Rubber duck meetingsthree days beforeWhen I am looking for new insights, a generative conversation with colleagues…A Solution

Understanding2022Once the notion of a problem is sufficiently semantically disambiguated, we can…If we are looking at a problem, and as we learned earlier, our understanding of a problem is a model that includes us, our intention, and the phenomenon that is a subject of it, then a solution is the problem understanding-based prediction that resolves the problem’s intention, aligning the state of the phenomenon with it.

Touching infinity2022As we explore the process of understanding, it may not be immediately…Because the problem’s model includes us, the solution often manifests as a set of actions we take. For example, for my trying to repel that mischievous bunny from the previous piece, one solution might look like the list of a) grab a tennis ball, b) aim at the tree nearby, c) throw the ball at the tree with the most force I can muster. However, solutions can also be devoid of our actions, like in that old adage: “if you ignore a problem long enough, it will go away on its own”.

Lenses, framings, and models2022At a meeting this week, I realized that I use the terms…Note that according to the definition above, a solution relies on the model, but is distinct from it. Same model might have multiple solutions. Additionally, a solution is distinct from the outcome. Since I defined it as a prediction, a solution is a peek into the future. And as such, it may or may not pan out. These distinctions give us just enough material to construct a simple framework to reason about solutions.

Change2022Polarity of intention, structure, and capacity2022

Prediction errors and jank2021It seems that the retained mode is our way to compensate for…Let’s see… we have a model, a solution (aka prediction), and the outcome. All three are separate pieces, interlinked. Yay, time for another triangle! Let’s look at each edge of this triangle.

The value triangle2022My colleagues and I were chatting about the idea of a “good…A problem2022To get a more solid grounding of the newly born decision-making framework,…When we study the relationship between solution and outcome, we arrive at the concept of solution effectiveness, a sort of hit/miss scale for the solution. Solutions that result in our intended outcomes are effective. Solutions that don’t are less so. (As an aside, notice how the problem’s intention manifests in the word “intended”). Solution effectiveness appears to be fairly easy to measure. Just track the rate of prediction errors over time. The lower the rate, the more effective the solution is. We are blessed to be surrounded by a multitude of effective solutions. However, there are also solutions that fail, and to glimpse possible reasons why that might be happening, we need to look at the other sides of our triangle.

The edge that connects solution and model signifies the possibility that our mental model of the problem contains an effective solution, but we may have not found it yet. Some models are simple, producing very few possible solutions. Many are complicated labyrinths, requiring skill and patience to traverse. When we face a problem that does not yet have an effective solution, we tend to examine the full variety of possible solutions within the model: “What if I do this? What If we try that?” When we talk about “finding a solution,” we usually describe this process. To firm this notion up a bit, a model of the problem is diverse when it contains many possible solutions. Solution diversity tends to be only interesting when we are still looking to find one that’s more effective than what we currently have. Situations where the solution is elusive, yet the model’s solution diversity is low can be rather unfortunate – I need to find more options, yet the model doesn’t give me much to work with. In such cases, we tend to look for ways to enrich the model.

This is where the final side of the triangle comes in. This edge highlights the relationship between the model and the outcome. With highly effective solutions, this edge is pretty thin, maybe even appearing non-existent. Lack of prediction errors means that our model represents the phenomenon accurately enough. However, when the solution fails to produce the intended outcome, this edge comes to life: prediction errors flood in as input for updating the model. If we treat every failure to attain the intended outcome as an opportunity to learn more about the phenomenon, our model becomes more nuanced, and subsequently, increases its solution diversity – which in turn lets us find an effective solution, completing the cycle. This edge of the triangle represents the state of flux within the model: how often and how drastically is the model being updated in response to the stream of solutions that failed? By calling it “flux”, I wanted to emphasize the updates that lead to “interesting” changes in the model: lack of prediction error is also a model update, but it’s not going to increase its diversity. However, outcomes that leave us stunned and unsure of what the heck is going on are far more interesting.

Being Strategic2022

Solved, solvable, unsolvable2022I have been noodling on a decision-making framework, and I am hoping…Settled and “not settled yet” framings2021I was working on decision-making frameworks this week and had a pretty…The OODA Loop2021One of the lenses for which I tend to reach frequently is…Life of a solutioneight days after, links hereLooking at the framework in the previous piece, I am noticing that…Model compressionlinks here, 2022At the end of each journey in our process of understanding, we…Model compression and uslinks here, 2022Alas, combining technology and a large-enough number of people, it seems that…The problem understanding frameworklinks here, 2022The layers are at the top, arranged (left-to-right) from more concrete to…Limitslinks here, 2022This story builds on the one I wrote a while ago, and…A vision and a hallucinationlinks here, 2022To be compelling, a vision must be posed as a solution. That…The cycle of not-learninglinks here, 2022It’s always surprising to me how, when back at Lament, we grapple…Wait. Did I just reinvent the OODA loop? Kind of, but not exactly. Don’t get me wrong, I love the Mad Colonel’s lens, but this one feels a bit different. Instead of enumerating the phases of the familiar circular solution-finding process, our framework highlights its components, the relationships between them and their attributes. And my hope is that this shift will bring new insights about problems, solutions, and us in their midst.