Category: Systems

Long Absences

You never intend to step away for very long. A week goes by, then another. Without realizing it, a month has passed.

It can sometimes be hard to keep up a weekly blog. I don’t know how the daily folks do it – Seth Godin says it’s just consistency, but does that mean it’s easier to show up everyday than once per week? Maybe… It’s harder to push off to tomorrow when the deadline is always midnight. I’m not impressed by the folks whose job is to churn out multiple pieces of content per day. Creative burnout aside, there is a difference between being paid for the content and doing it without pay.

Excuses are easy, especially when they are real. Yes, I didn’t set time aside to write, but I also had a major deliverable due at work. I even set up auto-responders on my emails to manage people’s expectations while I was in focus mode. These are reasons, but they do not excuse the absence when you know what you are getting yourself in to.

And when you return to the notion of an update, you feel the need to write something profound to offset the time away, but the ideas feel crusted and not worth sharing. Instead, you hide away, and figure you’ll get back to it next week, meanwhile the feeling of panic and dread increases at the thought of delivering that perfect post.

But next week comes and goes.

There is no magic solution beyond showing yourself compassion, resetting the clock or counter, and shipping the next thing by trying again.

Stay Awesome,

Ryan

Workplace Weakness

I’ve been thinking about personal weaknesses I have in the workplace – besides missing my regular posts for this blog…

Focus and persistence are two things I think I am weakest at. On a macro level, I have poor focus to stay on task. The consequence of poor focus means I either flit from project to project, or I self-sooth to avoid the pain of friction (typically by going on YouTube).

Poor day-to-day focus leads to poor persistence, which means I don’t carry things to completion. I stick in the ideas or early implementation phase. I chase the next shiny distraction. This would be somewhat remediated through better habits and intentional prioritization of my tasks and time. It would also be partially addressed through better task management, where everything is organized and resurfaced at the times I need them.

Solutions:

Focus
– short work sprints (pomodoros)
-discrete tasks (break projects into small, well-defined, finite steps)
-block out the world (headphones and white noise)
-block out distractions (website blockers)

Persistence
-organized task management system
-calendar blocking
-show up each day with focus habits (see above)
-project and tasks planning
-recognize that progress is made in small steps

Stay Awesome,

Ryan

Forced System Growth

It’s been a busy few weeks between work and a sick kiddo at home. Sorry for missing the last two posts.

The changes I’ve recently experienced at work has inspired some thinking on this post’s topic. While I typically have a good mind for keeping track of projects (with some liberal use of a notebook), the updates to my job and the sheer scope of accrediting an engineering degree has proven to be more than my current organizational and productivity systems are capable of managing. Tasks were rapidly multiplying and open-loops weren’t being migrated for tracking; there was no translation between meeting notes and what was getting scheduled into my calendar.

I functionally hit a crossroad. One path was to keep trying to do the same thing and fall further behind, and the other was to force a systems growth to accommodate my new workload. What got me here won’t get me there, if you will. Put another way, my outputs were optimized to how I managed my workload, so if I wanted to change or improve my output, I would have to change the system. Changes in work forced the system to grow.

On one level, I want to deny this – why do I have to constantly adapt the system to new work? Can’t I find one universally applicable approach to managing my workload? Sadly, no. This is the pipedream sold by productivity wizards who claim their one system will take care of everything. The reality is that those systems are often tweaked to meet the unique cognitive needs of the person. If you want to use those prescribed systems (GTD, Building a Second Brain, etc), you will need to adapt it to how your mind processes information. And it makes sense that as you grow in your career, you will need to grow the systems that you use to keep on top of things.

Most of my systems have developed “organically.” I would implement new features on an ad hoc basis in response to specific needs. This is one of the first times that I’ve had to make large changes by first thinking through what I needed and how I wanted things to play out. As weird as it is, it reminds me of Stephen Covey and seems to combine two of his principles – begin with the end in mind, and sharpen your axe. By knowing where you want to go, and by spending a lot of front-loaded work setting things up, you have a better chance of dealing with bumps as you go.

Stay Awesome,

Ryan

Optimizing, Values, and the Right Answer

Engineers love clear problems with delineated right and wrong answers. Data, especially quantified data they think, is objective and clean. Without painting too strong of a stereotype, they don’t like to muck around with soft skills, or social/political factors in problems. They like to keep engineering pure.

The problem with this view is that it’s not correct – it makes an underlying assumption about what makes something a right or wrong answer to a problem. Most problems that engineers deal with when designing a solution are not value neutral. When we think of problems with clear right or wrong answers, we think of problems that are purely mathematical or having discrete binary solutions (e.g. “will the object handle the forces that it will be subjected to under normal conditions?”). The secret is that all problems have “right” and “wrong” solutions based on the underlying values you are trying to optimize for.

An engineering problem that is optimizing for maximizing return on investment might have different solutions than one that optimizes for addressing systemic inequity for particular people. The tradeoffs are not just opportunity costs, but instead are tradeoffs on which values inform the vision of the final outcome of your solution. When you seek to return on investment, to maximize profit, the answers are pretty clear – drive down expenses, raise prices as high as the market will bear, communicate the value proposition to the customer, and produce enough goods at the right rate to meet demand without excess goods sitting idle. When you seek to address systemic inequity, your solutions will have decidedly different considerations – your expenses will go up as you pay fair wages, prices might not maximize your margins, you will be more candid with your customers, and your manufacturing and distribution will be likely slower and more intentional as you make ethical considerations in your processes. You will also consider all sorts of other externalities that pop up as a result of your solutions, boosting the positives while capping the downsides.

This is not to say that all solutions will be equally easy to implement under any one set of values systems that you choose. However, it’s fallacious to believe that the same answer will always be given for “can we build this?” and “should we build this?” if you aren’t also examining the underlying values that you set in your assumptions.

Stay Awesome,

Ryan

Getting the Need for GTD

I seemed to have hit an inflection point in my job recently that I’ve been struggling to overcome. While my work has had multiple buckets of concern, I’ve been able to managing things fairly well using my memory and jotting notes and to-do’s in my notebook. However with moving into a position that requires managing complex, long-term, and poorly-defined processes, I’ve been increasingly finding it difficult to keep everything straight in my mind. My tasks aren’t are clearly defined, and I’m required to be more independent in how I manage both my own personal workflow and the various areas under my responsibility.

Simply maintaining a to-do list doesn’t seem to cut it anymore. There is too much to keep track of, too many legacy pieces of information that has accumulated over time, and the pace at which things are added or change is steadily increasing in velocity. Add to this the need to keep on top of things in our personal life at home, volunteer work, and activities that I find gratifying, and I’m feeling slightly paralyzed in knowing what I should fix my attention to.

In an effort to get a handle on things, I’ve picked up David Allen’s Getting Things Done. It’s the first time in a while where it feels like the text is speaking to me. I went into the book a little leery of going after yet another gimmick or shiny new toy. GTD is a seminal system in the productivity space, and so it sometimes carries with it some baggage from some of the more problematic areas of the space. Yet, I’ve found it helpful so far in thinking through my problems. At its core, my problem is in two areas: the meaningful transformation of input, and in execution.

I suppose GTD will eventually help me with the latter (I don’t know – I haven’t finished the book yet as of writing), but it’s been incredibly insightful in tackling the former. I tend to take notes and capture to-do items all over the place. However, what I’ve been lacking is examining each of these pieces of input and doing something with it; processing them into their buckets. The list has grown so large and unwieldy that I am having trouble finding stuff when I need it. I have tried popping items into information systems like Notion, Trello, or using tags to help me find it later, but most of these systems have lacked the context to help make the inputs useful later. Instead, they sit in whatever capture system was used to grab them at the time – physical notebook, email inboxes, Trello, tags in OneNote, calendars, or tasks in Teams.

I’ve found GTD helpful in suggesting organizational structures and parse out what will be meaningful later and what can be archived out of mind. I’m still working through developing a system, but so far embracing ideas from GTD has helped keep things more readily at the top of my mind, which has translated into less general anxiety as I go through the work day.

Stay Awesome,

Ryan

Cross-Domain Knowledge

I’m a huge fan of cross-domain knowledge. Coming from an academic background in philosophy, I feel my greatest strategy for creating and building a career is leaning in hard to knowledge and skills that are learned in one domain or context, then applying it to a unique area. You get a large confidence boost when you make connections by spotting patterns and connections that map analogical cases to each other.

The first time I truly appreciated this was in my days working for the university gambling lab. We were collecting data on slot machine players by recruiting participants into our study to measure the effects properties of the machine user-interface had in gambler’s cognitive awareness. In other words, did how the graphics and sounds play on the screen help the gambler understand their relative wins and losses over time. In one study, the simulation we were using for participants to play on during the trial had been modified, but on some of the laptops the wrong version of the software was copied over, and we didn’t realize the mistake until the end of the day. Of the three laptops, two had the right software, and one did not. At the end of each session, we uploaded the user data to a secure repository and deleted the local files, which meant that once we were back in the lab, there was no way of knowing which participant file batch came from the defective software.

We thankfully caught the issue early and limited the damage, but afterwards we had an issue with figuring out which files to exclude from analysis. On the face of it, there was no way of knowing from the participant’s biometric data which simulation they used. So instead we had to dig into the debug files that were spit out by the machine to verify that the simulation ran successfully.

All the files were generated in an XML format, however I had neither experience in basic coding nor reading XML files. I had to figure out a way of showing whether the version of the software was correct. To me, the XML files were largely gibberish.

But, I was able to spot a pattern in the files that reminded me of my formal logic courses from undergrad. While I did poorly in the courses at the time, I did retain some of the strategies taught for understanding the structuring of the syntax of formal logic arguments, specifically how nested arguments worked and how assumptions were communicated. I started to see the same structure in the XML code, how sub- and sub-sub arguments were written to call different files into the program, and where those files were being drawn from.

And there it was. At the bottom of one of the debug files, was a list of the files being called on by the simulation. In the broken simulation, the file path to a certain sound that was meant to be played was empty, meaning that when the simulation was supposed to play and auditory cue, there was no file name to look for, and so the simulation moved on.

I compared this with the files we knew came from the working simulators and saw that this was the main difference, giving us the key for finding the bad data points and justifiably excluding them from the overall data set. By finding this, I saved an entire day’s worth of data files (a cost savings that includes the some-30 participant files, their remuneration, three research assistant wages, per diem costs, travel, and consumable materials on site).

I grant that computer programming is entirely built on the foundations of formal logic and mathematics, so it’s not that I was gaining a unique insight into the problem by bringing knowledge from one separate domain into another. However, this was one of the first times I encountered a problem where I lacked the traditional knowledge and skill to address it, so I came at the problem from another angle. It was a case where I gained confidence in myself to be resourceful and tap into previous learning to address new/novel problems.

As I noted above, being trained in academic philosophy has pushed me in this direction of career development. On a superficial level, relying on cross-domain knowledge is a career survival strategy because philosophy doesn’t always teach you skills that are easily applicable to the working world. I have sadly, never once, had to use my understanding of Plato’s arguments in my workplace. But on a deeper level, I think training in philosophy naturally pushes you into this kind of problem-solving. Most of my experiences in philosophy involves approaching a thought experiment or line of thinking, considering what it’s trying to tell us, then testing those arguments against counter-factuals and alternative arguments or explanations. To do this well, you have to reduce a problem down into its constitutive parts to tease out relevant intuitions, then test them out, often by porting those intuitions from one context into another to see if they still hold as both valid and sound.

It’s not all that dissimilar to the processes used by engineers or designers to gather data and accurately define the problem they are intending to design for. Whereas the engineer will apply the tools they’ve been taught fairly linearly to create a design for the problem, my strategy is to adopt cross-domain knowledge to make connections where they might previously had not been apparent. The results can often be solved quicker or more efficiently if I had the relevant domain knowledge (e.g. an understanding of coding), however when I lack the specific experience to address the problem, as a generalist thinker I have to rely on analogical thinking and a wider exposure to ideas to suss out those connections. What I lack in a direct approach, I make up for in novelty and creative/divergent thinking, which has the benefit of sometimes opening up new opportunities to explore.

Stay Awesome,

Ryan

Slipped Time

Sorry for the lack of posts these last two weeks. I have lots of reasons (the holiday Monday, work has been keeping me busy, feeling tired from childcare, and our family being sick the last week), but those are poor excuses for not carving out some dedicated time to put thoughts to screen. I have been doing a decent job of holding myself accountible with work, but knowingly allowing two weeks to go by unplanned without posts shows that my systems still have some issues with keeping me on top of everything.

I appreciate the grace you have offered in my absence.

Stay Awesome,

Ryan

Blocking Distraction

For as much as think I am in control of my impulses, the reality is I am buffeted around by my whims far more than I wish were true. The biggest bane to my daily work is the mighty well of distraction that is YouTube. I’ve lost hours of time in a day allowing my subscriptions to serve me fresh content. I try to justify it to myself – “I’m just going over for a quick mental break,” or “I just need to see a tutorial on how to do x-action in Excel.”

Then, I look up and hours might have passed without me consciously knowing it.

Some time ago, I used a browser blocker to prevent me from accessing the worst offenders for distraction (all social media, YouTube, and Reddit specifically). I’m no stranger to signing an Odysseus contract, which I’ve written about before. However during the pandemic, I relaxed it a bit since, hey, we are all going through a rough time.

As of late, I’m forced to conclude that enough is enough, it’s time to hold myself to a higher standard. I went back in, and toggled StayFocusd back on, and so far have done a better job of accounting for my time. Between blocking distractions, using pomodoro sprints, and writing down what I do in my time blocks (quick estimates, nothing too detailed), I’ve done a pretty good job of limiting distracted time.

It’s not perfect, but it’s more than a 1% improvement, which will hopefully compound over time.

Stay Awesome,

Ryan

Drip By Drip

A reminder to myself –

I have a tendency to measure progress according to leaps forward in productivity. I block off my calendar with large swaths of time, which gives the illusion that the time spent in a labelled block of time will be proportionate to how far the needle is moved.

But these are just that: illusions.

There are only two kinds of progress I make – the last minute panic against the deadline, and the lesser used but more sustainable drip by drip of micro-steps. The former is very cathartic, but we have to remember that catharsis means to purge, and so in the end you are left drained and must recover.

A focus on small steps, in the 1% change, is harder to track without perspective, but ultimately is an easier trek if you have the focus to stay on the path.

Stay Awesome,

Ryan