Four pitfalls of hill climbing28 Feb 2016
One of the great developments in product design has been the adoption of A/B testing. Instead of just guessing what is best for your customers, you can offer a product variant to a subset of customers and measure how well it works. While undeniably useful, A/B testing is sometimes said to encourage too much “hill climbing”, an incremental and short-sighted style of product development that emphasizes easy and immediate wins.
Discussion around hill climbing can sometimes get a bit vague, so I thought I would make some animations that describe four distinct pitfalls that can emerge from an overreliance on hill climbing.
1. Local maxima
If you climb hills incrementally, you may end up in a local maximum and miss out on an opportunity to land on a global maximum with much bigger reward. Concerns about local maxima are often wrapped up in critiques of incrementalism.
Local maxima and global maxima can be illustrated with hill diagrams like the one above. The horizontal axis represents product space collapsed into a single dimension. In reality, of course, there are many dimensions that a product could explore.
2. Emergent maxima
If you run short A/B tests, or A/B tests that do not fully capture network effects, you might not realize that a change that initially seems bad may be good in the long run. This idea, which is distinct from concerns about incrementalism, can be described with a dynamic reward function animation. As before, the horizontal axis is product space. Each video frame represents a time step, and the vertical axis represents immediate, measurable reward.
When a product changes, the intial effect is negative. But eventually, customers begin to enjoy the new version, as shown by changes in the reward function. By waiting at a position that initially seemed negative, you are able to discover an emergent mountain, and receive greater reward than you would have from short-term optimization.
3. Novelty effects
Short-term optimization can be bad, not only because it prevents discovery of emergent mountains, but also because some hills can be transient. One way a hill can disappear is through novelty effects, where a shiny new feature can be engaging to customers in the short term, but uninteresting or even negative in the long term.
4. Loss of differentiation
Another way a hill can disappear is through loss of differentiation from more dominant competitors. Your product may occupy a market niche. If you try to copy your competitor, you may initially see some benefits. But at some point, your customers may leave because not much separates you from your more dominant competitor. Differentiation matters in some dimensions more than others.
You can think of an industry as a dynamic ecosystem where each company has its own reward function. When one company moves, it changes its own reward function as well as the reward functions of other companies. If this sounds like biology, you’re not mistaken. The dynamics here are similar to evolutionary fitness landscapes.
While all of the criticisms of hill climbing have obvious validity, I think it is easy for people to overreact to them. Here are some caveats in defense of hill climbing:
- The plots above probably exaggerate the magnitude and frequency with which reward functions change.
- There is huge uncertainty and disagreement about what future landscapes will look like. In most cases, it’s better to explore regions that increase (rather than decrease) reward, making sure to run long term experiments when needed.
- The space is high dimensional. Even if your product is at a local maximum in one dimension, there are many other dimensions to explore and measure.
- We may overestimate the causal relationship between bold product moves and company success. Investors often observe that companies who don’t make bold changes are doomed to fail. While I don’t doubt that there is some causation here, I think there is also some reverse causation. Bold changes require lots of resources. Maybe it’s mostly the success-bound companies who have enough resources to afford the bold changes.
Special thanks to Marika Inhoff, John McDonnell and Alex Rosner for comments on a draft of this post.