How Can We Learn If Decisions Are Disconnected from Impact?

Posted on Published by Eugene Eric Kim

Two years ago, there was a ballot initiative in California, Proposition 10, which would enable city governments to enact rent control on any buildings. I had no idea whether or not this was a good idea, and I was going to go to my default in situations like this, which is to vote no. But I decided to check with my friend, Steph, who works in affordable housing. She was thoughtful, knowledgeable, and even, and after my conversation with her, I decided to vote Yes.

This year, there was a similar ballot initiative, Proposition 21, which would enable city governments to enact rent control on buildings that was first occupied over 15 years ago. Once again, I had no idea whether this was a good idea or not. Once again, I turned to Steph. Once again, I voted Yes.

Here’s what troubled me about finding myself in almost the exact same situation two years later: I had learned absolutely nothing. I didn’t even remember whether or not Proposition 10 had passed. (It didn’t. Neither did Proposition 21.) Even if it had, I would have had no idea what the impact of that measure was.

I believe strongly in collaboration, democracy, and the wisdom of crowds. It’s why I do what I do. And I understand why folks don’t have faith in a population’s ability to govern itself. Our track record, especially recently, is terrible.

Here’s the thing: In order to act in intelligent ways, people need to be responsible for the impact of their decisions. If we don’t know the impact of our decisions, we are not going to make good decisions.

In his book, The Signal and the Noise, Nate Silver explains that pundits are terrible at predicting financial markets, but meteorologists are exceptional at predicting the weather. Why? For starters, we are more likely to remember a meteorologist’s track record, because the feedback loop is tighter. Last night, the weatherperson said it would be sunny. Today, it rained. You’re going to remember that.

If we could figure out better ways to tie decisions with impact, I think we would find society generally doing the right things. This is obviously incredibly hard, but I don’t think it’s impossible.

A Rant About RACI

Posted on Published by Eugene Eric Kim

If you’ve ever worked in a large organization and especially if you’ve worked with or are a consultant, you’ve probably come across something called RACI. Or RASCI, or DARCI, or MOCHA, or any of its many variations. If you haven’t, don’t feel bad. As you’ll see in a bit, you’re better off not knowing.

Sometimes, it’s not clear who’s responsible for something getting done, who needs to be informed, who would like to be informed, and so forth. Sometimes, this is a problem.

In my household, we expect the dishes to get cleaned, but no one is assigned that role. It generally works itself out, but sometimes, the lack of clear roles creates contention. I won’t lie, when there is contention, I’m usually the cause. Fortunately, I live in a functional household, where we are usually able to handle the conflict constructively (i.e. I get off my lazy butt and do the dishes.)

Frameworks like RACI try to help people by defining a clear-ish set of roles and encouraging groups to agree on who has which roles when. The intention is good. I am a big proponent of being explicit about agreements.

Unfortunately, RACI is often more onerous than helpful. First, the distinctions between roles are not always obvious. For example, what’s the difference between “responsible” and “accountable”? I can draw a distinction between these two terms, but if I have to do that, then I question whether or not the framework is that useful in the first place.

Second, the roles are not always useful. The reason there are seemingly hundreds of variations of RACI is that folks are always trying to fill in the gap.

Third, people often end up conforming to the framework blindly without checking to see if it’s actually working for them. I have never seen a group successfully implement RACI or any of its variations. Of course, that doesn’t mean it hasn’t happened. (If your group is successfully using RACI, I’d love to hear about it.)

Here’s what I’ve found actually works, both with groups I’ve worked with and healthy groups I’ve observed:

First, groups should have regular roles conversations, first to agree on them, then afterward to check in and make adjustments. In my working agreements template, I have folks do a simple exercise:

  • Write a bulleted list of your roles and responsibilities
  • Share them with each other, and let each other edit, add, or challenge until everyone agrees on each other’s list.

The key is not to simply do the exercise once and forget about it.

Second, groups should be clear about how decisions are made. It’s okay for this to be a shared role (i.e. consensus among two or more parties), but it’s important in these cases to talk explicitly about what success and failure look like. Again, the key is to check in regularly afterward and to make adjustments.

The Uncanny Valley of Leadership

Posted on Published by Eugene Eric Kim

I’m a reasonably responsible voter. I vote pretty much every year, including off-years, and I do my best to educate myself on the issues. I’m lucky to be surrounded by folks who are extremely engaged, and I often “consult” with them on issues or candidates I don’t know well. Sadly, “consult” often means simply voting the way my friends tell me to vote.

Four years ago, disturbed by the direction our country was moving, I took a hard look in the mirror about my own level of civic engagement. Because I was already spending a good amount of my professional time working on national issues, I decided to focus my personal time on local issues. It was an easy decision, because I quickly realized how ignorant I was about what was going on in my own neighborhood, much less the city of San Francisco.

I started attending local meetings (which bear a shocking resemblance to the meetings on Parks and Recreation) and reading up on local issues. I met my Supervisor, whom I had voted for, but whom I had known nothing about. I learned that San Francisco has a $13 billion (!) budget, and that roughly half of this money comes from self-supporting services, such as public transportation (although this has changed dramatically, thanks to the pandemic). It seems like I should have known all this stuff before happily asserting my civic rights, year-after-year, but I was happy to finally start correcting this.

Flash forward to today’s election. About a month ago, I looked at my ballot, and I was troubled to discover that I was no better equipped to make decisions this year than I was in any other year.

For example, there were seven candidates running for Supervisor in my district. I tried to read up on all of them, which helped me narrow the field to three, but didn’t help me beyond that. San Francisco has ranked choice voting, which meant that I could vote for all three (which I did), but it didn’t help me with the order. I ended up voting for the person endorsed by the current Supervisor. I happened to run into her at a neighborhood restaurant (after already voting for her), and she left a good impression, but good impressions — while important — don’t seem like the best criteria for making these kinds of decisions.

In animation, there’s this concept known as the “uncanny valley.” When we see cartoonish versions of people, we are untroubled. We know they are meant to be representative, not realistic depictions of human beings, and we can appreciate them as such. We also react well to perfectly realistic depictions. However, we find depictions that seem almost human-like to be creepy, even revolting. (Think The Polar Express.)

I feel like there’s also an uncanny valley when it comes to assessing leadership. Federal and perhaps even state-level officials are the equivalent to the cartoonish representations of people. There’s no way for us to really know them, so we form opinions based on things that may not actually say much about whether or not they would make competent leaders, such as their opinions on various issues or how likable they seem to be.

On the other side of the spectrum, there are the leaders we actually know — our bosses, for example. We form our opinions of their leadership based on working with them, which seems like an appropriate way to make these kinds of assessments.

How, then, should we judge folks running for Supervisor or our local School Boards? These are folks I might run into at a local coffee shop and could actually have a conversation with if I have concerns or questions. Why is it so hard for me to assess who might be good for these positions? I think it’s because they fall into this uncanny valley of leadership, where they seem accessible, and yet there are aspects of them that seem fundamentally unknowable, and that feels unsettling.

Why Are We Afraid of Data?

Posted on Published by Eugene Eric Kim

My friend, Gbenga Ajilore, is an economics professor. Last month, he gave a great talk at AlterConf in Chicago entitled, “How can open data help facilitate police reform?” It concisely explains how data helps us overcome anecdotal bias.

I was particularly struck by his point about how we need police buy-in for this data to be truly useful, and I was left with a bit of despair. Why is buy-in about the importance of data so hard? This should be common sense, right?

Clearly, it’s not. Earlier this year, I expressed some disbelief about how, in professional sports, where there are hundreds of millions of dollars riding on outcomes, there is still strong resistance to data and analytics.

On the one hand, it’s incredible that this is still an issue in professional sports, 14 years after Moneyball was first published and several championships were won by analytics-driven franchises (including two “cursed” franchises, the Boston Red Sox and the Chicago Cubs, both led by data nerd Theo Epstein).

On the other hand, it’s a vivid reminder of how hard habits and groupthink are to break, even in a field where the incentives to be smarter than everyone else come in the form of hundreds of millions of dollars. If it’s this hard to shift mindsets in professional sports, I don’t even want to imagine how long it might take in journalism. It’s definitely helping me recalibrate my perspective about the mindsets I’m trying to shift in my own field.

The first time I started to understand the many social forces that cause us to resist data was right after college, when I worked as an editor at a technology magazine. One of my most memorable meetings was with a vendor that made a tool that analyzed source code to surface bugs. All software developers know that debugging is incredibly hard and time-consuming. Their tool easily and automatically identified tons and tons of bugs, just by feeding it your source code.

“This is one of the best demos I’ve ever seen!” I exclaimed to the vendor reps. “Why isn’t everyone knocking on your door to buy this?”

The two glanced at each other, then shrugged their shoulders. “Actually,” one explained, “we are having a lot of trouble selling this. When people see this demo, they are horrified, because they realize how buggy their code is, and they don’t have the time or resources to fix it. They would rather that nobody know.”