So what do we trade off?
In this kind of impromptu sequel (from last post here), I want to now get deeper with some practical examples on what we actually end up trading off in the type of (product) work we do.
If there are no solutions, but only trade-offs (as Sowell would claim), what does it really mean in our context of developing products.
First, a bit of definition, by product I essentially mean the creative work associated to find a way of making the world (a little bit) better – and I know it sounds pretentious, but is a nice to articulate it – by tackling some problem. You may be thinking – “you mean, like finding a solution for a problem?! So there solutions in the end!?”. Well the “a” in front there actually matters. So what it means is that on a practical level when we find a proper trade-off to make progress we may coloquially refer to that as “a solution”.
But too often it’s technically not quite that. It is a way to make progress, which may have its consequences (for the good and for the bad), which circles us back to the idea of trade-offs.
That’s one angle, but there’s more to it.
The idea of trade-off also alludes to how we approach deciding what is that, coloquially put, “one possible solution” to the problem at hand (or where we want to make progress) we want to go after. In simple words, with an example…
If I have an option that is estimated to unlock $10,000 (over a period of time) as value and another one of $100,000 estimated value (over the same period of time), the trade-off is fairly straightforward.
What if each of them require disproportionate investment of our resources (time oftn being the main of them in context of products) to accomplish that? By when the trade-off could look different? Well, at the most basic level, we can say that, other factor aside, only if the difference in investment was of the order of magnitude of 10x or more, faster in favor of the lowest estimated value – by then we probably also put a bit of value, even in an intangible way, just intuitiverly, on having something earlier at hands of our customers.
But what if I told you that we also expect each of those options to have a different probability to be successful. Let’s imagine we did some due diligence and we expect the lowest value option to be much more probable (estimated 90% chance of success) whereas the highest value one to be more like a gamble (estimated 50% chance of success).
Now the picture again has changed, and the balancing of investment is now a little over 5x. So should the $100,000 option not be expected to take more than fivefold more investment (of time), we should probably still favor it.
Are we done now? Is that all – we do our due diligence, we try to find that slightly deeper understanding of the economics behind the scenes, and off we go?!
We wish… as I have written before:
The life of a product manager is supposed to be pretty easy… We would figure out the thing that has the most (estimated) value, with a fair confidence level, maybe contrast that to the level of effort needed, and use a sort of cost of delay principle for prioritization.
But then we hit reality and we start to understand that in those few factors we probably had to make a number of assumptions. That’s just to get to that understanding of the estimated value, of the confidence in success and the level of effort needed.
In simple words, all those things behave probabilistically, not deterministically, in reality.
So that tell us a few things:
That we should still aim at trying to have that deeper understanding, and attempt “to put a finger on” what’s the expected value (contrasted with efforts and an understanding of the chances of success).
That the factor time (or investment, effort needed, which tends to be correlated in the type of work in products, assuming a context with reasonable flow efficiency) can be seen as one we can use as a proxy to find that balance / optimization.
So, ultimately, we can focus on obsessing about (fast) flow, with a key element being the idea of reducing batch sizes (or as I prefer to call it, since there’s such a thing as too small in product, “right-sizing for flow”).
Think about it this way – if you were playing poker, when would you go all-in? Versus when do you trade-off a little for more information before going all-in?
That’s, ultimately, what this is all about! We are trading-off a little effort and investment of time (with a small thoughtful increment) so as to learn more and better assess the economics behind (and perhaps contrast with the original assessment).
Let’s go back quickly, to wrap this up, to the scenario used before. Let’s imagine our original assessment is as follows:
Option A estimation: value = $10,000; change of success = 90%; time to market = 1 week;
Option B estimation: value = $100,000; change of success = 50%; time to market = 5-6 weeks;
That is to say, we are in a position where the options seem to be roughly the same kind of risk (other factors not playing a considerable role). Wouldn’t you consider investing 1 week worth of work in a well-designed experiment that could help to give more insight on B, as being the potentially most valuable option?
Maybe you will reassess the chance of success given the outcome of that 1 week of effort, or maybe you now understand better the time to market. Depending on which direction and with which intensity that goes, it may well be at the point you can finally go all-in, or way or another.
P.S.: In case you are interested in being inspired by some of the underlying ideas from this post, here are two complimentary books. Reinertsen’s is a classic on flow-based approach with the discipline of applying that deeper economical understanding as much as possible. And Duke’s reminds us that we can get as disciplined as we want in trying to assess things upfront, but reality is that living is probabilistic, and we need to find that balance on when we have enough information to move forward (while not getting stuck on analysis-paralysis).
By Rodrigo Sperb, feel free to connect, I'm happy to engage and interact. I’m passionate about leading to achieve better outcomes with better ways of working. How can I help you?