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DEEP Framework: Documenting Decisions, Events, Explanations, and Proposals in Your Org
Summary:
The DEEP framework emphasizes the documentation of decisions, urging the recording of the rationale behind business and general decisions.
It also stresses the importance of documenting events such as meetings and town halls, highlighting the need for summarization. Furthermore, the framework encourages documenting explanations, especially in the context of onboarding, as they often involve repeated material.
Lastly, it emphasizes documenting proposals or ideas, allowing individuals to present their rationale to others and providing time for considered reactions.
The acronym 'DEEP' serves as a reminder for teams to consider the documentation created within their workflow.
Transcript:
Speaker 1
So I came up with an acronym as well, and I call that acronym deep. I think you'll identify with some of these. So deep for decisions, if there's ever a decision, then you should record the rationale for it. And we've talked about it endlessly on our tech radar's decision record systems. But I extend that to business decisions as well and general decisions as well. So similar format. Then there's events. So you have a town hall, you have a meeting, all of those are events, right? And you better document them for the benefit of other people. And when I say document, I mean, summarize, sure, you can have a recording or snippets of recordings if they are useful for people, but the summary is the more important thing. Then there's explanations, and I found these very useful in the context of onboarding, because there's a lot of explainer material that gets repeated in onboarding. And those are definitely great candidates for documentation. And the last one is proposals. And I called that proposals, but really I'm trying to talk about things like ideas. So let's take an example. I want to use this new library on my project. I have a certain rationale for it. Let me write down the thought process. What value is it going to bring? Let me present it to everyone. Everyone has the time to consume it. Oftentimes we go into decision making with a lot of cognitive load, where, you know, Ken explains in rapid fire things that he's been thinking about for the last 15 days. And now I have to consume it in the next 30 minutes and give Ken a year or nay. It's really difficult because Ken's done all the deep thinking, I need the time to process it and writing gives me the time to process it, right? And I can also not give knee jerk reactions, but considered reactions. So proposals, and that starts to include design documentation, idea papers, any kinds of proposals that you make on the team. So that acronym deep is a good trigger for teams to kind of hold on to and think about what is the documentation we're creating in the flow of work.
Asynchronous Collaboration — Getting It Right
Thoughtworks Technology Podcast
Providing Mental Scaffolding and Tools Drastically Increases Human Cognitive Performance
Summary:
Scaffolding people's experiences with tools like mind mapping can raise their performance above their innate capacities.
Studies have shown up to a 40% increase in cognitive capacity when individuals are taught and encouraged to use tools for problem-solving and understanding. This highlights the significant role of tools in enhancing human cognitive performance, akin to how a computer is described as a 'bicycle for the mind' by Steve Jobs.
Transcript:
Speaker 1
So but Kotzky was this Russian educational theorist, right? And he and his whole notion was, if you scaffold people's experiences, so just training wheels, right, basically, you can raise the level of their capacity and their performance above And beyond their innate capacities. So mutual friend of Danglish Marktemberg, who's in Jordan Hall's, and I was Zack Stein, as a Harvard psychologist, very thoughtful guy. And he was working with an organization, his whole dissertation was on standardized testing and how whacked it is, right? And how the inequities it bakes into the system and that kind of thing. And they did studies where they would have somebody, you know, fundamentally on an intelligence or cognitive capacity assessment, right, makes sense of your life, makes sense of The world, makes sense of this word problem, whatever it would be. And then, you know, and then someone would score, you know, a 60% or a three out of five on a Leica scale, right? But then they would teach them how to mind map, right, a tool scaffolding, right? And they'd say, okay, so now everything you just said there, now hit the like draw connections, draw bubbles, draw dotted lines, like, sort and establish the relationship here about What you were thinking, and then retested them. And they would score a five out of five. So there's sort of up to this 40% swing in someone's intelligence or cognitive capacity, just based on did you give them a tool, right? It's like Steve Jobs saying, you know, that a computer is like a bicycle for the mind, right? And you're like, oh, okay. So how many bicycles for our minds, right? Can we share and create such that we can all pedal faster?
#11 - Jamie Wheal — Tackling the Meaning Crisis
Win-Win with Liv Boeree
The Danger of Incorrectly Mapping Between Scientific Measures and Truth
Transcript:
Speaker 1
And it's a problem when scientific culture tolerates too much ambiguity. There's always a caveat there, which is that at the early stage of theory development, sometimes you need ambiguity because you don't actually know really what you're talking about Yet. And so you need to allow for multiple interpretations to be possible until you can figure out what you mean. But a mature theory should be minimally ambiguous. This is at odds with things like metrics in terms of let's say how to evaluate something because people think, oh, well, it's scientific. Therefore, I want to use this to then therefore impose a value judge on something. It's better because it has a higher score on it. But that's not what science is actually able to do. Science can say, it has this score and it measures this thing because what it measures is this. If you say what it measures is this, and therefore it means this other thing, that's a problem because that's a false mapping. And it's not really about ambiguity versus precision. It's about, I think, the imprecision of the mapping between the measure and the term. So if you want to measure something like happiness or economic prosperity, you can say, well, we'll measure the genie coefficient, we'll measure GDP. But those are rigorous, clearly unambiguous measures. They have a meaning. This is what they are. This is how we measure them. We can compare things on this measure. And that's not problematic until you then say, and it is better to have a higher GDP full stop.
Paul Smaldino & C. Thi Nguyen on Problems With Value Metrics & Governance at Scale
COMPLEXITY: Physics of Life
...catch up on these, and many more highlights
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