Imagine with me: what if novels were written like software. Sometimes it’s useful to approach absurdity and look inside. There might be treasure there. I’ll define software as an executable, a set of instructions, that are interpreted by a machine for some reason. As a data scientist, I think of software as a product, and I think, constantly, of turning data into product. I think of data as inertia and all the code around it as flexible. I worry a lot about the people that use the software (if anybody) and think of them as heterogenous segments. I think of a novel as an executable, a set of instructions, that are interpreted by a human brain for some reason. As[…]

Ikigai represents a pretty basic segmentation. So of course I love it. I love it so much I want to share. And you might love it too! The word comes from Japan. It means a reason for being. The segmentation recognizes four attributes of activities and jobs you could do – What You Love, What The World Needs, What You Be Paid For, and What You Are Good At. Combinations of two represent Mission, Vocation, Profession and Passion. Combinations of three segments represents Delight/Poorness, Excitement/Imposter, Comfortable/Empty, and Satisfaction/Uselessness. Doing something at the intersection of all four is called Ikigai. It’s a very elegant segmentation. It can also represents a surface. Assume a 2 dimensional plane representing all the activities and[…]

W1A is so much fun because the main character, Ian Fletcher, tries. And he fails. But he keeps on trying. And even though Ian isn’t aware of the character flaws that cause him to fail, he persists in trying. Ian Fletcher’s tragic character flaw, the source of so much of his pain and anguish throughout the series, is his optimism. That’s what makes it funny. I hope you’re finding this blog, and the twitter feed, funny. Because like Ian, I’m struggling. Like you, I’m composed of a couple thousand hours of meetings, deckage, talks, seminars, code, charts, stories, bullet points, facilitation, deliberation, analysis, email, papers, and pure rage. My stance as a scientist has informed the tools that I use,[…]

This is a dense post. Feldman and March, in 1981, wrote “Information in Organizations as Signal and Symbol”. And it makes good predictions about what a management scientist type would say about the purpose of information in an organization. Indeed, just last month, I hyped Carl Anderson’s 2015 original position yet again, in the framing of information as assisting learning. Feldman and March are cited by another piece that’s been weighing heavily since February. Alvesson and Spicer’s 2012 hit “A Stupidity-Based Theory of Organizations” explains why seemingly intelligent people pretend to be dumber than they are. Please don’t misinterpret this passage. It’s not the case that everybody is stupid. Sometimes people act dumber because they have to go-along-to-get-along. Are you[…]

This post describes a fast follow startup and the implication for how that startup learns. Define Startup A startup is a market hypothesis looking for validation. It’s an organization in search of a business. If they’ve accepted funding, then it’s a group of people looking for a liquidity event. Define Follow Follow means imitation. It means that an entrepreneur or a herd entrepreneurs have been observed pursuing a particular product-solution-market fit, or a hypothesis, and some founder wants to join the herd. Define Fast Fast means that the organization is imitating fast enough to nip at the heals of the lead innovator. It is imitating fast enough to be contention of overtaking the leader, or close enough to experience a[…]

It’s easier to link to this text than it is to repeat the intuition every time. Those who learn fastest win One of the core reasons why, as I write this in mid-2018, Silicon Civilization has the world in their teeth is because they figured out that it wasn’t just about learning. It was about learning quickly. Look at it from their perspective. A startup is a hypothesis looking for validation. Those startups that are able to learn fastest have a greatest chance of pulling up before the runway runs out. Those that learned survived takeoff. Those that really thrived never stopped learning. They win because they got really good at learning. It isn’t purely about data, it’s about how[…]

Data scientists spend so much time focused on learning: both machine learning and human learning. A machine can learn. A data scientist spends a lot of time just trying to persuade a machine to learn. It just takes a lot of labelled data. What about collections of people? Organizations can learn too. It’s just that the data isn’t all labelled well. Why Organizational Learning is Important I was so impressed with Carl Anderson’s synthesis two years ago, about Data Driven Cultures, that I unpacked it and applied it to startups and strategy. Coming back to it now, in 2018, a lot of what he was saying is purely about learning. Carl Anderson, 2015, described a data driven culture as on that:[…]

We visited Koh Tao from March 18 to April 1, 2018. Here are some notes for fellow Canadians thinking about visiting Koh Tao. Getting There: The Flights A wise graduate supervisor once advised that one should always break up my trip so that you’re spending no more than 8 hours a day traveling. Eight hours in an airplane is a good work day, and you want to show up refreshed and ready to go. We didn’t do that. For the first leg, we did Cathay Pacific 829, Toronto to Hong Kong. Flight time was 15h30 minutes. It departs Pearson at 0h130 and lands the next day at 05h00. The way this flight works is impressive. There are stands to manage[…]

Who do you trust to manage your attention? Because now that the news cycle has surfaced Cambridge Analytica issue – that’s the real thesis question. Let me explain. How the Newsfeed manages your attention I really can’t understate just how powerful amplified engagement really is. When you overlay the like/share verbs on top of a network of individuals who all have something in common, or who procure people who have something in common, you get some pretty strong effects. Don’t believe me? Just check out the clothing in your drawers and the items in your fridge. You, my friend, are an outcome of considerable social contagion effects. Facebook’s newsfeed algorithm shelters you from a power law distribution of content that the[…]

We visited Buenos Aires from Feb 9 to March 1, 2018. Here are some notes for fellow Canadians thinking about visiting Buenos Aires. Taking a vacation in Buenos Aires as a Canadian requires some planning. If you do not enjoy planning, don’t go just yet. If the trend holds through to 2020, it’ll become easier and easier to visit. These notes are for Canadians. Getting There: The Flight We did Air Canada 92, which flies to Buenos Aires via Santiago, Chile. The flight was late because of mechanical issues prior to its Morning run to Beijing, via Vancouver. Delays are the rule, not the exception, with AC 92. Check out FlightAware to verify for yourself. It has a terrible on[…]