The Pull of Well-Crafted Product Visions and Release Goals

There was even a trace of mild exhilaration in their attitude. At least, they had a clear-cut task ahead of them. The nine months of indecision, of speculation about what might happen, of aimless drifting with the pack were over. Now they simply had to get themselves out, however appallingly difficult that might be. [1]

In the early 20th Century, Sir Ernest Shackleton led an expedition attempting to cross the South Pole on foot. He was unsuccessful in that attempt. What he succeeded at, however, was something far more impressive. After nearly two years of battling conditions south of the Antarctic Circle, Shackleton saw to it that all 27 men of his crew made it safely home. As Alfred Lansing notes, “Though they had failed dismally even to come close to the expedition’s original objective, they knew now that somehow they had done much, much more than ever they set out to do.”

There is much I could write about the lessons from Shackleton, his crew, and the Endurance that apply to our own individual endeavors – personal and professional. For the moment, I wish to reflect on the sheer clarity of the goal 28 men had in 1915-1916: To survive, by any means and nothing short of complete dedicated effort.

To be sure, their goal was self-serving – no one can judge them for that – and no product team is ever likely to be placed in a situation of delivering in the face of such high stakes. Indeed, the lessons from Endurance are striking in their contrast to just how feeble the drama is that is often brought into product delivery schedules. We call them “death marches,” but we know not of what we speak.

One of the things we can learn from Endurance is the power of a clearly defined objective. Do or die. That’s pretty damn clear. Time and time again, Shackleton’s crew were face with completing seemingly impossible tasks under the harshest of conditions with the barest of resources and vanishingly small chances for success.

What kept them going? Certainly, the will and desire to live. There were many other factors, too. What interests me in this post is reflected in the opening quote. The emergence of a well-defined task that cleared away the fog of speculation, indecision, and uncertainty. Episodes like this are described multiple times in Lansing’s book.

Why this is important to something like a product vision is that it clearly illustrates a phenomenon I learned about recently called “The Goal Gradient Hypothesis,” which basically says our efforts increase as we get closer to our goals. But here’s the rub. We have to know and understand what the goal is. “Do or die” is clear and leaves little room for misunderstanding. “Let’s go build a killer app,” not so much.

From the research:

We found that members of a café RP accelerated their coffee purchases as they progressed toward earning a free coffee. The goal-gradient effect also generalized to a very different incentive system, in which shorter goal distance led members to visit a song-rating Web site more frequently, rate more songs during each visit, and persist longer in the rating effort. Importantly, in both incentive systems, we observed the phenomenon of postreward resetting, whereby customers who accelerated toward their first reward exhibited a slowdown in their efforts when they began work (and subsequently accelerated) toward their second reward. [2]

Far away goals, like a product vision, are much less motivating than near-term goals, such as sprint goals. And yet it is the product vision that can, if well-crafted and well-communicated, pull a team forward during a postreward resetting period.

But perhaps the most important lesson from the research – as far as product development is concerned – is that incentives matter.  How an organization structures these is important. Since most people fail The Marshmallow Test, rewarding success on smaller goals that lead to a larger goal is likely to help teams stay focused and dedicated in the long run. Rather than one large post-product release celebration, smaller rewards after each successful sprint are more likely to keep teams engaged and productive.

References

[1] Lansing, A. (1957) Endurance: Shackleton’s Incredible Voyage, pg. 80

[2] Kivetz, R., Urminsky, O., Zheng, Y (2006) The Goal-Gradient Hypothesis Resurrected: Purchase Acceleration, Illusionary Goal Progress, and Customer Retention, Journal of Marketing Research, 39 Vol. XLIII (February 2006), 39–58

Center Point: The Product Backlog

If a rock wall is what is needed, but the only material available is a large boulder, how can you go about transforming the latter into the former?

Short answer: Work.

Longer answer: Lots of work.

Whether the task is to break apart a physical boulder into pieces suitable for building a wall or breaking up an idea into actionable tasks, there is a lot of work involved. Especially if a team is inexperienced or lacks the skilled needed to successfully complete such a process.

Large ideas are difficult to work with. They are difficult to translate into action until they are broken down into more manageable pieces. That is, descriptions of work that can be organized into manageable work streams.

We choose to go to the Moon in this decade and do the other things, not because they are easy, but because they are hard; because that goal will serve to organize and measure the best of our energies and skills, because that challenge is one that we are willing to accept, one we are unwilling to postpone, and one we intend to win, and the others, too.President John Kennedy

That’s a pretty big boulder. In fact, it’s so big it served quite well as a “product vision” for the effort that eventually got men safely to and from the moon in 1969. Even so, Kennedy’s speech called out the effort that it would take to realize the vision. Hard work. Exceptional energy and skill. What followed in the years after Kennedy’s speech in 1962 was a whole lot of boulder-busting activity

A user story is a brief, simple statement from the perspective of the product’s end user. It’s an invitation for a conversation about the what’s needed so that the story can meet all the user’s expectations.

In it’s simplest form, this is all a product backlog is. A collection of doable user stories derived from a larger vision for the product and ordered in a way that allows for a realistic path to completion to be defined. While this is simple, creating and maintaining such a thing is difficult.

Experience has taught me that the single biggest impediment to improving a team’s performance is the lack of a well-defined and maintained product backlog. Sprint velocities remain volatile if design changes or priorities are continually clobbering sprint scope. Team morale suffers if they don’t know what they’re going to be working on sprint-to-sprint or, even worse, if the work they have completed will have to be reworked or thrown out. The list of negative ripple effects from a poor quality product backlog is a long one.


Boulder image by pen_ash from Pixabay

Book Review: Tribes – We Need You to Lead Us

Tribes: We Need You to Lead Us by Seth Godin

Reading Godin is a lot like going for an enjoyable mountain hike and finding a handful of small gold nuggets along the way. No heavy effort to dig for miles in order to find the deeper, richer vein of wealth. Just enough interesting shiny bits of useful wisdom scattered along the trail to invite the reader to explore further.

“Tribes” isn’t so much about the composition and character of tribes, per se, but more a call to serve as a leader for tribes yet to be formed. “Human beings can’t help it,” he writes. “[W]e need to belong. One of the most powerful of our survival mechanisms is to be part of a tribe, to contribute to (and take from) a group of like-minded people.” But left to their own devices, tribes dissolve or evolve into something directionless, perhaps unruly. What they need to persist is some form of leadership to set the rules and customs.

Speaking to aspiring or future leaders, Godin presents what he views as the biggest blocker to people stepping up and fulfilling leadership roles.

The only shortcut in this book, the only technique or how-to or inside info is this: the levers are here. The proof is here. The power is here. The only thing holding you back is your own fear….Dr. Laurence Peter is famous for proposing that “in a hierarchy every employee tends to rise to his level of incompetence.” In other words, when you do a great job, you get promoted. And that process repeats itself until finally you end up in a job you can’t handle….I’d like to paraphrase the Peter Principle. I think what actually happens is that “in every organization everyone rises to the level at which they become paralyzed with fear.”

And the source of that fear is rooted in misaligned beliefs about criticism and failure.

As with almost everything I read, my eye is searching for ways the information I’m acquiring can be applied to improving team performance. The notion of tribes appeals to me from a social community perspective. I firmly believe there are deep psychological patterns in the human mind that unconsciously gravitate toward the idea of belonging to a tribal structure. And yet, there are limitations to that structure in the 21st Century business world. As Godin notes, “[I]n addition to the messages that go from the marketer or the leader to the tribe, there are the messages that go sideways, from member to member, and back to the leader as well.” What about communication between tribes? How might we avoid the formation of silos and corporate turf battles? These are questions for which I’ll need to continue searching as they are not addressed in “Tribes.”

Written more than ten years ago, there are elements of the book that have not aged well. For example, writing at a time which many today are considering the Golden Age of the Internet, Godin observes “In the nonsquishy tribal world of this decade, Twitter and blogs and online videos and countless other techniques contribute to an entirely new dimension of what it means to be part of a tribe.” And later, while writing about how easy it is for tribes to connect, communicate, and spread messages: “The tribe thrives; it delivers value and it spreads. Internet folks call this viral activity, or a virtuous cycle.” More commonly today the technology noted by Godin – particularly Facebook and Twitter – have resulted in the formation of more mobs than tribes and the cycles are 2019 are more vicious than they are virtuous.

However, I don’t think Godin was casting his gaze into the future through entirely rose colored glasses. He notes that crowds (and their blunt force object version: mobs) and tribes are “[t]wo different things: A crowd is a tribe without a leader. A crowd is a tribe without communication. Most organizations spend their time marketing to the crowd. Smart organizations assemble the tribe. Crowds are interesting, and they can create all sorts of worthwhile artifacts and market effects. But tribes are longer lasting and more effective.”

Several of the gold nuggets I picked up pointed to the importance of systemic thinking and analysis:

Leaders don’t care very much for organizational structure or the official blessing of whatever factory they work for. They use passion and ideas to lead people, as opposed to using threats and bureaucracy to manage them. Leaders must become aware of how the organization works, because this awareness allows them to change it.

Working in an environment that’s static is no fun. Even worse, working for an organization that is busy fighting off change is horrible.

When you fall in love with the system, you lose the ability to grow.

The status quo is persistent and resistant.

The last quote is a clear reflection of Shalloway’s Corollary. The status quo is the system pushing back.

I’ll round out this review with a few quotes that apply to a life in general.

Leaders have followers. Managers have employees.

If you need the alternative to be better than the status quo from the very start, you’ll never begin.

Life’s too short to fight the forces of change. Life’s too short to hate what you do all day. Life’s way too short to make mediocre stuff.

Defending mediocrity is exhausting.

Instead of wondering when your next vacation is, maybe you ought to set up a life you don’t need to escape from.

People don’t believe what you tell them. They rarely believe what you show them. They often believe what their friends tell them. They always believe what they tell themselves. What leaders do: they give people stories they can tell themselves. Stories about the future and about change.

Crafting a Product Vision

In his book, “Crossing the Chasm,” Geoffrey Moore offers a template of sorts for crafting a product vision:

For (target customer)

Who (statement of the need or opportunity)

The (product name) is a (product category)

That (key benefit, problem-solving capability, or compelling reason to buy)

Unlike (primary competitive alternative, internal or external)

Our product/solution (statement of primary differentiation or key feature set)

To help wire this in, the following guided exercise can be helpful. Consider the following product vision statement for a fictitious software program, Checkwriter 1.0:

For the bill-paying member of the family who also uses a home PC

Who is tired fo filling out the same old checks month after month

Checkwriter is a home finance program for the PC

That automatically creates and tracks all your check-writing.

Unlike Managing Your Money, a financial analysis package,

Our product/solution is optimized specifically for home bill-paying.

Ask the team to raise their hand when an item on the following list of potential features does not fit the product/solution vision and to keep it up unless they hear an item that they feel does fit the product/solution vision. By doing this, the team is being asked, “At what point does the feature list begin to move outside the boundaries suggested by the product vision?” Most hands should go up around item #4 or #5. All hands should be up by #9. A facilitated discussion related to the transition between “fits vision” and “doesn’t fit vision” is often quite effective after this brief exercise.

  1. Logon to bank checking account
  2. Synchronize checking data
  3. Generate reconciliation reports
  4. Send and receive email
  5. Create and manage personal budget
  6. Manage customer contacts
  7. Display tutorial videos
  8. Edit videos
  9. Display the local weather forecast for the next 5 days

It should be clear that one or more of the later items on the list do not belong in Checkwriter 1.0. This is how product visions work. They provide a filter through which potential features can be run during the life of the project to determine if they are inside or outside the project’s scope of work. As powerful as this is, the product vision will only catch the larger features that threaten the project work scope. To catch the finer grain threats to scope creep, a product road map needs to be defined by the product owner.

Show your work

A presentation I gave last week sparked the need to reach back into personal history and ask when I first programed a computer. That would be high school. On an HP 9320 using HP Educational Basic and an optical card reader. The cards looked like this:

(Click to enlarge)

What occurred to me was that in the early days – before persistent storage like cassette tapes, floppy disks, and hard drives – a software developer could actually hold their program in their hands. Much like a woodworker or a glass blower or a baker or a candlestick maker, we could actually show something to friends and family! Woe to the student who literally dropped their program in the hallway.

Then that went away. Keyboards soaked up our coding thoughts and stored them in places impossible to see. We could only tell people about what we had created, often using lots of hand waving and so much jargon that it undoubtedly must have seemed as if we were speaking a foreign language. In fact, the effort pretty much resembled the same fish-that-got-away story told by Uncle Bert every Thanksgiving. “I had to parse a data file THIIIIIIIIIS BIG using nothing but Python as an ETL tool!”

Yawn.

This is at the heart of why it is I burned out on writing code as a profession. There was no longer anything satisfying about it. At least, not in the way one gets satisfaction from working with wood or clay or fabric or cooking ingredients. The first time I created a predictive inventory control algorithm was a lot of fun and satisfying. But there were only 4-5 people on the planet who could appreciate what I’d done and since it was proprietary, I couldn’t share it. And just how many JavaScript-based menu systems can you write before the challenge becomes a task and eventually a tedious chore.

Way bigger yawn.

I’ve found my way back into coding. A little. Python, several JavaScript libraries, and SQL are where I spend most of my time. What I code is what serves me. Tools for my use only. Tools that free up my time or help me achieve greater things in other areas of my life.

I can compare this to woodworking. (Something I very much enjoy and from which I derive a great deal of satisfaction.) If I’m making something for someone else, I put in extra effort to make it beautiful and functional. To do that, I may need to make a number of tools to support the effort – saw fences, jigs, and clamps. These hand-made tools certainly don’t look very pretty. They may not even be distinguishable from scrap wood to anybody but myself. But they do a great job of helping me achieve greater things. Things I can actually show and handle. And if the power goes down in the neighborhood, they’ll still be there when the lights come back on.

Improving the Signal to Noise Ratio – Coda

In a Scientific American column delightfully named “The Artful Amoeba” there is an article on a little critter called the “fire chaser” beetle: How a Half-Inch Beetle Finds Fires 80 Miles Away – Fire chaser beetles’ ability to sense heat borders on the spooky

Why a creature would choose to enter a situation from which all other forest creatures are enthusiastically attempting to exit is a compelling question of natural history. But it turns out the beetle has a very good reason. Freshly burnt trees are fire chaser beetle baby food. Their only baby food.

Fire chaser beetles are thus so hell bent on that objective that they have been known to bite firefighters, mistaking them, perhaps, for unusually squishy and unpleasant-smelling trees.

This part is interesting:

A flying fire chaser beetle appears to be trying to give itself up to the authorities. Its second set of legs reach for the sky at what appears to be an awkward and uncomfortable angle.

But the beetle has a good reason. It’s getting its legs out of the way of its heat eyes, pits filled with infrared sensors tucked just behind its legs.

A strategy suggested by the fire beetle life cycle is if you want to maximize a signal to noise ratio, iterate through three simple things:

  1. Work to develop a super well defined signal/goal/objective.
  2. Remove every possible barrier to receiving information about that signal – mental, emotional, even physical – that you can think of or that you discover over time.
  3. Repeat

Also, the “Way of the Amoeba” is now the “Way of the Artful Amoeba.” Update your phrase books accordingly.

Improving the Signal to Noise Ratio – Revisited

Additional thoughts about signals and noise that have been rattling around in my brain since first posting on this topic.

At the risk of becoming too ethereal about all this, before there is signal and before there is noise, there is data. Cold, harsh, cruelly indifferent data. It is after raw data encounters some sort of filter or boundary, something that triggers a calculation to evaluate what that data means or whether it is relevant to whomever is on the other side of the filter, that it begins to be characterized as “signal” or “noise.”

Since we’re talking about humans in this series of posts, that filter is an amazingly complex system built from both physiological and psychological elements. The small amount of physical data that hits our senses and actually makes it to our brains is then filtered by beliefs, values, biases, attitudes, emotions, and those pesky unicorns that can’t seem to stop talking while I’m trying to think! It’s after all this processing that data has now been sorted according to “signal” (what’s relevant) and “noise” (what’s irrelevant) for any particular individual. Our individual systems of filters impart value judgments on the data such that each of us, essentially, creates “signal” and “noise” from the raw data.

That’s a long winded way to say:

data -> [filter] -> signal, noise

Now apply this to everyone on the planet.

data -> [filter 1] -> signal 1, noise 1

data -> [filter 2] -> signal 2, noise 2

data -> [filter n] -> signal n, noise n

As an example, Google, itself a filter, is a useful one. Let’s assume for a moment that Google is some naturally occurring phenomenon and not a filter created by humans with their own set of filters driving what it means to create a let’s be evil good search engine. To retrieve 1,000,000 pieces of information, my friend, Bob, entered search criteria of interest to him, i.e. “filter 1.” Maybe he searched for “healthy keto diet recipes”. Scanning those search results, I determine (using my “filter 2”) 100% of the search results are useless because my filter is “how do i force the noisy unicorns in my head to shut the hell up”. The Venn diagram of those two search results is likely to show a vanishingly small set of relationships between the two. (Disclaimer: I have no knowledge of the carbohydrate content of unicorns nor how tasty they may be when served with capers and a lemon dill sauce.)

Google may return 1,000,000 search results. But only a small subset is viewable at a time. What of the rest of the result set that I know nothing about? Is it signal? Is it noise? Is it just data that has yet to be subjected to anyone’s system of filters? Because Google found stuff, does that make it signal? Accepting all 1,000,000 search results as signal seems to require a willingness to believe that Google knows best when it comes to determining what’s important to me. This would apply to any filter not our own.

All systems for distinguishing signal from noise are imperfect and some of us on the Intertubes are seeking ways to better tune our particular systems. The system I use lets non-relevant data fall through the sieve so that the gold nuggets are easier to find. Perhaps at some future date I’ll unwittingly re-pan the same chunk of data through an experienced-refined sieve and a newly relevant gem will emerge from the dirt. But until that time, I’ll trust my filters, let the dirt go as noise, and lurch forward.

Improving the Signal to Noise Ratio – In Defense of Noise

[This post follows from Improving the Signal to Noise Ratio.]

All signal all the time may not be a good thing. So I’d like to offer a defense for noise: It’s needed.

Signal is signal because there is noise. Without the presence of noise we risk living in the proverbial echo chamber. When we know what’s bad, we are better equipped to recognize what’s good. I deliberately tune into the noise on occasion for no other reason than to subject my ideas to a bit of rough and tumble. Its why I blog. Its why I participate in several select forums. “Here’s what I think, world. What say you?”

Of course, noise is noise because there is signal. Once we’ve had an experience of “better” we are then more skilled at recognizing what’s bad. I remember the food I grew up on as being good, but today I view some of it as poison (Wonder Bread anyone?) And there are subjects for which I no longer check out the noise. The exposure is too harmful.

There are subjects for which I seem to be swimming in noise and casting around for any sort of signal that suggests “better.” I’m recalling a joke about the two young fish who swim past an older fish. The older fish says to the younger fish, “The water sure is nice today.” A little further on, one of the young fish asks the other, “What’s water?” I’m hoping to catch that older fish in my net. He knows something I don’t.

To understand what I mean by noise being necessary it is important to understand the metaphor I’m using, where it applies and where it doesn’t.

Taking the metaphor literally, in the domain of electrical engineering, for example, the signal to noise ratio is indeed an established measure with clear unit definitions as to what is reflected by the ratio – decibels, for example. In this domain the goal is to push always for maximum signal and minimum noise.

In the world of biological systems, however, noise is most definitely needed. One of many examples I can think of is related to an underlying driver to evolution: mutations. In an evolving organism, anything that would potentially upset the genetic status quo is a threat to survival. Indeed, most mutations are at best benign or at worst lethal such that the organism or it’s progeny never survive and the mutation is selected against as evolutionary “noise.”

However, some mutations are a net benefit to survival and add to the evolutionary “signal.” We, as 21st Century homo sapiens, are who we are because of an uncountable number of noisy mutations that we’ll never know about because they didn’t survive. Even so, surviving mutations are not automatically “pure” signal. There are “noisy” mutations, such as that related to sickle cell anemia. Biological systems can’t recognize a mutation as “noise” or “signal” before the mutation occurs, only after, when they’ve been tested by the rough and tumble of life. This is why I speak in terms of “net benefit.”

For humans trying to find our way in the messy, sloppy world of human interactions and thought, pure signal can be just as undesirable as pure noise. I’ll defer to John Cook, who I think expresses more succinctly the idea I was clumsily trying to convey:

If you have a crackly recording, you want to remove the crackling and leave the music. If you do it well, you can remove most of the crackling effect and reveal the music, but the music signal will be slightly diminished. If you filter too aggressively, you’ll get rid of more noise, but create a dull version of the music. In the extreme, you get a single hum that’s the average of the entire recording.

This is a metaphor for life. If you only value your own opinion, you’re an idiot in the oldest sense of the word, someone in his or her own world. Your work may have a strong signal, but it also has a lot of noise. Getting even one outside opinion greatly cuts down on the noise. But it also cuts down on the signal to some extent. If you get too many opinions, the noise may be gone and the signal with it. Trying to please too many people leads to work that is offensively bland.

The goal in human systems is NOT to push always for maximum signal and minimum noise. For example, this is reflected in Justice Brandeis’s comment: “If there be time to expose through discussion the falsehood and fallacies, to avert the evil by the process of education, the remedy to be applied is more speech, not enforced silence.” So my amended thesis is: In the domain of human interactions and thought, noise is needed by anyone seeking to both evaluate and improve the quality of the signal they are following.

A final thought…

If we were to press for eliminating as much “noise” as possible from human systems much like the goal for electrical noise, I’m left with the question “Who decides what qualifies as noise?”

Improving the Signal to Noise Ratio

A question was posed, “Why not be an information sponge?”

I’d have to characterize myself as more of an information amoeba – (IIRC, the amoeba is, by weight, the most vicious life form on earth) – on the hunt for information and after internalizing it, going into rest mode while I decompose and reassemble it into something of use to my understanding of the world. Yum.

More generally, to be an effective and successful consumer of information these days, the Way of the Sponge (WotS, passive, information washes through them and they absorb everything) is no longer tenable and the Way of the Amoeba (WotA, active, information washes over them and they hunt down what they need) is likely to be the more successful strategy. The WotA requires considerable energy but the rewards are commensurate with the effort. WotS…well, there’s your obsessive processed food eating TV binge-watcher right there. Mr. Square Bob Sponge Pants.

What’s implied by the WotA vs the WotS is that the former has a more active role in optimizing the informational signal to noise ratio than the latter. So a few thoughts to begin with on signals and noise.

Depending on the moment and the context, one person’s signal is another person’s noise. Across the moments that make up a lifetime, one person’s noise may become the same person’s signal and vice versa. When I was in high school, I found Frank Sinatra’s voice annoying and not something to be mingled with my collection of Mozart, Bach, and Vivaldi. Today…well, to disparage the Chairman of the Board is fightin’ words in my house. Over time, at least, noise can become signal and signal become noise.

But I’m speaking here of the signal quality and not it’s quantity (i.e. volume)

Some years ago I came across Stuart Kauffman’s idea of the adjacent possible:

It may be that biospheres, as a secular trend, maximize the rate of exploration of the adjacent possible. If they did it too fast, they would destroy their own internal organization, so there may be internal gating mechanisms. This is why I call this an average secular trend, since they explore the adjacent possible as fast as they can get away with it.

This has been interpreted in a variety of ways. I carry this around in my head as a distillation from several of the more faithful versions: Expand the edge of what I know by studying the things that are close by. Over time, there is an accumulation of loosely coupled ideas and facts that begin to coalesce into a deeper meaning, a signal, if you will, relevant to my life.

With this insight, I’ve been able to be more deliberate and directed about what I want or need to know. I’ve learned to be a good custodian of the edge and what I allow to occupy space on that edge. These are my “internal gating mechanisms.” It isn’t an easy task, but there are some easy wins. For starters, learning to unplug completely. Especially from social media and what tragically passes for “news reporting” or “journalism”these days.

The task is largely one of filtering. I very rarely directly visit information sources. Rather, I leverage RSS feeds and employ filtering rules. I pull information of interest rather than have it pushed at me by “news” web sites, cable or TV channels, or newspapers. While this means I will occasionally miss some cool stuff, it’s more than compensated by the boost in signal quality achieved by excluding all the sludge from the edge. I suspect I still get the cool stuff, just in a slightly different form or revealed by a different source that makes it through the filter. In this way, it’s a matter of modulating the quantity such that the signal is easier to find.

There is a caution to consider while optimizing a signal-to-noise ratio, something reflected in Kauffman’s comments around the rate of exploration for new ideas: “If they did it too fast, they would destroy their own internal organization…”

Before the Internet, before PCs were a commodity, before television was popular it was much, much easier to find time to think. In fact, it was never something that had to be looked for or sought out. I think that’s what is different today. It takes WORK to find a quiet space and time to think. While my humble little RSS filters do a great job of keeping a high signal-to-noise ratio with all things Internet, accomplishing the same thing in the physical world is becoming more and more difficult.

The “attention economy,” or whatever it’s being called today, is reaching a truly disturbing level of invasion. It seems I’ve used more electrician’s tape to cover up camera lenses and microphones in the past year than I’ve used on actual electrical wires. The number of appliances and gadgets in the home with glowing screens crying out for bluetooth or wifi access like leaches seeking blood are their own source of noise. This is my current battleground for finding the signal within the noise.

Enough about filtering. What about boundaries. Fences make for good neighbors, said someone wise and experienced. And there’s a good chance that applies to information organization, too. Keeping the spiritual information in my head separate from my shopping list probably helps me stop short of forming some sort of cult around Costco. ( “All praise ‘Bulk,’ the God of Stuff!)

An amoeba has a much more develop boundary between self and other than a sponge and that’s probably a net gain even with the drawback of extra energy required to fuel that arrangement. Intellectually, we have our beliefs and values that mark where those edges between self and other are defined.

So I’ll stop for now with the question, “What are the strategies and mental models that promote permeability for desired or needed information while keeping, as much as possible, the garbage ‘out there?’”