For 10x Growth: Leverage Systems Thinking, Apply First Principles.

In this series, I have previously discussed the exponential nature of the challenges we face today when building our strategic organizations, and driving implementation; and presented more detail on the Cognitive Transformation Model I built, that can help your organization choose the right focus areas in terms of technology: whether it's automation, augmentation, or social-driven, in order to drive 10x growth.

This post steps back to explore how organizations often approach strategic exercises today, and the gaps in their approach that often cause failure.

To do so, I start with a simple note about mindsets, and how they may limit or empower the people in organizations. The mindset of your organization defines whether you will be a 10% company, or a 10x company.

The article linked there is a great read in itself: this essay distills it further into an approach and a set of mental heuristics you can adopt in order to execute that kind of thinking.

The two mindsets in question are the "plan-oriented" mindset, and the "strategy-oriented" mindset.

A dictionary search for "Plan," versus "Strategy" would reveal to us:

Plan: "A detailed proposal for doing or achieving something."

Strategy: "A plan of action designed to achieve a long-term or overall aim"

Not very useful, since they don't seem like particularly mutually exclusive terms, so let's go back further: and explore the etymologies of the two words:

Plan: 1670s as a technical term in perspective drawing; 1706 as "drawing, sketch, or diagram of any object," from French plan "ground plan, map," literally "plane surface" (mid-16c.), from Latin planum "level or flat surface," noun use of adjective planus "level, flat". The notion is of "a drawing on a flat surface." Meaning "scheme of action, design" is first recorded 1706, possibly influenced by French planter "to plant," from Italian planta "ground plan."

Strategy: 1810, "art of a general," from French stratégie (18c.) and directly from Greek strategia "office or command of a general," from strategos "general, commander of an army," also the title of various civil officials and magistrates, from stratos "multitude, army, expedition, encamped army," literally "that which is spread out" + agos "leader," from agein "to lead". In non-military use from 1887.

Now that gets more interesting. One word, Plan, refers to the idea of "drawing on a flat surface." The other, Strategy, is referred to as an art. It brings in additional variables. It is expansive.

This may seem to be just an exercise in sophistry or wordplay, but it is not: our words are the media through which we think, through which we formalize our thoughts, and through which we communicate.

Therefore, our words, and the meanings we ascribe to them, will either restrict or extend our thoughts, expressions and communication.

To be plan-oriented is to ignore the variability of reality, in order to create a flat, well, plan. But things never go << according to plan >>.

To be strategic is to embrace variability and expansiveness and experimentation. These usually deliver significant alpha -- 10x, not 10%.

And these are two fundamentally different mindsets.

Planning is about filling our knowledge into a framework. Strategy is about using frameworks and experimenting, in order to understand.

And the trouble with most organizations is that they implement planning processes thinking they are the same thing as strategic processes.

I had a chance recently to reconnect with one of my favorite professors at IE.

He directed me to an interesting TED Talk, which had this great excerpt:

Not far from where I live is a place called Death Valley. Death Valley is the hottest, driest place in America, and nothing grows there. Nothing grows there because it doesn't rain. Hence, Death Valley. In the winter of 2004, it rained in Death Valley. Seven inches of rain fell over a very short period. And in the spring of 2005, there was a phenomenon. The whole floor of Death Valley was carpeted in flowers for a while. 

What it proved is this: that Death Valley isn't dead. It's dormant. Right beneath the surface are these seeds of possibility waiting for the right conditions to come about, and with organic systems, if the conditions are right, life is inevitable.

Planning mindsets will never be able to make inevitable what is dormant, because that is not the question they are concerned with.

It is the strategic mindset, which is fundamentally variable, expansive, and experimental in nature, that can.

Or, as Sir Ken Robinson, the speaker, summarizes later on in the talk, it's not about Command-and-Control, but about Climate-Control.

That is the shift in mindset needed, and that is where the tension lies in organizations today: where the bias and focus is often on templating, rather than maximizing, tasks, actions and ideas in order to deliver results.

Most of our estimations on market size and market potential, or on what is possible with the technologies we have at our disposal today, or on the willingness of individuals to engage with us is off by orders of magnitude due to the lack of experimentation: of exploring to understand what is dormant.

So where does one start?

You start by focusing on, whatever discipline you are in, the constituent first-principles, as Elon Musk would refer to them: and unpack the underlying assumptions: focus on the fundamental truths: and build strategic and operational models from there on up.

The first principle method forces you to identify the contingent variables within a system, allowing you to focus on influencing those variables which give you the best impact.

To identify the relevant and contingent variables, you need to develop a deeper appreciation for system dynamics.

What are the fundamental components of a system?

To start to build a framework, you can look at existing ones: whether it's Michael Porter's Five Forces Model to study your industry, or Alex Osterwalder's Business Model Canvas to study your own business, or David Bach's (IA)3 framework to study the relationship between your market and non-market environments.

Each of these models allow you to frame your question better.

Do I have a pricing problem?

Do I have a supply chain or logistics problem?

Is the problem related to my brand, my partners, my channels of engagement?

Is the problem regulatory?

What are the set of contingent variables that I should focus on, in order to effect change?

And then you go down the rabbit hole.

If the challenge is based upon your value chain or on component parts, your first-principle exploration is based on your supply chain, your production model, and on the material sciences.

Or, as Elon Musk talks about with his Tesla example:

Someone could — and people do — say battery packs are really expensive and that's just the way they will always be because that's the way they have been in the past. They would say, "It's going to cost $600 / kilowatt-hour. It's not going to be much better than that in the future."

But first-principles thinking will not heed the pundits' advice.

Instead, you start asking fundamental questions. Musk continues:

What are the material constituents of the batteries? What is the spot market value of the material constituents? It has carbon, nickel, aluminum, and some polymers for separation, and a steel can. Break that down on a materials basis, if we bought that on a London Metal Exchange, what would each of these things cost?

Oh jeez, it's $80 / kilowatt-hour. Clearly, you need to think of clever ways to take those materials and combine them into the shape of a battery cell, and you can have batteries that are much cheaper than anyone realizes.

If the challenge is based upon non-market challenges, your first-principle exploration is based on the regulatory environment, and on the public discourse that influences it.

Take the Toyota example presented in the aforementioned Non-Market Strategy paper:

Toyota Motor Corp. is a market leader in hybrid cars. But the company has stretched the competitive playing field beyond the market.

In California, it successfully lobbied to include its flagship Prius hybrid model in a program granting low-emissions vehicles access to the state’s carpool lanes, even with only a single occupant. Support from environmental groups made it easy for legislators to endorse the proposal, one that cost the state of California next to nothing and that burnished its environmental credentials.

With minimum financial investment, Toyota managed to give its product a decisive competitive advantage. 

Building on this success, the company next won Prius owners the right to park for free at public meters in Los Angeles and other cities.

Through skillful nonmarket management that deftly complements the company’s existing market strategy of selling the product primarily to upper-middle-class, environmentally conscious urban professionals, Toyota has reinforced its competitive advantage.

And if the challenge is based upon your consumer-facing offerings or channels of engagement, then your first-principle exploration is based on human behavior.

Exploring these challenges is only partly about domain expertise: the larger part of the challenge is in finding the correct framework to isolate the contingent variables that will best effect change.

In anything with a direct consumer interface, the first principle: the baseline upon which all creation is based is the user's cognition.

In terms of applied models, the tools best suited to understanding arise from the field of game theory: the nuance being that the application must be experimental, not normative: with our objective being to study shifts in behavior, not to arrive at a singular definition of behavior. (That is many data cycles away from reliably happening, if ever.)

People respond to stimuli based on many scenarios, ranging from the functional components of the scenario (the stimulus itself - the app they're playing with or the advertisement they have been presented); the environmental components of the scenario (the context they are in: are they stuck in traffic, or perhaps in a meeting?); and the emotional state of being (how's their day going so far?).

There is no plan-oriented approach that can help you optimize for this.

The system will continuously shift: and you must therefore study the trendlines of actions performed, build clusters around the dominant actions, and test new hypotheses to infer the behavior behind those actions.

And this cognitive approach needs to be replicated and tested at each point in your value chain if you want to truly maximize user adoption: from your service UX and the underlying technology architecture that enables it, to the service design and messaging that users interact with.

In the field of behavioral economics is the idea of prospect theory, which, simply put, refers to the difference in the value that people place upon losses (higher value) versus gains (lower value) – which makes the default state of being one that is averse to risk.

Any gap within your consumer-facing interface then, is a potential loss-maker, and a reason for your user to exit the engagement.

To successfully build and execute strategy across the full-stack of opportunities, you need to think like a full-stack strategist.

Which is not to say you are a master of all disciplines: but that you have, and are able to apply the right mental models (systems thinking, first-principles modeling) across disciplines within your company, across your value chain, across your industry environment, and across your regulatory environment in order to identify the gaps and opportunities you face.

That is how you get to 10x, not 10%.