- Devices--the machines and tools we use
- Connections--how machines communicate with each other, the networks, and how “pipes” evolve
- Applications--the programs we use. Also the evolving architectures around cloud computing and how information flows and interacts
- Interactions--how we manipulate the world, and how it communicates back to us
- Authorization--in its first iteration, this would have been about authentication and security. It is in the process of growing to encompass a big new field around role management and personalization.
- Community--social networks, social marketing, social tools--these are the sites, companies, and programs we use to create and live in our communities. Some are communities of place, but in most cases that involve technology, they are defined by shared interests.
So how do these elements interact to provide innovation insight? Here are examples:
Innovation 1 PCs made “what if” questions answerable on individuals’ desktops, disrupting the previously-unchallenged domain of mainframes. Each program: stand-alone, the only data sharing was by floppy disk and “sneakernet.” Trigger from other domain: local-and-wide-area networks. Innovation in third domain: client-server computing, and the rise of shared data.
Innovation 2 Cell phones for voice reached low-enough cost for mass adoption. Trigger from other domain: Internet 1.0, e-mail, PDAs created demand for mobile access to more than voice. Innovation in third domain: BlackBerrys, and the rise of the smartphone.
Innovation 3 Cassette recorder and VCR enable culture of user-recordable media, and of sharing. Introduction of CD enables tripling of cost of albums, from $5 to $15, music industry clings to cash cow. Trigger from other domain: broadband internet connections become common. Innovation in third domain: Napster, mp3.com, BitTorrent, and the near-collapse of music industry (but also the rise of youTube, iTunes, and the Web 2.0 revolution of user-added value.)
Here is the graphic. Although the timelines are not precise in the interest of listing major milestones, the important idea is about the way we think of innovation. Not just “I have this great idea,” which will always be with us, but “If I know A, and I see B happening, what consequence C is likely?”
This is the highest-level view, but now that we envision the framework, we can also zoom in and create a more detailed version for a more specific need, such as barriers, triggers, outcomes for cloud computing. Or on an enterprise level, relative internal maturities of IT services, mapped against culture, competitive pressures, and economic conditions.
I propose two patterns of investigation you might consider for this model.
- Working forward: what are the consequences of the horizontal maturity graph? (in the example above, several are suggested by the rightmost entries) If you create your own graph based on your specific situation, what is implied by the possibilities of current or emerging abilities?
- Working backward: “I know I want this consequence to occur. What triggers are missing between what exists now, and the innovation I want to see?” In this case, you may have multiple opportunities to exploit: not just the end state you want, but to be the creator of the enablers that will make it possible.
The point is this: genuine innovative thinking needs a big-picture approach, and some insight across multiple ideas and histories. The better grounded you are as a generalist, the better prepared you are for that “great a-HA!” moment as a specialist. Or as a company. Or as an entrepreneur. Or as an agent of social change.