Of course you remember my previous example of a cyberspace product — the sheep-goat dating website ovicap.org? As you’ll recall, cyberspace applications have a low barrier to entry as compared to those that have to produce real-world results, i.e., “meatspace” products, and this fact makes connecting-A-to-B -and-somehow-monetizing-the-connection websites such as the sheep-goat dating website altogether too common.
You’ll also recall that I described meatspace as being difficult for its problems of prying something that works from the breast of Nature, although this balances against the appeal of the high-tech requirements that usually underly something in meatspace. I gave no graphic example before, I now direct you to the “cat piano” shown above (Imaginary Instruments — Cat Piano), which is about as close to a “red in tooth and claw” implementation as it gets, although I admit the cats in the illustration look pretty placid.
A story bifurcates depending on whether it’s of cyberspace or meatspace; regardless, for either domain a story falls within an ambit of possible alternative embodiments — a pivot landscape — and can and should be developed with a very clear idea of what falls within the ambit of that pivot landscape and what falls outside it.
In other words you have to define the outer limits of your technology, which means knowing not just 1) what you can do and 2) what you might do, but also very definitely 3) what you absolutely cannot do.
In order to better explain this idea, let me start with a brief summary of the currently favored “lean-startups” methodology. There are an enormous number of on-line resources that explain the lean-startups model, my brief summary is that:
- A typical (non-startup) business can be modeled by way of already-existing comps, for example the success of a new pizza restaurant can be estimated by looking at the number of other pizza places in the area, diner population, costs of space, known costs of making pizzas, labor costs, etc.
- A “startup” is difficult or impossible to model in the same way since it’s producing a product that’s “new,” and therefore has no easily available comps.
- Startups often try to solve this problem by creating a feature-heavy product, particularly when the startup is making a high-tech product that’s easily laden down with engineering-based features. This feature-bloat is, at best, bad, and most likely lethal, because it spends resources to develop a product that the market doesn’t want.
- The solution for a startup is therefore to implement a “Minimum Viable Product” (“MVP”) as quickly as possible and test it against the market Voice-of-Customer (“VOC”) to see if the MVP meets market pull. And if it doesn’t, iterate the MVP to a different configuration and test against the market again. And so on and so forth until the series of iterations (“pivots”) leads to a good product-market fit, i.e., the MVP-VOC-pivot cycle defined in the lean-startups model.
There are a lot of things to like about this model, foremost the idea that you “fail” early and fast and small, and that each “failure” is really just a mismatch to the market which can be pivoted by revamping the MVP and retesting until a market match is identified. In other words, even for a startup, success is obtainable. As a result, the lean-startups Standard-Operating-Procedure (“SOP”) focuses heavily on small ideas (MVPs) tested against lots of customers.
Thing is, the lean-startups SOP pays little if any attention to 1) the ability to pivot and 2) the extent of possible pivots. In other words, if real-world reaction to an MVP is to a different product that’s too hard for the company to make because it lacks the resources, the identification of this potential pivot isn’t useful. And, worse, if the pivot is to a product that the company cannot make under basically any circumstances, the MVP-VOC-pivot idea is really rather worthless, at least without more.
My standard example is a company that makes nuclear weapons — call it “Nukes-R-Us” — that’s looking to expand its business because the market’s dropped off for thermonuclear devices. Assume this is some sort of startup situation, so apply the MVP-VOC-pivot cycle. And let’s say that what immediately becomes apparent is that there’s a huge market pull for children’s toys … should the company pivot to making children’s toys?
No, of course not, even if the demand is vast, Nukes-R-Us can’t go from a core competency of making bombs to making Elmos or even plushy toy robots. And by “can’t” I don’t just mean “we don’t have the resources to pivot to that model,” I mean it’s so insanely not within Nukes-R-Us’s competency to go from nukes to Elmos that it’s flat out not possible, not even if you roll in something catchy like “Nukes-R-Us-Bitcoin-Toy-Company” to attract lots of investment dollars (you know, of course, that everything’s better with bitcoin).
On the other hand, within the landscape of possible pivots — the landscape that definitively does not include pivots like the nukes-to-toys one — Nukes-R-Us might actually be able to pivot to fun rides that involve reentry into the atmosphere on warheads without the plutonium or the bang, e.g., as shown in the lovely graphic to the left (Riding On Nuclear Bombs). It wouldn’t be a straight shot, but presumably Nukes-R-Us is good at making the bomb casing and fins and guidance systems in addition to the bangy part inside, so the pivot is at least possible, although admittedly not altogether fundable.
The above discussion captures the idea that the lean-startups MVP-VOC-pivot model isn’t infinitely malleable; instead, pivots are constrained both in terms of 1) getting from one MVP to another in pivot range, and also in terms of 2) the impossibility of access to whole areas of MVPs altogether — the ability and extent parameters I referred to above.
I haven’t quite decided what graphic best describes the situation, one possibility is the figure to the left, which shows the pivot landscape as a series of obtainable “islands of opportunity” defining MVPs, with these islands rising up out of a sea of exclusion and surrounded by a crimson wall outside of which there are no MVP pivot points at all, just monsters. In this graphic each of the colored columns represents a particular defined island of opportunity with its own MVP, so that, for example, MVP1 might be the green column, which on testing against the market led to a pivot to MVP2, which is red, and then to MVP3 (purple) and so on. Thus the graphic can be used to show an actual trajectory of MVP discovery, in the example from green to red to purple MVPs.
Alternatively, I’m tempted to provide the representation to the right, where these MVP-containing islands of opportunity are largely shrouded in mist, indicating that the landscape of possibilities (alternate MVPs) isn’t particularly clear. This is a better parallel to the real-world situation, and certainly captures the key concepts that 1) a company’s technology encompasses a set of distinct (and disjoint) MVPs, 2) hopping/pivoting from one MVP to another can be easier or harder depending on their separation in the landscape, 3) some of the MVPs are easier to define than are others, and 4) the set of MVPs isn’t infinite in extent across the landscape — outside the islands is just water, and that water is deep and dark and not explorable. Again, Nukes-R-Us might see that there’s money in toys, but it’s not likely they’ll ever be able to pivot to that kind of MVP, they’re stuck with the pivot landscape that their business experiences and connections and brick and mortar and cyber capacities dictates.
To summarize this post, startups are hard to model because they do “new” things that are without comps, and the lean-startups methodology addresses this by an iterated pivot model of MVP-VOC-pivot repeating itself as the company titrates its product towards what the market wants.
This is a legitimate framework with many advantages. However it fails to recognize that 1) pivots aren’t automatically obtainable, they occur along a path of possibility through a pivot landscape, and 2) that the pivot landscape is finite in extent, you can’t pivot to models that are (to quote “The Princess Bride”) “inconceivable.”
I’ll pursue a framework for analyzing pivot space to understand the potential pivot points (“islands of opportunity” if you will), trajectories between them, and explicitly defining what the company cannot do, and not just what it can.