Week of 2022-01-17
Normative, Informative and Generative Voices
I’ve been thinking about how to convey the style of writing that I’ve learned while writing here, and this lens materialized. And yes, once again, the distinctions come in threes. As Nicklas Berild Lundblad suggested, I might be suffering from triangulism… and I like it.
The normative voice is spurring you to action. Normative voice aims to exert control, which may or may not be something you desire. For example, signs in public places tend to be written in a normative voice. Objectives, team principles, political slogans, and codes of conduct – all typically have that same quality. Normative voice usually conveyed some intention, whether veiled or not.
The informative voice is not here to tell you what to do. Informative voice goes “here’s a thing I see” or “here is what I am doing.” Informative voice does not mean to impose an intention – it just wants to share what it’s seeing. As such, the informative voice tends to come across aloof and unemotional, like that of a detached observer.
Given that our primary medium of communication is of human origin and thus deeply rooted in feelings, it is incredibly challenging to separate normative and informative voices. I might believe that I am writing something in an informative voice, but employ epithets and the turns of the phrase that betray my attachment. Similarly, I could be voicing something that looks informative, but actually intends to control you – aka the ancient art of manipulating others. Let’s admit it, my teen self saying: “Mom, all kids have cool <item of clothing> and I don’t” was not an informative voice, no matter how neutrally presented. Another good sign of “conveyed as informative, yet actually normative” voice is the presence of absolute statements in the language or subtly – or not! – taking sides as we describe them.
Conversely, I might be trying to write normative prose, yet offer no firm call to action or even a sense of intention. My experience is that this kind of “conveyed as normative, yet actually informative” voice is commonly an outcome of suffering through a committee-driven wordsmithing process. “I swear, this mission statement was meant to say something. We just can’t remember what.” – oh lordy, forgive me for I have produced my share of these.
Within this lens, the constant struggle between the two – and the struggle to untangle the two – might seem rather unsatisfying and hopeless. Conveniently, I have a third voice that I’ve yet to introduce.
The generative voice accepts the struggle as a given and builds on that. Generative voice embraces the resonance-generating potential of the normative voice and the wealth of insights cherished by the informative voice. Yet at the same time, it aims to hold the intention lightly while still savoring the richness of feelings conveyed by the language. Generative voice is the voice that spurs to improvise, to jam with ideas, to add your own part to the music of thinking.
This is the language that I aim for when writing these little essays. For example, I use the words “might” and “tends to” to indicate that these aren’t exact truths, and I don’t intend to hold these firmly. I try to explore every side of the framing with empathy, inhabiting each of the corners for a little while. But most significantly, I hold up hope that after reading these, you feel invited to play with the ideas I conveyed, to riff on these, departing from the original content into places that resonate more with you. When speaking in the generative voice, I primarily care about catalyzing new insights for my future self – and you. And in doing so, I am hopeful that I am helping us both find new ways to look at the challenges we’re facing.
🔗 https://glazkov.com/2022/01/17/normative-informative-and-generative-voices/
Behavior over time graphs and ways to influence
I was geeking out over behavior-over-time graphs (BOTG) this week and found this neat connection to bumpers, boosts, and tilts. My colleague Donald Martin first introduced me to BOTG and they fit right in, given my fondness for silly graphs.
The idea behind BOTG is simple: take some measure of value and draw a graph of its imagined behavior over time. Does the line go up? Does it go down? Does it tepidly mingle at about the same level? To make it even more useful, we can use BOTG for predictions: draw the “today” vertical line on the graph, splitting the space into “past” and “future.” Now, we can use it to convey our sense of how things were going before, and predict what happens next.
Now, let’s add another twist to this story: the goals. Usually, if we care about a value, we have some notion of a goal in relation to this value. Let’s draw this goal as a horizontal line at the appropriate level. If our goal is reaching a certain number of daily active users, and capture this notion by drawing our BOTG squiggly in a way that crosses the goal line in the “future” part of the graph.
It turns out that by considering how we’ve drawn this intersection of goal and BOTG lines, we can determine the type of the influence that might be effective to make our prediction come true.
If our BOTG curve needs to touch and stick to — or asymptotically approach — the goal line, we are probably talking about a bumper. There is some force that needs to keep that curve at a certain level, and that’s what bumpers are for. For instance, if I want to keep the size of the binary of my app at a certain level, I will likely need to employ team processes that enforce some policy about only landing changes that keep us under that magic number.
If we picture the curve as temporarily crossing the goal line, we are probably looking at a boost. This is literally the “we just need to get it across the line” case. A good example here is the intense march toward a release that many software engineering teams experience. There are some criteria that are determined as requirements for shipping, and, spurred by the boost, the team works their hearts out trying to meet them. A common effect of a boost is the slide back across the line after the team ships, relaxing and resting ahead of another round of shipping.
Last but not least, the curve that permanently crosses the goal line and never looks back is likely a marker of a tilt. Here, the goal line is just a checkpoint. Did we reach N daily active users? Great. Now let’s go for N x 2. When such ambition is part of the prediction, we are likely looking for some constant source of compounding energy. A good question to ask here is — where will it come from?
One of the common mistakes that I’ve seen leads make is confusing the outcomes of boosts with those of tilts. Both offer gains. Boosts feel faster and provide that satisfying thrill of accomplishment, but they are at best temporary. Tilts are slower, but their advances are more lasting. So when leaders employ a boost and expect the curve to just stay over the goal line, they are in for an unpleasant surprise. Early in my tenure at the Chrome team, I organized a task force to reduce the number of failing tests (shout out to my fellow LTTF-ers!), a small scrappy band of engineers dedicated to fixing failing tests. At one time, I reported that we brought the number of failures down from a couple of thousands to just 300! Trust me, that was an amazing feat. I am still in awe of us being able to get there. Unfortunately, my strategy — organizing a task force — was that of a boost. The spoils of the hard-won victory lasted a week after the task force disbanded. For a sobering reference, that list of failing tests is currently clocking at 7623 lines.
See if the BOTG with goals can help you puzzle out what might be the strategy for that difficult next endeavor you’re facing. Use them to clearly capture your predictions – and perhaps glimpse which method of influence might be needed to make them a reality.