How Game Theory Can Inform Product Creation And Management

We've all seen this situation: a new company creates what looks like a dumb product that experts say has zero chance of taking off. Said product is released to the marketplace, and it takes off like a rocket. Users love it. Our experts are dumfounded. There are of course web monuments to the canonical foolish prediction of experts.

So that begs the question - why do some products succeed while others fail? 

I believe that the mathematical area of game theory can offer a useful framework for understanding this phenomenon, specifically the concept of the Nash equilibrium. You may remember it from the movie "A Beautiful Mind" (though oddly enough what was depicted in the movie isn't quite the Nash equilibrium). A Nash equilibrium in a game exists when the players in that game, taking into account the strategies of the other players, can't improve their payoffs by changing strategies. In other words, they have arrived at a strategy that they believe maximizes their payoffs, given their understanding of the strategies of the other players around them.

A new product, therefore, must play within a 'game' where the 'players' are customers, competitors and influencers. The current game is at a Nash equilibrium point, where players don't have an incentive to change behaviors. Thus, a new product must positively change payoffs for some players within this universe, and enough of them, such that the system as a whole moves to a new Nash equilibrium. 

This implies three important insights that make intuitive sense to those who have experienced both successful and unsuccessful product launches. 

First, it is important to understand at the most granular level possible who the players are within the system. In the case of an enterprise product, it is tempting to classify a large corporation as a single player, but in most cases this would be suboptimal. A large corporation is composed of multiple business and administrative units, each with its own set of goals and concerns. And each person within these departments brings their own goals, ambitions and concerns. It's easier to sell a new product if you understand these concerns of these players and can align its benefits to their goals. In other words, you are changing their payoffs and giving them an incentive to push toward the new Nash equilibrium you desire. For a mobile app, the analysis is somewhat simpler. Without understanding who the players are in your game, however, it's unlikely that your product can align up to their desires, and thus unlikely to generate traction in the marketplace.

Second, the payoff change should be significant enough for the various players to want to change their strategies. This is more pithily explained by Paul Graham's phrase "Make something people want". If you understand who your target players are, then it becomes much easier to understand their wants. In many cases, especially for a somewhat revolutionary product, the target players may not realize they want it till it's available. Even after something is available, targets may be underwhelmed by what's released. However, understanding how they view the game and the payoff will allow you to set a starting point that maximizes the product's chances. And this understanding will allow you to chart out the path for refinement of the product's features, giving you a better foundation for choosing which features to change and which to drop.

Third, if you've played the game correctly, and the system is now at a new Nash equilibrium, then congratulations! - you have a payoff too in the new dispensation. Understanding the payoffs of the other players will let you understand what your likely payoffs might be. Note that your payoff may not directly be from your users - ad supported models, for example. Understanding how your payoff relates to that of the other players within the game lets you craft a payoff for yourself as well.

By reframing product creation and management within the context of game theory, I hope to enhance your understanding of your own product ecosystems, whether enterprise or consumer. Note that the framework is generalizable to pretty much any product - whether a SaaS product, a mobile app or even a burger joint! I'd be happy to hear your thoughts and comments.

PS I've been thinking of further implications of this framework, and have a series of blog posts planned. Be sure to sign up on the left to be notified of new posts.
7 responses
Tony - great insights. When I tackle this situation, I use a decision pattern and explicitly score my solution's value proposition (or market positioning) against the incumbents, i.e. look at it through they eyes of the stakeholders (game-players). What I haven't done yet is roll-up the analysis from the various decisions involved to predict a new equilibrium point. We have recently added a new Multi-Decision Trade-off (roll-up) feature to our SaaS decision management framework. It would be an interesting experiment to work on together. - John
John - thanks for the kind words. I agree that there are interesting overlaps between your framework and my thoughts here. I was mostly trying to explore if there was a theoretical basis that might be useful for understanding product creation and introduction.
The mathematical bases for products depends on whether the underlying technology is continuous or discontinuous. Continuous is nice, linear, Euclidean or spherical, and amenable to approaching the Nash equilibrium. Note that the Nash equilibrium is chaotic and asymptotic. We can approach it, but we cannot hit it. Continuous innovation happens within an existing category. Discontinuous innovation gives rise to a new category. The games here are Poisson games, or games of unknown player populations. Poisson games are modeled by Poisson distributions. These distributions tend to the normal over the technology adoption life cycle. The geometry is hyperbolic, hence non-linear. The typical financial analysis ignores the issue of the underlying geometry assuming Euclidean or spherical geometries, so the analysis fails by rejecting the idea, but really its the organization that can't do business in a hyperbolic environment. Every category has its own Nash equilibrium, and competitive share allocation.
Interesting perspective. However, it's not clear to me that a Nash Equilibrium is a necessary constraint for the original system nor is it clear that a Nash Equilibrium is a desired end point. If I know who the buyers are and the value proposition (and it's a strong one), then whether the existing prospects are settled with their current choices or not will have an effect on the length of the sales cycle, perhaps, but not on whether my new-to-the-world product is attractive to them. Likewise, until I have all the prospective customers, I'd prefer that there is no equilibrium as long as it's the other company's solution that is in flux as a preferred choice. Or am I missing something?
Unfortunately, there is always a Nash equilibrium, and a category allocation. Those are constraints. They shouldn't be a problem, because you are nowhere near them at this point. Prospective customers are prospects. You will always have prospects. You don't need all of them to get started. You actually need exactly one client, but you built your application before you had any clients/customers, so it's wrong right now. What technology are you using? A new to the world product is not necessarily discontinuous. These days everyone is using long ago adopted technology, so you face consumers and promo spend, not a new category or market power.
David T-L - the Nash equilibrium is not a constraint, but an emergent aspect of the system where players are free to choose their strategy seeking their individual payoffs. In your framing, if the value prop is super strong, buyers are changing their strategy - using you instead of the older solution. At some point later, when the market is mature, a new Nash equilibrium is established. Of course, this is an idealized analysis, and real life is always messier, but it helps me to think in a more rigorous way about product introduction. David L - I believe that the framework holds whether the innovation is continuous or not. Note that a Nash equilibrium also generally exists in Poisson games. In discontinuous innovation, a new and large class of player emerges, and then the system tends to a new equilibrium with these new players also part of the mix.
Nice one.