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 to his insights, despite modern fads like “Lean” this, that and the other. Put plainly: I am not a technologist for technology’s sake. I mean business.
I am not an “innovation theorist” with “big idea” Powerpoints or feelgood sticky-note frenzies. I produce tangible, well researched outputs: I can propose, design, architect and build. My track record in technical execution is backed by many satisfied clients and numerous project and patent achievements.
Data- and Design-Driven
I come from a signal processing background, so data-processing is my “first language.” I am also a mathematician. But I am also well schooled in design. My approach is to fuse data-driven analysis (bottom-up) with design-driven innovation (top-down).
Most “digital transformation” is speeding up existing processes rather than reinventing them. This is not sustainable in the world of cognitive computation (AI) and decentralized technologies (Web3). They have unique natures that transcend traditional transformation mindsets and methods.
The chaotic reality of today’s markets stems from the fact that businesses are Complex Systems. Mere “simplification”, the essence of many management approaches, no longer works. Complexity needs harnessing, not reducing.
If your org cannot continually adapt at the rate of change of complex external stimuli, then you will fail in the face of smarter competitors, drown in irrevocable technical debt and suffer organizational decay.
Organizational intelligence is rapidly becoming synonymous with “organizational cognitive intelligence”. If cognitive computing (AI) isn’t at the core of your transformation, you are most likely falling behind.
Many orgs claims to be data-driven, yet confuse data abundance with data literacy. Even then, bottom-up data-driven is not enough. It has to be met with top-down systems thinking and interpretive design that enable breakthrough performance via empowered talent.
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 business into its essentials, mostly via data-driven critical reasoning and interview-based research, not some faddish jargon-laden “consulting framework” that produces hundreds of dense slides.
I help interpret where untapped value might lie irrespective of existing corporate narratives, which are often laden with mythologies. When necessary, I enlist design-interpreting partners, such as Rick Lewis (former Ideo, former Frog, Braun Prize winner).
Using design-driven innovation, which is a form of conceptual blending, I re-interpret core competencies through the lens of advanced technology trends. In other words, I combine top-down with bottom-up. I then propose a landscape of future possibilities suitable for converting into meaningful strategy.
Often, I am hired to form an “Innovation Lab” that develops PoCs and strategic technology. Where necessary, I draw upon an extensive global network of talent. I prefer to also work hands-on developing core tech as part of the team or via solo experiments.
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.