shot from the hip

after thinking about william cockayne’s presentation at LIFT08 and my last blog post about it, i’ve sketched out an idea as to where innovation/development cycles might be going, or at least the successful ones who manage to deliver relevant products/services and timely awesomeness. i like cockayne’s model, and he provides a clear perspective on the corporate innovation process and the role that foresight plays. however, i wonder if it can be extended further to include the changes that manufacturing and production are undergoing in parallel with design, innovation and invention. in particular would be changing the assumption that the decline of ambiguity throughout this process is a good thing.

moar his slides illustrate the nature of an ambiguity curve, the stages and gates, the roles people play, the types of interactions, etc. the assumption is that as the process develops, ambiguity goes down. but we can question – what is ambiguity? does it have to do with the internal focus of a company/team required to justify resources and satisfy metrics? does it have to do with locking down expectations and positing what outcomes or effect your product/service/experience will bring, based on formal research methods such as interviews and statistics? and why is ambiguity necessarily a bad thing? ambiguity encourages inquiry throughout, takes into consideration external forces/trends/changes, and ensures that communication is a top priority.

part of the struggle i see is that a process like this limits the territories being explored, creates further difficulties in communicating the vision and integrity between teams at the transition points/gates, and potentially cultivating failure or risk aversion by making too many assumptions too far in advance.something i seem to be taking more and more issue with of late is the need for a prescriptive methods for innovation or creative endeavours … from a to b along a path of increasing certainty…

as well, do the stages themselves need to be rethought and rapidly iterated to ensure agility in the development of a concept, maximizing the ability to troubleshoot and adapt to changing circumstances/resources/markets/etc? one alternative is a more agile model that embraces ambiguity, complexity and emergence. would a post-industrial innovation model happen in rapid iterations, with visioning, sketching, designing and prototyping happening throughout, as though on a continuum? at times the context is more appropriate for visioning and intuitive tools, and at times more appropriate for tactical, on the ground actions. the research – action research, for example, doesn’t necessarily stop throughout the process, continually informing next steps.

this sketch of an innovation path, still a bit loosey goosey, uses cockayne’s role-icons (expert, breadth+depth, breakout and innovator) throughout to demonstrate the places that people gravitate towards across the path. inflection points – named for the point where a curve changes from concave to convex – are the points at which either a) a discovery or idea shifts or breaks out the process or b) points when the focus of engagement needs to move towards implementation or vision – ie mtgs, wksps, deadlines, etc, etc.

not flowing along a regulated path, each eddy is an iteration, receptive to changes in external and internal environs, and accept the nature of ambiguity as something to work with. larger eddies flow towards foresight and visioning, smaller eddies flow towards prototyping and design. research does not stop. the process ebbs and flows between the two. regular inflection points mean increased ability to adapt to changing circumstances, trends, etc. we both need to return to and expand the scope of vision, sketching out possible pathways and allowing for failure and recovery if need be, as well as branching out on other currents. tough to measure with standard metrics, maybe, but more accurate in cultivating agility and emergent strategy. the roles of people become more fluid, as team members have the opportunity to increase knowledge and skills in tighter groups…

perhaps without the linear clarity of most diagrammatic representations of innovation, it communicates that we’re engaging in complex processes, that complex and adaptive tools are needed throughout, and that maybe part of the trouble is that we need to be more open to complexity and ambiguity and emergence. maybe the most critical thing is to maintain or be open to active research and design throughout – to allow for changes, contingencies, failures and recoveries, breakouts, etc, etc. the point is to create lightweight, organic frameworks that perhaps complement existing structures, especially as they’re not going anywhere for awhile…

the older models of innovation and value chains (identifying a need, over-engineering the hell out of a design, going to market and ’satisfying’ the user need) reflect a heavily industrialized, mechanized society, codified in the material and mechanized process/metrics. but with agile manufacturing systems and DIY production (of material and digital goods) (among other factors) on the increase, we see more and more ‘emerging value chains’ taking hold in the production of material culture and goods. in the book, we spoke primarily about how to map out new models for the discovery and invention stages of development. however, less attention was given to changes in later stages of the production chain… and we’re seeing an enormous shift in building the tools that produce new media, tools, services, etc. a flattening of hierarchies and silos across the entire chain as opposed to in one area or the other.

manufacturing is slowly embracing more rapid prototyping and micro-production, with a concentration in asia for now… when a manufacturer has access to granular/modular processes, smaller production runs and a shorter time to market, doesn’t that change the nature of the game? and indicate that maybe a different territory needs to be mapped..? as well, this isn’t to say that this process is new – the engineering and software industries have been tweaking it for years. what’s interesting is the effect and transition to other industries and institutions. there’s been a lot of discussion about a post-industrial society… are we now seeing the shift happen across geography and industries?