If you are a growth product manager like me, you spend a significant amount of time finding opportunities and business metrics that can be maximized. In an effort to do so, at times, it is easy to get confused and start assuming it is your responsibility to maximize/optimize every metric that comes your way.

Growth is about maximizing — Not always. Growth is about finding what needs to be maximized, what needs to be optimized, and what needs to be ‘Satisficed’.

Coined by U.S. Nobel Prize-winning economist, Herbert A. Simon in his 1956 paper, Rational choice and the structure of the environment [1], Satisficing is a portmanteau of Satisfying and Sufficing.

Satisfy + Suffice = Satisfice

So when should we satisfice instead of optimize or maximize?

Diminishing return beyond Satisficing: Suppose you have a business goal at hand and a metric that you will use to measure success. You brainstormed all possible solutions and arrived at one that adequately addresses the business goal. Any other solution may lead to marginal improvements with significantly higher investment. Recall The 80/20 rule, also known as the Pareto Principle, which asserts that 80% of outcomes (or outputs) result from 20% of effort. In that case the ‘adequate solution’ may be the best possible solution.

Finding the mountain not the peak: Growth Team is usually tasked with finding the next big thing, quickly prototyping to prove the business opportunity with least effort possible, and then handover the knowledge to the core product team to find the peak through optimization. If you are part of such a team, not getting attached to a surface area of a part of product is your job. The faster you help find new mountains to scale, the faster you get the team to 10x growth. In some sense, you embody the quote — “if you do something and it turns out pretty good, then you should go do something else wonderful, not dwell on it for too long. Just figure out what’s next.” — Steve jobs

Some metrics are inherently Satisificing: Let us take an example of hotels. Hotels could optimize for N number of metrics — Occupancy, Length of Stay, Revenue, Gross Margin, Repeat bookings etc. But many of these metrics have a tradeoff such as Occupancy and Gross Margin. Hotels could easily increase occupancy by lowering the rates, but is that the right metric to optimize for? No, in fact it is the kind of metric that should be categorized as Satisificing metric. Many a times product managers confuse this type of metric with Guardrails — a metric that you want to keep intact while optimizing for other metrics.

This is where it is helpful to know what drives the business — at the end business is all about profit maximization. Any other metric such as DAU, time spent on website, posts liked that growth product managers run after are vanity metrics.

Do not spend resources maximizing metrics that do not yield business value

Let us consider the example discussed above — It is true that higher occupancy leads to higher revenue, but many a times there is an opportunity cost of optimizing for occupancy. Beyond a threshold, higher occupancy wont be as effective. But then why not drop Occupancy as a metric altogether? Because it still is a good metric or an indicator of how many users are getting value from the product. But if you use Occupancy as your North Star Metric, your team will start discounting, dropping prices to help achieve the occupancy. Also occupancy is a great proxy to your pricing power. Higher occupancy especially for advance dates, is a strong indicator that the business holds the pricing power.

This is why the idea of a satisficing metrics come into picture. Define what is a good level of occupancy is, this could be 80%, 90% or some other number. Defining the exact number is out of the scope of this article but let us define a threshold. Once we achieve this threshold, increasing this anymore does not yield value for the business and instead you should turn focus to the maximizing metric such as Gross Margin in this case.

Using that as a satisficing criterion, hotels could start optimizing for Gross Margin. Best illustrated with the diagram given below (For simplicity, we are using only the above two metrics — Occupancy and Gross Margin. In this case, occupancy does not mean anything.

As Occupancy reaches a determined threshold, start optimizing the Gross margin by increasing the prices. This will help maintain the occupancy and find the optimal pricing. This could easily be part of your dynamic pricing algorithm — Occupancy drops below the threshold, lower the prices incrementally (Of course this simplistic model assumes that prices and not any other factor is responsible for the occupancy drop — which may not be the case but it drives home the point on how to think about Satisificing metric), occupancy trends higher, start raising the pricing. Notice that in this example, we are strictly treating occupancy as a satisficing criteria.

Satisificing is not a search of mediocrity, it is a tool that helps you identify what drives business value and focusing on what truly matters. Before you get to optimizing, think whether good enough is more than enough.

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Read our other articles on Product Leadership, Product Growth, Pricing & Monetization strategy, and AI/ML here.

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References:

[1] Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological Review, https://psycnet.apa.org/doiLanding?doi=10.1037%2Fh0042769

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