I just published a big post on our company blog about how we came up with our priorities and roadmap for Postmark for the next few months. From the intro to How we built a product vision and roadmap:

So, armed with some whiteboard markers, a mountain of sticky notes, and one very enthusiastic team, we set off to plan out the next few months of our product. In this post I’d like to give an overview of what we did, why we did it, and how it’s going to help us (and our Postmark customers!) in the coming months.

This one took a while to write and edit, and there’s some nice illustrations as well as downloadable templates, so take a look!

I’ve done a fair bit of hand-wringing about wireframes myself (see here and here), so I read Travis LaFleur’s Toward a More Expansive View of Wireframes with great interest. I really like Travis’s approach of expanding wireframes beyond their traditional use:

Rather than thinking of the wireframe as a low-fidelity, grayscale snapshot of what a page will eventually look like, coming further and further into focus as the design is refined, we can embrace a broader view of the wireframe as a thematically rich conceptual model — one that is now depicting page-level details, reinforcing previous models of the system as a whole.

Click through to his post for some examples.

Charles Duhigg has a long feature in the New York Times called What Google Learned From Its Quest to Build the Perfect Team. It includes a summary of really fascinating research on the core elements of a healthy, productive team:

As the researchers studied the groups, however, they noticed two behaviors that all the good teams generally shared. First, on the good teams, members spoke in roughly the same proportion, a phenomenon the researchers referred to as “equality in distribution of conversational turn-taking.” On some teams, everyone spoke during each task; on others, leadership shifted among teammates from assignment to assignment. But in each case, by the end of the day, everyone had spoken roughly the same amount. “As long as everyone got a chance to talk, the team did well,” Woolley said. “But if only one person or a small group spoke all the time, the collective intelligence declined.”

Second, the good teams all had high “average social sensitivity”—a fancy way of saying they were skilled at intuiting how others felt based on their tone of voice, their expressions and other nonverbal cues. One of the easiest ways to gauge social sensitivity is to show someone photos of people’s eyes and ask him or her to describe what the people are thinking or feeling—an exam known as the Reading the Mind in the Eyes test. People on the more successful teams in Woolley’s experiment scored above average on the Reading the Mind in the Eyes test. They seemed to know when someone was feeling upset or left out. People on the ineffective teams, in contrast, scored below average. They seemed, as a group, to have less sensitivity toward their colleagues.

So, effective teams are built on equality and empathy. Seems terribly obvious, of course, but I feel like very few teams actually live these values. We can do better.

Daniel Zacarias’s Moving from Solutions to Problems is a must-read for all product managers, and anyone who’s involved in product prioritization. Daniel’s main thesis is that prioritizing problems results in much better products than prioritizing features—and I wholeheartedly agree with him. He addresses many issues with focusing on features, but the one that really resonated with me is that it’s much harder to prioritize features:

Products and features are versions of a solution to a problem. What this means is that by thinking in terms of the former, the problem they’re solving gets more difficult to grasp. Either because it’s a non obvious problem, or the product/feature are poor solutions for it.

In practical terms, this makes it much harder to prioritize a list of features than a list of problems. There are added layers of indirection that make us evaluate priorities in a different way. It gets difficult to determine the intent and expected impact from a feature. On the other hand, a problem (“low number of transactions”) can more easily lead to an objective (“increasing number of transactions per customer per month by 30%”).

Horace Dediu has a characteristically astute analysis of Apple’s business model in Priorities in a time of plenty. The part I’m particularly interested in is where he discusses how Apple prioritizes their product roadmap:

Conventionally, product development is filtered through a sieve of metrics, market sizing and impact on top/bottom income lines. These “financial” measures of success are considered prudent and optimized for return on equity (also known as the maximization of shareholder returns).

But this can be a toxic formula. The financial optimization algorithm always prioritizes the known over the unknown since the known can be measured and is assigned a quantum of value while the unknown is “discounted” with a steep hurdle rate, and assigned a near zero net present value. Thus the financial algorithm leads to promoting efficiency at the expense of creation. Efficiency may be the right priority when times are difficult and resources are scarce but creativity is the right priority in a time of plenty. And abundance is what being big is all about.

The difficulty is that creativity is hard to quantify, and therefore hard to measure, and therefore hard to prioritize—particularly in large enterprises. Horace speculates that “the creation and preservation of customers” is Apple’s primary focus (above revenues), which changes the way they prioritize:

Seen this way each centralized resource allocation question can be assumed to be prefaced with “In order to create/preserve customers should we…?”

This leads to answers quite different from questions that start with “In order to sell/profit more should we…?”

Much to digest here, particularly around the role of managers to identify the right balance for prioritization, and the right metrics to measure if your primary goal is, in fact, “the creation and preservation of customers”.

Cliff Kuang wrote an excellent article on Microsoft’s push for more inclusive design. From Microsoft’s Radical Bet On A New Type Of Design Thinking:

Dubbed inclusive design, it begins with studying overlooked communities, ranging from dyslexics to the deaf. By learning about how they adapt to their world, the hope is that you can actually build better new products for everyone else.

What’s more, by finding more analogues between tribes of people outside the mainstream and situations that we’ve all found ourselves in, you can come up with all kinds of new products. The big idea is that in order to build machines that adapt to humans better, there needs to be a more robust process for watching how humans adapt to each other, and to their world. “The point isn’t to solve for a problem,” such as typing when you’re blind, said Holmes. “We’re flipping it.” They are finding the expertise and ingenuity that arises naturally, when people are forced to live a life differently from most.

This is similar to the points I tried to make in Beyoncé, Coldplay, and the myth of the “average” user. The advantages of having more diversity in our design and development processes go far beyond the moral rightness of it. We end up with better products that serve a much wider cross-section of a population.

Maria Konnikova digs into the research on How People Learn to Become Resilient:

[Developmental psychologist Emmy Werner] found that several elements predicted resilience. Some elements had to do with luck: a resilient child might have a strong bond with a supportive caregiver, parent, teacher, or other mentor-like figure. But another, quite large set of elements was psychological, and had to do with how the children responded to the environment. From a young age, resilient children tended to “meet the world on their own terms.” They were autonomous and independent, would seek out new experiences, and had a “positive social orientation.” “Though not especially gifted, these children used whatever skills they had effectively,” Werner wrote. Perhaps most importantly, the resilient children had what psychologists call an “internal locus of control”: they believed that they, and not their circumstances, affected their achievements. The resilient children saw themselves as the orchestrators of their own fates. In fact, on a scale that measured locus of control, they scored more than two standard deviations away from the standardization group.

Kate Bowler’s Death, the Prosperity Gospel and Me is the best thing I’ve read this year so far. It’s funny, sharp, and deeply moving. Kate recently got cancer, some time after writing an academic book on the prosperity theology phenomenon in many American churches. Prosperity theology—the idea that “good” faith in God can make you rich and keep you healthy—is an immensely damaging philosophy, and Kate addresses this with poise and clarity.

I hesitate to quote anything from the essay because you really should read the whole thing, but one of my favorite paragraphs deals with the recent rise of the #blessed hashtag:

Over the last 10 years, “being blessed” has become a full-fledged American phenomenon. Drivers can choose between the standard, mass-produced “Jesus Is Lord” novelty license plate or “Blessed” for $16.99 in a tasteful aluminum. When an “America’s Next Top Model” star took off his shirt, audiences saw it tattooed above his bulging pectorals. When Americans boast on Twitter about how well they’re doing on Thanksgiving, #blessed is the standard hashtag. It is the humble brag of the stars. #Blessed is the only caption suitable for viral images of alpine vacations and family yachting in barely there bikinis. It says: “I totally get it. I am down-to-earth enough to know that this is crazy.” But it also says: “God gave this to me. [Adorable shrug]. Don’t blame me, I’m blessed.”

I am thankful for people like Kate who, instead of saying “Everything happens for a reason,” says “Life is really hard—and yet, I still believe.”