer social networking and how businesses can engage that network.

Now, a perfect storm is bringing social networking into the cross hairs of business process. Starting with the example where businesses are connecting with consumers consider two further developments:
  1. a new workforce that grew up in the socially connected electronic world expects the same capability within the work place itself; and, 
  2. globalisation, especially where achieved through M&A has contributed to siloed business units where collaboration and innovation are near impossible and where simple communication has become scarily non-existent.
A cottage industry of SBS providers ranging from start-ups to a single decade old company from the world of Online Forums (remember those?) is emerging to meet these challenges. Gartner even produces magic quadrant analysis on three different segments of the SBS industry.

Even in its infancy, social networking is mature, old, even ancient. In The Tipping Point, Malcolm Gladwell writes about the ideal size of the social network or our “social channel capacity” (Dunbar's Number).   Where modern research and analysis suggests that a network of 150 is about right, Gladwell points out that all kinds of social groups (military, religious, hunter-gatherers) going back hundreds of years evolved around the same magic number of 150. This is old stuff.

What’s new is the ability to capture all this social chatter and the opportunity to analyse it. Enter data analytics, predictive analysis and artificial intelligence.

Analytics: TIA, AI, BI, FutureMAP, PAL

The idea of Total Information Awareness originally emerged during WWII from the CIA listening to the enemy and using the data or “chatter” to discern relevant and valuable information. This continued through the Cold War to modern day where the Internet contributed to an explosion of raw data so great that it was declared a matter of national security to figure out what people were saying.

DARPA, which invented the Internet, began a number of artificial intelligence (AI) initiatives to help solve this problem. One of these was FutureMAP, which attempted to predict political unrest and threats to national security based on market trading mechanisms.  Recent example: Twitter and Libya.

The program was controversial - " the idea of a federal betting parlor on atrocities and terrorism is ridiculous and it's grotesque" - and ultimately dropped but not before one smart DARPA engineer saw the writing on the wall. He worked on the related Personalized Assistant that Learns (PAL) programme, creating a new generation of cognitive assistants that could reason and learn from experience. That engineer eventually founded Proximal Labs to analyse social noise.

(Jive Software, arguably the world’s leading social business software provider, is no slouch in this game. They acquired Proximal Labs in April 2011 along with that DARPA engineer who’s now their new Chief Social Scientist. Keep an eye on Jive.)

The clever work that Proximal Labs does is this: it analyses chatter to discern relevant information. It cuts through the noise. That’s the problem DARPA tried to solve for the CIA and that’s the problem that outfits like Proximal Labs solve for businesses wanting to understand the social network conversation.

Where this gets really interesting is in the predictive capability. Researchers at Indiana University, for example, found they could predict the stock market with 87% accuracy by using AI to analyse Twitter. Call it Business Intelligence (BI) on steroids.

This is scary stuff for existing businesses that come from the "old way."   The new reality these businesses face is that analysing all that noise is no longer about the possibilities. It’s about the threat - the threat of an upstart getting to it before you and disrupting your business.


One of the interesting things about the cloud and connected smart devices that fit in your pocket is how they enable entirely new ways of doing things far more quickly than the enterprise has been able to act. The dramatic growth in connected smart mobile devices is fuelling more new ways to connect faster than we can keep up: SMS yesterday, GPS enhanced social networking today, gamification tomorrow.

Where’s the enterprise? They're still deciding how to use the cloud! Paraphrasing a top strategist at one of the world's biggest technology corporations, they’re not really doing anything but the cloud, nevertheless, is driving all the dialogue. In the meantime, monthly Android activations will double from 500,000 to one 1,000,000 in just four months.

TRIZ gives us high speed R&D. The DesignShop gives us accelerated solutions. The social network gives us speedy collaboration and raw data to analyse.  AI speeds up our understanding of what's being said and even tells us what will happen before it happens. That's fast! Smart mobile devices connected to the cloud speed the delivery model.

Is speed the missing link?  Altshuller and the Taylors didn't necessarily claim a better solution, just a faster one.  Now, all of a sudden, social networking and the power of the crowd is much faster than jetting stakeholders around the globe to a physical environment.

Is the Venn diagram beginning to coalesce? Can we combine scientific study and analysis with physical group interaction and stick it all together with mobile SBS? And, can we analyse the SBS chatter and discern something relevant that we can study scientifically and use as fodder for group interaction?  And, can we speed it up, perhaps with mobile solutions?

Of course we can.  Whoosh!

To follow: Who will transform the transformers, Part 2: Business model