I have a track record of creating novel solutions across a wide set of industry problems from digital art to fintech to racing cars. I use design-driven innovation to reinvent businesses via the application of advanced computation (e.g. AI).
I learned from the legendary Tom Peters about the language and art of business. There is nothing new to add via trends like “business model canvas”. This is just to say that I am not a technologist for technology’s sake. I mean business.
I am not an “innovation theorist” with “big idea” Powerpoints. I produce tangible outputs that include building, designing & architecting solutions. My track record in technical execution is unparalleled.
Coming from a signal processing background, data-processing is my “first language.” I fuse data-driven analysis (bottom-up) with design-driven innovation (top-down).
Find Order in Chaos: Cognitive Transformation
Most “digital transformation” is speeding up processes rather than reinventing them. The same mistake is being made with the adoption of cognitive technologies, like AI.
Many orgs are unwilling to acknowledge the chaotic reality of rapidly changing technology and continue to make the same mistake of fitting technology to process rather than process to technology.
If your processes can’t adapt at the rate of change of technology, then it doesn’t matter how great your strategy is because it will eventually fail in the face of smarter competitors and increasing technical debt.
Failing to explicitly acknowledge organization uncertainty is a recipe for disaster: chaos is the new normal.
The only hope is to make organization intelligence synonymous with computation intelligence. The premise is simple: that machines can find order in chaos. This is the crux of cognitive transformation.
This is an actual clustering visualization from a project I worked on in e-commerce. There’s meaning in this data. Modern orgs/markets are similar — they contain clusters of behaviour and opportunity that are discoverable via cognitive computation and strategy.
I interpret your business into its essential principles, mostly via critical reasoning and interview-based research, not some faddish “framework”.
This includes understanding where the real value exists irrespective of existing corporate narratives and dogmas, and as seen in terms of information processing rather than more traditional framing (e.g. SWOT analysis).
Using design-driven innovation, which is a form of conceptual blending, I re-interpret these core competencies through the lens of cognitive technology, like AI. From here, a landscape of future possibilities emerges that can be selected from and transposed into meaningful digital strategy for your business.
Where necessary, I draw upon an extensive network of talent from across the globe. If requested, I can assist with building solutions, often within the context of an innovation lab (which may need to be created).
1. Establish the true mandate.
What do you *really* want? This is always the starting point. Everyone says “we want to innovate” but seldom do they articulate the real constraints. Via a series of conversations with executive sponsor(s), I tease out the true mandate, which is often tricky. If I don’t see a meaningful mandate, I walk away. I have no desire to get paid $$$ for delivering slides that will never translate into value. Life’s too short for vanity projects.
2. Capabilities discovery
Clients know their business the best, but often via a biased, dogmatic or historical lens. I tease out current capabilities so that I can begin to fit them into a different framing – i.e. one of advanced computation. This step includes a kind of “digital what-if”, like if X is the digital future of Y (e.g. some pivotal capability or market characteristic) then how might that impact our view of capabilities.
3. Map a digital landscape
Irrespective of what a client tells me about their business, I develop an independent view of the landscape with the goal of unearthing foundational limits. For example, if the core of a client’s financial business is essentially aggregating data, then I will explore the limits of aggregation were we to apply any amount of resources. Are these limits informational, process, speed, or something else? I then explore these limits through the lens of computation and interpret the possibilities. Doing this over a range of core processes, I construct a digital landscape of possible business futures.
4. Develop a design framework
Via a process akin to design-driven innovation, I frame your industry category in terms of its product futures. This is an attempt to unveil the actual meaning of a current product and/or intended innovation in the mind of the market. For example, perhaps a financial loan product is really an “insurance policy” in the mind of its users. In which case, the “insurance qualities” of that product might become its design-driven purpose. This might entail looking more broadly at the theme of “insurance” and seeing how it might be re-imagined via the use of computational technologies, if applicable. This approach reveals a set of possible product strategies to frame the innovation.
Finally, I synthesize the digital landscape and design framework in order to describe a set of digitally-native strategic futures and tangible actions to get there. To be clear, I seldom make strong recommendations at this point as it causes a bias in the process. Rather, I aim to expose a set of proposals via what I call “pillars of change”. These are themes around which an actual strategy might be constructed. It is not my place to state a strategy, but rather to suggest what it could be via “digitally emergent” ways of operating.